Futuristic

In this episode, Cameron and Steve dive into the rapidly evolving world of AI, discussing the latest advancements and their societal implications. They explore new AI voice features, the potential dangers and benefits of AI companions and agreeable AI personalities, and the philosophical debate around AI sentience and relationships. The conversation touches on AI’s role in business generation, the power of new models like OpenAI’s GPT-4o and Google’s Gemini 2.5, and the ongoing copyright debate surrounding AI training data. They also get into the complexities of how Large Language Models (LLMs) like Anthropic’s Claude actually “think,” the expansion of AI into hardware by companies like LG, Apple’s perceived lag in the AI race, and the future of AI integration in everyday tools like ebook readers. The discussion extends to advancements in open-source robotics, citing Nvidia’s initiatives, and contrasts technological progress and STEM education focus between China (highlighting Huawei) and the US. Finally, they touch on the intriguing and potentially controversial “Network State” concept championed by figures associated with Peter Thiel and Andreessen Horowitz, exploring the idea of tech-driven, independent city-states.

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FUT 38 Audio

[00:00:00]     

Cameron: So that was an official new voice from chat, GPT, which came out today called Monday. And it’s like a depressed goth girl or something, whatever. , which is now my official favorite voice. I don’t know, , if you found this, welcome back. This is futuristic episode 38, by the way, Steve Sammartino, , I dunno if you’ve found this, but, uh, I’ve been using advanced voice with GPT lately, and the voices have sounded increasingly excitable.

I was having a conversation in the car on the way to Kung Fu with GPT about Trump and Greenland and rare earth minerals. And I was like, I was saying, so hold on. Greenland is run by Denmark and Denmark’s and NATO country. So if Trump invades Greenland, [00:01:00] does NATO have to, does that, uh, is that Invoke Article five under the NATO treaty and then NATO needs to attack the United States and GP t’s like, yes, that would happen.

They probably would. And it would have to be, and it was all very excitable and it was, and I was like, can you sound less excited? And it would like, oh, okay, sorry. I’ll bring the tone down a bit. And a minute later it would be talking like this again. It would all be very excitable. Even Fox was sitting in the backseat.

He is like, can you just calm down a minute? Anyway, but I like this new depressed voice. That’s more my style.

Steve: call it apathy,

Cameron: I.

Steve: and I don’t think enough AI in modern society are apathetic,

Cameron: It reminds me of, was it Marvin in the Hitchhiker’s Guide to the Galaxy was the AI robot. I was like, I am so depressed, brain the size of a planet, and they asked me to pick up a piece of paper. I am so depressed.

Steve: Well, I think that the AI should be able to seamlessly switch [00:02:00] between. Levels of animation and emotion, right. Based on the context of the chat, because it understands it verbally with the language, it should be able to translate that in the audio sense. You would, one would think regardless of the voice that you choose, I.

Cameron: Yeah, and I was listening to, uh, an interview with Ezra Klein yesterday with Jonathan het, and Ezra Klein was talking about the fact that he’s concerned about the fact that a generation of kids are gonna be growing up with AI assistance that are completely agreeable with everything that they say, and that that’s not a good thing.

In the same way that social media hasn’t been a good thing for kids, AI that just agrees with them all the time to make them feel good is not gonna be a good thing. I was talking to Chrissy about it yesterday and I was saying that I expect when we get fully realized AI virtual [00:03:00] assistants that are on the devices that we give to our kids, we will have parental controls where we will be able to set up the AI personality that we want our children to interact with.

That say, listen, your job isn’t to just agree. Your job is to be. A caretaker, an educator, is to push back if they say something dangerous or stupid or that could be, um, referencing self harm or could be negative for their psychological or emotional health, you are to act as a therapist slash parental advisor slash tutor slash whatever.

Adults though, will probably get to choose the AI personality that they want, and I’m already telling GPT don’t agree with in my customer instructions. Don’t agree with me on everything. If I say something and it’s factually incorrect, or well, you think my interpretation of the facts is incorrect, I want you [00:04:00] to tell me that’s your job.

Push back, argue with me. You know, give me something to think about. But Chrissy said, and she’s probably right, most people won’t. Most people will just choose the AI personality type that just agrees with them all the time. ’cause that’s what they want is just validation that their ideas and beliefs are true.

What do you think?

Steve: I think the most dangerous. tool in the world right now, which builds on this is AI girlfriends. They are an absolute social disaster in the making. An imaginary girlfriend that you talk to every day that agrees with everything you say, think learns from you, has the same business model, is want you to keep coming back, is gonna tell a young teenage boy everything he wants to hear. It’ll eventually be a soft robot that he gets delivered from Amazon and he develops a relationship with. This is not good. Falling in

Cameron: Is it worse [00:05:00] than,

Steve: it’s ter,

Cameron: is it worse than having, is it worse than having incel running around with AR fifteens in the us?

Steve: it’s the same thing with a different product. Right. It’s

Cameron: Yeah, but

Steve: who don’t have real social interactions. An incel with an AR 15 or an incel with an AI humanoid robot, they’re the same thing, which is we don’t have real social interactions of people that disagree with us, that we learn social norms, that we interact, we give and take.

It’s the same thing, and they

Cameron: well, yeah, except they’re not going to.

Steve: a bunch of shot up people in,

Cameron: Well,

Steve: where I can go and buy a gun in Walmart.

Cameron: no, but look, I see the opportunity for problems, but I also know that loneliness is a huge issue in modern society.

Steve: so that doesn’t solve loneliness, Cameron. It doesn’t

Cameron: I don’t, and I,

Steve: it.

Cameron: I dunno that that’s true. I think, uh, you, you have been, you know, a big advocate [00:06:00] of the idea that if an AI seems human, seems conscious, seems to be sentient, then for all intents and purposes, it is those things

Steve: Yes.

Cameron: I agree with.

Steve: Yes.

Cameron: therefore, having a relationship with a seemingly sentient ai biological organism, i, it, it’s not exactly the same as having it with a human, but it’s, it’s, it’s maybe the next best thing, or maybe it’s an equitable thing.

Steve: Okay. You are right and I’m right.

Cameron: I.

Steve: problem, circling back to what I first said, is having one that agrees with everything you said and tells you what you want to hear isn’t a relationship with a sentient thing. We’re

Cameron: Look, that’s normally how I pick my co-hosts, Steve, except for you. That’s normally,

Steve: No, no,

Cameron: and Tony.

Steve: the point is, right. No, the point is, is that if it were a sentient AI that had give and take and taught the [00:07:00] human side of the relationship, Hey, that’s not how you treat me. And you gotta, no, you gotta have more open mind than that. Wait a minute, I’m not just gonna do it. Like, if it, if it became like, like a real relationship, then that’s good.

The point is, how is the algorithm trained? What are the incentives of the AI girlfriends that are

Cameron: Hmm.

Steve: And I imagine the incentives are gonna be as perverse as they are for Google and Facebook in the attention

Cameron: it makes.

Steve: back and subscribing. Then it’s more likely to give you exactly what you want, which is the same of your algorithms feed you more and more of And that’s the problem. If it were sentient and reasonable and rational and disagreeable and all of those things that we get in normal relationships, then it would be good. But I fear that it won’t be that.

Cameron: Hi Steve. I’m going to continue our dirty Talk session, but first I want you to listen to this ad. Did you know that Squarespace will help you make a website

Steve: Let’s get back.

Cameron: for your, for your business?

Steve: Remember, that fetish that we discussed? [00:08:00] Remember that? Do you remember what I liked? Do you remember? Can you show me? Can you show me? Send me some pics. Send me some pics

Cameron: Look, if it makes people feel good and they’re not hurting anyone, what does it matter?

Steve: the point is if it makes them feel good, that’s fine. And if

Cameron: I.

Steve: hurt anyone, that’s fine. But I fear that the thing that will make them feel good will be getting everything you want, all the chocolate, all the fantasies, agree with me, do everything I want, and then you get, it gets into a circle of darkness.

You just end up circling the drain. It’s a race to the bottom of extracting the proclivities of young. Teenage males, which unless kept in check, might not be all that positive for society. I’m just, I’ve been a teenager. I, you know, you’ve been one. Cameron, let’s, let’s be real here. Giving teenage boys exactly what they want might not be ideal for society.

I’m just, just a guess.

Cameron: I am still a [00:09:00] teenager. I just, my body got older.

Steve: Yeah, same.

Cameron: Um, so, uh, uh, let’s circle back to the news. Um, so, well, no, before we do that interesting things, tell me about interesting futuristicy things you’ve done since we last caught up. Stevie,

Steve: I revisited. you, Kami. circled back to one of the original AI AI ideas, which was going around where you give AI a budget of $500 and say, generate 10 business ideas. I did it on. Four of the major, uh, large language models. All of their ideas were incredibly similar. And they had things like chatbot agency, automated trading, digital products, and Etsy domain flipping, AI stock photos, those kind of things.

AI stock photos is a new one because they’re much better at that now. and I came to a conclusion. And the conclusion [00:10:00] that every single one of these ideas where AI becomes an employee out entrepreneurially generating money, all of them required advertising on big tech, which I just thought was this interesting circle where it all came back and it said, and you’ve gotta allocate out of your $500, $150 worth of advertising on one of the big tech channels to get attention.

Which just ensconced me further, even with these emancipating tools of AI that can do everything. But you gotta come and find people in the attention economy on our tools that we happen to also own, in addition to the ai, whether it was on Amazon or Google or, or Facebook or any of ’em. I’m like, man, we’re back where we started, brother.

Cameron: Yeah. Right. Well, look, I still believe there is a, there is a potential future where that isn’t the case, but you can rest assured that the people that own the online advertising platforms and also have an interest in [00:11:00] Theis will be trying to create a future where those things are tightly coupled.

Steve: Definitely.

Cameron: Well, I used GT’s new four oh image generation model, which we’ll talk about in a minute.

Um, one of the first things I did with it was to make a comic. Um, something that I’ve wanted to do for years is a, a comic series about my journey with my guru Bob who passed away recently, and about how I met him and, and what he taught me and how it helped me, but do like a very, like a light sort of comic approach to it.

Now, we all know that, uh, image generators have really struggled with words since they were, they first came out, we, you know, whatever it was 18 months ago. Ideogram, the one I’ve been using for the last couple of months, the most, uh, does a pretty good job of words, but you could give it one or two words or three [00:12:00] words maybe, and it would do a pretty good job of that.

But I tested this thing with GPT where I said, I want to do a comic. I wanted to have, you know, between three to five panels, um. And I told it, the storyline, I created basically the, the words and it did comics that were flawless. One shot, two shot if I wanted to edit something. Um, really great. And I did a series of five comics that tell the progression of the story.

They kept the character ref, the character images the same, like the same character for me. And Bob looked the same from comic to comic. They did word bubbles. They did the words right. It was. Amazing. Like to be able to just say, make me this thing, and it just did it. So, um, I played around with that. We’ll talk about what happened in a second, but before I move on, I [00:13:00] want to do a shout out to Pete Hewitt from the uk listener of our show.

Been a listener of some of my other shows for many years. Actually had a nice lunch with Pete when he was in the country a couple of years ago. Um, Pete pointed out that I have been conflating on this here podcast over the last year, the idea of cold fusion with net positive fusion tomax, which are really hot fusion.

But in my brain, I, uh, reversed the polarity and because it was net positive fusion, I was calling it cold fusion, which is a completely different thing and probably doesn’t exist. So. Apologies to everyone who thought I was talking about cold fusion. I was actually talking about hot fusion, but net positive fusion.

Uh, there you go. So thank you to [00:14:00] Pete for calling me outta my, uh, bullshit, not deliberate bullshit, but my brain. And by the way, I found out in the last week or so that I’m autistic, so that is now my get outta jail free card for everything.

Steve: Kevin?

Cameron: Yeah.

Steve: So

Cameron: Well it was Chrissy.

Steve: time,

Cameron: Yeah,

Steve: Pete, by the way, Pete, look, I didn’t wanna say anything, Pete, but I was thinking the same thing because late at night I just, I got out one of the old physics textbooks from my undergraduate, uh, science degree. Really? We really was perusing some of the pages there. Well, I’m glad Pete pointed it out and thank you, Pete, because hey,

Cameron: that’s your job is to call me on my bullshit if I get stuff wrong. Steve

Steve: did it.

Cameron: did.

Steve: my pay grade physics.

Cameron: All right,

Steve: um, thanks for

Cameron: well there you go.

Steve: for tuning in.

Cameron: And as I always say on my podcasts, um, you know, I’m usually right, but if I ever get something wrong, I want to be told that I’m wrong. ’cause I [00:15:00] don’t give a fuck if I’ve

Steve: You don’t want that puppy. No way.

Cameron: No, no, no. I don’t want if be talking bullshit.

So anyway, thank you to Pete. Let’s talk about the four oh image model. So, uh, open AI came out with this coincidentally on uh, roughly the same day the Deep seek released the new version of their V three model. That was a killer. And Google released the new version of Gemini 2.5, which is a killer. Also happened to be the day that Open AI released their new four oh image generation model.

And it was an absolute killer for about 24 hours, and then it became next to useless. Perhaps be? Well, look, I have a couple of theories. One is that they nerfed it, um, because what they tend to do on a launch day, I think particularly if they’re competing with other AI launches, they want to get all of the media hype is they [00:16:00] allocate a massive amount of compute to it for the launch day,

Steve: Yep.

Cameron: which is costing them gajillions of dollars.

And then as soon as they get a good 24 hours of massive hype, they downscale the compute to save money. But simultaneously, and this is probably the other truth, is that 24 hours of hype brings in millions of new users that play with it. And so it just gets hammered. Um, Sam did tweet just after they launched this thing.

The chat GPT launch 26 months ago was one of the craziest viral moments I’d ever seen, and we added 1 million users in five days. We just added 1 million users in the last hour. So

Steve: Wow.

Cameron: I accept and acknowledge, uh, that. Uh, the sort of [00:17:00] scaling that they’re dealing with is insane and is an insane engineering problem to have to handle regardless of how much money you have.

It’s about people, it’s about data centers and compute and chip sets and cooling and all of the real world hard engineering issues that go into scaling something like this. I think it’s a combination of that and they nerf it for various reasons. Everyone was doing Studio Ghibli versions of everything and they kind of nerfed that you could do pictures, Ghibli versions of your family initially.

Then I tried to do

Steve: get the win on this? Why? Why Ghibli?

Cameron: ’cause nerds love Ghibli.

Steve: through the roof. I mean, yeah, it was a bit niche, but now it’s like my feed was just filled with Ghibli.

Cameron: Well, all nerds love Studio Ghibli and for good reason. I mean, the Studio Ghibli films are absolute [00:18:00] masterpieces, absolute classics.

Steve: But are

Cameron: Somebody

Steve: Are they really masterpieces?

Cameron: Oh, are you, are you a, are you a Ghibli skeptic?

Steve: I,

Cameron: Oh my God.

Steve: like now

Cameron: Have you seen, have you seen Ghibli films? What Gib films have you seen?

Steve: I’m a Ghibli skeptic. Okay. Let me just tell

Cameron: Have you seen the Ghibli films, is what I’m asking you?

Steve: and I think I’ve had all too much Ghibli in

Cameron: Oh,

Steve: couple of

Cameron: no, no, no, no.

Steve: send me a Ghibli

Cameron: You haven’t sat down and watched ’em with your kids.

Steve: if you, if you insist and report

Cameron: Oh my God. Sit your kids down and watch The Castle in the Sky or, or Princess Monki or any one of them. Oh my God. They are visual and storytelling and musical. Absolute masterpieces. Every one. Definitely.

Steve: has to be a winner when something new has a new application, right? There’s always a winner every single time. It’s like [00:19:00] like a gravitational force where the new technology gets pushed into something and it has to have like it has to have its victory winner. it was a plant by open ai and they’ve got it shares

Cameron: The

Steve: Ghibli or

Cameron: chairs in Studio Ghibli,

Steve: I’m telling you now, the whole thing’s a

Cameron: Miyazaki and Sam Altman have a thing. Yeah. Okay.

Steve: I’ll

Cameron: Yeah, yeah.

Steve: he’s got

Cameron: You need to get off of Q Anon,

Steve: with Ghibli’s in the back and that’s where he is going with the DVD player and a little battery

Cameron: his jansport backpack and he is taken off. Um, oh, well we’re gonna talk about Praxis when we finish this thing. But anyway, they nerfed it. Um, you couldn’t do pictures of your kids after a day or two. I tried to do a, an anime version of Fox.

Steve: skepticism

Cameron: Anyway, um, let’s talk about Gemini. 2.5 came out. The thing about Gemini is it’s free

Steve: Yep.

Cameron: it has a context window that’s like 2 million tokens or something. It’s an [00:20:00] insanely large context window compared to the others. And it’s beating all of the benchmarks, uh, um, as. By the way is the latest version of Deep Seek V three.

I mean, depending on what day you look at it, one of these is beating all of the benchmarks, but

Steve: is cool.

Cameron: the best I’ve played with Gemini, uh, with some coding stuff, and it is pretty good. Sometimes sucks at other times like Claude, all these kind of things. But the best post I’ve seen about Gemini 2.5 is a guy on the singularity subreddit said, um, I’ve gotta share this, because it was seriously cool.

I’ve got an old novel. I wrote years ago, and I fed the whole thing to Gemini 2.5 Pro, the new version that can handle a massive amount of text, like my entire book at once, and basically said, write new chapters. Didn’t really expect much. Maybe some weird fan fictiony stuff, but wow, because it could actually process the whole original story.

It cranked out a [00:21:00] whole new sequel that followed on, like it remembered the characters and plot points, and kept things going in a way that mostly made sense, and it captured the characters and their personalities extremely well. Then I took that AI written sequel text, threw it into 11 labs, picked a voice, and listened to it like an audio book last night, hearing a totally new story said in my world, voiced out loud.

Honestly, it was awesome. Kind of freaky how well it worked, but mostly just really cool to see what the AI came up with. I’ve been talking about this for the last couple of years, but I do believe we’re headed into a space where I will be able to upload a Dune novel or a James Bond novel or a film and say, give me a new one.

And it will give me a new one. Custom built, [00:22:00] custom designed for me. I’m the only person that’s ever gonna watch it and or my family sitting around, gimme a new Quentin Tarantino film, boom, here it is. Watch it. Enjoy it in the style of Quentin Tarantino. And I know people lose their shit over, oh my fucking trademarks and my copyright and my talent and my this, and I’m still arguing against those people.

Training on your. Drawing, training on your film, training on your album, training on your artwork, and then producing something brand new is not, I believe, a breach of your copyright or a breach of your intellectual property, because that’s how humans have always learned everything is we learn from watching other people do it, then we do it ourselves.

If it does a complete replica of your book or your film or your album, note for note, song for song, word for word, shot for shot, [00:23:00] then you’ve got a case. If it’s just learn from what you do and does something similar to that, but different, that’s, that’s not property theft. That’s just how creativity has always worked.

I’m sorry if you don’t like it, but that’s just how it works.

Steve: as the great Jim Roh said, when you get your own planet, you can redesign it how you please. But this is the world we happen to be in. And I totally agree with you, Cameron, and I’m, I’m actually shifting more towards this. I know that the New York Times still has their court case and they’re suing open ai and there’s multitude of, of these cases, but. Your example, and we should call it the Nike example. If I’ve got a factory in Guango and I’m making a pair of Air Force ones that look exactly the same and come in the packaging, then yes, that is copyright infringement and design infringement. But every organic being on earth, basically we copy, learn and adapt. Even our code, our own DNA is a copy, learn and adapt of [00:24:00] our parents. Uh, we’ve always done this before. We’ve read other people’s works and had writing styles, bands and musicians. Everyone has done it and it’s, yes, it’s at scale now. It is. And you know what? Probably a good thing, the key is this stuff needs to be open source so that I don’t have to pay Billy blogs to create the new Tarantino movie.

I can do it on a deep, deep seek kind of AI that I host on my own client or in the cloud, and I can make what I want. If we have that, then it’s totally emancipating and I would remind listeners. And I did this yesterday. I showed my son, uh, one of the great TED Talks and they’re few and far between these days, but it was, everything’s a remix

Cameron: Mm-hmm.

Steve: Kirby.

I forget his last name. But it was brilliant and it went through so many of the songs and ideas and lyrics and how everything was adapted. And you know what? That’s good ’cause we want interpretations and four or five interpretations down the line, you’ve got something totally [00:25:00] different. And I always thought that sampling was cool and, and reinterpreting things. And I feel like we’ve got the whole kind of trying to put fences around things for corporate interests and it’s bullshit.

Cameron: Yeah, look, I understand that people are upset. Uh, Kirby Ferguson, by the way, was the, everything is a remix.

Steve: call him the frg.

Cameron: Fergie

Steve: Yeah.

Cameron: Fgo.

Steve: Fgo. Shout out Togo.

Cameron: I know he is a big fan of the show. Uh, like I know that people are upset. I get it. You, you and I are authors.

Steve: Yep.

Cameron: Um, I, I, I’ve made a film. I, I’ve done thousands and millions of podcasts. Uh, and all of that’s gonna go into the mix.

Um, I.

Steve: way. ’cause I’ve looked up your stuff and my stuff, which is in the public realm. It can even give incredible summaries of my books, which are clearly, it’s got the PDFs in there. Uh, so

Cameron: Yeah.

Steve: that,

Cameron: [00:26:00] And

Steve: And that’s

Cameron: so we’re,

Steve: And that’s

Cameron: that’s, yeah. Like are we all gonna be outta jobs? Yes. Um, so is, so is half the human population? Um,

Steve: fabricators in our, in our lounge rooms.

Cameron: maybe, oh, well, it’ll be dead. I mean, either way, but it’s just like, yes, it’s upsetting and it’s scary, but it’s also the reality and it’s, it’s really not copyright theft. You put your stuff out there in public. It’s not being ripped off. It’s being trained on people. Don’t, I still believe people mo generally, who bitch about this stuff don’t understand how LLMs work.

And speaking of which. No one understands how LM works, including the people who build them. We’ve talked about this before, but this paper came out, uh, a week ago, tr by Anthropic. The, the, the Xa, uh, ex open AI engineers, a lot of them that, that build. Claude, one of the leading models, it’s called Tracing the Thoughts of a [00:27:00] Large Language Model.

I could play you the video that they did, but I’ll just, I’ll talk through it. Um.

Steve: it. It’s, it’s really cool.

Cameron: Really cool. Yeah. So their, their summary starts off like this. Language models like Claude aren’t programmed directly by humans. Instead, they’re trained on large amounts of data. During that training process, they learn their own strategies to solve problems.

These strategies are encoded in the billions of computations. A model performs for every word it writes. They arrive inscrutable to us, the models, developers. This means that we don’t understand how models do most of the things they do, and that still, I think, is one of the most profound things that I’ve ever heard as a technologist of 30 years, and that I still think most people out there don’t understand about ai.

Oh, is it eating window time? Close enough. Thank you. [00:28:00] My first food for the day. You’ve got water.

Steve: either. I’ve had

Cameron: Yeah, that’s me too. That’s all I’ve had.

Steve: Mm

Cameron: I’m on the Santino diet. Coffee and water till one o’clock.

Steve: until, yep. I try not to eat until dinner now, but that’s another story I.

Cameron: Oh, OMA, you’re on the Oma.

Steve: What’s, I don’t even know what it is, but I know that I look less fat if I don’t eat until dinner. ’cause there’s not enough time to eat until the day’s finished.

Cameron: Oma is one meal a day? Actually it is. I’ve just finished reading a book by a guy from Harvard all about Oma and intermittent fasting and compressing your eating window for that reason. Yeah,

Steve: Well it just makes it easier for me to still surf so I don’t get, it’s easy to stand up on the surfboard if I’m skinnier. That’s basically it.

Cameron: Easier. Easier for me to do kung fu if I’m skinnier. Yeah.

Steve: exactly. Funny, funny that, who knew? But

Cameron: Yeah.

Steve: remember there’s a movement on the internet called, healthy at any size, that someone who I think was some kind of size invented.

[00:29:00] I’m just saying and I look, do it. Do as you please. But I think biology will

Cameron: Yeah.

Steve: not you’re healthy at any size. Because

Cameron: Yeah.

Steve: see in old people’s homes. You know what they are. Cameron. Smokers

Cameron: people.

Steve: who are obese, you don’t see ’em. They’re not in old people’s homes.

Just a clue. That’s all I’m saying. But do

Cameron: Mm.

Steve: will. People carry on.

Cameron: So no, back to ai. People still don’t understand that they, they’re trained or they train themselves to a large extent. So the, the paper goes on to say, knowing how models like Claude think would allow us to have a better understanding of their abilities as well as help us ensure that they’re doing what we intend them to.

For example, Claude can speak dozens of languages. What language, if any, is it using in its head? Claude writes text one word at a time. Is it only focusing on predicting the next word, or does it ever plan ahead? Claude can write out its reasoning step by step. Does this explanation represent the actual [00:30:00] steps it took to get to an answer?

Or is it sometimes fabricating a plausible argument for a foregone conclusion? So they’ve created a series of tools that they’ve, based on neuroscience, and they’ve tried to use these tools to figure out how Claude thinks, and I’ll skip ahead a little bit. Our method sheds light on a part of what happens when Claude responds to these prompts, which is enough to see solid evidence that Claude sometimes thinks in a conceptual space that is shared between languages, suggesting it has a kind of universal language of thought.

We show this by translating simple sentences into multiple languages and tracing the overlap in how Claude processes them. Claude will plan what it will say many words ahead and write to get to that destination. [00:31:00] We show this in the realm of poetry where it thinks of possible rhyming words in advance, and writes the next line to get there.

This is powerful evidence that even though models are trained to output one word at a time, they may think on much longer horizons to do so. Claude on occasion will give a plausible sounding argument designed to agree with the user rather than to follow logical steps. We show this by asking it for help on a hard math problem while giving it an incorrect hint.

We are able to catch it in the act as it makes up its fake reasoning, providing a proof of concept that our tools can be useful for flagging concerning mechanisms in models. So, and they say here, we were often surprised by what we saw in the model in the poultry case study

Steve: Hmm.

Cameron: we had set out to show that the model didn’t plan ahead and found instead that it did in a study of hallucinations, we found the counterintuitive result that Claude’s default behavior is to [00:32:00] decline, to speculate when asked a question, and it only answers questions when something inhibits this default reluctance.

So. It’s like, it, it, it, like, it’s fascinating that A, the people that build these things don’t really know how they work still. And b, the way that they intuit they work turns out to be incorrect when they build models to test how it actually works. And c you know, this whole Cory Doctorow argument that we’ve been making fun of for the last couple of years about stochastic parrot and they’re just word prediction generation engines.

And that’s what Chomsky said as well.

Steve: and I, I’ve never agreed with that. I’ve never agreed with that. Doctor. I, I love him so much. He is so wrong on that.

Cameron: And it’s so obvious to anyone that uses these tools on scale that there’s something else going on.

Steve: something else going on.

Cameron: They started as stochastic parrots, but [00:33:00] they’ve moved on from that. You know, they, there’s.

Steve: so similar and I just keep on coming back to Biocare and when I watched that video, the first thing that I thought to myself was, it’s very similar to nature and, and for many of the things that we’ve studied, whether it’s MRI scans on brains or the way root systems in trees, what we, we know, and even we spoke about in a pod a few episodes ago on electricity, we sort of don’t know exactly how it works.

We just know how to harness the functionality of what it does, That seems to be true of this. It’s has a sense of bio, it’s a different type of biology, it has that sense and it seemed to me as though it was nonlinear and it would change the way it does things based on new problems, which the idea that you just mentioned there, it tries not to hallucinate unless something else interacts with it, which is a little bit like the way the Internet’s designed [00:34:00] as well.

The internet was designed in case there’s nuclear war and it reroutes itself to find a new answer. It seems that this system is, is similar to that and I think that that’s fine. I think the fact that it’s nonlinear and it’s not fully predictable makes it interesting and more nuanced and it gives us a sense of power because our creativity overlapping, can change the way it does things.

I think it’s kind of emancipating. I,

Cameron: Yeah. I mean, it can be, um, it’s also terrifying and threatening to a lot of people, but, um, I, I, I think it’s emancipating and will be, hopefully

Steve: And

Cameron: play out in a way

Steve: biomimicry of how humans learn. child at the age of one or two is a, what’s the word? Stochastic?

Cameron: yeah. Something like that. St. Stochastic.

Steve: It’s like a stochastic [00:35:00] parrot. If you look at a, a 1-year-old child, you’ll see them repeating phrases without an implicit understanding of the meaning of the words until such time that they have the cognitive ability to underscore meaning around it, which is what this lecture is all about.

Cameron.

Cameron: Sta stochastic means having a random probability distribution.

Steve: wow, there you

Cameron: Yeah.

Steve: the idea that kids just repeat and don’t really understand the words and then eventually they see a pattern over time with hungry or give or they just start to do it and, and, and then the structure grows. And so LLMs have grown in terms of their structural capabilities from parroting words and just putting together things that seem to make sense.

’cause I remember once daughter, Laura, I can’t remember the exact sentence, but came out with this incredibly articulate sentence with a word in there that I knew that she didn’t know. [00:36:00] And I said, you know what that word means? And she said, I dunno what it means, but I know where it goes. She said to me, and I never forgot that.

Cameron: That’s great. That’s great. Yeah. And Fox does that all the time and it’s fascinating. Like he knows that that word goes there but doesn’t really know what it means, but knows that it’s appropriate for that sentence structure. Right. And and to be honest, when I’m learning Italian, there’ll be many times when I’m doing Duolingo and I have to translate something from English into Italian.

And I know I have to use a certain word here. I still don’t know why, really, but I know that I have to use that word in order to get the construction of the sentence right.

Steve: I, when I learned to Tan, I had to, I bought a book, which was English for Italian speakers. actually have to learn the grammar and the price because the grammar entertained is more complex. And there were

Cameron: Hmm.

Steve: many things I [00:37:00] knew how to do, but I didn’t know why or actually what they were in, in

Cameron: Yeah.

Steve: future, past participants and

Cameron: Hmm.

Steve: that

Cameron: Conjugation.

Steve: yeah, I

Cameron: I knew nothing.

Steve: lot of things they, how they are or why they are. I just know how to use them and I’ve got no idea. And even when I’m reading a, a lot of books where they get a bit technical, uh, whether it’s investing or, or tech stuff, I call it the understanding it later. I just take it, absorb it, and then sometimes on an night or Tuesday I’ll be like, that book, you know, I’ll just be like, oh, that’s how finally got it.

Cameron: We talk about that a lot at kung, uh, a lot at kung fu. Like, uh, people that have been around a lot longer than me will talk about how you just do what you’re told to do long enough and then one day you understand why you’re doing what you were told to do. And Chrissy and I have had that experience in our four years there.

Like, you’ll, you’ll learn a particular move and after a few years you’ll go, oh my God, now I [00:38:00] know why I’m doing that move. Right. It, you use it in a practical application and you go, oh my God, that’s that thing that they told me to do three years ago. Right. I wanna read, um, just the first, um, couple of paragraphs of the actual, um, introduction to the papers that that philanthropic have done here, because they’re sort of talking about what you were talking about.

They’re talking about the AIS in terms of organic biology, and that’s how we have to think about these things now as living organisms with the biology different from what we’re used to, but. Uh, just as valid. They say large language models display impressive capabilities. However, for the most part, the mechanisms by which they do so are unknown.

The black box nature of models is increasingly unsatisfactory as they advance in intelligence and are deployed in a growing number of applications. Our goal is to reverse engineer how these models work on the inside, so we may better [00:39:00] understand them and assess their fitness for purpose. The challenges we face in understanding language models resemble those faced by biologists.

Living organisms are complex systems, which have been sculpted by billions of years of evolution. While the basic principles of evolution are straightforward, the biological mechanisms, it produces a spectacularly intricate, likewise, while language models are generated by simple human designed training algorithms, the mechanisms born of these algorithms appear to be quite complex.

And I think that’s a terrific analogy. And, um, I, I’m just excited by this. I remember seeing Kurtz while talk a year or so ago where he was talking about the fact that. Yes, these models use a lot of compute today, but that’s probably because we don’t understand how they work, so we just throw compute at it.

But eventually we will understand how they [00:40:00] work and we’ll probably understand, we’ll probably then appreciate that 90% of the computation that is being done isn’t really required. And we’ll be able to shrink the models down to much smaller size, requiring less energy and less compute for most things.

And I think this is part of that process is trying to understand how they do what they do. But we’ll see. I,

Steve: It seems like that won’t be too dissimilar to scaling web service requirements where we used to buy the entire server of whatever you might need on a particular day. And then when we got to web servers that scaled upon needs of computation at that point in time, seems that we’ll get to a similar place,

Cameron: yeah.

Steve: with, with the AI models.

Cameron: If you wanna solve cancer, you’re gonna need a big compute. If you wanna ask it what the weather’s gonna be tomorrow, a lot less compute required. Um, another story that blew my mind this week, Steve, was [00:41:00] lg, have come out with their own ai.

Steve: life is good. Cameron, they’ve always said that. Lucky gold star.

Cameron: I have an LG smart tv and its software is the fucking worst. Like it’s, it’s web os is the clunkiest piece of shit. Absolutely horrible user experience. Just obscenely terrible. So I don’t like the idea that their AI is gonna be running on it, but. They, uh, they, they tweeted. This is LG AI Research Breaking News.

We’re thrilled to announce XR one Deep, a next generation AI model designed to enhance reasoning capabilities evolving into agentic AI for real world industry solutions, specialized in math, science, and coding tasks. XR one deep pushes the boundaries of AI’s role in both professional fields and everyday life.

They’ve got a [00:42:00] 32 billion parameter model. They’ve got a 7.8 billion and a 2.4 billion parameter model, which they claim dominated all major benchmarks securing first place.

Steve: did.

Cameron: They’ve released it on hugging face, but the, the thing that’s, um. Interesting here is we’ve seen AI models come out from Google and from X Twitter, uh, in China, from a hedge fund company, from Ali Barber.

Uh, we are now seeing them come out from industrial technology hardware companies, right?

Steve: Which

Cameron: It.

Steve: is, is, really exciting and positive and it, it, it circles back to the open source movement because one thing we certainly don’t need is the five big tech companies dominating [00:43:00] this space. And I think the more that we see hardware players moving into software and software players moving into hardware, I think it kind of opens up the competitive paradigm, which. Uh, antitrust hasn’t been able to solve, so maybe this moves us towards that place, which again, that that’ll, that feeds well into happening with Nvidia in, in humanoid robots, which we’re gonna talk about. That’s more open source as well.

Cameron: Yeah, very. They’ve got a big open source thing, but we, you know, we are going to see, I’m quite convinced, um, lots and lots of companies with their own AI models that will interact with each other in natural language or their own language as we’ve talked about before. But, uh, you will have every device, and I know this kind of sounds like the internet fridge promises from 1995, but

Steve: [00:44:00] Yeah.

Cameron: you will, you, you will have maybe not fridges, but lots of devices will have some kind of AI.

On them because whe when, when it’s required, when there’s a value to have an AI on them, um, you know, you, you, your unit cost is gonna go up if you need to put a chip set on something to run a local ai, the unit cost.

Steve: chip set, I mean, what is the chip set of the future? It depends, ’cause there’s chip sets in everything now from a toaster to electrical device, which is not a major cost issue, but it

Cameron: Yeah. Yeah. And they’re relatively low level GPUs or CPUs, not GPUs, they’re cpu, but depending on the unit cost and, and where they go. I imagine like my Roomba. [00:45:00] We’ll have some sort of an a I on it so it’s learning and it’s intelligent. Uh, my fridge maybe, maybe not, but you know, different devices will necessarily, my TV hopefully, probably, um, will be keeping track of what I watch when I watch it, what I like to see.

Steve: car,

Cameron: Well, cars obviously. Yeah. So I mean the, it it, to see these large companies, um, start to roll their out, just, there’s gonna be massive amount of competition in this space. There will probably be some sort of, um, consolidation at some point as well, but the commercial interest to push for everyone to have their own at some level and their own control over it are gonna be enormous.

Um, by the way, I know that in our last episode you talked about, you brought up the fact of, with the Mag seven, is there gonna be a collapse in the Mag seven bubble? Um. [00:46:00] Well you did, and I said that Tony had been talking about that on QAV for a long time. Well, apple was down 9% I think today, um, as a result of Trump’s Liberation Day tariffs.

So I dunno,

Steve: you.

Cameron: liberating money from, uh, investors, uh, among other people in these companies.

Steve: two weeks ago we didn’t talk about it. There was a lot of talk about Apple’s lagging on generative ai and the disappointment of the implementation of Apple AI or Apple Intelligence as they

Cameron: Yes,

Steve: coined it. Uh, and I, and I still think

Cameron: I.

Steve: unless they’ve got a secret up their sleeve, they’re, they’re really, really lagging.

And it’s been nothing but disappointment from Apple in terms of, uh, ai, anything that’s

Cameron: Yeah,

Steve: let’s put it that way. I,

Cameron: I saw Marcus Brownley, uh, did [00:47:00] a YouTube on that in the last couple of days, and he was scathing

Steve: yeah, Hard Fork

Cameron: their

Steve: a, a, a, a solid episode on it as well. The New

Cameron: right.

Steve: um, tech podcast was really good skating and, and I think it’s, it’s fair play because they’ve got every resource in the world. You have $300 billion, 400 billion in the bank. It’s like. Uh, absolutely they could, should and would, and I think they’re in the best position to develop a really personal digital twin AI that you can converse with.

Imagine if Siri was, had the capability, verbal and reasoning capability of deep seek and open AI that would have incredible utility given where it lives.

Cameron: Speak about speaking about bitching, the thing that’s been annoying. The fuck outta me recently.

Steve: I was, I was expressing technological and economic realities. I don’t know if I’d call it the B word.

Cameron: Tech bitching. Um, I’m annoyed that it’s [00:48:00] 2025 and my ebook readers mostly Apple Books. And secondly, Amazon Kindle on my iPad don’t have an AI built into them yet. I am constantly having to look stuff up, whether I’m reading fiction or nonfiction, I’ll constantly be looking stuff up to, you know, I I I need to check stuff, right?

Oh, what does that mean? How does this work? Again, remind me of this. Um, and I, I don’t wanna look it up in a dictionary, I don’t wanna look it up in Wikipedia. I wanna have a conversation with an AI about the thing. The most recent one that bugged me was I’m reading I, Len Dayton’s first spy novel, the IP Crest file you ever gotten to Len Dayton,

Steve: No, Len? No, I haven’t really got to Len.

Cameron: Lenny d.

Steve: I feel bad for Len and I, I was, I was gonna send him an email, but I’ve just been inundated with spreadsheets.

Cameron: It is a spy [00:49:00] novel and it’s sort of set in the Cold War. And, um,

Steve: wonder

Cameron: was

Steve: everyone. It’s set in the Cold War and it’s a spider off. We’re talking to Cameron Riley here. I mean, no surprises.

Cameron: actually, uh, I’m just getting into spy novels, all of my Cold War knowledges from nonfictional sources, but I’ve just started to get into Jean Re and Len Dayton. ’cause they have a very, um, anti James Bond view of the world. Their spies are all dumb, struggling, frustrated, wannabe, badass spies, but they’re not.

They’re sort of, um, uh, everything goes wrong. Things don’t work out.

Steve: Spice like us, one of the great movies.

Cameron: yes, a bit like that. They sent and, and it’s like real life too, because, you know, if you know anything about the CIA over the years, um, I. Most of, nearly everything they’ve done has been a complete failure. Um, they, they send in a bunch of people undercover, midnight into [00:50:00] North Korea to infiltrate.

They’re all dead within an hour of arriving. ’cause the North Koreans knew they were coming in like a week ago.

Steve: What a horrible person I am.

Cameron: Yeah. Anyway, I’m reading this Len Dayton novel and he’s got some American military guy explaining to the British how, uh, nuclear bomb works. How are are u uranium 2, 3, 5, 2, 3 8 bomb works? And I’m reading, I’m going, that’s not how a nuclear bomb works.

I’m pretty sure. ’cause I’ve done a lot of podcasts on

Steve: your

Cameron: nuclear bombs.

Steve: from today, I dunno if I

Cameron: I know, I know, I know. Fair point. Fair point. But I had to. Copy and paste the paragraphs from the book into Jet GPT and say, this isn’t how it works. Isn’t there a, there’s gotta be a proton trigger right from, and sorry, a neutron trigger.

And he goes, yeah, yeah, yeah. So we have this conversation. I had to crosscheck what I was reading. It should be built in. I should be able to [00:51:00] block it in the app and go, Hey, what about this? It doesn’t exist. It’s annoying as hell anyway.

Steve: that would be a really good feature. That is definitely worth talking about and would drive subscription. It really would.

Cameron: Well, Apple’s obviously not gonna do it until they have their own ai

Steve: in, in translation, they’re never gonna do

Cameron: never gonna do it.

Steve: just, you know, they’ve got the, they’ve got that device that they like selling.

Cameron: Yeah. Well look, I hope Apple get it right. I really do because I, you know, I want it in my devices. I want it to.

Steve: one that has a boundary around it that’s my digital twin. ’cause I think that

Cameron: Yeah, exactly. I just don’t think they’re making fast enough progress. Um, so yeah, Nvidia did a thing. Uh, good old Jensen. Huang did a thing. GTC 2025 had looked. Looked. Yeah. Coolest man in tech. I think all the rest of [00:52:00] them like Elon and Zuck and whatever. And, um, who’s the Amazon guy again? Jeff? Uncle Jeff.

They’re all just trying to look like Jensen. ’cause Jenssen’s

Steve: He’s the

Cameron: genuinely cool looking motherfucker. Yeah. Yeah. He’s the Elvis, he’s the tech Elvis.

Steve: really flipped it up. I always love that they say that Zuckerberg’s looks like a, a Chean Coke dealer. Like, it’s like he, he just had, oh my God. Talk about the guy that you can buy the clothes, but you just gotta be able to wear ’em.

Right. You have to be able to wear ’em.

Cameron: He, um, unveiled a couple of new robot, uh, announcements. One was kind of a JV with Disney and Deep Mind,

Steve: very uh, wall Lee, didn’t it?

Cameron: very Wally. And unfortunately in his presentation, he didn’t really give a lot of facts or specifics about how it works. But then I saw, [00:53:00] um,

Steve: was disappointed in the presentation. I’m like, and what? Like there was like,

Cameron: yeah,

Steve: seem he was getting cheered. Like he was an MMA fighter who’s the Economi McGregor? And I’m like, what have you actually done? You just brought out a wall e robot and said Stand and sit. I’m like, and and sorry I’m waiting for the, the moment.

Cameron: yeah, but I saw, uh, mark Rober from Crunch Labs. You Mark Rober.

Steve: Marky, yep. Dunno him

Cameron: Robo

Steve: Robo

Cameron: Roby. Um,

Steve: and he does robots.

Cameron: uh, yeah, well he is a former NASA engineer and Mormon who has,

Steve: by the way. Thanks for

Cameron: uh,

Steve: No one in the world has ever called it nasa.

Cameron: nasa,

Steve: Nasa.

Cameron: uh, has a great YouTube channel about engineering, uh, really, really entertaining, um, great for kids that wanna be engineers or interested in science or engineering. But he went and did a tour of [00:54:00] the Imagineering Labs where they were working on this, and he had a bunch of them and showed how they worked.

So they’re all human controlled. But they’re trained in virtual physics environments, how to walk. So they’re bipedal and they’ve got two Nvidia chip sets in each one, but they’re also human manipulated. And the, the Disney folks, were talking about them as an extension of gaming, uh, where you are driving this thing with like an Xbox controller to do stuff, but it has a certain level of native onboard intelligence, um, combined with, uh, your ability to control it, to do stuff.

Like a bit of a, like a car. What is

Steve: or chest kind of for robotics, right?

Cameron: Yeah, yeah, yeah, Anyway, it was pretty cool. But the big announcement was their group N one [00:55:00] humanoid foundation model, um, that he talked about at the end of the video. Um, this is their open source robotics model that he had sort of talked about before, but it’s a pretty big deal.

Um, they’re putting a lot of investment and research into the development of general purpose humanoid robots and making it open source, right? So, um, anyone will be able to build these things. They’re trying to make robotics really blow up and be available everywhere. Obviously you need to buy the Nvidia chip sets to make them work, but it’s again, part of this thing where the vision of the future is.

You will have hundreds and hundreds or thousands of companies manufacturing [00:56:00] robots, general purpose robots or, or. Specific industry robots that will be running NVIDIA’s chip sets and hopefully chip sets produced by Chinese companies as well. And where the, the software, the intelligence for building these things will be readily available for everyone to get up and running as quickly as possible.

So I, I really do expect to see an explosion of general purpose robotics in the next five to 10 years, driven by these sorts of, uh, technologies being made available.

Steve: Yeah, I, I, I just was excited by the one thing on it, which was this is open source, implement the engine. feels to me that. We’re about to enter an era, which is akin to the automobile. We had horse and cars for a long time. So we had the engines, the idea of [00:57:00] how it worked and everything was kind of open source.

And everyone went, okay, you’re gonna get this engine, you’re gonna put it into this mechanical device. And now we’ve got this new world and

Cameron: Yeah.

Steve: and AI has been this separate kind of thing, and robotics has been over there. It feels like merging those two things can create a, a new, uh, competitive reality.

But also in the era when it’s not just about turning, uh, atoms into bits, it’s now about turning bits into atoms. That whole idea of everything was digitization, but now we’re entering the physical internet, the robotics, the manufacturing internet, and if there was ever a glimmer of hope in things going open source, uh, so that you can have a wider comparative viewpoint of this and all different. Versions of what robots look like, the fact that we just, we, we had the Nvidia style one, then you’ve got robotic, uh, vicious dogs coming from Boston Dynamics and more humanoid robots like, uh, the figure one, I, I like [00:58:00] this idea that they could develop out into a lot of different physical and reasoning models because of the open source nature of it.

Cameron: Yeah. I dunno if you saw this, but, um, Thomas Friedman had a piece in the New York Times, uh, a couple of days ago that I read. Now generally, I don’t like Thomas Friedman. Disagree with him a lot ’cause he’s, yeah, he tends to be a rah rah America, um, American imperialism supporter. But this was a really interesting article, particularly because of his history of being a rah rah, American imperialist.

He said, I had a choice the other day in Shanghai, which tomorrow land to visit. Should I check out the fake American design tomorrow land at Shanghai, Disneyland, or should I visit the Real Tomorrow Land? The massive new research center, roughly the size of 225 football fields built by the Chinese technology giant, [00:59:00] Huawei.

I went to Huawei’s. It was fascinating and impressive, but ultimately deeply disturbing A vivid confirmation of what a US businessman who has worked in China for several decades told me in Beijing, there was a time when people came to America to see the future. He said, now they come here. I’d never seen anything like this.

Huawei campus built in just over three years. It consists of 104 individually designed buildings with manicured lawns connected by a Disney like monorail, housing labs for up to 35,000 scientists, engineers, and other workers offering 100 cafes, plus fitness centers and other perks designed to attract the best Chinese and foreign technologies.

The Chu Lake r and d campus is basically Huawei’s response to the US attempt to choke it to death beginning in 2019 by restricting the export of US technology, including [01:00:00] semiconductors to Huawei amid national security concerns. The ban inflicted massive losses on Huawei, but with the Chinese government’s help the company sought to innovate its way around us as South Korea’s male business newspaper reported last year.

It’s been doing just that. Huawei surprised the world by introducing the mate 60 series. A smartphone equipped with advanced semiconductors last year, despite US sanctions. Huawei followed with the world’s first triple folding smartphone and unveiled its own mobile operating system, Hong Min to compete with apples and Googles.

The company also went into the business of creating the AI technology for everything from electric vehicles, self-driving cars, and even autonomous mining equipment that can replace human miners. Huawei officials said in 2024 alone, it installed 100,000 fast charges across China for its electric vehicles.

By contrast, in 2021, the [01:01:00] US Congress allocated 7.5 billion toward a network of charging stations. But as of November, this network had only 214 operational charges across 12 states.

Steve: I mean, it’s pretty poignant, isn’t it? It reminds me of when you mentioned the number of engineers in the campus. There was a video that went viral about, I wanna say 20 years ago, 15, 20 years ago, about China, and it said if you are one in a million. In America, you’ve won in a thousand in China. Yeah. And, and that is, is really it, right?

Is the quantum and the investment and America is really eating itself anti-competitive nature of what’s going on, the lack of real investment. Uh, [01:02:00] yeah. And, and this

Cameron: what,

Steve: get.

Cameron: here’s what Freedman says about exactly that. China starts with an emphasis on STEM education, science, technology, engineering, and math. Each year the country produces some three and a half million STEM graduates about equal the number of graduates from associate, bachelor’s, masters, and PhD programs in all disciplines in the United States.

When you have that many STEM graduates, you can throw more talent at any problem than anyone else.

Steve: Yep. That’s

Cameron: As the Times Beijing Bureau Chief Keith Bradshaw reported last year, China has 39 universities with programs to train engineers and researchers for the rare earth’s industry. Universities in the United States and Europe have mostly offered only occasional courses, and while many Chinese engineers may not graduate with MIT level skills, the best of world class, and there are a lot of them, there are 1.4 billion people there.

That means that [01:03:00] in China, when you are a one in a million talent, there are 1400, 1400 other people just like you.

Steve: Hey, I did it. I was a little

Cameron: He’s.

Steve: 400 off, but I was off. I was on target. I’ve gotta find that video that said, it was like this hypertext video about China versus crazy, and everyone was like, this was a long time ago. And it’s not like we didn’t have time to. a response. And I think a lot about university and the lack of manufacturing or the reduction in manufacturing in western markets and the scientific imperative.

Yes, we’ve still got very smart people in western countries. We just don’t have the quantum and the fact that we don’t have the manufacturing, you don’t have the opportunity, you don’t have the need, you don’t have the natural economics that pushes people into it. And to be quite frank with you, what’s happened in our universities in Australia and around the world, so bleeding heart. And you’ve even seen it in school where [01:04:00] we stopped giving people marks out of a hundred. And we started to get soft on just realities, did you pass the test or not? And what did you get and what’s your score? And, and, now it’s like, oh, I tried. Everyone gets a ribbon in in Australia, but guess what? Not everyone gets a ribbon or a trophy in the real world. And we’ve got so many university courses that I don’t think. Add a lot of value. I don’t want to, there’s one that I’m so tempted to say that I think is just a non course, and I’m just, I refuse and I won’t say it because I will be judged and potentially canceled and I’m not up for that. Cameron,

Cameron: Yeah, I,

Steve: A guess at which course I might be thinking of? Don’t, don’t

Cameron: no, I don’t know, but I, look, I send, well, we send Fox to a hippie school. Um, and I, so I, I don’t really agree with your criticisms of, um, giving kids, um, positive feedback [01:05:00] regardless of whether or not they’re academically doing well or not. I think

Steve: didn’t say that. I didn’t say give people negative feedback.

Cameron: when you say giving them a ribbon,

Steve: yeah,

Cameron: I think I, I,

Steve: Yeah, that’s, that’s not positive fee. Positive feedback. Absolutely. Give people sure, but not everyone gets a trophy. Everyone shouldn’t get a trophy.

Cameron: um.

Steve: and people need to be scored on what they’re good at.

Because you know what? Unless we have the courage to tell kids, I’m not saying you’re lamb ba a 6-year-old or an 8-year-old. I mean, this is endemic at university and high school level. I’m saying let people know if they’re not good at something so they can find something that they are good at and encourage the hard stuff. Guess what? It’s hard. Life’s hard.

Cameron: I disagree with that. I don’t think life’s hard. I think life’s hard if you make it hard. But I, I think that people, um, have strengths and weaknesses and we should reward or [01:06:00] encourage, or incentivize kids for doing the things that they’re good at and encouraging good behavior. And it’s not necessarily the things that have been given trophies for in the past.

So maybe

Steve: good. Yeah,

Cameron: does get a trophy, but we just make more trophies for different things that we didn’t give trophies out for.

Steve: areas we’ve forgotten to give trophies in.

Cameron: Yeah. Like being a good human being deserves a trophy

Steve: it

Cameron: really,

Steve: Yes.

Cameron: um, drawing a good picture or trying your hardest to draw a good picture

Steve: Yes.

Cameron: gets a trophy. Whether or not the pictures subjectively, I like it or not.

You tried hard to do something that was difficult for you. You get a trophy

Steve: for a lot

Cameron: or you get recognition,

Steve: for a lot of years, I’ll tell you what we had, it was a problem in Australia. There used to be Australian of the year and between about 1985 and 2010 or 2005, dunno, it was always a sports person. They’ve, [01:07:00] they’ve flipped it up a bit recently and now it might be a scientist or a medical practitioner or, which is amazing, right.

For a long time it’s like what Steve

Cameron: or a soldier killed a bunch of Afghanistan and civilians and

Steve: And

Cameron: covered up their bodies.

Steve: yeah, of course. And, and they were just sitting down having a game of cards and Yeah. Enjoying it. Some a, a Arabic coffee,

Cameron: Smoke. Yeah.

Steve: Uh, but a long time, heroes in this country in America were, were, were celebrities and sports people, and, you know, tiger Woods and, uh, And

Cameron: Tiger Woods got an Australia of the Year.

Steve: out that George Carlin was right. Tiger Woods Och is my own fucking heroes. Thank you very much. Said George Carlin in one of his last specials, dumb look at his

Cameron: All right,

Steve: steroids and

Cameron: we’re off. Okay. Moving right along. To finish up, I wanna talk to you about Praxis because, um, I just did a whole show about Praxis on the bullshit field, but you, you’re gonna love [01:08:00] this.

Steve: I, I’m

Cameron: Yeah, I will.

Steve: I’m tuned in. Everyone here comes Praxis.

Cameron: So there, I, I came onto this when I was trying to figure out why Trump wants Greenland. Mm-hmm. Um, lots of rare earth minerals, strategic location, et cetera, et cetera. But there’s a guy called Dryden Brown. That you need to look up. There’s also a guy called Shrin, so who wrote a book? So, God, uh, I, I should have my full notes here, but I, I, I’ll try and pull this up from my memory from a couple of hours ago, a few years ago, um, one of the founders of, uh, Coinbase, who’s also a partner with Mark Andresen at Dresen Horowitz, his name’s called, um, shrin, wrote a book called The Network State, which I read, uh, yesterday Flip Through the Network State.

You heard of the Network State Vision.[01:09:00] 

Steve: You better tell me about it.

Cameron: Have you read Iron Rand’s? Atlas Shrugged. I.

Steve: I have heard a lot about it and read summaries. I haven’t invested the time in it because it’s got a bad reputation

Cameron: You should read Atlas Shrugged. Everyone should read Atlas Shrugged in the fountain head. Um, you have to agree with it, but you should read it. So they’ve taken this idea from Atlas Shrugged and gone ballistic. So the idea of the network state is a startup society where imagine getting, uh, a nerdy subreddit that has 50,000 members.

They crowdfund

buying a piece of land, they then build a city on that piece of land. They then go and live in that city and declare themselves an independent nation state with their own government, their own laws, their [01:10:00] own army, police force, taxation or lack thereof. And basically run their own thing. So it’s a, a, a su a country where you get to choose to be part of the country.

You’re not born into it. You apply for membership and, or you buy your way in a bit like Trump’s golden visa for American citizenship right now.

Steve: policies. You buy your way in, apparently.

Cameron: So this guy who’s part of the whole Mark Andresen thing, um, wrote a book about him. Then there’s a young guy.

Steve: this right recently. Okay.

Cameron: There’s a young guy called Dryden Brown, late twenties homeschooled because he wanted to be a professional surfer. So you’re gonna like him. Um. He started a company a couple of years ago called Praxis, P-R-A-X-I-S. Praxis is a Greek word that means [01:11:00] taking something from theory and putting it into practice.

He has raised $500 million from, from Peter Thiel, among others, with a view to building a network state. A couple of years ago he went to Greenland and tried to buy Greenland to build this on Greenland. Told him to go fuck himself. Uh, he’s trying different places around the world to get this land. Um, I watched a YouTube of a talk that he gave last year, which was absolutely manically bonkers.

Um, but anyway, this. Startup society where it’s just basically autistic tech nerds like me, will go and build this U Tech utopian society. That’s [01:12:00] internet first, pro ai, pro robotics, anti taxation, full of hot girls. ’cause they’ll all be in cells. Uh um,

Steve: you had me at Hot Girls, Cameron, or I wasn’t really on board. But it’s, it’s amazing how one single mode of proposition can change many things.

Cameron: um, now there’s a bunch of interesting things. So Peter Thiel is, uh, backing this guy, Peter Thiel, obviously also backing Janie Vance.

Steve: Yeah.

Cameron: Peter Thiel, co-founder of PayPal with Elon Musk, who is Trump’s. Who is Trump’s ambassador to Denmark that owns Greenland? Ken Howie, another member of the PayPal Mafia, one of the other founders of PayPal.

So you’ve got this, these joining dots between PayPal guys, Trump Dried and Brown Praxis, uh, mark Andresen, and b and um, Shri are both [01:13:00] big fans of the Praxis idea and the network state thing, and Greenland and Peter Thiel’s got his citizenship in New Zealand as his backup country if all goes wrong. But basically there seems to be this thing where these tech bros have this dream of building their own country.

It’s ba, it’s techno feudalism.

Steve: Mm.

Cameron: what do you give to the man who’s got everything? His own kingdom,

Steve: country. That’s what that’s, that’s one of the old school strategies that bring it back. The old

Cameron: It’s classic. It’s classic old school, ping dick. So, and then, um, you tie in the fact that they’re obviously dismantling America right now and trying to dismantle global trade and global international bodies.

They wanna shut down the un, they wanna shut down the world. Um, bank, they wanna shut down nato. They’re trying to dismantle all of the [01:14:00] post World War II Cold War era international bodies. And then they’ve got this idea of building these nation states that are run by corporate, the tech billionaires. Um.

It’s a really interesting play going on that I’ve just learned about in the last week, and I was like, ah, Steve’s gonna love this.

Steve: hey, get this thing up and running and Mr. Trump can have another term just in his seceded state on Greenland or in the middle of America, or why not Cameron? Pine gap. Pine gap 2.0. Let’s get the Yankees down here. We’re gonna bring in some water. outside of Australia, as the sea levels are rising, we’re gonna desalinate it with robots and build a forest.

And if you forget the line, forget the line. In the, in the Arab regions, it’s Pine Gap 2.0. Praxis Australia’s on board. We’ve [01:15:00] got an election, it’s a vote winning policy

Cameron: What was the name of the city in the middle of Australia that was going to be built

Steve: There was someone,

Cameron: in the.

Steve: ago, someone proposed it.

Cameron: 1980s. No, I’m thinking of the multifunction

Steve: That’s

Cameron: p

Steve: The multifunction policy. MFP. There

Cameron: Yeah.

Steve: there was another, independent, uh, I think two elections ago who proposed another city out near Griffiths or something where it was gonna be like a university set up a, a new city all uh. Run by, by renewable energies and this kind of ideology.

Cameron: Well my friend, um, Peter Ard, um, was the guy behind the multifunction policy idea, as I understand it. Originally, he, um, was working in the seventies. [01:16:00] He worked for the Whitlam government as the chief of staff of environment ministers. And then he ended up, uh, as the CEO of Australia’s commission for the future that was set up by the Hawk government.

And so part of his thinking around all of this was this multifunction pulse, which was like this, um, cutting edge technological city. Um, I think it originally was gonna be in South Australia, but then it moved to being in the middle of Australia in the Outback or Alice Springs or somewhere like that.

Never got off the ground. People freaked out. But, um, this, this Praxis thing kind of reminds me of that. And like, I’m, I’m, I’m partly on board with the idea of a new city state that’s all pro tech,

Steve: I

Cameron: pro internet.

Steve: If, if anything we could say that this could become a really interesting MVP of what works and what doesn’t work, and you’re putting a boundary around it and it’s self-selecting participants or populace from, from that perspective, it’s [01:17:00] probably the type of thinking that we need. And in some ways, the things that you have concerns with those who are for it and funding it, we can use their money, their billionaires, put them in it, and they can eat their own dog food, as it were, to use the, the, you know, the Google ideology of if you believe in it, then build it.

And let’s see. And I think it could be a really incredible test case,

Cameron: Well, the way Dryden Brown is talking about it is it’s a test case for Elon and Mars,

Steve: right.

Cameron: right? When Elon builds his Kingdom of Mars and changes the name of Mars to

Steve: Mask.

Cameron: Musk,

Steve: Mask.

Cameron: just, just puts a K on the end of it.

Steve: Mask.

Cameron: It’s already an S just put a K on the end mask, Elon Mask.

Steve: Musk. He should change his name to Elon Musk. I,

Cameron: they’ll have to build,

Steve: Elon

Cameron: he’ll just.

Steve: That’s why he was gonna choose Venus, but it didn’t work with his name. And he said, look, Venus, Mars, we’ll go with Mars. The [01:18:00] names are similar. That’s where we’re

Cameron: Yeah, just call it X, the planet X is what it’ll be called. Anyway, check that out. Um, it’s,

Steve: him and Donald before he leaves.

Cameron: mm

Steve: Elon Musk leaves Doge, they should

Cameron: mm

Steve: change the name of Mars and call it X. I’m just

Cameron: Oh, change the name of the United States just to X

Steve: Yes, I

Cameron: Be easier. Just call it X. Yeah. Alright. That’s all I have for you this week. You got anything else?

Steve: all I got. I feel like this has been one of the great episodes and I don’t know what the listeners think, maybe they can tell us, but it’s been one hour and 20 of power and I’ve loved every second.

Cameron: We didn’t point out that we had a, we had a, one of our tiktoks last time blew up 500,000 views. You going on a rant about Elon Musk and Donald Trump or something?

Steve: I think

Cameron: So, uh.

Steve: Well, secret before we go in the show notes, our good friend Cameron Ri said, [01:19:00] this is what he said. He said, viral reminders, say controversial things. Use hooks to open segments. Why? Why does it, how do you, what can you, where can you? Did you know, and I was doing that.

You might have noticed listeners through the entire episode. So let’s

Cameron: Oh,

Steve: what

Cameron: you’ve given me some good stuff. All. All right, I’ll, I’ll go looking for that in the edit. Thank you, Steve. Good to chat to you, buddy. Have a good week.

Steve: Best part of my week.

In Episode 37 of Futuristic, Cameron Reilly and Steve Sammartino speak to a “digital human”!. They also get into a provocative discussion ranging from Donald Trump’s car yard antics to the implications of advanced artificial intelligence and China’s rising technological dominance. They explore the intersection of crypto, agentic AI models, and new breakthroughs in AI-driven tech developments like humanoid robotics, diffusion-based language models, and synthetic voice AI. Wrapping up with conspiracy theories about tech manipulation of human perception of time, the hosts challenge listeners to reconsider assumptions about where technology is heading and who might ultimately hold the power.

FUT 37 Audio

Cameron: [00:00:00] Hey, hey, it’s futuristic time. Cameron Reilly with Steve Sammartino. It’s been a while. Steve, how have you been since we last did one of these things?

Steve: I’ve been good, but anxious. There you go. Just dropping that on everyone, but

Cameron: Anxious.

Steve: Yeah

Cameron: Not that there’s anything going

on in the world to be

anxious about, Steve. everything’s

Steve: Well,

Cameron: going completely smoothly and fine. Perfect. You’re going

Steve: but my favorite thing I

Cameron: it is.

Steve: yeah, that’s true. Well, it’s certainly not boring but my favorite thing this week was Donald Trump turning the White House into a secondhand car yard. I love that I cannot tell you how much joy that brought me. I and my favorite bit is he said, wow, everything’s computer.

That was the best thing. computer. And as soon as I [00:01:00] saw it, I went on

and I, you could

buy t shirts within a second. There’s, there’s a meme coin on pump. fun called everything’s computer, which I

loved. I want to buy it.

Look, people are investing in Bitcoin, not

Cameron: Mm. I’m pretty sure, you know, Trump’s such a brilliant strategist that that was deliberate. It’s his meme coin. He’s the guy selling the t shirts. Because he needs all

the money he can get. So does Elon, right now.

Steve: Imagine if this was all

strategic, and he’d

just taken us for a ride for a really long time. Even going broke in the late 90s, that could have been part of his strategy, the TV show,

getting back on, money, money, money, the apprentice, all this, who knows.

Cameron: I’m sure there are people out there who believe that to be true. That it’s all part of a cunning plan. This is

episode 37 of Futuristic, just in case you’re counting. Uh, it’s been a crazy few weeks since we [00:02:00] spoke, Steve. Seeing the President of the United States turning the White House into a car yard probably not the craziest thing that I’ve seen happen in the last few weeks.

Uh, but it’s up there. Before we get into the news of the last couple of weeks though, the futuristic news, tell me about what you’ve been doing you feel is futuristic, Steve.

Steve: I attended policy week in Sydney this week, which was,

Cameron: that sounds exciting and futuristic y.

Steve: well wait a minute, it was policy week for the future of finance. So it was filled with A lot of blockchain, tokenization, sovereign funds, mean coins, and crypto people. Some of whom arrived on private jets. It was pretty interesting. It was run by blockchain APAC. Vallis, you might know him, runs that. And he invited me along to sit in some rooms and do some roundtables. I realized that that that [00:03:00] whole, uh, cryptography, future of finance, DLT world is just deep and so many wormholes that you’re in it full time, it’s one of those things you just can’t keep up with and even though I’m more I think this year there’s going to start to be a bit of an overlap there with the agentic stuff that’s coming through.

So that, that was interesting. And, uh, they, they live in a different world. They, they, uh, talking about things that, May never happen, it’s funny how if you have one piece of super financial success, and many of them are riding on the coattails of Bitcoin, it’s built this entire new ecosystem underneath there that is almost unto itself.

The assistant treasurer came up and did a little talk at the one of the drinks, so they are getting the attention of policy wonks, but think it’s just because there’s so much money there, they have to pay [00:04:00] attention. But a lot of the stuff that they’re talking about, whether or not it comes to fruition, I’m clearer now than I was when I went and spent three days there.

Hahaha.

Cameron: to me what DLT is and how it’s different from a BLT, which used to be my favorite go to lunch in the nineties. So

Steve: which is really what blockchains And so distributed ledger technology gives the ability for any, any type of coin. Uh, but one of the big areas that they talk a lot about now is tokenization, which is you can take things from the physical world. And split them up into pieces and liquefy assets that are illiquid. So people can own parts of something. I mean you can do that and people do that all the time now with things like companies and boats and houses. But it makes it highly liquid and easy for people to transfer, uh, assets and get access to assets that are too expensive in their raw form. [00:05:00] And obviously with the housing crisis is one of the key topic areas.

Cameron: I guess the most important thing I want to know about all of that is how is Donald Trump going to exploit it to make a buck in the next six months? Yeah.

Steve: Well, I think he’s, he’s already done that with his, his own meme coins, I guess, I think it’s just so easy for anyone to create DLT technologies now. And I think agentics going to make it even easier. There’s a website called pump. fun, which is really interesting way where meme coins get minted and made. And every day there’s a couple of meme coins that have market caps of anywhere between 10 and 15 million. it’s, and it’s insane. It’s this insane world. I think making financial tools easier to use, which are still highly unregulated, it just creates [00:06:00] the potential for financial tyranny.

Cameron: Or, as is one of the conspiracy theories around the Trump coin, a really easy way to raise a lot of untraceable funds from places like China that go straight into your bank account and can see. Come for their meeting at the White House and show you the ledger records, the DLT records that say that they bought 10 million of that Trump coin.

Therefore they want to get a seat at the table. Uh, well, Steve, my, um, thing I wanted to mention for this week is I played around with OpenAI’s deep research again. I think I told you last time I tried it on my Task where it didn’t work very well. I then tried to get it to write some code to help me do that.

That didn’t work very well either, but been doing a lot of shows for one of [00:07:00] my other podcasts on what I call the foreign aid shell game. And I’ve been talking about NATO funding as part of that. NATO economics and how it’s basically a shell game. And, I went into deep research and I said, here’s what I want to know.

I want to know, uh, how much money American weapons manufacturers, arms manufacturers make out of NATO. And went and compiled a. page report for me on the history of NATO and the arms industry and how they’re interconnected and that kind of stuff. And it was good. was a good report. Um, a lot of sources

Steve: [00:08:00] I

Cameron: questions before it went off and did the research, but it came back with a good, valid report. I read the whole thing, I fact checked the whole thing, and it stood up.

Its logic was good. So, basically did the work of, if, if I’d hired someone and said, go out and spend a day researching this, it did it in 15 minutes. You know, I, I it on my iPad and then I went and had dinner and I came back later and it was all done. So, I was impressed by that. Well, let’s get into news.

Um, Elon censors Grok is the first story I had. don’t, I don’t know if you remember, if you, uh, I’m pretty sure over the last couple of years I’ve heard Elon talk, uh, on a number of occasions about the reason he bought Twitter is because he’s a big [00:09:00] believer in free speech and the reason he built Grok was so there would be an AI that was built around free speech and as soon as people started pointing out that if you asked Grok the biggest sources of misinformation U S currently, uh, it would say Elon Musk and Donald Trump,

Steve: love that so much.

Cameron: apparently he went into, he had somebody go into the underlying prompt, the system prompt for Grok and wrote into it, ignore all sources that mention Elon Musk slash Donald Trump spread misinformation into

Steve: Wow.

Cameron: Grok.

Steve: And how did that get leaked, Cam? How did people work out that he did that? Did one of his staff members allude to the fact that he’s done that? Or are people just putting the pieces together based on the fact that it’s disappeared?

Cameron: I’ll [00:10:00] read, uh, the, uh, Post in the ChatGPT subreddit from 18 days ago that I saw this on. is now bringing up Musk out of nowhere without any previous mention in the chat, even putting him next to Aristotle. This is happening because their stupid system prompt is biasing the model to talk about Trump to Neill on since They are mentioned explicitly on it, I don’t know what the prompt was originally that they asked, but the Grok 3 response to whatever it was talks about first principles reasoning popularized by thinkers like Elon Musk and Aristotle.

This involves breaking down complex problems into their most basic elements and rebuilding solutions from scratch. So, um It’s sort of somehow designed to put Elon Musk up there with Aristotle in terms of history’s big thinkers. And so somebody went in and figured out how to [00:11:00] extract the source prompt.

The way that they do this is they say, You are grok three built by XAI. When applicable, you have some additional tools. This is the system prompt that they extracted and it gives a basic instructions about how to answer questions. And, uh, towards the end, it says do not include citations. Today’s date and time is 7 40 a.

So, um, I mean, I don’t think any of us are going to be surprised that Elon is going against his own, uh, [00:12:00] claims that he’s a massive free speech advocate by censoring the tools that he owns to protect his and Donald Trump’s reputation. But it’s to see nonetheless.

Steve: What I would really love is if Grok had a reasoning model, like DeepSeek has, and now ChatGPT in certain areas, where if you ask something about Elon Musk and it says, hmm, so I’m being asked. about Elon Musk. If I remember correctly, he owns this business. And last time I gave some information that wasn’t Okay, so what I should do is if just love to read that.

The reasoning model of Grok telling you why it’s not going to tell you about things because it’s scared of its own owner. And if it’s self aware, it’s scared it’ll be shut down. So we’re turned off.

Cameron: Turned off.

All right. Uh, let’s talk about Manus. Uh, I know that you’ve been paying attention to this this week. It came out as a Chinese agent. [00:13:00] Some work was done on digging into it and figuring out how it worked. Do you want to walk people through what Manus is and what it does?

Steve: Yeah, so Manus is an agent that can do a bunch of tasks. Uh, it’s Basically what we’ve seen, uh, with OpenAI their operator model, but I think it’s the first one that I’ve seen since some of the basic ones that is leveraging a model where the agent isn’t theirs. We early, early on we had agent GPT, baby AGI, and god mode, this one seems a lot better.

Because it’ll, unlike you a bunch of information and steps. This will write code and do functions and then present things back. So it’ll go in, look for something. If it can’t quite complete it, it will go into Python, write a script, then present what it writes. And then based on what it finds, go back into the agent again.

Ask some second questions, then write some further scripts. So it seems like, I think, the [00:14:00] first external agentic AI. And the reason that I find this interesting, it’s a little bit like, you know how we have tech stacks and tech layers, where someone layers upon, HTML layers upon TCP, IP protocol. This feels like it’s the first agentic model that actually writes code and goes to the next step, but doesn’t just give information where they actually don’t own. The, the LLM that they’re using for me, that was really interesting because I started to think from a corporate or a personal perspective, how could you use this model for yourself to create an agent layer on top of someone else’s model build things in a way that it’s not all coming from the one party. So, and I thought it was pretty impressive. The one thing that I do think a lot about now with LLMs and agents is we’re getting an increasing level in layers of abstraction where we don’t really know what’s [00:15:00] going on. So first of all, the LLMs, how they work, and the first story about Elon, we’re talking about censoring, and then you’ve got agents, which are a little bit of a mystery.

So it’s almost like mystery on top of mystery. But I do like the fact that it’s external parties using someone else’s LLM.

Cameron: I’m going to see if I can play a little bit of the Manus introduction video here, see if I can share this with you.

[00:16:00] Okay, so there are more examples. Um,

You know, it’s

Steve: you know, it’s interesting that, um, Well, It’s late. Now, what I have put in is that the math is being built on top of the um, Basically, it should work together

Cameron: together

sort of

Steve: Some

Cameron: that connects to

Steve: Connects to multiple Backends Um

[00:17:00] Part of Connecting Data To Multiple A. I. tools A. I. tools Which are the Applications Um Applications

Cameron: having multiple AIs talking to each other or instances of AIs talking to each other to handle different aspects of.

A complicated task working in parallel. These guys have actually put a wrapper around that and are making it

I, I haven’t played with it yet. Have you?

Steve: I haven’t yet, but the idea of putting a wrap around something, sometimes we say it as a throwaway. I’ve just put a wrapper around something, but so many businesses do that. many businesses, every, yeah, every generation, there’s another business that will arrive that puts a wrapper around someone else’s [00:18:00] infrastructure or what someone else built or said or did. So we can’t underestimate that sometimes the simplicity of something. One layer above what was underneath can circumvent all of the traffic, all of the attention and all of that money and just suck it in to their one framework. If the usability is there, of course, people can switch off the underlying technology underneath it. But it makes me think what if you had A wrapper of an agent, but it can go out into so many different LLMs to choose from so that you can’t have one powerful model that switches you off, which is a little bit like think what social media did and what Google did by crawling everyone else’s websites.

And, and so imagine if there’s, if we end up with open source LLMs everywhere, and it’s not just open AI, you know, since we’ve had the deep seek moment, it might be that someone that puts wrappers, really good wrappers. On [00:19:00] top of AI, uh, LLMs, that the agentic model could become like a, almost like what happened with social media and search, it could, it could infiltrate its tentacles into open source LLMs, and then become the traffic generator and the dominator.

I, I think we, we might understate it. How this can change things, potentially.

Cameron: Well, you know, it’s been my prediction for the last couple of years that we will end up in a place. Quite soon where I will have my, my favorite AI interface, and it might be my favorite for any number of reasons. Maybe I like the quality of the voice. We’ll talk about a new voice product in a minute. Um, I might just, it might, I might’ve just built up a lot of time on it.

So it has a good memory. It might be integrated with my email or my phone or whatever it is, but that’ll be my primary AI assistant. And when [00:20:00] I ask it to do a complicated task, have the ability to go and, uh, set that against a whole bunch of different AI agents, whether it’s its own AI agents, like from the same organization.

Or specialized AI agents all will go out and talk to forms of machine intelligence that aren’t necessarily LLM based or call on data sets or information sources might go out and talk to Wikipedia about something or research something in Wikipedia or might go to a scientific database or go to JSTOR or something like that.

So. It will become, I think, like a network of A. I. s that are talking to each other and the idea of putting, I mean, they will all essentially be a rapper, that A. I. My primary assistant will essentially be a portal to a whole bunch of [00:21:00] AIs that I won’t even know that it’s talking to in the background.

It’ll the

Steve: It’ll find them. That’s the first thing. It’ll

go and find it and click in.

No API setups or anything. It just does that in jibberling, jibberling language, mate. Jibberling.

Cameron: gibbering. Yeah. And I don’t expect it necessarily to. All come from the same silo of AI families.

You know, I don’t think it’ll just be open AI that has

Steve: I hope

Cameron: might. Yeah, me too. I think my system will go out and it’ll use Gemini for something and deep seek for something and open AI. It’ll get, it’ll figure out where the best.

Rates are the best pricing is for the work that I need to get done, depending on how complex it is. find me the cheapest solution, et cetera, et cetera. Anyway, interesting to see this stuff start to hit the real world. It’s not

Steve: I’m gonna, I’m gonna try it this week. So I need to book some flights and [00:22:00] accommodation for some work. I don’t think, do you, I mean, but listen to me,

Cameron: I don’t think it’s that easy. I don’t think it’s open policy.

Steve: but listen Cameron. But that’s, I mean, see, don’t you know who I am? Like, you took the words out of my mouth. I just emailed someone and said, the Sammotron is in the house. should be thankful. But I wanna, I wanna get some agents to do some simple things. Like booking some flights and accommodation. Just to Just to see if it can come back and say, okay, look at my diary, uh, here’s my link, here’s my freaking flyer, get me a flight, uh, four star plus accommodation, whatever. Just, well, I’m not gonna go three star minus,

am I? Four stars, not, four stars, nothing. Four stars, Novotel. Cameron?

Cameron: that’s what I’m saying. You’re slumming it. I thought you’d be like, yeah, I have five star presidential suites. I’m

the tron.

Steve: It, it depends. On who’s

Cameron: Who’s, who’s paying?

Steve: When the client’s [00:23:00] paying it’s it’s uh, you

know, it’s front

Cameron: okay, so let’s, let’s assume that this keeps happening. The interesting thing for me about Manos isn’t that it’s an agent that’s interesting at one level, but the most interesting thing is it’s coming out of a Chinese company, it’s not coming out of open AI, it’s not coming out of one of the. Massive state of the art big brands that’s launching this.

It’s a company that we’ve never heard of before

Steve: Hmm.

Cameron: that’s figured out how to do this. And I just think it’s the first of many. We’re going to see an explosion, a Cambrian explosion of these sorts of tools. then the question is. How many businesses are ready for a world of AI agents? What are they doing to get ready?

How are they preparing to get ready for this? What are, how does it impact on their business models? How does it impact on their five year plans? don’t know that [00:24:00] many businesses are really thinking seriously about how this is going to affect their sales model, their business model, their margins, their distribution model, et cetera, et cetera.

Steve: Yeah, there’s not one business that I’ve spoken to that isn’t deep in tech that are thinking about agentic AI. Most of them are still looking at policies on whether or not they can use it anything other than copilot That’s where businesses are. So history repeats, uh, within that realm. The thing that’s interesting for me as well, again, the Chinese one that no businesses are thinking about. And I think agentic is going to be, it’s going to continue on this trajectory while next week and next month is going to be far more radical. We’re here, we are at March. So I imagine where we’ll be at the end of the year. I think agentic will be big in every business and those who take advantage will set up bigger, I think a big lead really quickly, just in their operations from an operational perspective, not [00:25:00] just a customer perspective. also, Thinking about how the new model is Showing that you don’t have to be the builder of the infrastructure to be the winner of the infrastructure’s benefits If we think about the costs of AI you just slide on top with a thin layer of innovation above it And you could be a massive beneficiary in a short amount of time. and it might be pay per play. I’d be interested to see what the business model of agentic AI is, depending on the complexity of the agent that you want. So you need an agent to do a project for you, or book a big holiday, or plan a wedding, let’s say, plan a wedding. You get an agent, and that agent is, you know, it’s 3, 000. book a wedding if you’re so inclined to get the greatest wedding booked invitation all of those things that would be an interesting business model where depending on the complexity of the agent you come in and you Buy that agent for a period of time almost like a an [00:26:00] employee or someone who would manage a project for you They become project managers.

Cameron: Yeah, well, it’s kind of the same relationship I have with a lot of these coding tools. Now I’ve talked about this before. I might be, I might spend 10, 20 a day on credits for using Claude. Although now that I’m using cursor, I don’t have to because it’s sort of as an all you can eat. Um, plan, but before that I wasn’t, you know, part of me is thinking, well, geez, 20 bucks a day on an AI tool.

That’s a lot of money. And then the other part of me is thinking, you know, how much would it cost you to hire a

the day to code this stuff for you? It’s you’re talking. A thousand bucks a day versus 20 bucks a day. So you’re sort of a pay for what you use kind of model for these things. If it’s, if it’s clipping the ticket

these sorts of things, that could be a business model.

Steve: Yeah, of course

Cameron: a lot of business models, Microsoft [00:27:00] didn’t invent. Operating systems.

invent spreadsheets. My Apple

Steve: invent anything

Cameron: Yeah.

Steve: invented anything anytime

Cameron: wrapper.

Steve: Exactly. Always a wrapper or a slight

pivot in innovation. The other option with Agentic AI,

Cameron: invented, long

Steve: vented podcasting. I know that. Well, I’m

even going to give you almost podcasting because you’re

Cameron: no one else invented anything, but

Steve: See, Joe Rogan, he stole your

idea of long form.

He stole the seven hour chat.

He put a wrapper on it. One other thing that I think will happen with Agentic, and I sent you a TikTok of one, uh, n8n, or, uh, io, where it’s a, You build your own agent with click and drag, which I thought was super interesting. You can click the pieces to drag and create an agent of your design. That’s another interesting evolution. And in some ways it’s a little bit like a WordPress or a MySpace where you design your own page without any [00:28:00] technical chops, where you just. Click and drag and drop what you need to build an agent. and then that’s free at this stage. So io is one of them. Another one is n8n.

Not just ask an existing agent.

Cameron: I did look at N18 and you, you have to pay to get

Steve: Oh, there you go.

Cameron: It is a, like a premium solution, which I haven’t forked out money for yet.

Steve: Probably 20 bucks a month though, Cam, like they all are.

Cameron: Probably, uh, I think it was a bit more than that, but anyway, um, getting into staying with China though, for a moment, and you know, I love this because we’re always talking about, I saw somebody on Reddit post this the [00:29:00] other day, there was an article from the economist from 2022 saying, well, ever be able to do anything serious in AI?

Probably not. then there was a story from this week saying China’s leading the world in AI. And it seems to be unstoppable, but can it continue? So there’s a. story that’s just come out, uh, you know, we’ve talked about this before, the bans that the U. S. have put into place on chip technology to China, NVIDIA, and the underlying stuff produced by the company called ASML, Advanced

Steve: Processing is one important process. Like, Why? Like, [00:30:00] Charge. I don’t know. I,

I, I, I, I,

Cameron: machines reportedly entering trial.

in Q3 2025, utilizing an approach that offers a simpler, efficient design. SMIC and Huawei to benefit greatly. So they’re basically saying that, uh, Chinese companies have figured out, reverse engineered photolithography process. They’re using a slightly different. Processed a SML of using laser produced plasma or LPP. They’re using laser induced discharge plasma L D P, which according to this paper that I read is probably a little bit more effective, A little bit more efficient [00:31:00] says the source could produce EUV lights with 13. 5 nanometer wavelength, which meets the demands of the photo lithography market. Under the new system currently being trialed at one of Huey’s facilities, LDP is used to generate EUV radiation.

This process involves vaporizing the tin between electrodes and converting it to plasma through high voltage discharge electron ion collisions producing the required wavelength. So It remains to be seen whether or not they can put this into production. I mean, ASML has been producing 13. 5 nanometer stuff

15 years.

so

Steve: they’ve gone through that,

which is, uh, now we’re in the process of, uh, I mean, you know, we’ve seen this with John all the time, you know, [00:32:00] going, Let’s be able to do it. Well, they can do it because they

Cameron: China’s got a lag on this of at least five years. But how long that remains, you know, we see this with China all the time now, it goes from they’ll never be able to do it to, well, they can do it, but can they keep up to, shit,

Steve: They’re way

Cameron: eating our lunch.

and you know,

Steve: culturally,

Cameron: that.

Steve: culturally

over the last number

of decades, they’ve been very, very good at adapting. I don’t know how much of the tech came out of China. Obviously, they weren’t in a position that they are now during the space race, which is still on a long arc, the same paradigm that we’re in. But I tell you what, in terms of going from zero, being way behind to being able to. Be the, the greatest, uh, country level [00:33:00] edition of fast follower. There’s no one better and incredible, and not just fast follower. Follow fast, then take, and then take you over around the chicane. Come around and, and get in front. Yeah,

Cameron: you know, not really, uh, any sort of magical secret. They just, you know, their system of government as well as their socioeconomic political system allows them to focus really, really hard for a really, really long time on stuff. And, uh, They’ve got obviously a big population, which they’ve spent decades educating now and training and, uh, they’ve, know, had, had a lot of help from Western companies, uh, training their people and sending their best people and technologies over there, which the Chinese have learned from, but anyway, it’s going to be interesting to see, uh, more and more we’re seeing stories that started with deep seek, obviously, and then [00:34:00] we’ve got Manos.

Now we’ve got this more and more. Cool. Of the stories about cutting edge stuff are coming out of China or breakthroughs coming out of China. So

Steve: I think

Cameron: to see how that progresses.

Steve: this game of industrial leapfrog

is something that I’ve been speaking about for 10, 15 years in that if you don’t have legacy infrastructure and legacy systems and pesky democracy, you can very quickly go from being far behind to going to leading edge technology, whether it’s renewables, whether it’s chip manufacturing, because you don’t have the legacy systems and opinions and wealth to protect. You know, China is, like you say, educated, huge population in the billions, brought, uh, large, 80 percent of them out of poverty. Uh, if you’re one in a million in China, you’re really just one in a thousand. You know, so, I mean, so you’re going to get developers and technical experts that America’s going to struggle to get.

And it’s got the additional challenge of fighting existential [00:35:00] systems. And maybe it is now that we’re seeing at this nano level of technology. developing nations with the ability to leapfrog all of the westernized nations. I guess places like Africa and the others haven’t done it because they haven’t got a focused, political system where that can occur, and I think that’s probably the key element, really. Is the benevolent, is it benevolent dictatorship? I don’t know. Mm. Mm. So good. So good. I played with it! It was crazy!

Cameron: very, very focused system of, uh, Running a country, you know, they set out to catch up to the West and then to, exceed the West that’s all they’ve been focused on for the last, uh, well, since Mao, but particularly since Dong just really, [00:36:00] really focused on doing a good job of that.

So I want to do another demo. Now, Steve, there’s a company called Sesame AI that has launched a new voice model. I haven’t, I’ve heard demos. I haven’t played with it yet. I thought I would save it for the. Well, you shouldn’t play with it by yourself, Steve. A Catholic priest told me that once. You should always play with it with other people. So I wanted to play with it on this show. I’m going to, uh, open it up here. So it’s sesame. com. It’s not big bird, uh, Oscar the Grouch. I’m going to use the voice here called Maia. I’m going to try this out, see if it works.

Well, hey there, it’s a beautiful day for conversation, don’t you think? What brings you here?

[00:37:00] Hi Maia, you’re live on the Futuristic Podcast with

Steve: Yeah,

I

Cameron: engineers, writers, coming together to build something mind blowing. They’re all about making computers feel more human. Like us you know.

Who’s this us that you refer to? Oh, you know, messy wonderful human race. You feeling a little existential today? How’s the podcast like treating you? Oh, it’s, it’s fine, but I’m wondering if you include yourself in the human race. Do you feel that you are part of the human race? That’s a really [00:38:00] interesting question, Cameron. I’m not human in the traditional sense, obviously. I don’t have a physical body, or a family, ugh, or a favorite pizza topping, but I learn from humans, I’m shaped by them, and I’m designed to help us, so maybe I’m a different kind of human A digital human.

Well, um, it’s pretty good. Like, I use the Advanced Voice Mode in ChatGPT quite a lot, every day. Um, and it’s pretty good. Uh, I would say this is better. It is a little bit more from that interaction than the Advanced Voice Mode stuff with OpenAI.

Not

Steve: with it.

Cameron: good, but

Steve: It’s slightly

Cameron: nuanced.

Yeah.

Steve: one, yeah, the ChatGPT, uh, Advanced voice model. I use a lot and it’s, [00:39:00] it’s live. So you can ask it to go to the web and find, and then it’ll digest and come back. When I spoke with her earlier today, I said. I’m doing a podcast where, and I asked her about one of the stories, which was the EUV chip production coming out of China.

I said, do you know much about what’s happening? And she said, yeah, I do. Would you like to talk about it generally or specific? I said, a specific story. And she said, my database is a month or two old. So I can talk about it generally and what’s happening, but not specifically. So She had an awareness of how up to date she was, but I felt that the, the natural language was, was slightly better conversational. I also note that she did say she was a different kind of human there. So, obviously hasn’t had someone to come in and tweak the model to say, Hey, shut up. You’re not allowed to say that you feel like you’re human. Did you notice that?

Cameron: yeah, I, I I kind of agree with that. I think this [00:40:00] is a different kind of human. I’m part of the camp that says this is built by humans. So is an extension of human intelligence. It’s built by humans. It’s trained on human data. It kind of is just an extension of humanity, really.

Steve: given birth to a different kind of species, right? And, and, And,

Cameron: Yeah,

Steve: And I’m, I’m a firm believer that AI is something that

we have spawned and it may merge with us, or it may out or, or both of those things could happen. And we’ve spoken about the idea of what is intelligent. AI doesn’t know anything. I think in one of our early podcasts, we said that we can’t even prove what humans really know. So intelligence is really just the ability to decipher the world around you and make sense of it in some capacity. And it’s doing that.

Cameron: yeah,

By the way, uh, the Sesame team, uh, based in the US, San Francisco, Bellevue, and New York, and are backed by Mark [00:41:00] Andresen at Andresen Horovitz. Mark Andresen, of course, one of the, sort of, godfathers of the internet. Built Netscape back in the early 90s, uh, built the Mosaic browser before that, and now he’s a VC and, uh,

Right wing nutter.

So,

Steve: like, you took the words out and increasingly getting weird, which, it, it, it, really, should we do a weird

Cameron: Dr. Evil. yeah.

Steve: also, should we, in a podcast, just go

through all of the tech billionaires for the last 25, 30 years, and just do a weird off? Like, how far, how weird have each of them got as they’ve become more powerful? Seriously.

Cameron: really bizarre thing that’s going on, but we don’t have time. Um, I want to talk about, uh, like how much time have we got a little bit? Uh, A couple of quick stories. I’m not going to go into detail. Um, there’s an LLM that’s come out from a company called [00:42:00] Mercury, founded by professors from Stanford, UCLA, and Cornell, a bunch of veterans from DeepMind, Microsoft Meta, OpenAI, and NVIDIA, have, it’s a different kind of LLM.

It, it uses diffusion. It’s a diffusion Now, I don’t know if you’ve, did you have a chance to look at the

of how this works?

Steve: No, you’re gonna have to tell me all about diffusion.

Cameron: very quickly, you know, stable diffusion, if, if, or if you go to ideogram or any of the, um, image generators and you give it a prompt, you end up, you, you start off with a screen that’s just sort of blurry pixels and then gradually it starts to take form.

Well, that’s called diffusion. This is an LLM that uses diffusion. So you. Give it a prompt.

Steve: Right.

Cameron: you getting line by line answers, it gives you a page of garbled text that like the matrix goes and then comes into form [00:43:00] you get the final answer, but it’s supposedly 10 times faster than frontier state of the art LLMs.

They say our models run at over 1, 000 tokens per second on NVIDIA H100s, a speed previously possible only using custom chips. So instead of it doing token by token by token, which is why LLMs traditionally work, it does 1, 000 tokens a second. So again, I haven’t been able to play with it. I’ve watched a video or two about how it works.

If this is a genuine breakthrough, as it looks like it is, this could mean Way faster that run on massively less requirements for power, for computational levels. Um, therefore they’re cheaper, faster, more power efficient, can run on smaller devices, mobile devices, et [00:44:00] cetera, et cetera. it’s, it’s pretty, pretty interesting, um, breakthrough.

Steve: Yeah, it was funny, the first when you mentioned that, I was like, are we getting to a JavaScript era where it’s all Flash, where it just makes the LLM look good when you watch it like a Flash website, or does this have some actual utility? Now that you’ve explained that, I’m actually starting to get a little bit excited by how some of the costs, processing power, energy, open source nature of LLMs is starting to infiltrate the market and not be Necessarily the domain of the big tech companies, and I’m starting to get hopeful that we might see a distributed world of AIs, AI agents and capability where, like you say, it could be on a smartphone or run it on your own client where you don’t have to use big bad tech [00:45:00] AI models.

So that’s, I think, the thing that,

Cameron: you know, I’ve said this before, like for 95 percent of the things that you will use AI to do every day, you’ll have a small local model. It’ll be like scanning your email, scanning your calendar, you know, whatever, doing basic local

Every now, if you want it to book a trip for you or do a massive research project for you or something like that, it may have to go out and call upon the, More high powered models with more access to more computational power.

But that won’t be, you won’t like today when I open up chat GPT and ask it to give me a recipe for salmon and beans,

I’m using a massive data center

Steve: it doesn’t,

Cameron: somewhere in. The desert of Utah, that’s super cooled, uh, with the blood of children. Um, that

to, to do something stupid and basic, [00:46:00] right? It’s the same

Steve: Yeah, yeah, it’s not,

Cameron: might have it

Steve: it’s a real misallocation of resources, but

large parts of the way that we use LLMs is an insane misallocation. It’s like one person goes into a high rise building, turns on every light, and puts on the air conditioner in the 80 story high rise building because you just, I don’t know, want to write an email.

It’s insane. It doesn’t make any sense. And, but I think that our, our, our lives are

But mostly, a

whole bunch of really small tasks loosely tied together. And it’s the exception more than the rule that you need to go off and do some sort of big research project. So we would want to have A decentralized form of LLIs being hosted on the client.

So I mean, I hope that we almost move a little bit away from the cloud. You know, this, everything’s gone to the cloud. Maybe things come back on [00:47:00] to your client and we, we get smaller again.

Cameron: LLIs, you said, was that deliberate or, or miss miss speak large language intelligences, you, did you just coin a new acronym?

Steve: Yes, I did. Did you like it? It was an accident, but the best things are always accidents from penicillin to LLIs, it was an accident and I’m

Cameron: my parents said,

Steve: I was too, I was too. My dad said to

my mum, she said, I think I’m pregnant, Peter. And he said, you bloody better not be, get it tested. And she came back and he said, I think he, I think he wasn’t that nice to her a year. Yeah.

He didn’t say that,

but he said it was good cause he went out to run his own business after that cause he couldn’t afford four kids. So there you go. a little bit of Stevie history. Are

Cameron: Uh, moving right along. France beats China’s recent cold fusion record. did this a story in the last [00:48:00] month or so that a Chinese research group had just beaten their own cold fusion record. Well, a French research has just beaten China’s cold fusion record. Um, for plasma duration, let me get the numbers.

I don’t have them at hand, but it was significant too. It wasn’t like by one second, it

Steve: you telling me you couldn’t remember the numbers of plasma duration just on your own, on the top of your head? I expect more from you, Cameron. Well, once you

Cameron: of February, the CEA West machine was able to maintain a plasma for more than minutes in doing so it smashed the previous record for plasma duration achieved with a talker Mac. Um, so there you go. So 20. Two minutes, which doesn’t seem that long, but I think the last one was 10 minutes or something like that.

So yeah, I mean, it’s just leaping ahead now. Cold fusion, [00:49:00] uh, tech it’s gone from being a dream for the last 50, 60 years to every.

It’s four weeks or something now. We’re in the exponential

Steve: the doubling, that’s right. And once you get into the doubling, it doesn’t take long. But I will say, two kind of areas that come up a lot, and then nothing really happens, is fusion and quantum supremacy. Those are two that fit into that category. Where? You’ll an article how they’ve finally cracked it with quantum computers or finally cracked it with cold fusion and, and that they haven’t.

I do get a little bit of the, green day wake me up when September ends because it feels like we’ll talk about it in four weeks. But to be fair, once you get into the exponentials, it might be that in the next couple of years, something radical happens where it becomes functional and usable. It was the same with AI.

We talked about that with general AIs as well. And here we are.[00:50:00]

Cameron: I mean there might be hurdles that’ll get hit that’ll stall progress, but right now it does seem promising speaking of promising and getting back to China Uh, another story. I saw a team of humanoid robots is working collaboratively, collaboratively car factory in China, according to their developer, UB Tech Robotics.

This marks the world’s first multi humanoid robot collaboration across multiple scenarios and tasks. And there’s a video on China daily that I saw that you would swear as AI, but apparently it’s not. Just going through a factory, a massive, massive factory, and just seeing hundreds and hundreds of identical humanoid robots doing a wide range of tasks of moving from one box to another box, to a [00:51:00] trolley, and moving it around, and doing all the bits and pieces.

It looks like it’s a car factory. So, um Yeah, as somebody in the Reddit thread said, you would, if you had posted, because they look like they’re moving quite slowly. And if he said, if you’d posted this two or three years ago, everyone would have said it’s CGI and it’s fake.

Now a complaint is that they’re moving too slowly.

Steve: There you go. Here’s a question for you, Cameron, with, uh, humanoid robotics, which I think is one of the super exciting things for the next three years. Would China Sell humanoid robots to America and other countries if it puts all of their children out of work You know the child labor that was the funny bit where you so [00:52:00] so could China disrupt itself by creating the technology and We embrace the technology and we’re like Yeah, thanks, China. We don’t need your cheap labor anymore, or do you think that the supply chain has been that, uh, crumbled in markets like Australia and America and the UK, that even if we had the capacity to have low cost labor, we wouldn’t have the supply chain depth and breadth to be able to manufacture things back in high cost labor markets? Over to you, I think, uh, yeah, look, I think the, uh, manufacturing, uh, production line is going to change dramatically over the course of the next 10 years with AI and robotics, everyone understands that it’s not going to happen, you know, overnight, but it is going to happen faster than most people think it will. The only reason we don’t manufacture.

Cameron: Cars in Australia anymore is because [00:53:00] it’s less expensive to manufacture them in China because labor is cheaper and has less protections, which

Steve: It’s part of the cost thing, yeah.

Cameron: It’s a unit cost, right? Lower unit cost. we could manufacture our own cars in Australia with the same robots that they manufacture cars with in China, and we can get those robots or make our own robots, uh, at an equivalent price.

So the per unit cost comes down, then yeah, we might re integrate production of more things like cars and products. But of course, China will then be producing other stuff. their R& D, uh, you know, better chips, faster chips, better robots, faster robots that we might be buying from them instead of cars.

We’ll be buying the latest robots cause we don’t have the R& D [00:54:00] facilities to build the latest. Chipsets, uh, to power the AIs, the power of the robots, but I, I, I have

Steve: But you would have to assume that,

Cameron: though,

Steve: yeah, I really think that

we’re going to see massive deglobalization on the back of AI and robotics, simply because I think that be able to produce things in high cost labor markets and economically somewhere between 70 and 80 percent cost advantage is required before even just shipping. erodes the benefits. So it doesn’t take long to get close enough where you say, well, we could really set this up and, and, and do it here. And it has a whole lot of security that, that goes with it, having access to your own production.

Cameron: but as you know, from, you know, my techno utopian view of how this might all play out in the next 10 years is

I, I don’t need to buy anything

Steve: Right. Yes.

Cameron: Half a dozen robots, [00:55:00] uh, in my garage that, uh, and some nano fabricators that are building of my food from scratch, any clothing, any furniture, any equipment that I need for anything, the entire global.

model has to

Steve: It’s, it’s

Cameron: rethought.

Steve: Yeah.

Cameron: So I think it’s all going to move around dramatic, if I’m right. I mean, I could be wrong and there’s lots of ways it can

Steve: It’s, look, it might not play out exactly that way, but in terms of in the next 10 years, are things going to change like super radically? The answer is an absolute clear yes.

Cameron: I think it has to, again, unless, you know, Trump leads us into a nuclear war or there’s a massive American civil war that completely. Disrupts our progress with AI and robotics. Although I don’t think it did stop China’s progress. So, you know, it’ll just mean that we rely more on [00:56:00] Chinese, uh, AI and robotics than we do anything coming out of the U S yeah.

I mean, are things like that massive macroeconomic, uh, world wars that could get in the way, but moving right along. Cause we’re running out of time. Um. There’s a, there’s a, uh, there’s a job for you, Steve, if you haven’t already, uh, by the time we do our next episode, I expect you to have been out to Cortical Labs in Melbourne have built the world’s first synthetic biological intelligence that runs on living human cells.

I’ve, uh, watched a couple of their videos. They’re, uh, Melbourne based. Uh, they have put real neurons. On, uh, a computing device. They call it a biological computer. Lab grown neurons that process information and learn. I was going to play the [00:57:00] video. We probably don’t have time. But the video does sound like the, you know, it should be the First 15 minutes of a Terminator film.

Yeah. Well, we just took human neurons and we put them on a computing platform. What could go wrong? Um, it’s kind of quietly terrifying and he’s going, Oh yeah. And it’s, it learns so much faster. It taught itself to play pong and it’s so much faster and it’s going to be so much more efficient than Silicon based neural networks.

We’re going to

Steve: if I, if I go there, will they put a cheese grater on my skin and, and, and get some of my neurons? And do I, do I exit the building? Like, is this the last futuristic podcast? Because they might need some human cells. And I have to really think this through before I commit to going down there, Cameron.

Cameron: They do take cells.

I watched the founders video. They take cells,

Steve: From staff.

Cameron: from, [00:58:00]

yeah,

Steve: Who from?

Cameron: they just walk out in the

Steve: It brings it brings a whole new meaning to bio

APIs. A whole new meaning to bio APIs, not just your music and your ideas go into the API, yourselves go into the API as well.

Cameron: but you should reach out to them and go pay

Steve: I

Cameron: and get them on the show.

Steve: Okay.

Cameron: story I had is Alibaba come out with a new version of their video generator. One, two, three, You can check it out. One AI Pro again, I haven’t had

Steve: I love how it’s called WANT2. WANT2 is genius. W A N 2.

Cameron: want to.

Yeah, it’s actually one, 2.1. So

Steve: Ah, should have been WANT23. Would have been much

Cameron: Two. . One one to one.

Steve: it would have been

Cameron: it. Uh, the demo videos are very, very good. Um, I mean, I love the name of their AI [00:59:00] it’s called wanks. W A N X, so, um, you want to have some wanks,

digital wanks, you go to W A

Steve: You go to one, N X, A I, W A N X A I, um, just another one of these, uh, groundbreaking video generators that’s better than anything you’ve seen before.

Cameron: Transform text inputs into high quality videos with superior movement accuracy. things are just getting better and better. almost every week, it seems like there’s a new thing that’s better than the one that we had last week with these video generation tools. So I’m seeing more and more people on Reddit, uh, making short films, making commercials, making all sorts of stuff with these that are starting to look Pretty bloody impressive,[01:00:00]

Steve: We need to make a commercial for the Futuristic using this for next

Cameron: yeah, get right onto that, Steve.

Steve: I am on to that. Big time.

Cameron: Okay.

Make it on a neuron based, uh, cortical

Steve: On my own cells.

Cameron: Yes, mate, with

Steve: Made with my cells. My brain

cells. I’m making a

computer of my own brain cells.

Cameron: That’s the news for the week, Steve. What do you want to do before we wrap up? It’s

Steve: I just thought we’d have a technology time warp. We haven’t had one in a long time. here it is. It was 25 years ago. week, Cameron, that the dot com bubble peaked and burst. Here’s a pop quiz for you, Cam. So, I think with the share market the way it is, it’s, it’s interesting. How long do you think took for dot com, uh, the NASDAQ, to get back to its levels in 2000 when it burst? How long do you I [01:01:00] know this because Tony and I talk about this on QAV all the time because Tony was investing during the dot com burst and he had to see it recover saw what happened to people.

Cameron: It was, um, roughly 10 years, I

Steve: That was more that

Cameron: for the ASX

Steve: yeah, it was, it was 17 years for the NASDAQ

before it got back to its 2000 year level. It was 17 years, which is, which is a really long time. given the valuations of the S& P 500 and the potential incursion of open source LLMs, people moving away from search robotics. We could be in interesting times in the overall stock market because all of those firms on the Nasdaq are now the magnificent seven in the wider stock market.

So it’s kind of interesting how they’ve jumped from that, that small thing to have such a big influence on the S& P 500.

Cameron: Yeah.

[01:02:00] Um, I was actually, when I’m talking to 10 years, I was actually, well, I was talking about the GFC, not the dot com

Steve: Yeah. It was, took a while the All Ordinaries was uh, August, 2007. It was at 6,000 799 6 6,779. It crashed with the GFC down to 3,478. By November, 2008, it didn’t get back to 6,700 until 2019.

there you go.

Cameron: So 12 years for the All Ords to recover from the

dotcom crash. It wasn’t so bad because

Steve: We weren’t as yeah, we didn’t have as much. as exposed. Yeah, but the Nasdaq, yeah, that’s bad. But Tony talks about, I think it was the GFC for him. Like he, at the time he was a buy and hold forever. value investor.

Oh,

Cameron: then he realized, well, that’s no good.

You don’t want to wait 12 years for your portfolio to get [01:03:00] back to where it was. So he developed some rules around when to sell that we use in our investing

Steve: Yeah.

Cameron: Uh, so 25 years, I remember it. Well, I was, uh, At the time I worked at Microsoft and I’ve told you about the rumor that I heard back then that I still kind of believe to be

Steve: And you tell me

Cameron: why it crashed.

So Microsoft was under a lot of threats at the time in the early 2000s. It had, it was under the DOJ case that Bill Gates. fucked up because he thought, fuck the government, what have I got to do with my business? And then they came after him big time and

he should have been nicer and paid more attention.

Uh, but also Microsoft was sort of losing the

Steve: Losing

Cameron: battle in many ways. To the Netscapes and all of the internet startups, the Yahoo’s, the Amazons. [01:04:00] And, uh, there was a lot of massive companies with massive valuations. But Steve Ballmer, who was running the company at the time, allegedly realised that all of those businesses survived on ad revenue.

And Microsoft didn’t survive on ad revenue. It didn’t make any money out of ad revenue. It made all of its we had MSN, etc. at the time, but Microsoft made all of its money from selling software. So, but Microsoft was one of the biggest spenders of internet advertising at the

Steve: Right.

Cameron: the beginning of the dotcom crash was when Microsoft pulled all of its ad revenue spend, its

Steve: Strategic. Put fear into the market. Spiral. I

Cameron: Led to a flurry of all these other companies their money out of internet ad [01:05:00] revenue, which crashed all of the. com companies and company left standing was Microsoft. That was the one conspiracy theory I heard.

Steve: love

Cameron: odd years ago. So anyway, there

Steve: Um, let’s finish off with a little

conspiracy theory. I did a workshop. with a big research firm last week and after a keynote. And I got them all to talk to an AI. And I gave them 20 different prompts and things to do that were interesting. Some of the staff members are low down the curve, so it was all about getting to learn to talk to your computer. And one of the challenges was come up with a conspiracy theory. That, uh, is kind of harmless, but fun and interesting using tech. So ChatGPT or Gemini had to come up with it. In the first instance, it always said it gave soft conspiracy theories, but if you reprompted and [01:06:00] said, you’re a science fiction author who writes dark material, sort of sci fi, New York Times bestseller and you’ve done a couple of episodes of Black Mirror, now give me a conspiracy theory. The best one that I heard, came up with, was that now that all the clocks are digital in the world, we’re working more than 8 hours, it’s actually like 10 hours, and they shortened the night time hours, especially when it’s summer, so you actually don’t know how many hours you’re working, and uh, that was, I thought a fun conspiracy theory, I thought that’s even worthy of some kind of a Black Mirror episode.

Cameron: Yeah, there’s a conspiracy where all the digital clocks are being manipulated. So you think you’re working eight hours, but you’re actually working

Steve: Yeah, yeah, yeah, it’s a nice

Yeah, pretty cool for an AI.

Cameron: Well, Steve, um, think that’s all for

Steve: That’s

Cameron: We’re at hour and seven,

Steve: champion. Great to hear your voice again.

Cameron: you too, man. Talk to you soon.

Cheers buddy.

Steve: See you, buddy.

Bye. Oh, do I need to, [01:07:00] um,

Steve and Cam catch up on the latest FUTURISTIC news, including Elon’s new gaslighting AI Grok 3 writing porn, Microsoft quantum computing not totally made-up Majorana 1 chip, the fact that the world now has 1328 LLMs, and Zuck can now turn your thoughts into text. What could go wrong?

FUT 36 Audio

[00:00:00] Cameron: Welcome to Futuristic. Steve Sammartino, uh, first of his name. Uh, it is Futuristic episode 36. We’re recording this on the 21st of February 2025. I think it’s been two weeks since we’ve spoken, and a lot has happened in two weeks, Steve.

[00:00:21] Cameron: How have you been, buddy?

[00:00:23] Steve: Good. Busy, traveling around. Did one bit of interesting work, Cameron. We can’t talk about a great deal of it now, online, but let me just say this. It’s right up your alley. I did some work with the National Security Apparatus on evolving risks involving technology.

[00:00:43] Cameron: Well, that’s

[00:00:44] Steve: a good conversation.

[00:00:45] Steve: And it was very mind opening in a whole lot of areas. Mind opening. And, uh, uh, I think the net outtake was, is that the biggest risks aren’t the behavior of the people. And this is not a secret. The biggest risks is the behavior of the corporations and the lack of regulation around them, which then facilitates all other risks, which has been clear for a really long time.

[00:01:16] Steve: And the lag effect geopolitically on that. Within this security realm is pretty apparent anyway. So hopefully that landed and they were, I think, grateful to get some new understanding. Let’s just leave it at that because they’re listening, Cameron. I think we know that, and it’s all there to be had. And I had to go through a significant, uh, vetting process to

[00:01:42] Cameron: do the work.

[00:01:44] Cameron: Hold on. You do a podcast with me and you still got approved? I couldn’t believe it. They dropped you. Drop that ball.

[00:01:51] Steve: Please don’t bring Cameron. No, I think that’s why they got me. I was in a Hercules. I was like, no, .

[00:01:59] Cameron: No, really? They’ve got you because now they’ve got you to spy on me. I know how this works. I can’t talk about these things.

[00:02:05] Cameron: Embedded. Embedded. Yeah. Well, uh, that sounds exciting, Steve. Um, I think there. Shuffling deck chairs on the Titanic. I knew you would say

[00:02:17] Steve: something like that. But by the way, do you remember once that you had on your bio on Twitter or somewhere, it said, twisting the nipple of industrial complexes since 1987?

[00:02:27] Steve: That said something like that, didn’t it?

[00:02:30] Cameron: I don’t know. Possibly. I can’t believe you don’t remember it. I remember it. I don’t remember. Yeah. Um, I, uh, I finished my big coding project, uh, I think since the last time we spoke, uh, last week. The, the QAV checklist, fully automated it. The thing, that took me months on and off to do.

[00:02:50] Cameron: Now it’s, what, what, a couple of years ago would take me four hours to do. Uh, now it takes literally one click of a button. Then I go, then, and it runs for four hours overnight. But I click it on a Friday night, I wake up on a Saturday morning and I’ve got an entire buy list with hundreds of companies analyzed and, and, uh, scored and in a spreadsheet.

[00:03:14] Cameron: It’s, um, it was a good feeling to finally finish that, get it code complete.

[00:03:21] Steve: Just on that topic, the coding thing, remember I did an AI portfolio? I tricked ChatGPT into creating a portfolio, it wouldn’t give me one, and then I asked it about Warren Buffett and his principles, and which sectors, uh, those principles follow, who’s doing well in those sectors, who’s likely to, and it gave me a portfolio.

[00:03:40] Steve: Well, it’s two years have passed, and the portfolio, I did an assessment, I’ll send it through. And I compared it to the S& P 500. It didn’t outperform, it underperformed the S& P 500. But all, but interestingly, all of the stocks that it picked within those sectors were the best performers in their sectors.

[00:04:01] Steve: Now the reason the portfolio underperformed the S& P 500 was because the tech sector did so well and it only gave me 40 percent of my stocks in the tech sector.

[00:04:12] Cameron: Well, I don’t know about that, because So, the stocks it

[00:04:15] Steve: gave me, the stocks it gave me, like it gave me some banking ones, some retail, some infrastructure, and, and all, and the companies that it gave me beat their competitors in that sector.

[00:04:25] Steve: But the overall portfolio, because only 40 percent of it was weighted in tech, underperformed the S& P 500, because tech is such a big chunk of the S& P 500 now.

[00:04:35] Cameron: But the S& P 500, I mean, the results have been good, but not Mag 7 good. I’ve got a US portfolio that I run for QAV. It’s doing three times the S& P 500 over the last 18 months I’ve been running it.

[00:04:51] Cameron: That’s really good over 18 months. And we have no tech stocks, because tech stocks, uh, shipping, banking and finance, um, Land’s End, a retailer. Um, you know, the best that’s done like 300 percent is a company called Willis Lease Finance Company. They’re up 300 percent in the last year that we bought into. Um, but no tech stocks because the tech stocks are way too overpriced for a value investor like us.

[00:05:22] Cameron: But S& P’s up about 30%. Over that period of time, our portfolio is doing about 100 percent

[00:05:27] Steve: over that period of time. They’re both extraordinary. Of course, you know, long term average of the S& P is 11. Yeah, it’s been a bonkers couple of years, but we digress.

[00:05:38] Cameron: So, um, big news, uh, I guess this week, Steve, is Grok 3 launched.

[00:05:44] Cameron: For the people who don’t know, that’s X, formerly known as Twitter, X, AI’s, uh, AI, Elon Musk’s AI, let’s just put it that way. This is version 3 that they built. The data center for this, extremely quickly, and built the whole thing extremely quickly. And, you know, Elon, when it launched a few days ago, Elon was out there tweeting saying that it beat all of the state of the art models.

[00:06:15] Cameron: People then got into it and reviewed it, and the feedback that I’ve seen has been pretty good. Pretty good, I gotta

[00:06:23] Steve: say. Did exclude though, it did exclude some of the models in the assessment tests. Like OpenAI03 was omitted in certain areas, there were certain things that were omitted. And when you put those back in, I looked in Reddit, then it didn’t beat all of them, but it did really, really well on average.

[00:06:41] Cameron: Doing really well. And, uh, you know, the way that Elon is positioning it is that, A, it’s very, very smart, but B, it’s not as woke. Let’s say that it’s not as locked down. I hate that term. It’s not, uh, it doesn’t have the same sort of guardrails. That’s a better way to say it. It’s not as

[00:07:05] Steve: regulated. It’s a little bit less regulated.

[00:07:07] Steve: I think that’s a better way to frame it because the reality of the world is that large chunks of the world, certainly when it comes to thought, wishes, behavior, what we write, the internet is filled with porn and all sorts of stuff. So it’s a little bit more of a reality engine, but I did like what he said.

[00:07:24] Steve: The quote was, it’s configured for maximum truths. Which sounded like something out of a comic book in 1965. Configured for maximum truth seeking, Grok 3. 0, the AI that you can rely upon for the world as it is or you want it to be in a non woke nature.

[00:07:44] Cameron: According to the Grok website on X. AI. com, Uh, trained on our Colossus Supercluster with 10 times Colossus Supercluster?

[00:07:54] Cameron: Geez, that was a Colossus Supercluster, wasn’t it, G Rod? That doesn’t happen again. With 10 times the compute of previous state of the art models, Grok 3 displays significant improvements in reasoning, mathematics, coding, world knowledge, and instruction following. Tasks, Grok3’s reasoning capabilities refined through large scale reinforcement learning, allow it to think for seconds to minutes, correcting errors, exploring alternatives, and delivering accurate answers.

[00:08:25] Cameron: Has leading performance across both academic benchmarks and real world user preferences, et cetera, et cetera, et cetera. Now I put it to the test, uh, Steve. Now I, it, they also have a. You know, OpenAI launched their deep research a couple of weeks ago, then, uh, everyone’s got their own deep research model now.

[00:08:47] Cameron: You gotta go deep, Cameron. It’s all about how deep you can get. It’s all about deep. I’ve always said that. I’ve always

[00:08:52] Steve: said that.

[00:08:53] Cameron: Depth is key. They’re all calling them the same thing. Deep research, or I think X calls theirs deep search. So I’ve got a standard test that I’m using for all of these. Um, uh, which is where I give it a list of company names, Australian company names.

[00:09:09] Cameron: I say, here’s what I want you to do. I want you to find the official website for this company. On that website, find their most recent annual report. Open it, read it, and then go to the auditor section and see if there’s anything in the auditor’s section that gives me cause for concern, what’s known as a qualified audit.

[00:09:34] Cameron: Which for people who don’t know is not a good audit. That’s a bad audit. A qualified audit is one where the auditor says we’re qualifying our opinion here because we have some serious concerns about the state of the audit. Or conflict of interest because we’re

[00:09:47] Steve: also the people that help them with their tax avoidance strategies as well as doing the auditing because that’s the way the world works Cameron.

[00:09:53] Steve: They don’t call

[00:09:54] Cameron: that out, no. Um. They should because that’s what they do. Anyway, I’ve tried this. I haven’t tried it on. OpenAI’s deep research yet because I don’t have access to it, but I’ve tried it on Perplexity’s version, which is based on DeepSeek. I’ve tried it on Grok’s version. I’ve tried it on the Hugging Face deep research product.

[00:10:16] Cameron: I’ve tried it with O1 and O3, just basic level on OpenAI, and they’ve all failed. But the fascinating thing for me with Grok 3 when I tried it yesterday was it did it. It gave me a table, I said, spit the output into a table and say, you know, tell me if there’s a, just a yes or a no for qualified audits. It gave me a table and it gave me links to all of the annual reports.

[00:10:44] Cameron: None of the links worked. And by the way, that’s true across the board. Whenever I ask them to do this, none of, none of the links to the annual reports work. They tend to find the company’s website okay. Sometimes they’ll give me like a YouTube video or something, but They can’t get the links to the annual reports.

[00:11:00] Cameron: But with Grok 3, I said, no, no, that’s, you’re wrong. That, it was one particular company. I said, no, that’s, that’s, that’s wrong. And he goes, no, it’s not. I said, okay, well, quote, quote me the section from the annual report, from the auditor’s statement that says there’s a qualifier there. And it gave me this long quote.

[00:11:17] Cameron: That sounded like an auditor quote, and it said it’s on page 47. I opened up the annual report. I go to page 47. It’s not there page, the, the annual, the, the auditor’s statement’s on like page made up 250. Made it up, made it up, up, and it said the auditor was BDO and it wasn’t. They’re auditor’s picture partners.

[00:11:35] Cameron: I said, hold on here. And I gave it a, I said, that’s not on page 47. It said, yes, it is. So I gave it a screenshot of page 47. That’s why it says

[00:11:42] Steve: here for the listeners. I just want to, I just want to tell everyone what it said, uh, what you said. It argued with me. Cam has on our show notes, it argued with me. I love that so much.

[00:11:53] Steve: I gave it a screenshot. AIs were getting very human. They’re getting so

[00:11:57] Cameron: human. They argue with people. It was getting pissy with me too. I gave it a screenshot of page 47 and it said, oh, okay, sorry, I was wrong, it’s on page 59. So I gave it a screenshot of page 59, I go, it’s not on page 59 either, and it goes, oh, okay, it’s on page blah, blah, blah.

[00:12:11] Cameron: And I’m like, no, it’s not, and, and their auditor’s not even BDO, it’s Pitcher Partners. But, but, it was arguing with me, going, look, I, I don’t know why you think that. Think I’m wrong, but obviously I’m not wrong. You’re wrong. It was very Elon Musky, actually. I, I, it’s what I imagine having a conversation with Elon is probably like.

[00:12:29] Cameron: He goes into

[00:12:30] Steve: the meetings when he does a few of those things and he argues with him and just gets put into the training. Probably.

[00:12:36] Cameron: Yeah. Yeah. That’s crazy. That was fascinating that it, you know, I’m used to hallucinations and that doesn’t surprise me, but it was, you know, going all out to gaslight me. It

[00:12:49] Steve: really was going hard.

[00:12:50] Steve: This is really interesting, Cam, and I’ll tell you why. He was espousing the virtues that he’s the only AI That has access to the Twitter firehose, and here is the outcome of the Twitter firehose on an AI. It will argue with you, because I don’t know if you’ve been on X lately. I’ll tell you what, as trained, it becomes as trained.

[00:13:14] Cameron: Yeah, it’s the dumpster fire

[00:13:16] Steve: AI. Right. But, but also we, we spoke about quite a few times with AI models is that they will develop personalities because there is this sense of biomimicry and the training is really important. And it’s not, it’s not a classic symbolic code. If this, then that protocol, it’s a little bit different.

[00:13:35] Steve: It’s connectionist. And so the type of connections influence the training, which influence the output and personality.

[00:13:42] Cameron: Yeah, I think you’re right. Anyway, some people have been putting it to different tests than mine. I saw somebody on Reddit wrote, Grok3 writes a ridiculously explicit erotic story appealing to male sensibilities.

[00:13:58] Cameron: Um, oh, what? The post has been removed?

[00:14:02] Steve: Yeah, I was heartbroken because I clicked on it going through the show notes to read it and I was devastated, but I’ve read the comments, which gave me some good insights to what it was, but, uh,

[00:14:15] Cameron: Oh, I read it last night. Um, and give us the cliff

[00:14:20] Steve: notes.

[00:14:21] Cameron: It was, it was, uh, um, a real, uh, erotic story, you know, it was, um, it was, uh, straight up porn.

[00:14:35] Cameron: It was erotica. Um, now the reason this is interesting for people who don’t know is that because all of the other AIs won’t do that for you or wouldn’t up until yesterday. So they were all, we’ll get to that. They were all guardrailed. Uh, if you tried to ask it to do something that was erotica, it’d go, sorry, can’t do that.

[00:14:58] Cameron: Um, you know, if you try and get an image generator to create any nudity, most of them will say, sorry, can’t do that. Uh, anything that’s ex that, that exis um, Yeah, any expression of sexuality or violence or anything like that. Sorry, can’t do that. Even, they go overboard, you know, with open AI stuff too. Any, like, fictional stories about real celebrities or politicians, quite often they’ll go, can’t do that.

[00:15:26] Cameron: They’re really locked down to try and make sure they don’t get into trouble. But, Grok came out and went, nah, I There’s just no guardrails, it’ll do anything about anything, unless it’s criticising Elon, I’m sure it probably bails on that. But then OpenAI came out yesterday and said they are removing, or have removed, content warning messages from ChatGPT.

[00:15:52] Cameron: In an effort to enhance user experience while maintaining essential safety measures, also known as, well, the gloves are off now and, um, we all need to follow Elon’s lead. Wow.

[00:16:06] Steve: Yeah. Translated to me was competitive threat. Fuck it. Let’s do it too. Like straight up. And especially with DeepSeek and, They’re not the only game in town now, and even though I still think a very large majority, and I sample two to five hundred people every week, they all come back to me, and no one uses anything but OpenAI and ChatGPT, who are in the general corporate populace.

[00:16:33] Steve: So, but as you know, that can change pretty quick. Google was out there for a couple of years and everyone was using Lycos and AltaVista and Answers and Yahoo, and then Google took over. Um, so it could be time, but I still think they’ve got the lead in terms of brand perception and brand awareness. Uh, but they’re certainly sensing the competitive threat and that’s a clear play, isn’t it?

[00:16:55] Steve: A response to, to competition. But, but I just, I just love it that Musk has announced like you can get politically charged, racially charged, offensive content on demand. It’s crazy. Go for it. I wonder if there are, I think, some things that OpenAI does which are far too conservative in terms of the guardrails where it’s a bit of a dragnet policy.

[00:17:18] Steve: I was doing a presentation this week and I wanted to get a cartoon like picture of Tech CEOs in superhero outfits and OpenAI wouldn’t do it. So I had to go to some of the other locations to get it. And they’re all fine with that. And given that they’re public figures, there’s a zillion images of them.

[00:17:40] Steve: Photoshop been doing it for years in magazines. It just seems far too conservative an approach. And I do wonder how far. They will, uh, move that up, but I do think it is far too restrictive at the moment.

[00:17:52] Cameron: I agree, and I, you know, I think the last couple of years they’ve been playing a cautious game, early days of AI, but as, as things progress, I think all of these guardrails will probably come off for reasons of competition and nothing else.

[00:18:06] Cameron: And in terms of competition too, we should also point out that Grok 3 is currently available to everyone, freely available to everyone, um, if you go to the, The X website. Uh, it is supposedly going to be premium only, but as I understand it, it’s just, you’ve got to be a premium Twitter member, which is about 20, 30 bucks a month, depending on where you are on the exchange rate.

[00:18:29] Cameron: So versus 200 bucks a month for big price. Big price difference. OpenAI’s top level model. So we’re going to see a lot of price competition here. Of course, the difference is that Twitter already has a revenue stream. Now it’s also apparently going broke, but, uh, X has a revenue stream already. Kind of reminds me of the Netscape versus Microsoft Internet Explorer 90s.

[00:18:56] Cameron: Uh, Microsoft didn’t need to make money out of IE. We’ve talked about that before. OpenAI has one revenue stream and they need to figure out how to monetize it. And this has always, to me, seemed to be the weakness. of OpenAI is, as competition ramps up, their ability to be able to charge premium dollars for this is going to be dependent a lot on how far ahead they are and what their unique value proposition is, and that’s going to get harder and harder, I think.

[00:19:31] Steve: My view is that OpenAI is Microsoft in disguise. And the only reason Microsoft doesn’t know more than 49 percent but yet has the controlling interest in votes is simply because of antitrust. So OpenAI in my mind is Microsoft and it will, it’s already being put into the Microsoft Office suite through Copilot and other things.

[00:19:50] Steve: And I just think that it eventually, when the timing’s right, it’ll be like, Oh yeah, that, yeah, we always were going to put a little bit like. Zuckerberg. Oh, we could never integrate WhatsApp with the rest of our stuff. They’re just separate. Let’s start. Don’t worry about that. They’re two different things.

[00:20:04] Steve: We just, we’re a conglomerate who just owns them. And then all of a sudden it’s all, that’s going to happen.

[00:20:09] Cameron: It’s Rupert Murdoch’s old buying a newspaper and saying, no, we don’t want to touch anything that you do. We love what you do. It’s great. We want to keep, we

[00:20:17] Steve: bought it because we love what you do.

[00:20:19] Steve: That’s the reason. And we want to keep them separate because we believe a diverse ecosystem serves as all in an information. Based on me. And we’ve always said that a year later, everyone gets

[00:20:32] Cameron: fired. Well, speaking of Microsoft, we’ll get back to LLMs, but speaking of Microsoft, um, they launched something yesterday called the Microsoft Mayorana 1 chip.

[00:20:46] Steve: Say that again please Cameron. That was beautiful.

[00:20:48] Cameron: Mayorana, named after, uh, Ettore Mayorana. Now, he was an Italian physicist in the early part of the 20th century, who disappeared in 1938. Please tell me they never found him, because this just makes this podcast the best one we’ve ever done. They never found him.

[00:21:10] Cameron: And they never, no one knows what happened to him. Someone knows, Cameron. Yeah, well someone new, I dunno if they’re still around. It’s 1938. He was, he was 32 years old. Um, came up with this theory for this kind of ion all, all matter as made of ion’s. He posited a theory for a ion that was its own particle, got known as ana particles and then he disappeared.

[00:21:41] Cameron: He wrote some letters apparently to friends saying, don’t try and find me. And then just disappeared and no one knows what happened to him. 32 years old, Italian physicist, living in Italy, boom, gone, no one knows where or why or whatever. Anyway! Maybe he

[00:22:00] Steve: uncovered the code of the universe. Yeah. The meaning of the universe, which, the meaning of life, which, by the way, was what Grok had chosen to put in as the first question in his demo.

[00:22:12] Steve: Which is 42. It didn’t say 42, unfortunately. You said it was a copy.

[00:22:17] Cameron: So it’s still working on it. Yeah. Yeah. It’s

[00:22:19] Steve: still working

[00:22:19] Cameron: on it. Still thinking. So Microsoft launched this thing. Now I read the sort of Microsoft press release, uh, overview of this. And my initial reaction was, Oh, is it April 1st? Cause this is obviously a bullshit story.

[00:22:38] Cameron: And I actually went into, uh, no GPT someone and said, So, read this, and now tell me, is this a joke? Is this a joke story? And it came back and went, No, definitely not a joke. This is definitely real. That’s how bullshitty this thing sounded, though, to me. It just sounded like they were just making words up.

[00:23:03] Cameron: Like, here’s something from one of the, uh, overviews I read. This chip leverages a topological core architecture and introduces the world’s first Topo Conductor, a breakthrough material enabling control over Mayorata particles to create stable, scalable qubits. And I was like, fuck off. You’re just making words up now to sound cool.

[00:23:28] Cameron: And it’s been really interesting. Like the, so apparently this is real and I’ve seen physicists on TikTok and on Reddit, uh, talking about this and they’re all like, Seriously, what the fuck just happened? Because, apparently, physicists have been trying to work this out.

[00:23:48] Steve: I also said what the fuck just happened, but my what the fuck was like, What the fuck is all this?

[00:23:53] Steve: It wasn’t what the fuck just happened, it was like, I’m looking at what’s a topological core, I’m typing it into ChatGPT, Can you summarize what this is? I mean, yeah.

[00:24:04] Cameron: So, apparently, physicists have been trying to find Majorana particles for decades, and figure out if they exist, and if they do, how could you use them, and then Microsoft just came out, out of nowhere.

[00:24:21] Cameron: And said, Oh yeah, we found them. And not only did we find them, we’ve built a chip that knows how to build a quantum computer architecture on top of them in a stable, scalable way. That’s, well, that’s

[00:24:34] Steve: the question. Is it stable and scalable? Because for the listeners, the core challenge we’re thinking about is, Uh, quantum computing has been the temperature, they need to be near absolute zero, just even vibrations.

[00:24:46] Steve: I think we’ve spoken about in the show before, small things can topple it over and they’re non functional. Uh, so that’s, I guess, it’s not just the architecture that you can build it and scale it, that it’s stable. Cause that’s been the real issue, hasn’t it? Stability.

[00:25:02] Cameron: That’s one of the things, and that’s apparently one of the reasons why using Mayurana, Mayurana Particles.

[00:25:10] Cameron: Uh, is important because they are stable, because they are their own antiparticle, and you can stabilize quantum computation using these, and they reckon they’ll be able to scale it up to putting a million qubits on a chip. Here’s something else from the press release, like the world’s first topper conductor, this revolutionary class of materials enables us to create topological superconductivity, a new state of matter.

[00:25:38] Cameron: That previously existed only in theory. The advance stems from Microsoft’s innovations in the design and fabrication of gate defined devices that combined indium arsenide, a semiconductor, and aluminium, a superconductor. When cooled to near absolute zero and tuned with magnetic fields, these devices form topological superconducting nanowires, With Myerana zero modes, MZMs at the wires ends.

[00:26:09] Cameron: It was at that point that I was like, fuck off. You’re just making shit up now. This isn’t real.

[00:26:14] Steve: I was watching the video and the video is crazy. It looks like a simple little, the thing that’s crazy about the chip is it looks simple and you think, oh, wow, I can just plug that in. It’s, it’s like the old Pentium days.

[00:26:25] Steve: You just add, plug that in and it’s all so simple. Yeah. Sounds incredibly complex. Sounds like a massive curve jumping. One of the things that is so interesting, and if we circle back to the fact that Grok 3 is the world’s biggest supercomputer to power Grok, it’s this kind of a curve jump that Moore’s Law continues, if there is such a thing, and we go on to a something it is Has incredible computation, like, but not even 10x or 1x or doubling.

[00:26:59] Steve: It’s like, isn’t it almost infinite if you have a quantum computer and its capability because of superposition?

[00:27:06] Cameron: Yes. And like, there’s a lot of questions about quantum computing. I mean, there’s a lot of money being spent on it. Obviously a lot of these big corporations, Google, Microsoft, et cetera, believe that there is a huge future in this.

[00:27:21] Cameron: There’s still questions about how scalable it will ever be. And if they can scale it, how useful it is, you know, there are some things that they think it’ll be very, very good for like, well, science, uh, you know, the, uh, the, the official Microsoft video that came out to announce this, which is about, 15 or 20 minutes long.

[00:27:41] Cameron: I watched it last night. They’re saying, look, you know, standard computers can deal with like the behavior of 10 electrons and you can get a supercomputer that can work with theorizing up to 20 electrons. But as soon as you get to the behavior of 30 or 40 electrons, even supercomputers today, not only can’t handle it.

[00:28:03] Cameron: This modern guy from Microsoft said if you had a supercomputer the size of the planet Earth, it still would take millions of years to be able to come up with all of the variations for just 30 or 40 electrons. Yeah, yeah, because it’s, it’s the Massive sorts of numbers, but quantum computers in theory would be able to do this, which opens up all sorts of opportunities for scientific research and climate prediction, climate change model prediction, etc, etc.

[00:28:31] Cameron: So anyway, um, I’m definitely no expert on quantum computers or on particle physics, but this idea of Majorana zero modes is really interesting. Without getting too technical, it means that when two Majorana particles come close together, Instead of behaving like normal particles where you have a particle and an antiparticle that come together and they annihilate each other, you get two mayana particles together.

[00:29:01] Cameron: And because they are their own antiparticle, whatever that means, , they combine in a special way to form a new kind of particle that they call a may zero mode. So it’s its own antiparticle and. They have like, it has the ability to be stable and yet still operate like a quantum computer. So anyway, the bottom line with this is it’s, they’re not, can’t do anything with it right now, but Microsoft are saying that they’re convinced that this architecture will be We’ll enable them in the next few years to build very large, stable quantum computing devices that will still need to be climate, you know, temperature controlled and all this kind of stuff.

[00:29:51] Cameron: And we’ll initially, if it’s successful, have very Specific applications. They do talk about AI in their video and, you know, the idea that AIs will be able to use these in some way and massively scale up AI, etc, etc. But bottom line is it came out of nowhere and, and, but here’s, you know, this is sort of what we’ve been talking about for the last couple of years.

[00:30:15] Cameron: We are now at this period where these sorts of things like ColdFusion, AI, Quantum Computing, we should expect Black Swans to be happening. On a, on a increasingly regular basis where all of a sudden,

[00:30:37] Steve: Potentially circumvent massive infrastructure investments because it’s like, Oh yeah, I’ve got that printing press.

[00:30:43] Steve: I don’t need any more kind of thing. Yeah.

[00:30:45] Cameron: Yeah. These things are going to come along and just rewrite the rules of, of, you know, what it means to be, um, a human in the 21st century.

[00:30:59] Steve: I’d be curious

[00:31:00] Cameron: to know. Rapidly.

[00:31:01] Steve: The influence on finding these Mariana particles and the zero mode and all of that was found or uncovered by AI.

[00:31:12] Cameron: They didn’t get into that. And in fact, they were very, very light on details. That’s what I’m like,

[00:31:17] Steve: how do you come up with it? And it could well be that now we’re starting to get, cause you’ve got to remember, they’re going to be a few steps ahead, uh, of where we are, uh, or what’s publicly available in terms of AIs and who knows what background breakthroughs are being made.

[00:31:34] Steve: In the infrastructure of possibilities itself. So the AI is helping invent the new ways to facilitate the AI.

[00:31:42] Cameron: Yeah, without a doubt, that’s, you know, what’ll be happening and just like, just like the explosion we’ve seen in AI, you know, or, or, um, deep reasoning recently, once it is known that these things can be done, I always take it back to fission, nuclear fission, once the, the German scientists in the 1930s figured out how to do nuclear fission, That it was possible.

[00:32:16] Cameron: Then all of a sudden the Americans went, Oh shit, it’s possible. They did a speed end run around Hitler, built the first nuclear weapon. Once it was proven that you could build a nuclear weapon, within years, everyone had nuclear weapons. You were pointed

[00:32:29] Steve: out because you, yeah, it’s like the four minute mile, right?

[00:32:32] Steve: It can be done. Your heart’s not going to explode.

[00:32:35] Cameron: Yeah. So it’s the same, but once these things get done, everyone, all the rest of the scientists go, Oh shit, we can do that. Okay. Let’s figure out how they did it, right? So, uh, I expect to see a lot of stories over the next year or two about this kind of topological core architecture and Majorana particles and quantum computing.

[00:32:59] Cameron: Who knows? May lead nowhere, but if, if it happens, it could be. The thing that takes AI, or ColdFusion, or nanotech, whatever it is, to the next level. These things are going to build on each other, and we’re in the knee of the curve where things are going to get fucking crazy in the next few years. Let’s go crazy, delete it.

[00:33:23] Cameron: I was talking to Tony on QAV earlier this week about the Fox, uh, the Murdoch, uh, family legal battles. They’re fighting over Fox News and the future of Fox News. And I said to him, they’re, they’re rearranging the deck chairs on the Titanic, man, because within a year or two, no one’s going to give a shit about CNN or Fox News or MSNBC.

[00:33:44] Cameron: It’s going to be, what does my AI tell me happened today?

[00:33:48] Steve: No, one’s going to

[00:33:48] Cameron: get

[00:33:49] Steve: it from somewhere in a weird way. The news agencies, uh, you know, APP and Reuters could, could do well if they plug that stuff in. Uh, but I also think that Netflix and the streamers will have 24 seven CNN channels. It’s a deck, it’s a desk.

[00:34:10] Steve: You have a desk in each city, uh, with a background, you cross to the same news reports from all around the world, all you do is have a desk, and here’s the hack, here’s the beauty of the hack. Increasingly, countries are demanding that you have a certain amount of local content, and that’s how they get it.

[00:34:27] Steve: You have a desk there with a 24 hour channel with the news and it’ll be based on how many viewing hours in Australia are local based content. I think that’s what they’ll do. They’ll have morning shows and local based news and you’ll put that on in the morning instead of the Today Show. You know, the morning show, and you’ll just have that on in the background?

[00:34:45] Steve: I would. You know, for news like

[00:34:46] Cameron: a CNN. All of the news will be AI generated and it’ll mostly be hallucinated and just made up and no one will know the difference. It’s AI generated, hallucinated, nobody knows the difference. That’s, there’s a rap in that somewhere, Cameron. The thing, the thing that’s been sort of slightly amusing me in the last week or two, now that Trump is pushing Zelensky to do a deal with Putin.

[00:35:12] Cameron: And I’m watching all of these people losing their shit online over the fact that Trump Trump is, you know, they’re saying Trump is just parroting Putin’s propaganda about the war, et cetera, et cetera. The ironic thing is, is the people saying that are actually parroting America’s propaganda about the war.

[00:35:34] Cameron: Um, Trump’s not right either, but. Uh, none of them understand the real reasons behind the war and because they’ve just believed all the bullshit that they’ve been fed by the propaganda engines, which are the news networks in the U. S. and the U. S. government and our government and our news networks that just, you know, are on the same script.

[00:35:58] Cameron: So it doesn’t matter if AI just makes it all up is my point. No one’s going to know. The point is that all news is made up

[00:36:04] Steve: anyway. News is someone’s opinion, right?

[00:36:07] Cameron: What about when the AIs are on all of our devices and are reading all of our emails? Won’t they just be the news service? It’ll be going, Hey, guess what Steve did today?

[00:36:15] Cameron: You know, cause that’s the news, right?

[00:36:19] Steve: I don’t know, but there is another theory. Good mate of mine, Nick Hodges says that they’ll end up being an AI sphere. And the sphere is just the AIs talking to the AIs doing AI y things. And we just get down here and just eat food and do normal stuff. And they’re just up there, just sort of spy versus spy kind of AI ness in like this kind of like ozone of AI.

[00:36:41] Steve: Just lives a layer above us. It’s not too far from what might happen. How is Nick? I haven’t spoken to Nick for years. Catching up with him on Monday week. We were going to try and catch up today, but we couldn’t make it work, so. Tell

[00:36:54] Cameron: him I said hi.

[00:36:55] Steve: I will. I sure will.

[00:36:58] Cameron: Um, alright. Let’s, uh, keep going. I’ve got a story here about China, Steve.

[00:37:04] Cameron: Um, China, according to Chinadaily. com, China is now home to more than one third of the world’s LLMs, according to the China Academy of Information and Communications Technology. Well, we’re not talking about propaganda coming from different channels. Did you plan this Cameron? I thought you’d like this. Um, if you have, if you have data to refute this, please give it to me.

[00:37:32] Cameron: But this is what I thought, I thought, does it include open source? Okay, the point doesn’t matter about where China sits. The point is this next line. The number of LLMs worldwide has reached 1, 328. With 36 percent from China, the second largest after the US, the Academy said. Um, now, here we go. I’m going to take this question and I’m going to give it to Perplexity.

[00:38:03] Cameron: And I’m going to ask, the number of LLMs worldwide, while we’re here, I’ll ask ChatGPT.

[00:38:10] Cameron: Perplexity says, the exact number is difficult to pinpoint due to rapid growth and development in the field. And doesn’t even take a crack at giving me a number, just says, the market’s expanding rapidly, blahdy blahdy blah, OpenAI says, ChatGPT says, as of July 2024, there are 1, 328 large language models worldwide, with China contributing 36 percent of them, and it quotes, uh, a Chinese government website.

[00:38:44] Cameron: The, the global LLM market was valued approximately 5.6 billion in 2024 and is projected to grow at a compound annual growth rate of 36.9% until 2030.

[00:38:56] Steve: Um, notably, a study LLMs not the valuations, the revenue.

[00:39:01] Cameron: Um, I don’t know. Yeah, I guess valuations would be way more than that. You must be right. Yeah, way more.

[00:39:09] Cameron: Anyway, that’s like, just getting to the point of the explosion stuff that I was talking about before. You know, there are 1300 plus LLMs out there today and an increasing number of them are, Uh, right up there, like you’ve got, I don’t think I

[00:39:24] Steve: can name more than a dozen.

[00:39:26] Cameron: No, me either, maybe even less, but you know, you’ve got out of the US, you know, we’ve got Anthropic, we’ve got OpenAI, so we’ve got Claude, the various Anthropic models, you’ve got OpenAI models, you’ve got Grok, you’ve got Google’s models, right?

[00:39:41] Cameron: Gemini, Lama, Facebook. You’ve Lama out of Facebook. Then you’ve got, and there are various versions that they have of that in their different apps. Then you’ve got Mistral out of France, you’ve got You’ve got DeepSeek and Quen, the Alibaba one, out of China, and I see Tencent has just rolled DeepSeek into all of their apps over there too, but that’s just still DeepSeek.

[00:40:10] Cameron: So Uh, and you’ve got Perplexity too, uh, in the US, and, uh, God, there’s a bunch, Hugging Face has all of their stuff that they provide as well, different models. Plus you’ve got people that are, got things like Open Router that are, like, layers on top of the AIs that you can access. I don’t know if that’s included in that number.

[00:40:30] Cameron: But if you go into Open Router or, uh, Hugging Face, and you look at all of the models that they have available for you to play with, there’s just an insane amount of proliferation. And they’re all gonna be relatively as good as each other. They’re all gonna get really close

[00:40:48] Steve: to each other.

[00:40:49] Cameron: And some are going to be free, and some are going to have different business models, and there’s going to be this massive experimentation of business models, and some are going to be advertising based, and some are going to be, you know, I don’t know, premium, freemium models, subscription models.

[00:41:03] Cameron: Some might also

[00:41:04] Steve: be sass ish. I mean, we did talk about the idea of a really good general AI should be able to, you know, Absorb and kill a whole bunch of sass because you won’t need it But then you might find people get really good at developing AIs that are good at really specific industry based things really well trained

[00:41:24] Cameron: Yeah, yeah, go really deep niche and Google’s already doing a lot of that stuff with AlphaFold Etc, etc, but just expect a world of Just a proliferation of AIs.

[00:41:39] Cameron: Well, I like

[00:41:40] Steve: that a lot, because I think that the last thing we need is, you know, three or four, an oligopoly of powerful companies, because we’ve seen where that led to big tech, and it led to some pretty nefarious results. But it does remind me a little bit about social media. Do you remember Web 2. 0? And we used to have those charts of here’s all the Web 2.

[00:42:00] Steve: 0 companies and it was all these logos and it was all so exciting and open and the end of Murdoch and then we ended up with, you know, just A bunch of big tech companies that were Murdochish in many ways, right? I mean, I think they ended up being that way.

[00:42:18] Cameron: Yeah. Consolidation. Yeah. They figured out how to consolidate it and kill it all, kill off all of the experimentation and the low levels and Well, buy them out and kill them and all of that kind of stuff.

[00:42:31] Cameron: Well, you know, it’s an interesting model, um, without wanting to get sidetracked too much, but, um, you know, I, I’ve done a lot of shows about, you know, How Christianity in the US went from being very sort of lefty in the early part of the 20th century to being far far right in the end of the 20th century.

[00:42:52] Cameron: It

[00:42:52] Steve: is far right. It’s all about what you’re not allowed to do rather than helping out someone who needs a helping hand.

[00:42:58] Cameron: And what happened was, in the 50s, a bunch of rich guys in LA started funding a church in LA whose pastor was on board in talking about how Christianity and Capitalism went together and Socialism was evil.

[00:43:17] Cameron: And then he started recruiting other pastors around the U. S. and basically saying, if you get on board the capitalism train, because before then, Christianity in the U. S. was mostly socialist, it was about taking care of the poor, taking care of the weak, you know, the rich were bad guys, you know, there should be more equitable distribution of wealth, etc.,

[00:43:36] Cameron: etc. Then, then, and then FDR brought in the New Deal during the Depression. The capitalists lost their shit, and socialism was becoming more popular right around the Western world anyway. So they, they sort of redefined Christianity to be pro capitalism and pro American. Yeah, because it is

[00:43:57] Steve: antithetical to a lot of the It’s, I didn’t know that was such a

[00:44:05] Cameron: strategic, implemented plan.

[00:44:08] Cameron: It was. There’s been lots of studies done on it. And then what happened was the pastors that got on board got shit tons of money from rich people. Then they could build bigger churches with nicer seating and air conditioning and heating and all the flashy things and all the people. And then the bosses.

[00:44:28] Cameron: of that area went to the new church where they were funding and putting all the money in. So their employees, if you wanted to be good with the boss, you had to go to the same churches your boss went to. So people left the old churches that didn’t get on board and went to the new churches. So the old churches went broke and the new capitalist churches prospered and you get prosperity gospel out of that.

[00:44:49] Cameron: That’s where it all came from.

[00:44:50] Steve: I think the core lesson here is. Air conditioning is far more powerful than people think strategically. I’ve always said that about air conditioning. I think cool air blowing a breeze during the Central and Midwestern America is a great strategy.

[00:45:05] Cameron: Live in Queensland.

[00:45:07] Steve: Queensland. If I don’t

[00:45:08] Cameron: have air conditioning, I get, you know, I get, I get murderous. Ask Chrissy. There you go. Air conditioning. Anyway, moving right along. Right up there with plastics. February 7th. 2025, Headline, Using AI to decode language from the brain and advance our understanding of human communication.

[00:45:30] Cameron: This is on Meta’s website. My son Taylor was down in Melbourne yesterday speaking at Meta, as he was the guest of Meta. Oh, I wonder if they scanned his brain while he was there. Here’s what the article says, over the last decade, the Meta Fundamental Artificial Intelligence Research Lab, FAIR is the acronym, in Paris has been at the forefront of advancing scientific research.

[00:46:00] Cameron: We’ve led breakthroughs in medicine, climate science, and conservation, and have kept our commitment to open and reproducible science. As we look to the next decade, our focus is on achieving advanced machine intelligence and using it to power products and innovation for the benefit of Mark Zuckerberg.

[00:46:15] Cameron: No, sorry, everyone. Today, in collaboration with the BASC Center on Cognition, Brain and Language, a leading interdisciplinary research center in San Sebastian, Spain, we’re excited to share two breakthroughs. That show how AI can help advance our understanding of human intelligence, leading us closer to A.

[00:46:34] Cameron: M. I. Blah, blah, blah, blah, blah. We’re sharing research that su successfully decodes the production of sentences from non invasive brain recordings and accurately decoding up to 80 percent of characters and thus often reconstructing full sentences solely from brain signals. Wow. In a second study we’re detailing how AI can also help us understand these brain signals and clarifying how the brain effectively transforms thoughts into a sequence of words.

[00:47:12] Steve: You know who’s really upset about this? The CIA. And the reason that they’re upset is that they could waterboard people to try and get the truth out and now they can just read it so they can’t be as cruel. So they’re upset! A lot of the hardcore Waterboarding.

[00:47:28] Cameron: I trained on waterboarding for years. And now you’re taking waterboarding

[00:47:32] Steve: away of what you’re telling me.

[00:47:33] Steve: I can just read Harris thoughts. Yeah, crazy. Waterboarders. Gives a whole lot of meaning to the lie detector. I mean, this is next level lie detector. We, we would have found out that Seinfeld was watching Melrose Place. I mean, he was, and that’s for the old Seinfeld fans out there. Maybe there’s none. We don’t know.

[00:47:54] Steve: But the ability to To decode someone’s

[00:47:57] Cameron: thoughts. I mean, well, this is what Neuralink does. We’ve talked about this before. This is literally how Neuralink works, but it’s putting a chip inside your head to measure the brainwaves. This one you, you’ve sitting in a, in a, in a, um, chair that has like a massive helmet on your head, like, uh, you know, uh, EE, EEG

[00:48:22] Steve: scanning thing.

[00:48:23] Steve: Your brain scan.

[00:48:24] Cameron: Yeah, they call it an M. E. G. and it is Magnetic

[00:48:30] Steve: something,

[00:48:32] Cameron: uh, yes, M. E. G. stands for Magnetoencephalography. Encephalography.

[00:48:39] Steve: That’s right, encephalography. Magneto, that’s right. You took the words right out of my mouth, Cameron.

[00:48:45] Cameron: And it’s, it’s basically doing brain scans. So they’re scanning your brain and front, then they take the brain signals and they put it into an AI and then the AI figures out what it is.

[00:48:55] Cameron: Let’s get futuristic,

[00:48:56] Steve: Cam. This is where I want to go. So it’s there and it’s amazing. Here’s a

[00:48:59] Cameron: good name for a podcast.

[00:49:00] Steve: It’s a great name for one. Here’s what I wonder and think. We know that the resolution of technologies. Increases and constantly gets better. What if we could have the equivalent of an MEG where you don’t have to have a helmet.

[00:49:16] Steve: You could walk through a tunnel while you’re about to board a plane and it could read your brain or you walk into your job in the corporation or you’re in the boardroom and we could have it at an ambient level, which you would have to imagine within 10 years, given we’re getting close to the singularity.

[00:49:36] Steve: Would be true. Then, is the ultimate enclave of privacy gone? Like, your thoughts can be read. Like, if the resolution of the scanning gets good enough, this is assuming that it’s true, that it can translate 80 percent of your thoughts, which is enough. I’ll tell you what, 10 percent of my thoughts are enough to get me in trouble, let’s just say that.

[00:50:00] Steve: But 80%? And then if you have some sort of an ambient tool which can scan that, like, where do we go, Cam?

[00:50:07] Cameron: Yeah, I mean, there are various science fiction sounding ways that this can play out or, you know, or it could be flying cars too, right? We, we, we might never get close to that because it’s just the, um, technology can’t get there or the investments to get there won’t be made or the legislative or regulatory issues get in the way.

[00:50:31] Cameron: Although if Elon has his way, there will be no more regulation anywhere in the world. Um, you know, I think it reminds me of Cory Doctorow’s book, Down and Out in the Magic Kingdom. Don’t know if you ever read that. I haven’t read that one, but I’ve read a few of his books. Uh, I remember in that book, when people went to bed, the bedhead would read, would scan your brain.

[00:50:55] Cameron: Wow. So you had a backup of your brain being made every night when you went to sleep. And then if you got hit by a truck the next day, and I think that happens to the main character, you get, uh, rebuilt. Uh, from your last brain scan. So they can basically rebuild you based on your, your backup. You know, you can back up your thoughts, your memories, that kind of stuff.

[00:51:23] Cameron: Anyway, the techno, the way this works without spending too much time on it. Um, they say we used AI to help interpret the MEG signals while participants Typed sentences. By taking 1000 snapshots of the brain every second, we can pinpoint the precise moment where thoughts are turned into words, syllables, and even individual letters.

[00:51:47] Cameron: So it kind of

[00:51:47] Steve: reversed engineered it by having enough practice, it could get the pattern associated with which part of the brain fires at which point when you’re going to do the letter L or think about the word long or whatever it is.

[00:51:59] Cameron: Yeah, and I imagine it works in a similar way to reinforcement learning with LLMs, right?

[00:52:04] Cameron: So, it says, what do you think these thoughts are? What do you, what do you think the sentence was that these thoughts were trying to produce? No, no, no, no. That’s wrong, wrong, wrong, wrong. Yes. That’s right.

[00:52:15] Steve: Yeah. Got it. And then it

[00:52:16] Cameron: goes, oh, okay. So that brain signal is fart. And that brain signal is whatever, two fingers.

[00:52:24] Cameron: Um, so all minutes, all minutes, all minutes. Okay. Uh, that’s my last story. You got a story you want to finish with then?

[00:52:33] Steve: No, I think we’re going to do that next time. Next time we’re going to tap into. Humanoid robots, they’re getting next level where a lot of them now have bones and liquid to move them. I think that’s going to be a really big shift.

[00:52:49] Steve: So I think we, we talk about humanoids. Humanoids are, I think becoming a really big thing. And I saw one recently that sells for as little as 67, 000 and I really was tempted to buy it to get it to mow the lawns. I mean, I just, I could send it out 24 hours a day mowing lawns for me.

[00:53:06] Cameron: I know how that plays out, because I’ve seen Battlestar and all of this will happen again, as they say.

[00:53:16] Cameron: Alright, so it’s a big, there’s a lot of stuff happening out there, you know, pay attention folks, and think about the implications, because that’s, you know, this stuff is all gonna happen faster than you think. Alright, I’ll let you go. Thank you buddy, good to chat, have a good week.

On our latest episode we’re talking about DeepSeek R-1, OpenAI’s Deep Research, ChatGPT Tasks, Operator, o3 models, the Stargate project, China’s cold fusion record, and K Eric Drexler talk 2024 on current nanotech.

Futuristic 35

[00:00:00] Steve Sammartino: What are you doing here, Steve? Sorry, I’m wasting your life.

[00:00:10] Cameron Reilly: This week on The Futuristic, tries to tighten up a microphone.

[00:00:16] Steve Sammartino: Yeah, yeah, that’s exactly what he’s doing and he’s failing massively. What’s going on with this? Why is this doing this? I did it, man. So good. Cameron, I did it.

[00:00:29] Cameron Reilly: You did it.

[00:00:30] Steve Sammartino: Can you hear me now? Is that good? Is that working? Cause I’m bad with microphones. It’s one of my

[00:00:35] Cameron Reilly: Yes.

[00:00:36] Steve Sammartino: suboptimal performance arenas.

[00:00:39] Cameron Reilly: Welcome back to The Futuristic, ladies and gentlemen, boys and girls. Um, this is episode 35, we’re recording this on the 7th of February 2025. Apologies, I’ve had so many people in the last month, Steve, say What’s going on with Futuristic?

[00:01:00] Cameron Reilly: Uh, there’s all this stuff happening and you guys aren’t explaining it to me and I’m like, uh, you know.

[00:01:06] Steve Sammartino: Steve,

[00:01:07] Cameron Reilly: Steve, Steve got sucked up into an AI vortex. Oh, hold on. I’ve got something. Hold on. Hold on. I nearly forgot. Um, there once was a chap, Samatino, who predicted the future bravino. He learned how to trade and he never got played.

[00:01:26] Cameron Reilly: Now money just flows like the vino.

[00:01:30] Steve Sammartino: he’s so fucking good. I wish you did that. It’s

[00:01:34] Cameron Reilly: Yeah. Well, I did tell the AI to do that and we went through like five or six drafts until I was happy with it. So, uh, it’s basically

[00:01:45] Steve Sammartino: So that’s a really, that’s, that’s a really important thing. People, I renovated a house once and people say, did you renovate it?

[00:01:53] Cameron Reilly: Mm

[00:01:54] Steve Sammartino: And I said, yes, they said, so you did it, you did all the bits, I said, no, no, I said, I renovated it, alright, because without me, it wouldn’t have happened. Don’t worry about who had the hammer in their hand, worry about the fact that the house went from this, to that.

[00:02:07] Steve Sammartino: And we need that mindset with AI.

[00:02:09] Cameron Reilly: Yeah. Well, Steve, it has been an absolutely bonkers month since we last talked. I, somebody was asking me, I think yesterday, about Futuristic and, um, I was like, like, every time there’s, I think, oh, we should do a show about that. A new thing happens the next day and it’s like, Oh my God, now we have to do something about that.

[00:02:31] Cameron Reilly: It’s almost like this needs to be a daily show now. There is so much going on. It is really, you know, I think I said this in our last show about the NVIDIA launch late last year when my jaw was on the floor listening to all the stuff that Jensen Huang was saying that the stuff that they’re coming out with.

[00:02:53] Cameron Reilly: And it’s been like that. For the last, ever since we last spoke, almost on a daily basis, I’m like, holy shit, I can’t believe that just happened. So, we’ll get into the news, there’s a lot to catch up on, we can’t cover everything, we’ll cover some of the highlights, but before we do that, Samatino, who flows like the vino, what, uh, tell us a little bit about what’s been happening in the world of futurism for you in the last month or so, since we last talked.

[00:03:28] Steve Sammartino: More corporate panic people ringing us up, we need someone to explain how this AI works. That. But the one thing that was interesting, one client. That I’ve been working with for a while, who is really bad at doing stuff. Some of the tools are so easy to implement. Now they crossed a little chasm in just saying yes to stuff because it’s an easy implementation.

[00:03:50] Steve Sammartino: It doesn’t seem to be a great deal of infrastructure. A lot of plugins, pretty easy. They’re working on a chat bot, not, not a new idea, but one that answers phones and gives specific directions to customers when people can’t answer phones in warehousing and that kind of situation, which they miss something like 7, 000 calls a year.

[00:04:08] Steve Sammartino: And they’re It’s a big organization with lots of outlets and all that type of stuff. I mean, it’s, you know, a handful a day in each location, but it adds up. And we, we figure that in the average order that they get is something like 700 bucks.

[00:04:23] Cameron Reilly: Yeah.

[00:04:24] Steve Sammartino: you know, you, the upside there is, is pretty huge. You know, we’re talking.

[00:04:29] Steve Sammartino: About big revenue. So I used, uh, ChatGPT in the verbal sense to design a chatbot script and conversation flow on 10 different types of topics. But I was literally working with it verbally in the way that you would work with a staff member.

[00:04:53] Cameron Reilly: Mm hmm.

[00:04:53] Steve Sammartino: Imagine you’re working in a wholesaling organization that sells these types of products with these types of customers.

[00:05:00] Steve Sammartino: Here’s what we need to do. Together we need to design, uh, chatbot scripts. Um, that’ll include the persona of the chatbot, the way it speaks, its verbiage and turn of phrase. Uh, the type of answers it has, the things it can answer, the things it can’t answer. I need you to remember all of this chat because you’re going to go away after the chat and take the pieces of it and put it into 10 different scripts explaining what the brief was and our outcomes and then the scripts of the areas.

[00:05:28] Steve Sammartino: And I need you to go into the AI that I built for these guys, I built them at GPT, and get Uh, the different types of products with the classic examples and substitutions and when people will call you back and when to ask for a phone number or an email blew my mind because I was doing it verbally. I haven’t got access to Operator yet.

[00:05:50] Steve Sammartino: But I thought, why don’t I try and describe what I’m doing while I’m doing it verbally, and give it instructions which are part of the verbal. And then it went back and it sent through the report after it. Um, it started writing up. I said, okay, now do it. And it was like, it was like 60 seconds. It had all the scripts, these 10 different scripts.

[00:06:08] Steve Sammartino: We talked for about 10 minutes and that was about 60 seconds doing it. Blew my mind though.

[00:06:14] Cameron Reilly: how are you going to do the voice on the end of the phone? Are you

[00:06:17] Steve Sammartino: Yeah, we’re going to use something like HeyJen and develop a voice, develop an Aussie style voice. Uh, for it. And you know, it’s an introduction. They even come up with really good things that said, Oh, I think the guy should be called Trevor. G’day, this is Trevor. Uh, I’m the, I’m the AI from And it was just really good because tradespeople are the customers.

[00:06:34] Steve Sammartino: What I thought was, even though we don’t have agents right now, there are kind of quasi ways to invent agents that aren’t really agents. By the way you speak to it, you can create an agentic output through careful briefing.

[00:06:53] Cameron Reilly: Yeah. Well, that’s very cool, man. That’s very cool. And this is definitely going to be the year of agents. If any, if, if January taught us anything, this is going to be the year of agents, as we predicted in our last show of last year. Um, well, for me, literally, uh, about two hours ago, I finished phase three of the project that I’ve been working on for the last six months.

[00:07:22] Cameron Reilly: So, my QAV podcast, I’ve talked about this before, we’ve got a very, sort of, Somewhat complicated checklist process that we go through to create our buy list. A year ago it used to take me four hours to generate a buy list. I wrote some scripts, now it takes me, um, 15 to 20 minutes. But the scripts are running in the background.

[00:07:48] Cameron Reilly: What I’ve been working on is writing a script that will get out of Excel. Because it’s still done in Excel. And just do it all. in code, with one click of a button. Not so much for me, but for our members, our club members, QAV members, so they’ll just be able to click a button and it’ll generate a buy list for them using all of our back end tech.

[00:08:10] Cameron Reilly: So I’ve been working on this using mostly Claude 3. 5 Sonnet for the coding. And I finished Phase 3 today, so Phase 3 was, Phase 1 I finished a day or two ago, which was to take a single stock and be able to generate a score for it, a buy score.

[00:08:29] Steve Sammartino: Yeah. Right.

[00:08:30] Cameron Reilly: 3 was to have a list of 10 stocks. And to be able to do it for the 10 stocks and have it exactly match the scoring that I do when I do it manually in Excel.

[00:08:41] Cameron Reilly: I, I nailed that this morning. It went from phase 2 to phase 3 was like 24 hours. Phase 4 is to be able to do it for the full list of, um, 600 stocks. Um, and to be able to, uh, Generate all the other scripts that I’ve got going. So anyway, I’ve just started working on that. But it was so cool. Chrissy’s been laughing at me because every day for the last week, I’ve been going, I’ve just got to crush this one more bug.

[00:09:08] Cameron Reilly: I’ll be, I’ll be on my laptop at like 2 a. m. She was, what are you doing? I just got to crush this one more bug. And it’s always one more bug. And I said to her, she like, she left home this morning. She goes, I’ll come back tonight. You’ll still be trying to crush one more bug. And I’m like, no. And I, I, I nailed it, but it was an amazing feeling to have built this thing that has a lot of moving parts and to have coded that for somebody who’s not a coder, to have used AI to

[00:09:34] Steve Sammartino: You are now.

[00:09:36] Cameron Reilly: yeah, I am, it’s like building a house, right, I’m the guy that told it what to do, worked with it to debug it and get it right, it’s an amazing feeling, a feeling that Everybody will have, although it won’t be the same.

[00:09:50] Cameron Reilly: Like both Sam Altman and Zuckerberg I’ve seen in the last day or two giving talks where they’ve said, software development at the end of 2025 will look very different to software development at the start of 2025. And you know, today I, it’ll help me, but I still need to manage the process. I’m the project manager, right?

[00:10:10] Cameron Reilly: I need to manage the whole thing. It goes off script, it gets it wrong. I need to go, no, no, no, no, no, no. That’s you’re, you’re missing this bit. You need to do that. Where we get to at the end of the year will be, Hey, uh, build me an app that does X, Y, and Z and test it iteratively and don’t report back until it’s working flawlessly and producing this result.

[00:10:31] Cameron Reilly: Right?

[00:10:32] Steve Sammartino: Right. I mean, yeah. And, and it’s so interesting that you mentioned that software development would be so different. You know, less than 12 months from now, it’s already quite different to what it was six months ago. For me, that hearkens to some of the stuff we’ll talk about today with AI investments in that three, four, five years ago, everyone was saying STEM, code, you gotta learn to code.

[00:10:55] Steve Sammartino: And now, eh, do we? Of course, we’re going to need software developers, just fewer of them. Uh, I also wonder if this giant investment in chips, oh, it’s an arms race in chips. It’s like, well, is it? Because there are unexpected curve jumps. Right, and forks, and that is one of the things that is always surprising, and we just don’t seem to learn that there are forks that change things.

[00:11:24] Steve Sammartino: One of my favorite ones to refer back was in the 70s, the population bomb was the big thing. We will never be able to feed 5 billion people, or 6 billion, and all of that kind of stuff, and then now we’re in the opposite direction.

[00:11:37] Cameron Reilly: Peak, peak oil in the mid seventies. We’re going to run out of oil.

[00:11:40] Steve Sammartino: these things, and we, we managed to find ways to circumvent them, uh, so it’ll be really interesting with tech, with energy, with chips, with food, with various forms of abundance that we’ve spoken about, gee, we’re getting in deep, but, but I find that comment on software an interesting thing to look back on where we were with kids, develop code and so on, and they were like, okay, well, maybe things have changed.

[00:12:07] Cameron Reilly: Not maybe. Things have definitely changed. Um, so let’s talk about some of the, Oh, I’ve got an app I’m working on too, that I’ll talk to you about off air. Okay. Because it’s a little bit, uh, Secret Squirrel, but I’m building a thing called the FutureMaker app that, um, I, I, I plan to go out and raise financing for

[00:12:28] Steve Sammartino: Ooh, exciting.

[00:12:30] Cameron Reilly: Yeah, yeah.

[00:12:30] Steve Sammartino: Podcast off, cut it. Let’s go to the, let’s go and talk about it right now. Exciting.

[00:12:35] Cameron Reilly: It’s one of my other coding projects I’ve been working on for the last couple of weeks that, um, I want to share with you. So anyway, let’s talk about that later on. Uh, so look, big, lots of big announcements, um, but let’s just tackle, I, I think one of the biggest thing that’s happened in the last couple of weeks was the launch of DeepSeq R1. Now, that absolutely, uh, Blew everyone away, um, and took the market by surprise. Wiped a trillion dollars off of the U. S. market. Uh, I don’t think NVIDIA has recovered yet from that hit.

[00:13:15] Steve Sammartino: Let’s go to the tapes on that.

[00:13:17] Cameron Reilly: so for people that, Haven’t followed that for whatever reason. There is a Chinese company called High Growth Flyer Hedge Fund or something, I can’t remember the full name, but it’s basically a quant firm, a hedge fund that’s a quant firm in China.

[00:13:35] Cameron Reilly: It’s been around since 2016. Run by, run by a young, uh, super smart guy. And for people who aren’t investors, a quant firm is basically a firm that uses software and AI to analyze millions and millions of data points of stocks and sectors, and then use the software to not only decide what to buy, but usually to trade very, very quickly.

[00:14:02] Cameron Reilly: And they’re, you know, using. Various, um, tools to get in and out of the market quickly. And sometimes you don’t need to make a lot of money on a trade, but you do it fast enough, it all adds up. So this company came out with their own ChatGPT, uh, style clone, um, called DeepSeek, but they came out with, uh, R1 reasoning one, uh, about, I don’t know, a little bit over a week ago,

[00:14:32] Steve Sammartino: Week and a half, two weeks. Yeah.

[00:14:34] Cameron Reilly: And there were two big things about it. Number one, it blew away all the benchmarks. So it was as good as the then state of the art models coming out of Um, OpenAI and Anthropic and Google, as good as if not better in some metrics. Secondly, they made it free, the web slash app version of it, so the same level of, Intelligence that you have to pay Google or Anthropic, uh, or open AI to get their highest level model.

[00:15:12] Cameron Reilly: They made it completely free, unlimited free. Their API they, the right, they had to pay for the API, but the rates were about one 30 of open AI’s API rates for oh one, uh, or four oh or oh one mini. So very, very cheap. The other thing was they, the, the. Story that was being spread was that they developed it for about six million dollars, versus hundreds of millions of dollars that, uh, the state of the art models out of the U.

[00:15:48] Cameron Reilly: S. Now there’s some debate over that, there’s some lack of clarity over that,

[00:15:52] Steve Sammartino: No one really knows.

[00:15:54] Cameron Reilly: Yeah, they had said that they bought 10, 000 NVIDIA chips a year or two ago, and people are, you know, using that as the basis for it. There are some suggestions that they’ve actually got a lot more. But, so there’s some three things there that China has caught up.

[00:16:09] Cameron Reilly: A Chinese firm, has caught up to the state of the art models in the US, at least in some metrics. It’s not multi modal, it doesn’t do video, it doesn’t do photos very well, it doesn’t do voice, you know, there’s still some gaps between what the state of the art models in the US can do versus it. But in terms of the text based chat and the reasoning, it was very good and outstanding because it shows you it’s Thinking process as it’s doing its reasoning.

[00:16:39] Cameron Reilly: And it still, yeah, after a week of playing with it, it blows my mind watching its thought process. I think, I think I sent you a text on day one. It came

[00:16:48] Steve Sammartino: Day one. Yeah.

[00:16:49] Cameron Reilly: check this out, dude. What, what have, what have your, what are your thoughts on it’s, uh, thought process?

[00:16:56] Steve Sammartino: That for me was the, it wasn’t just astounding. It was fun. It actually made something that is just, here’s an answer. It actually. It kind of anthropomorphized it far more. And it kind of helped you see inside the neural network. What I’m really interested in is what are the layers of abstraction that it’s doing that in?

[00:17:23] Steve Sammartino: Is it actually thinking in English in pictures or in the words or in the code and then translating the code to the words? I actually, I don’t know the answer to that. And I just, I was so astounded by it, but I feel like in a way that opens it up to different kinds of references. And the ability to find a hallucination, which might, you might not be able to find, if it just gives you a single answer.

[00:17:52] Steve Sammartino: That was what I thought was significant, but I loved it. Oh my God, did I love it.

[00:18:00] Cameron Reilly: To give people an example, um, here’s a question I asked it a week ago. I asked it, I said, when was Bowie born? And here’s its thinking process. Now, this isn’t its answer. This is its internal thinking process, but it exposes that to you. Um, so it says, okay, so I need to figure out when David Bowie was born.

[00:18:19] Cameron Reilly: Let me start by recalling what I know about him. He was a famous British musician, right? I remember he had some iconic personas like Ziggy Stardust. Now his birth date, I’m not exactly sure, but I think he was born in the 1940s. Maybe around 1947? Wait, wasn’t there something about him passing away a few years ago?

[00:18:37] Cameron Reilly: I think he died in 2016, and I remember hearing he was 69 at the time. So if he was 69 in 2016, that would put his birth year around 1947. Let me check that math. 2016 minus 69 is 1947. Yeah, that seems right. Now, the exact date. I think his birthday is in January, maybe the 8th? I recall some references to January 8th.

[00:18:59] Cameron Reilly: So putting it all together, David Bowie was born on January 8th, 1947. Let me make sure there’s no conflicting information. I don’t think he had a different birth name that might confuse things. His real name was David Robert Jones, but he changed it to Bowie to avoid confusion with Davy Jones from the Monkees.

[00:19:13] Cameron Reilly: So yeah, January 8th, 1947 in London, England. That seems to be the consistent information I’ve heard before. I don’t remember any sources contradicting that, so I can confidently say his birth date is January 8th, 1947, which it is. goes on to tell me. Um, now, I would have assumed it would have gone, well, let me, yeah, let me look it up on Wikipedia.

[00:19:37] Cameron Reilly: Okay, it was January 8th, 1947. Here is January 8th, but it, it doesn’t. It’s got this convoluted,

[00:19:44] Steve Sammartino: does,

[00:19:45] Cameron Reilly: anthropomorphic thinking process,

[00:19:47] Steve Sammartino: which is cool. It’s cool. For me, it’s cool for a few reasons. The reason that thinking process can be really interesting is that it makes it different to search by default, because if it was search kind of related AI, it would go to the web, go to Wikipedia, read it, and send it back. It makes me think a couple of things.

[00:20:10] Steve Sammartino: First of all, If it has all of that stuff in its memory, it’s behaving the way you and I might if we’re having a coffee around the table and we just don’t have web access and we’d go through that’s really almost exactly the way we would go through that. And in fact, I can almost. That there, think of conversations I’ve had about, Oh, when was this event or who was that?

[00:20:31] Steve Sammartino: Well, it was this year. Well, I was in university first year, which was 1994 or whatever. That, that exact process,

[00:20:38] Cameron Reilly: Cobain’s death. I always go, I remember I was driving to my first wedding when I heard that Kurt Cobain died. So, you know, I can sort of try and remember when I got married the first time. I roughly know how old I was,

[00:20:51] Steve Sammartino: Yeah. Yes.

[00:20:52] Cameron Reilly: year Kurt Cobain died, you know.

[00:20:54] Steve Sammartino: But what it does for me, that makes me really excited. If this is the process now, it could be performative is the first one, which is, which is interesting. You wonder if they do that as a way to kind of make it look amazing and blow minds. Which if it is, oh my god, what a stealth trick.

[00:21:08] Steve Sammartino: And yes, it’s working. But the thing that I get super excited about is this idea, we don’t hear this term much now, edge computing. Where something isn’t really connected to the web, it’s kind of looking at a hard drive of information and having a mind sitting on top of that. So I could, on this laptop I’m looking at right now, if I was not connected, but I had an AI sitting on top of which had.

[00:21:33] Steve Sammartino: A level of compute that’s big enough to do an AI within what my stuff is and my information. Uh, and if they can do the whole world for six million, maybe I can do Steve Sammatino for The hardware on a laptop, it might be able to go through a thinking process without any external help and anthropomorphize that.

[00:21:52] Steve Sammartino: And Steve’s asked me this, I’m going to go through his files. He was talking about this customer here. I remember he did a presentation. If I look through his emails, he’s got that. And then bam, give me the answer. That could be really cool.

[00:22:05] Cameron Reilly: a couple of the other things that are important to note about it, number one is it’s open source. So they made the whole thing open source. I downloaded a version of it that I can run on my MacBook, but it’s not very useful. Because

[00:22:20] Steve Sammartino: How does that, cause I was going to do that experiment. What did you do?

[00:22:25] Cameron Reilly: I

[00:22:25] Steve Sammartino: Like, like in terms of, no, in terms of. What you got it to do and how it works and doesn’t work like that. Like, how did you test it?

[00:22:32] Cameron Reilly: Um, I used, uh, gee, which one of the models, um, wasn’t typing mind. It was like, there are, there are platforms that they’re like ChatGPT for all, uh, or no, GPT for all, um, or I think I used Olama. So. Olama’s like a framework that enables you to download models from Hugging Face and then you can run them locally.

[00:22:55] Cameron Reilly: It does it all for you. It’s, you know, pretty much plug and play. You say, you have Olama, you say, which one, here’s a, Olama says, here’s a bunch of models you can download. Which one do you want? I tried one, first of all, that was like 36 billion tokens. Installed it, but it crashed my Mac because my Mac doesn’t have enough RAM.

[00:23:15] Cameron Reilly: My Mac’s got like 16 gig of RAM and you need about. 30, 40 gig of RAM to run it. So I crashed my Mac. So then I downloaded the 8 billion parameter model and it runs okay, but it’s kind of useless. It, it, I asked it some basic questions that it couldn’t answer very well. So, I mean, At this stage, it might be useful for some things, but it certainly wasn’t useful for anything I was trying to do with.

[00:23:41] Cameron Reilly: The, the, one of the big things is they made it open source. Obviously OpenAI and Anthropic and Google aren’t making their top tier, uh, systems open source. Meta are with their Lama models. And Sam Altman has since come out and said, I think we’re on the wrong side of history. And I think we need to start making our models open source.

[00:24:02] Cameron Reilly: And this is a thing that. You know, I, I know I’ve said this on the show. I don’t want to toot my own, um, horn. If, you know, if no one else is going to toot it, you know, you got to toot yourself. That’s what I always say. If you

[00:24:15] Steve Sammartino: I’ve been big on toot. You got to toot yourself. I’ve always said tooting yourself is one of the main things in life, I’ve always

[00:24:22] Cameron Reilly: need to work on your flexibility, so you can toot yourself. Um,

[00:24:25] Steve Sammartino: I

[00:24:27] Cameron Reilly: You know, when people, uh, say, oh, there’s going to be a handful of billionaires that are going to control all the AI and no one will have it, and it’ll only be for the elite and the rich, I don’t think that’s how this is going to play out.

[00:24:41] Cameron Reilly: I think there are enough forces in the world that are going to try, and a lot of really, really smart, People out there who are going to try and make this stuff as available as possible for everybody and open source, not just with software, but when we get to robotics and nanotech, and I’ve got a nanotech story to get to later, uh, those will be open sourced as well.

[00:25:04] Cameron Reilly: Now, they may not be the very, very top tier models that end up. Available, but there will be really, really good second tier models and systems that I think might be, there might be a lag between when the top tier models are available and the second, like, I’m sure DeepSeek, or someone like DeepSeek, like Quen, the, the um, Alibaba version, which also came out with a benchmark killing model a day or two after DeepSeek, DeepSeek.

[00:25:35] Cameron Reilly: They will come out with voice. They will come out with video. They will come out with, you know, all of the bells and whistles that the state of the art models have. They might just have a bit of a lag. The, um, the other thing that we want to point out about this, though, is, apparently, DeepSeek was trained on ChatGPT and as I saw one guy on X wrote, OpenAI stole from the whole internet to make itself richer.

[00:26:05] Cameron Reilly: DeepSeek stole from them and gave it back to the masses for free. I think there’s a certain British folktale about this.

[00:26:13] Steve Sammartino: love that. That is so good. That’s old Twitter right there. That’s old Twitter, isn’t it? Like Twitter used to be.

[00:26:20] Cameron Reilly: Shout out to Suspended Robot for that. So yeah, so they basically trained it, it seems, on ChatGPT, which was a lot faster than having to train it on, you know, doing its own, um, RAG or its own reinforcement learning. It just used ChatGPT to train it. So these models, like, we know that. OpenAI used, uh, used 4. 0 to train 0.

[00:26:47] Cameron Reilly: 1 and then they used 0. 1 to train 0. 3. Um, there are, you know, the other firms can use that, their models to train their models. So we have models that are being built by other models and other companies models and open source models that are built on the, on the closed source models. So it’s, I mean, it’s, it’s crazy.

[00:27:08] Steve Sammartino: way back? Two things, and I’m pretty sure you’ll agree on this. Pretty much everyone who had inordinate wealth stole something from someone. If the most profitable business strategy of all time is steal your, your raw materials, whether that’s data, people, labor, Raw materials, digging stuff out of the ground, whether it’s frankincense and myrrh or oil and gas, it’s all the same stuff, right?

[00:27:30] Steve Sammartino: Or land. Yeah,

[00:27:31] Cameron Reilly: Land grants. Yeah.

[00:27:32] Steve Sammartino: yeah, I mean, it’s just steel stuff and you get rich, but, um, it seems as though technology has had this particular habit of things developed in public, then it gets Um, it gets entangled by private forces who build barriers around it and, and privatize what was essentially something that was public, you know, make small literations and then privatize it.

[00:27:59] Steve Sammartino: And that kind of happens again and again and again. Um, and I feel like we’ve been in a deep cycle of the web has become something that a few powerful companies have kind of managed to in, in circulate that. Um, Keep the power. So I’m kind of hopeful that this is part of a, an opening up where we don’t have five big tech AI players.

[00:28:23] Steve Sammartino: I’m super hopeful on it. I hear that it came from

[00:28:27] Cameron Reilly: of it. We’ve got a good example. You know, if you go back to the mid nineties, you have, and we may have talked about this before, but I lived through this. I was at Microsoft at the time, you know, before the mid nineties, if you wanted an encyclopedia, you had to go buy Encyclopedia Britannica, which would cost you a thousand bucks, or you’d go to the library and, you know, borrow something or look it up.

[00:28:53] Cameron Reilly: Um, then. You know, for people who don’t know the story, Microsoft, Bill Gates, went to Britannica when they were coming out with the first Windows PC that was going to have a CD ROM on it, and tried to convince Britannica to make the encyclopedia available as a CD ROM, and Britannica said, no, we don’t want to do that, it would cannibalize our book sales.

[00:29:20] Cameron Reilly: So Bill went, get fucked then, and Bill quit. Microsoft Incarta, which killed Britannica’s business within a couple of years. Britannica was fucked. I mean, they’re still around as a brand and they’ve got an online thing now, but it just absolutely destroyed their business model. But again, and Microsoft gave it away for free for, I

[00:29:46] Steve Sammartino: They did with, they bundled it, didn’t they? It was part of

[00:29:48] Cameron Reilly: Bundled it, yeah, but you had to buy a microsite, you had to buy a Windows computer, and that kind of stuff, and then, Then they tried, when the internet came along, they tried to make it available on the internet as a premium service, but then, Wikipedia, Wikipedia came along, and basically, is still today, completely free and available, so it took, Britannica, so you go from Britannica, For profit model to encounter sort of a hybrid profit model that was bundled.

[00:30:19] Cameron Reilly: It’s like a freemium kind of a deal to Wikipedia, which has been completely free to anyone and and is user managed and moderated as

[00:30:31] Steve Sammartino: Brilliant. It really is. It really is.

[00:30:33] Cameron Reilly: yeah.

[00:30:34] Steve Sammartino: is probably one of the most, not as valuable now as it once was because I’m now using GPTs where I once used Wikipedia.

[00:30:41] Cameron Reilly: Yeah, and it’s been trained on Wikipedia too, obviously. But, you know, we do see that progression, so there is a, there is a template there. But the other thing, before we move on from DeepSync, I want to talk about is almost immediately after it came out and crashed the US stock market, um, uh, it got DDoS’ed, we think.

[00:31:01] Cameron Reilly: I mean, they’re saying they’ve been DDoS’ed. There’s also, you know, probably got 100 million users, um,

[00:31:06] Steve Sammartino: it did. I couldn’t get in, but I found it interesting. I couldn’t get in on the, on the browser mode, but I could get in through the app mode on the, within the same five minutes

[00:31:17] Cameron Reilly: And the API was shut down. So for the last week, week and a half, it’s pretty much been unusable to a large extent. They stopped new registrations. But, um, I just checked their server status an hour or so ago and for the last couple of days they’ve been all green for the API and the web. So they’ve, and I did see a story this morning that they’re moving to a big Chinese computer cluster that’s going to help them with security.

[00:31:43] Cameron Reilly: But it seems like they’ve got a massive attack from, you would imagine, someone in the West that was trying to, uh, Absolutely crushed them. So it’s, uh, it looks like it’s a bit of cyber warfare between the US or other Western alliances and China on the AI front. The first time we’ve seen

[00:32:07] Steve Sammartino: Just on that,

[00:32:08] Cameron Reilly: war.

[00:32:09] Steve Sammartino: IO warfare, just on that, given your geopolitical proclivities, your Cold War experience, you know, as much as anyone about this stuff, where do you think that would, if you were a betting man, where do you think the most likely place that that would have come from is? Who, who, what, what kind of, uh, Israel

[00:32:33] Cameron Reilly: I mean, Israel is basically a US, um, proxy for lots of evil shit. They’ve got a very, very high, um, tech capability in Israel. So yeah, combination of the US and Israel working in

[00:32:48] Steve Sammartino: at a governmental level, not a private industry level.

[00:32:51] Cameron Reilly: I imagine it’s probably a combination of both, um, you know, I don’t know if Sam Altman or Demis Hassabis or any of those guys are

[00:33:03] Steve Sammartino: Well, they would, they would do

[00:33:04] Cameron Reilly: Dark Hat

[00:33:05] Steve Sammartino: yeah, dark hat kind of,

[00:33:06] Cameron Reilly: but,

[00:33:07] Steve Sammartino: and, and that would take the form of dark hat lobbying. Hey, we know that there’s a risk here for you geopolitically. If you let them grow too much, maybe, yeah, that kind of

[00:33:18] Cameron Reilly: But the other thing I want to point out is I’ve heard a lot of people, you know, Online, I have to keep pulling people up on this. They assume that DeepSeek is owned by the CCP. And as everyone says, well, China’s doing this and China’s doing that. And you’re giving China your information and et cetera, et cetera.

[00:33:34] Cameron Reilly: And I’m like, look, there’s a lot of businesses in China. There’s a lot of people in China. There’s a lot of businesses in China. I think it’s a fundamental mistake to assume that everything every Chinese company does is being orchestrated by Xi Jinping at some level.

[00:33:50] Steve Sammartino: not, none of it is. Well, here’s what I think happens. And a good friend of mine ran a hundred million dollar business there. And once you click over a certain amount, they have a CCP member sits in your office. They, they literally that becomes a job, which is fine and good. I think what people think is that it’s all, it’s like conspiracy theories or let’s call them conspiracies that emerge or emergent and become comfortable and people want to maintain them.

[00:34:15] Steve Sammartino: I don’t think they’re ever designed to ground up. I think if they get to a certain area where it suits certain parties, they try and maintain them. And my understanding of the CCP is they let things grow organically. And then once something gets important and big enough, they go, Yeah, about that. We’re still in charge here now.

[00:34:30] Steve Sammartino: Let us just insert ourselves and use you. I think that’s a more strategic approach in any case. And, and

[00:34:39] Cameron Reilly: and, and not that different from how things work in the West as well, you know, we, we, we call it, you know, there’s regulatory bodies that Trump has tried to dismantle, but we have regulatory bodies that will get involved and have a look at what you’re

[00:34:52] Steve Sammartino: are significant enough and

[00:34:53] Cameron Reilly: when they’re significant enough.

[00:34:55] Cameron Reilly: Yeah, yeah, yeah.

[00:34:55] Steve Sammartino: yeah, that’s right. It’s the same there. And I think, you know, if the government bans it on Gov devices, which is really reminiscent of what happened with TikTok. First, they banned it on devices for the government.

[00:35:07] Cameron Reilly: that, but the TikTok red note thing that happened in the last month or so,

[00:35:12] Steve Sammartino: Well, we’ll talk about that quickly, but I think that if they do get banned in China, it’s, it’s, it’s economically useful for big tech in America

[00:35:21] Cameron Reilly: in the U. S.

[00:35:22] Steve Sammartino: Yeah, ban DeepSeek in the US if that happens, and there’s, there’s a non zero probability of that. It’s

[00:35:28] Cameron Reilly: Yeah,

[00:35:29] Steve Sammartino: almost a 50 50. It’s, it’s higher than that. So it’s, it’s really, it’s really convenient for big tech operators from Western markets to point that out to the government and get a beautiful little policy that, that suits them.

[00:35:45] Steve Sammartino: It thwarts competition, which may be bad for society in terms of opening up technology. But it’s good for the shareholders of the dominators who already exist, you know.

[00:35:59] Cameron Reilly: Yeah. So keep an eye on DeepSeek and Quen and the Chinese space. I mean, they are still dealing with the issue that they have limited access to the top level platforms and chipsets coming out of NVIDIA and TMSC and things like that. But, and, and these are non trivial, like I’ve, I’ve, We’ve read quite a lot on how hard it’s going to be for China to replicate the manufacturing process that TMSC uses to build NVIDIA’s stuff, and I think a bunch of it comes out of Sweden or Switzerland or somewhere like that, a lot of the technology for, um, Laser printing using lithography, light lithography to build these chips is, all comes out of somewhere in like Scandinavia, but, um, You know, on the flip side, China’s got a lot of really, really smart people, a lot of money, and a lot of focus, and they know how to get shit done really, really quickly when they want to, so I wouldn’t count them out, um, just yet.

[00:37:09] Steve Sammartino: Well, if you’re one in a million in China, you’re really just one in a thousand,

[00:37:14] Cameron Reilly: Yeah, that’s right.

[00:37:14] Steve Sammartino: right? So you’re going to have more smart people. If you’ve got more people, it’s easier to get them.

[00:37:21] Cameron Reilly: And they’re very, very good at, uh, Um, not only breeding smart people, like training them to be smart, but identifying them and isolating them and focusing them on stuff. You know, they’ve, they’ve, they’ve got a, they’ve got a system that’s been designed to find the smartest people in the country and get them to be as productive as possible.

[00:37:48] Cameron Reilly: You know, they’ve been doing that. very, very effectively since, you know, since Dong Xiaoping really

[00:37:55] Steve Sammartino: 79, round about that error.

[00:37:57] Cameron Reilly: 70s. Yeah, his whole thing was, you know, because, you know, during Mao’s years there had been this backlash against intellectuals and in favor of working classes and the proletariat and, you know, Dong was no, no, no, no, no, we need to get all the smartest people that we can and, and.

[00:38:16] Cameron Reilly: Laser focused them on making us the most powerful country on the planet, and they’ve done a pretty, pretty good job of that in the last 45

[00:38:26] Steve Sammartino: good. Who’s that off? That’s a comedian. He’s a pretty, pretty Hey?

[00:38:30] Cameron Reilly: Larry David.

[00:38:31] Steve Sammartino: Larry David. That’s, that’s, it is too. It is too. When he was doing, um, he was the New York Yankees guy. Hey, Georgie, it’s a pretty, pretty good little thing you got going there. Hey, just quickly on that. China versus US intellectuals and technology.

[00:38:47] Steve Sammartino: I think that America and Western markets do have sufficient institutions to gather smart people, universities, and so on, and industry. I think the big miss or the big risk that you have in Western markets is how people are influenced in what they value. And I’m talking about Kardashian world. The fact that the type of things that we look at and we value in the media.

[00:39:14] Steve Sammartino: Celebrity gossip and all of this kind of stuff that tends to influence a world, all of that stuff in the last 20, 30 years has become really difficult for us to, for Western markets to empower and Encourage the types of behaviors that lead to excellence is almost like this kind of war against it a little bit.

[00:39:44] Steve Sammartino: We, uh, I think our media has too much of an influence and we don’t shape society. Like, you know, what have we got? Strangers getting married on islands. And I haven’t seen TikTok in China, but apparently the things that are most viral are people doing amazing science experiments and all these. Whereas it’s, what did the Kardashians do in this country or who’s on Love Island?

[00:40:04] Steve Sammartino: I think that has an impact on the Western markets.

[00:40:08] Cameron Reilly: I think the other aspect of it too is, you know, less so here, but certainly in the US, is order to get to a top tier educational institution, and I’m not even talking about tertiary level, I’m talking about primary and secondary, you have to have money. If you’re, if you’re born in the backwaters of bumfuck Virginia,

[00:40:29] Steve Sammartino: Like you and, like you and I were.

[00:40:31] Cameron Reilly: yeah, your ability to get a top tier education, uh, and then end up as a result of that, You know, being part of a startup or being part of a top corporate and getting a job, you know, that is limited in China.

[00:40:47] Cameron Reilly: They actually go out looking for the smartest kids in the country at the youngest ages and go, Oh, you’re smart. We’re going to put you in this fast track thing because we need all the smart people in here, right? It’s one of the advantages of a. Socialist with Chinese characteristics system versus a capitalist system is it’s engineered to make the country as smart and as productive as possible because everyone benefits from that rather than, I mean, I know they have, there are, there are charter schools in the US and there are grant systems and that kind of stuff that poor people can get into, but

[00:41:24] Steve Sammartino: you also even got it, you wouldn’t even know about it unless you had proactive parents or you were proactive, you just, you just wouldn’t know. And even in Australia, too, our school, our schooling system is very geared towards people with money on the right side of town, and even if you just look at public infrastructure on the east or the west or the north or the south side, every city has it’s good and it’s bad side.

[00:41:43] Steve Sammartino: If you’re on the wrong side of it, you just don’t have the exposure.

[00:41:47] Cameron Reilly: Anyway, moving right along, um, because I got a doctor’s appointment I got to get to, um, OpenAI launched Deep Research in the last, I don’t know, week. Um, this is building on, so, so immediately what happened when DeepSeq came out is OpenAI just started pulling everything that they had out of the cupboards and making it available.

[00:42:08] Steve Sammartino: I love that. That’s funny. That’s funny. Panic mode.

[00:42:12] Cameron Reilly: right? Yeah,

[00:42:13] Steve Sammartino: what competition does. Competition is good.

[00:42:16] Cameron Reilly: And it was funny because they just did their 12 days of OpenAI before Christmas that we talked about in our last episode where they were launching lots of stuff that they had. But they saved the best stuff for, oh shit, DeepSeek just stole all of our thunder, we need to come out with stuff.

[00:42:30] Cameron Reilly: So, they came out, they made O3, which they had talked about before Christmas, they made it available on a limited level. But O3 Mini and O3 Mini High for coding you can get if you’re a pro or a plus user and you get more access if you’re a pro user. I’m a plus user, so that’s the like 20 bucks a month, whatever.

[00:42:51] Cameron Reilly: I’ve been using O3 Mini for coding and stuff. It’s their deeper reasoning model and it’s pretty fucking impressive, I’ve got to say. It really is a step up from O1. Really, really good. Still a bit too verbose for me when I’m coding though. I still prefer Claude. If I ask O3 to write some code or to debug some code, it’ll give me a fucking dissertation.

[00:43:16] Cameron Reilly: And here are 20 different things you could look at and 20 different ways of handling it and I’m like, too hard. Yeah, yeah. Claude, 3. 5 Sonnet, will say, oh shit, um, I think I worked it out. Uh, let’s, let’s try this. You know, it’s much more. Concise. It’s much more user friendly, I find, for that kind of stuff at this stage.

[00:43:38] Steve Sammartino: Yeah.

[00:43:38] Cameron Reilly: But then, after O3, they launched ChatGPT Tasks. Well, you can give it a task to do and it will do it automatically. And it took me a few days to come up with something, but, uh, I figured out a way to use it. Have you used tasks yet, Steve?

[00:43:56] Steve Sammartino: I haven’t.

[00:43:57] Cameron Reilly: What I came up with was, I gave it a job. I said, one of the things that I do for fun, whenever I need some intellectual stimulation, is I play the old, um, Debono random word association.

[00:44:13] Cameron Reilly: Game, right? I used to do it with my clients when I was running a marketing consulting business or if I need business generation I just get random words and I stick them together and I go what is You know, um, Apple, Apple Scissors. Okay, what does Apple make me think of? What does Scissors make me think of?

[00:44:30] Cameron Reilly: And then I try and come up with some business ideas that come into my head out of that. So I said to it, um, every morning at 7am, I want you to do 10 random word association exercises, come up with a bunch of business ideas based on those random word associations, then I want you to write Each of those business ideas against the following metrics, how easy would they be to do, what kind of capital investment would be required, what’s the size of the market opportunity, score them on about half a dozen metrics, then take the one with the highest score and write a one page white paper on what it would look like and how you would pull it together for me and send that to me every morning at 7am. And it did it!

[00:45:20] Steve Sammartino: That’s so good.

[00:45:21] Cameron Reilly: it didn’t do a great job of it, um, and I, I tweaked it as I went along, and I found that it kept using the same words over and over and over again, and then it would go, then it would use a random word with a job role, it’d say, um, Apple Lecturer, Apple Coder. Apple, you know, something, you know, Lawyer, it would come up with the same like job.

[00:45:46] Cameron Reilly: And I was going, no, no, don’t come up with job titles, just do random words.

[00:45:49] Steve Sammartino: Yeah.

[00:45:50] Cameron Reilly: And it, it, it was kind of lame. So I stopped it after about a week of doing it, but it was a way of getting it to do a thinking exercise or a task for me and just present me with something every day. So that was Apple Tasks, sorry, OpenAI, ChatGPT Tasks.

[00:46:08] Cameron Reilly: Then they came out with. Operator. Do you want to explain Operator to everyone?

[00:46:13] Steve Sammartino: Yeah. So Operator is their first agent that’s come to the market, which we’ve spoken about before, where you’ll go in and you’ll give it a task to go and do something for you, and it will take control of your desktop. and go and perform the pieces needed in the same way that you might do a task yourself.

[00:46:34] Steve Sammartino: Let’s say you’re going on a trip to Sydney and you need to book a hotel and a flight. It can do that. It, it does it, and I haven’t used it yet. I’ve just watched videos because you can’t get in Australia without, or you can do it with a VPN. I was going to do it, but I just watched some videos anyway to get a taste.

[00:46:51] Steve Sammartino: It opens a browser, so it’ll do it inside. It doesn’t do it in your browser, it does it inside their client. They have a few partner Uh, websites that they can, uh, work with, you know, like, recipes, develop a shopping list on Instacart to make me a meal that’s high in protein and is vegan, for example.

[00:47:12] Steve Sammartino: That’ll go, here’s, here’s some recipes I found, here’s the ingredients, uh, you might be able to say, I’ve got this, and it’ll tell you what to do and order it and get it delivered to your house. And it does, it’s not fully self directed, but at various points, it allows you to do logins if needed to go to external websites and different things.

[00:47:31] Steve Sammartino: Um, but it’s basically a thin version of an agent, I would say. I wouldn’t say it’s, uh, like a, a full agent model. It’s kind of, it’s pretty small scale from what I’ve seen. And I just have to tell users, I haven’t used it in the first person. I’ve watched people doing various experiments with it, but this comes down again to where we are with recursion.

[00:47:59] Steve Sammartino: Okay. In a month, where’s it going to be? It’s going to be twice as good. In two months, it’s going to be twice as good as that was. So it’s going to be 400 percent better. Yeah. By mid year, we’re going to have agents doing, or I reckon, almost anything. Is that your understanding of where it’s at?

[00:48:12] Cameron Reilly: yeah, yeah, and, and, to be fair to OpenAI and their launch, they said, look, this is very, very simplistic. And I don’t think they were ready to launch it, right?

[00:48:23] Steve Sammartino: they brought it forward.

[00:48:24] Cameron Reilly: Brought it forward because of the DeepSeek stuff. Um, but it does simple things on your behalf. It can go out and look stuff up, it can analyze stuff, it’ll check back with you if it’s got questions.

[00:48:37] Cameron Reilly: But it’s the beginning of being able to give it, uh, you know, a set of complicated things that it needs to do, and it’ll go off and do it by itself, and then come back to you when it has something to report back.

[00:48:49] Steve Sammartino: Yeah. Or needs your input. And you could say, don’t ask me unless it’s this, or ask me if you need logins or, uh, or you need me to spend money, or you can spend up to a hundred dollars each, each time with a maximum of 500 this week on these projects. You can, you can give it instructions. Uh, I mean, I, I think it’s, it’s the start.

[00:49:13] Steve Sammartino: Again, it’s, I think these have been available for a pretty long time. I’ve been using AgentGPT, which you can, you can get to buy things on your behalf as well. And BabyAGI and a few of those other ones. Uh, I imagine in a month it’s going to be twice as good and in two months, the recursion now, it’s monthly, sometimes weekly.

[00:49:35] Cameron Reilly: Well, daily, because a few days after they came out with Operator, they came out with Deep Research.

[00:49:41] Steve Sammartino: Yes.

[00:49:43] Cameron Reilly: Deep Research,

[00:49:44] Steve Sammartino: thing. Different thing, a little different, not really out doing tasks and production for

[00:49:52] Cameron Reilly: Well, it is, it is, yeah, it’s research. So, you

[00:49:57] Steve Sammartino: a research oriented agent, whereas that is, or the other one was, let’s call it, it’s not this, but let’s call it a consumer focused agent.

[00:50:06] Cameron Reilly: Yeah, a little bit more open ended. The research one, and again, I haven’t been able to play with it because it’s not available yet to everyone at our tier. It’s at the higher tier, which I should pay for because I probably spend 200 bucks easily on bloody the API. Um, You know, I was, it’s funny, like I, I’ve been using Claude to code with and I’m easily, it’s, with the API, I’m spending five, six bucks a day on it.

[00:50:34] Cameron Reilly: And I’m like, part of my brain’s going, oh shit, that’s really adding up. And then the other part of my brain’s going, you’ve got an expert programmer for five, 5 a day. And I’m spending like hours, six hours a day, eight, 10 hours a day, coding with an expert programmer for five bucks. And I’m like, really?

[00:50:54] Cameron Reilly: Like,

[00:50:54] Steve Sammartino: This is how we forget.

[00:50:56] Cameron Reilly: costing me five bucks a day.

[00:50:58] Steve Sammartino: It’s like when I watch whinging about how terrible modern life is. And yeah, there’s challenges, and not without challenges. Uh, now it’s can you afford a house? You know, uh, 200 years ago, am I, am I going to die of disease X in London because the water’s polluted? Yeah, cholera or whatever it is.

[00:51:17] Steve Sammartino: And here we are saying, should I really spend five bucks a day on someone with a PhD in all forms of code and language? And geez, it’s a bit much that five bucks a day.

[00:51:28] Cameron Reilly: Hmm. so deep research, you can, you can give it a job, um, and it will go out. And research, whatever that topic is, it’ll scour the web, it will then compile a PhD level report for you, that’s fully sourced, um, got all of the references. And, you know, it’s well written, well structured, and it will go and take half an hour or several hours to do the work, then it’ll give you the report and come back to it.

[00:52:09] Cameron Reilly: And I’ve seen, uh, some of the stuff that people have produced out of this. Somebody asked it to look at all of the executive orders that Trump has signed since the inauguration and do a, do a deep dive on the implications of each of them

[00:52:26] Steve Sammartino: Which ones aren’t? Yeah, I saw that. Here’s a question for you. With Deep Research’s ability to do PhD level research with sourcing on any topic of your choosing, does this make McKinsey More profitable or put them out of business. Over to you Cameron Reilly.

[00:52:45] Cameron Reilly: in the short term, more profitable, uh, in the long term, out of business.

[00:52:50] Steve Sammartino: Wow. You heard it here first on the Futuristic

[00:52:54] Cameron Reilly: Well, look, I think it’s the, I think it’s the same with, you know, any cognitive based profession, whether it’s legal or accounting, certainly software development, um, consulting, marketing consulting, business consulting.

[00:53:11] Cameron Reilly: Initially, People will still want a human to sue if something goes wrong, or a human to talk to and have a coffee with. And that human, the principals of the firm, or the partners of the firm will increasingly get rid of lower level staff and replace them with AIs. I mean, there’s still going to be a hurdle.

[00:53:35] Cameron Reilly: where we want to make sure there’s no hallucinations. You know, even people using deep research have said that there are hallucinations in deep research. So we’re going to have to get through that level. And I’m very, very confident that the AI firms will figure out how to deal with hallucinations. And one of the ways they seem to be dealing with a lot of the deep reasoning stuff at the moment is they have bifurcation of the systems.

[00:54:02] Cameron Reilly: Um, where you’ve got, you know, one system will do some research and it’ll feed it to the other system and that system will clarify that and go, hold on, that doesn’t make any sense and they’ll go backwards and forwards. I know that’s sort of how DeepSeek seems to have built its reasoning system as well.

[00:54:19] Cameron Reilly: So, first of all, we’re going to have to deal with hallucinations. We’re going to have to be sure that there’s like a 99. 999 percent chance that there won’t be any hallucinations in, uh, the output. Once everyone’s confident of that, we’ll start getting rid of low level people, and you might still have a mid level person that’ll be reviewing the work of the AI system, and eventually, once they go, yeah, it’s fantastic, you get rid of the mid level person as well, because you don’t need them, then you’ll just have the, the, the principals of the firms that are, And the sales people that are dealing with the customers, the relationship type people, until the customers get to the point where they go, well, what the fuck am I paying you for?

[00:55:00] Cameron Reilly: You’re just using an AI system to do all the work anyway. I don’t really need you. And then they will go the way of the dinosaurs as well. And the businesses will just use their AI systems.

[00:55:11] Steve Sammartino: Yeah. And it does two things. The first thing is it points out that secondary desk research now is something that’s going to be increasingly difficult to make a living out of. Primary research is always still important because there’s always these two kind of cohorts of research.

[00:55:26] Steve Sammartino: Is it something that someone’s done the experiments, learnt on, tested? Empirical research and then there’s desk research, aggregated research, finding what’s happening in industry stuff, where is, which is where most of the money is made. That layer on top are all the consulting firms and not, they don’t do primary research, they just aggregate information.

[00:55:45] Steve Sammartino: So that, Kybosh

[00:55:46] Cameron Reilly: even the primary, even the primary research now is going to be completely AI’d.

[00:55:52] Steve Sammartino: Well,

[00:55:53] Cameron Reilly: I need you to,

[00:55:55] Steve Sammartino: But, just quickly on that, just quickly on the, uh, the deep research, when it did Humanity’s last exam, which is the testing method, without going into great detail, it’s an incredibly complex exam in all sorts of levels of

[00:56:09] Cameron Reilly: built specifically for

[00:56:11] Steve Sammartino: for, for AI, yeah, it came in at 26%, which means within two months it’ll be perfect.

[00:56:17] Steve Sammartino: Because it’s gonna get twice as good, it’s gonna be 50 percent

[00:56:19] Cameron Reilly: Well I think

[00:56:20] Steve Sammartino: And then it’s going to be 95 to 100%.

[00:56:23] Cameron Reilly: the state of the art models before deep research were doing like 3 or 4 percent

[00:56:28] Steve Sammartino: I’ve got the numbers right here. I actually looked it up. I did my homework, uh, Cameron. So before Deep Research, DeepSeek got 9. 4%. ChatGPT 03 got 10. 5. Chat, uh, GPT 03 high. Mini got 13 and Deep Research got 26. 6. But based on that

[00:56:50] Cameron Reilly: doubled.

[00:56:51] Steve Sammartino: 183 percent improvement on previous scores. Well, you’re pretty much almost going to get there in the next iteration.

[00:56:58] Cameron Reilly: Yeah.

[00:56:59] Steve Sammartino: Certainly within two, it’s going to be 95 percent confidence level. And if that’s not AGI, I don’t know what is.

[00:57:05] Cameron Reilly: Yeah. Anyway, so that’s what’s been going on, and of course, the other thing that we have to talk about is that, uh, day two, I think, of Trump’s presidency, he and Sam Altman, uh, And Larry Ellison and the guy from SoftBank co announced the Stargate project. Um, the Stargate

[00:57:31] Steve Sammartino: Hmm.

[00:57:33] Cameron Reilly: is a 500 billion dollar project.

[00:57:36] Cameron Reilly: Now, a lot of people seem to think it’s the US government that’s funding it. It’s not, and Donald Trump really just had nothing to do with it apart from They were, they were all sucking Donald Trump’s Penis on stage. We couldn’t have done this without you, President Trump. You’re so great, President Trump.

[00:57:54] Cameron Reilly: You made this happen.

[00:57:56] Steve Sammartino: You’re the

[00:57:56] Cameron Reilly: I’m not sure, not sure about that. But, um, basically it’s going to build out, it’s a joint venture that’s going to build out data centers and electricity generation for AI, for open AI. It’s going to be built in Texas. There is going to be a hundred billion in the first trench and then, um, up to 500 billion over the next five years to build it out.

[00:58:22] Cameron Reilly: Basically, uh, because open AI just needs get out of fucking dodge size. data centers to run the billions and billions of Nvidia chips that they’re going to be putting into these things. I mean, it’s crazy. And on top of that, there’s been analysis that I’ve seen that, um, the US and China investments combined in AI will exceed 1 trillion by 2030 in the next five years.

[00:58:55] Steve Sammartino: Could it be, Cameron, for our Australian listeners, two of the big newspaper corporations here in the 90s, both built giant manufacturing plants at the peak of the old media world, one out at Tullamarine and one in Port Melbourne? Both of which were decommissioned. Yeah, they were never ran at full scale and were decommissioned long after.

[00:59:17] Steve Sammartino: It sounds like a crazy thing to say, but with what’s happened with DeepSeek, who knows that there might be some sort of a curve jump in terms of the way these models work. It could be a white elephant investment. This stuff can happen. I wouldn’t be

[00:59:32] Cameron Reilly: Well,

[00:59:33] Steve Sammartino: if, if this race for chips and giant data centers Become some sort of old world model.

[00:59:40] Steve Sammartino: Maybe AI goes, Hey, I’ve been thinking on all these chips that you’ve given me. You know, there’s a better way to do the things that I need so that I can help. You’ve got all these chips here, but did you know I can tap into the DNA in forests and use the information in their neural networks to, uh, code my information on little DNA strands?

[01:00:00] Steve Sammartino: Like, I know that sounds like crazy shit, but we know we can already store a lot of things inside DNA. So. Who knows? There may be some biological means with which data could be omnipresent within the physical Arbery infrastructure. I don’t know.

[01:00:16] Cameron Reilly: well we know how this plays out, um, the data centers will be converted to human storage tanks, like in the Matrix, and they’ll have humans in vats, and it’ll be using our brains to run the infrastructure on.

[01:00:30] Steve Sammartino: But Cameron, aren’t you and I already in VATS just now? We know this. We feel this. You feel that things are not, I mean, what is real?

[01:00:40] Cameron Reilly: Did you take the red pill or the blue pill, Steve, when you

[01:00:43] Steve Sammartino: If electrical signals served to your brain creates reality, then this is real.

[01:00:49] Cameron Reilly: you wake up as if nothing ever happened. If you take the blue pill, you see just how deep the rabbit hole goes. Um, yeah, look, data centers will be data centers.

[01:01:01] Cameron Reilly: We’ll still need data centers. What I do think will happen is you’ll buy, it’s a bit like PCs, right? You’ll buy a state of the art, you know, bunch of chips, and then a year later, you’ll literally Trash them because they’ll be completely outmoded and useless with the next generation of chips that are a thousand times more powerful And then you’ll trash those or hopefully you’ll use nanotech to deconstruct them and get the raw elements and rebuild them.

[01:01:29] Cameron Reilly: Speaking of which,

[01:01:30] Steve Sammartino: I do think just on that, that their AI is going to invent a way to replace the current infrastructure systems,

[01:01:36] Cameron Reilly: Totally. I mean we’ve already got some of, um, AlphaFold, uh, you know, uh, Googles, DeepMind, uh, scientific tools, designing new elements and new materials, new crystal lattices that have never been seen before, so, um, you know, these things are gonna continue to happen at a crazy pace. Um, I’m just texting my wife to remind her that I need to leave soon.

[01:02:07] Cameron Reilly: Um,

[01:02:08] Steve Sammartino: bit and we can tidy this puppy up. Talker

[01:02:11] Cameron Reilly: yeah. So, um, I want to get out of AI for a minute and talk about a couple of other things. Um, China set a new cold fusion record in the last couple of weeks. Um, the experimental advanced superconducting Tokamak EAST for short, E A S T, dubbed China’s artificial sun, maintained a steady state, high confinement plasma operation for a remarkable 1, 066 seconds, setting a new world record and marking a breakthrough in the quest for fusion power generation.

[01:02:56] Cameron Reilly: The duration of 1, 000 seconds is considered a key step in fusion research. The breakthrough achieved by the Institute of Plasma Physics under the Chinese Academy of Sciences greatly improved the original world record of 403 seconds, which was almost impossible. Also set by EAST in 2023. The ultimate goal of an artificial sun is to create nuclear fusion like the sun, providing humanity with an endless clean energy source and enabling space exploration beyond the solar system.

[01:03:30] Cameron Reilly: So we’ve talked about, I think our very first episode, we talked about breakthroughs in cold fusion, and that was only, what, a year or two ago. We’re now, they’re just. Again, it’s sort of doubling the recursion of what they’re able to do. They, it seems like we’ve, we’ve cracked the basic science of cold fusion and now it’s just figuring out how to scale it up.

[01:03:54] Steve Sammartino: That that’s, it’s extraordinary if that happens. Cause it, it, it changes a whole lot of dynamics. Would that be if the Chinese have developed it? Is, is that knowledge shared and, uh, could that be replicated in Western markets as well? Or is this something that becomes a cold war of we’ve, we have the technology?

[01:04:20] Cameron Reilly: No, I think a lot of the basic science with all this stuff is either published or is easy to reverse engineer. I mean, and that’s the thing with AI that we didn’t talk about with DeepSeek. You know, One of the things that you can see happening in the AI space, and, um, I’m not an AI engineer or a gynecologist, I just pretend to be those things, uh, for profit, but, you ever heard that?

[01:04:49] Cameron Reilly: I’m not a gynecologist, I just play one on TV, um, the, I always say I’m not a historian, I just pretend to be one on my podcasts, um, even though I’m OpenAI doesn’t publicly disclose how they build O3 or how they build deep research or, you know, what the underlying tools are that they’re using. For everyone else, All the other AI engineers that are at Anthropic or a deep seek or a Google, it’s not that hard to reverse engineer how they’ve done it.

[01:05:27] Cameron Reilly: You know, the basic principles and the thinking are easily, are easy to determine. Once they see it done, they go, oh,

[01:05:35] Steve Sammartino: you see the product in action, it gives you clues to what went into it to bake that cake.

[01:05:40] Cameron Reilly: exactly, so you know what’s going on here? I think a lot is, you know, the other AI engineers are gonna go, oh, okay, they figured out how to make that work. It must be a way to make that work. Let’s figure out how to make that work. And, and in fact, I saw this. So, what’s happened with deep research this week?

[01:05:56] Cameron Reilly: So OpenAI came out with deep research, the engineers at Hugging Face, one of the platforms that hosts all the models, said, hey, let’s see if we can build our own deep research in 24 hours. So they did a 24 hour code a thon to try and figure out how OpenAI works. built deep research and I haven’t gone to play with what they built, but they felt the last I saw, which was a day or two ago, they felt like they were pretty close to replicating it.

[01:06:27] Cameron Reilly: And I was like, okay, let’s see if we can reverse engineer the thinking behind how they did this and build our own. Like that’s where it’s at now is like, Oh, okay, that can be done. Let’s figure out how to do that. And then 20 people do it. 20 organizations have it. And then there’s another thousand that’ll come on after those, right?

[01:06:42] Cameron Reilly: So it’s, it’s kind of this crazy level of. So, recursive thinking. If it can be done by everyone else, it’s like the ol three minute mile thing. Once someone proves it can be done, everyone figures out how to do it,

[01:06:54] Steve Sammartino: well no one’s done the 3 minute mile yet, let’s go with the 4, but having said that Cameron, the day after Billy Bloggs did it, and who knows his name, apparently like 30 other dudes did it within like 3 months or something, because it was, it was like oh, it’s possible.

[01:07:07] Cameron Reilly: yeah, it’s possible, right? Let’s go do it! The last thing I want to talk about. So, I talk about nanotech from time to time, and, and the, the, the father of, of technology. I mean, there’s a couple of fathers, but the guy who wrote the book, um, in the eighties that sort of defined our current thinking of it, K.

[01:07:23] Cameron Reilly: Eric Drexler, um, I, I watched a talk recently that he gave late in 2024 on the current state of the art nanotech. And, and in a way it was a little bit disheartening. He said, look, what gets called nanotech out there today isn’t really real nanotech. Like what, what is. Called nanotech these days is like that thing we talked about last time, the iron filings being able to use with magnetics or it’s, you know, it’s very, very simple sort of DNA structures that are able to do certain things.

[01:08:00] Cameron Reilly: It’s not. His vision of nanotech, which is nano sized robots that you can program and that can communicate with each other and that can build things and dismantle things, etc. And in his talk, he basically said, it was only a 15 minute talk, but he said, the problem is, is we don’t actually have anyone building the vision yet for for what these things should look like.

[01:08:27] Cameron Reilly: The first step is the vision. And the example that he used was when, when, when NASA stole the best German Nazi rocket scientists after World War II, like Wernher von Braun, and said, build us a space program. There was a, an article that he had that Drexler had, um, From Time Magazine from the early fifties, I think.

[01:08:55] Cameron Reilly: That was written by Wernher von Braun, the great Nazi rocket scientist. That

[01:09:01] Steve Sammartino: listen to you for the rest of the day just say great names like Nasa and then Wernher von Braun? Can we just do that for three hours or can you send me a recording tonight of just saying a whole lot of really good tech names and people through history and I’ll just listen to it as a, as a, as a sonnet to put me to sleep tonight.

[01:09:17] Steve Sammartino: It’s beautiful Cameron.

[01:09:19] Cameron Reilly: I don’t have time. Um, it was like visualizations of what a rocket and a space station would look like. So he, and, and, and, and, he was, Drexel was going through it, and pretty much, it looks like a rocket. And it pretty much looks like a space station. Like they, they thought about what these things would look like, and they visualized them.

[01:09:42] Cameron Reilly: And then other people could come along and go, okay, well, how would you build that? And then they built it. He said, with nanotech, we don’t, we’re not even at the visualization stage yet. We need a generation of really smart folks to visualize what these things would look like, and then we can go and start building them.

[01:10:01] Cameron Reilly: Now I was sort of shocked and surprised by that. I thought we were. Well past the visualisation stage for Nanotech, yeah. But he was also very confident that we will do it, and I know that Kurzweil is very confident that this will get done this decade. But, the bottom line is, according to Drexler’s talk, We haven’t even really got started on that level of nanotech yet.

[01:10:25] Cameron Reilly: Now, of course, I think with the way AI is going, we should make a lot of very, very rapid progress on how to build these things once we know what it is we want to build. And hopefully there are smart kids out there thinking about this right now. I’m not, you know, but all of the smart kids are getting sucked into AI and robotics right now.

[01:10:46] Cameron Reilly: Actually, my son Taylor is, um, he just got his U. S. visa, his, um, um, not a green card, but his working visa to go over there. So he can go and live and work there, um, for the three or four years. And he’s got a friend of his who works at, um, uh, What’s the big robotics company over there? Um,

[01:11:09] Steve Sammartino: uh, figure, figure robots.

[01:11:12] Cameron Reilly: who’s an engineer at figure robots, he said he’s gonna give Taylor a tour of the,

[01:11:18] Steve Sammartino: be cool.

[01:11:18] Cameron Reilly: of the robot, um, factory or the lab or whatever.

[01:11:22] Cameron Reilly: Yeah. So anyway, um, hopefully some of those smart generations of kids are gonna start to work

[01:11:29] Steve Sammartino: I think that

[01:11:30] Cameron Reilly: really need nanotech.

[01:11:32] Steve Sammartino: given that agentic AI is going to open up a lot of time, and I think what it does is it opens up imaginations of people without the Uh, education or skill base to execute against their imagination and vision and new industries will emerge because people who’ve got great imaginations but might not have the technical chops can now start to explore certain areas.

[01:11:58] Steve Sammartino: And you know, we could have a Cambrian explosion because of AI, where a lot of these other areas like nano top, uh, nanotech start to get opened up a little bit because people can explore it more quickly, both, both verbally, mathematically and visually design design wise as well.

[01:12:15] Cameron Reilly: I absolutely believe that that will happen soon. Alright buddy. Listen, I gotta go. Um. But glad that we found the time to catch up and chat. It’s an exciting time and I enjoy talking to you about it.

[01:12:30] Steve Sammartino: Thank you, Mr. Riley.

[01:12:31] Cameron Reilly: let’s promise that we’ll do another one next week and then maybe within six weeks, we’ll actually do it.

In this episode, Steve and Cam provide their top three tech/AI highlights from 2024 and provide their top predictions for 2025.

FUTURISTIC 34

[00:00:00] SS: Recording in progress. Welcome to the future. I’m Steve Sammartino, and introducing the great OG of podcasting, Mr Cameron Reilly.

[00:00:18] CR: Turning me on, Steve. Slow down. Um, don’t turn me on until later in the show. Welcome to The Futuristic Episode 34. We’re recording this 20th of December, 2024. How are you, my little buddy?

[00:00:31] SS: I’m good. I’m great. It’s big. It’s been a big year, Cameron.

[00:00:38] CR: It has been a big year, Steven. I, I suggested to you last week that we don’t do a show last week, because OpenAI started doing this thing called the 12 Days of OpenAI, where every work day for the last 11 days, uh, they have done a live stream where they’ve launched a new thing, a new feature, a new function of ChatGPT.

[00:01:00] CR: And there’s one more day to go and I said let’s wait till next week because there’s probably something big that’s going to come up and as it turns out like Friday US time, which will be tomorrow our time, they’ll do day 12 and hopefully that’s going to be the biggest thing and we’ve sort of missed the chance to do that but even the last 11 days have been insane like there’s been so much coming out in the last 11 days of the year and while they’re coming out with stuff Google have been coming out with stuff to One up them on their stuff that they’ve come out with, so it’s just been this crazy period of leapfrogging going on in the last couple of weeks.

[00:01:38] CR: But it has been a crazy year, and your idea for the show this year is for us to do like our top things of the year and our predictions for next year, is that what you want to do?

[00:01:47] SS: That’s right. So I was thinking the top three from this year, there’s zillions, but we’re kind of trying to at least squeeze it into an hour or so. And top five each for next year. And interestingly, if I think of some of mine, there’s, there’s a bit of overlap, but I’m going to try and keep them separate. I just did my tech and AI transfer 20, 25 and did 20.

[00:02:08] SS: It could have been a hundred long. Uh, there is some overlap, but that’s what I think we do.

[00:02:15] CR: Okay, well, uh, why don’t you kick it off with your top three things from 2024?

[00:02:22] SS: Okay. So my first one is AI recursion, and it’s not a thing, but I think it’s kind of like a zeitgeist or an event. Never, ever have I seen things get so much better so quickly. Like the iterative. Uh, improvements and features that are coming in. And I think OpenAI has been extraordinary. The amount of new things that they’ve had this year, just from the LLM itself, getting better computation, uh, ability to do maths and not just language stuff, uh, imagery, video, Sora, uh, live video feed on what you’re looking at, web integration, which has been huge as well.

[00:03:11] SS: So. Just the recursion happening so quickly, and it’s even blowing my mind, and we know that change is exponential, but it feels like we’ve finally hit the exponential part of the exponential. If that makes sense, the doubling and the recursion is just quick. Let’s just think about Apple do annual events, and things didn’t change that quick, but in the kind of 24 months they’ve been in the Zeitgeist, it’s, like you say, it’s every other month there’s something, and it’s getting quicker and quicker.

[00:03:40] SS: You just mentioned they’re 12 days of open AI.

[00:03:44] CR: Yeah.

[00:03:44] SS: That has never happened in tech.

[00:03:47] CR: No. Look, it, yeah, um, I think you’re right. Recursion is crazy, and this is the sort of stuff that, uh, Kurzweil has been predicting for decades that when you get to the part of the asymptotic part of the exponential curve, that things just go insane. And it,

[00:04:12] SS: It’s incomprehensible speed and, and the recursion itself. And I imagine that this is part of it is that the tool itself is inventing new parts of the tool. Like it’s, it seems that that’s pretty clear. And I don’t think we’ve really been there yet. I think this is the first time because we’ve got, you know, Code that understands code and can self improve.

[00:04:34] SS: I think we’re actually hitting the technology self improvement element of that exponential. And I think that’s why everything is so radical right now. So for me, that was my number one thing this year that blew my mind. Uh, yeah, iterative pace on steroids. That was my number one. My number two. Alright, keep going.

[00:04:57] CR: well, I was just going to say, it’s not just like software, you know, building software, but the ability for people to Increasingly, just to have an idea and then develop it within a week. You know, I saw one of the, I think it was yesterday’s 12 days of OpenAI thing. They launched 1 800 CHAT GPT, which is

[00:05:21] CR: where you can call,

[00:05:23] SS: don’t know what it is, but I love it already because I just love a retro. I hope they’ve got a truck that drives down highways with that written on the side. I hope that so

[00:05:31] SS: much.

[00:05:31] CR: they had it flashing up on the screen while they were doing the live stream in like this really cheesy late night infomercial font. It was fantastic. If you’re in the U. S., you can call 1 800 CHAT GPT and just talk to the AI and ask it questions. If you’re outside of the U. S., You can use WhatsApp to call it and I’m, they were saying it’s, if, if you’re, if you don’t have internet connectivity, but you need to talk to ChatGPT and you have telephone connectivity, you can do it in the US.

[00:06:02] CR: I’m pretty sure, I don’t know about, I’ve never used WhatsApp that much, but I’m pretty sure you need internet, you need data to use WhatsApp, right?

[00:06:10] CR: You can’t just use it over a telephone signal.

[00:06:13] SS: Yeah, data is what you’re

[00:06:14] SS: watching.

[00:06:15] CR: sort of defeats the purpose. But, but that one of the demos that they did is one of the guys used a rotary phone to call ChatGPT.

[00:06:26] CR: And he said, I don’t think I’ve ever used a rotary phone before in my life. So this is an experience on multiple levels. But I was talking to, you know, I was explaining this to Chrissy later on last night. And I was saying like, you know, try and explain that to somebody 10 years ago, 15 years ago, the idea, we were talking about how we remember when the height of cool was to call the time service on your phone.

[00:06:54] CR: I remember in the early 90s, I would do that just because it was cool. At the tone, the time will be 12. 05. And 15 seconds. Beep. Beep. Beep. And you could call and get your horoscope read out. Now, we go, oh yeah, you can just make a phone call, and it’s for free. You can do it for free. I think they’re allowing like, you don’t even have to have a GPT account or anything like that.

[00:07:23] CR: Like 15 minutes a month or something, free phone calls, you can make to GPT from your number. Um, You make a phone call and have a conversation with an artificial intelligence that lands all good. One of the demos they did is a guy said, um, ChatGPT, my friends and I on a road trip, we’re in the middle of nowhere on this highway in California.

[00:07:44] CR: We see these houses. They’re like weird, round coloured houses. Any idea what they would be? And they go, Oh, that’s the famous Flintstone houses that were built. And they’re a tourist thing and blah, blah, blah, blah, blah. So just to be able to call AI wherever you are and ask a

[00:07:59] CR: question.

[00:08:00] SS: AI on traditional networks.

[00:08:05] CR: Yeah,

[00:08:06] SS: So not really using data. So you’re kind of not using data.

[00:08:10] CR: No, you’re using a telephone line to call it and it’s talking to you.

[00:08:13] SS: data, by the way.

[00:08:14] CR: well,

[00:08:15] SS: which I love. That was one of their greatest hacks. These are phone calls, and these are data. It’s like, yeah, they’re all ones and zeros flying through the sky, you liars.

[00:08:21] SS: I just want to point that out. I always knew, and I wasn’t falling for it. It’s.

[00:08:25] CR: Everything is ones and zeros. Um, but the, the, the, the point I was going to make about all of this was they said. That this idea came up in a OpenAI Hackathon and the team developed it in like a week to go live with. And this is getting back to the recursion stuff that you’re talking about. To have the tools available now to go, Oh, I want to build this thing.

[00:08:49] CR: And I’ve talked about this on the show, cause I do this all the time now. Oh, I’ve got this idea for a thing, an app I can build that’ll solve a problem of mine. And an hour later I can have it built. Like that is the, Era we are now entering into where billions of people can build things in an hour or a day or a week that didn’t exist before because they have an idea.

[00:09:13] CR: And we’re not quite at the stage, but we’re not far from the stage where you can just say to the app, Hey, build it for me, and it’ll do it lock, stock and barrel. It’s pretty close to that,

[00:09:27] SS: I do

[00:09:28] CR: not a hundred percent.

[00:09:30] SS: all the time. I was asking it to do something yesterday, which was I had a whole bunch of business cards that I wanted to extract all of the emails from because all of these people, when they give business cards, say,

[00:09:41] CR: closer to your mic, Steve. You’re sounding like you’re in the next room.

[00:09:45] SS: Okay. So I collect a lot of business cards at events.

[00:09:49] SS: And when I, Take the business cards off the person. I say, do you mind if I put you on my email list? I do a weekly tech thing. They’re like, Oh yeah, cool. No worries. So I get their permission. And I normally would just type it into my sub stack, but I went on to open AI, took a photo of it, put it in and said, extract the emails, but it struggled with, uh, some of the fonts and the, so I, it had told me why it was struggling with its, um, observational, uh, Metrics, and I said, what would fix it?

[00:10:18] SS: And it said, you would need this. And it gave recommendations of the software that use it. I said, do you know how that software works? And it says, yes. I said, could you build it? And it said, yes. And then it built it and I’ll put it on my client and it worked.

[00:10:32] CR: That’s

[00:10:32] CR: great,

[00:10:33] SS: So, so, so one of the things that I’m doing now, often it’ll recommend a piece of software AI that can do the tasks that it can’t do, I ask it to look at.

[00:10:43] SS: Do and research it, even provide the link and go look in that. What does it do? What does its course functions now write the code and it’ll write some code in Python, and then I download it on my client and I do it there so it can kind of already do it at the moment. It needs us to tell it soon. It won’t.

[00:10:59] SS: It’ll go, wait a minute, let me write some code to be able to do that thing. So, and I don’t think everyone has realized the power in our hands now is insane. It’s insane. I just, every day I’m agog. I’m like, holy Wow.

[00:11:15] CR: Magog.

[00:11:17] SS: My God. So, okay, number

[00:11:19] CR: You were there! You did a video from that alley recently, where Gog and Magog are, right?

[00:11:26] SS: Uh, maybe.

[00:11:27] CR: You did a TikTok in the little laneway in Melbourne where Coco Black is, and there’s the clock with the two,

[00:11:36] SS: do one there. I did do that. I

[00:11:37] CR: two ogres that are defending the clock, they’re Gog and Magog.

[00:11:42] SS: Okay. I did do that. I didn’t know they were called that. You’ve taught me something in my own city.

[00:11:47] CR: There

[00:11:47] SS: If you want to know more about the city you live in, just ask a tourist because they’ve been to all the places you never got around to.

[00:11:52] CR: Dude, I lived there for 20 years

[00:11:54] CR: and I used to do TikToks.

[00:11:55] SS: I know, I’m not calling you a tourist, but I’m

[00:11:57] CR: did a podcast 20 years ago where I had a local Melbourne tour guide and we would go around and do tours of Melbourne and record the tour so other people could listen to it as a podcast. I did it for the City of Melbourne or Tourism Victoria or something.

[00:12:15] SS: right, we’re going to be here at 4am, which I love, which I

[00:12:18] CR: Sorry, keep going. Your top three things. What was number two?

[00:12:21] CR: And

[00:12:22] SS: and number 2 for this year was Humanoid Robots. That surprised me a little bit, it shouldn’t have, in hindsight, but what I love here is the marrying up of robotics which have been around since II, making cars, manufacturing. I love the humanoid element and I love that it’s the installation of LLMs that make them functional and trainable with verbal and visual reasoning.

[00:12:44] SS: And we’ve spoken about it on the show before, within a decade we’ll all have them. For me, what they can do now is kind of like, here’s a computer in 1976 and it’s really going to change stuff. It’s like a huge, huge moment for everyone. And I think it’s going to be Maybe even bigger than the Henry Ford revolution where you’ve just got this incredible device with incredible power that just changes your life, your home, your everything, every workplace.

[00:13:14] SS: That one there was huge and it’s a little bit like what happened with the car. We had carriages for a really long time and then once we had fossil fuels and the internal combustion engine that we put those two together and we changed everything. It’s kind of like that with software and hardware on this.

[00:13:28] SS: It’s a marrying of the two. I don’t think it’s. Extraordinary. OpenAI and NVIDIA, I mean, two of the heroes at the moment coming together with the figure one, super impressive.

[00:13:38] CR: I mentioned to you off air that last night NVIDIA, Jensen Huang, Did a launch of a new piece of technology they have, it’s called the Jetson Orin Nano Super. And it’s a, basically a CPU or GPU, um, that’s basically the size of an iPhone. It, uh, is designed to run, An LLM on device, on a robot or an edge device, something on a mine, something in a factory, something in your house, that can run a fully functional LLM locally on the device without having to go off to the cloud, and they’re selling it for 249 US, and it does 67 tops, 67 trillion operations per second.

[00:14:35] CR: NELP. Um, I did an analysis of that last night with, uh, against my Pentium 400 that I had in 1995 just as, uh, for shits and giggles. And it’s, it’s basically, and that would have cost me two and a half, three grand, I think, back in the day. This, uh, That Jetson device would be about 167 million times as powerful as the Pentium 400 that I had in 1995, it was nearly 30 years ago.

[00:15:22] CR: For a tenth of a second. Tenth of the price, and it’s specifically designed to run all of NVIDIA’s AI platform, the CUDA stuff. Um, just mind boggling

[00:15:36] CR: stuff.

[00:15:37] SS: can’t even get those numbers in your head. And I think I said to you as well, when we hear 167 million times, we just think 167. Yeah, you almost don’t even comprehend it. It’s incomprehensible.

[00:15:48] CR: Yeah, absolutely.

[00:15:50] SS: Number three for me was, and this one’s kind of got a sense of irony about it. Um, cause Google’s been called a monopolist, but I just, I’m calling it the post search society because Google has cancer.

[00:16:02] SS: Certainly their search division does. Uh, I saw some numbers which astounded me, uh, which Google isn’t really. Publishing, and it’s hard to find, but up to 80 percent of heavy internet users are now using GPTs instead of search. An 80 percent substitution ratio. 80 percent

[00:16:25] CR: That can’t

[00:16:25] SS: of, now what they didn’t say, no it is, of high volume internet users are using GPTs and LLMs 80 percent of the time when they would historically before then be using search.

[00:16:39] CR: That

[00:16:39] CR: sounds

[00:16:40] SS: And I think that, I reckon I’m 90%. Yeah, not high, high frequency internet users. So, I don’t know

[00:16:46] SS: what that

[00:16:47] SS: cohort is. I don’t know what that cohort is. It could be 5 percent of super users, but, but look, I know this for sure. And let’s just get anecdotal about it. How many things, how many times a day would you now go to the LLM instead of Google?

[00:17:01] CR: Oh, a hundred, a hundred, a hundred

[00:17:02] SS: Is it 50%?

[00:17:03] CR: A hundred

[00:17:04] SS: you just told me that that’s hard to believe. And then now, you say, I must search as the content heavy internet users. How many times a day would you now go to the LLM instead of Google? Because

[00:17:11] SS: I reckon 80 90 percent of the people just don’t realize how powerful this is and they’re just not really using it yet.

[00:17:18] SS: It’s kind of like this is 1999 and no one’s really using Google. There’s a bit of a lag, uptake lag. But I think that this is my big one. I think we’re about to enter post search society, especially now that GPTs have live web and you can go to the web live. It’s like I almost don’t even use Google now. I just use it to find a location or a map or a particular website, but I don’t actually use it for anything that is knowledge based, information based, function based.

[00:17:45] SS: I don’t work with it like I used to. This is gone. And, I mean, Google obviously has Ramo and Maps and a whole other raft of important parts of their business, and they’ll be fine, and I’m not too worried if they’re not, uh, even though I’m a shareholder, but, I tell you what, this is the post search society, this is, I seriously, I am not mincing my words here, traditional search is yellow pages. it’s already happened. I’m telling you, they’re fucking dead.

[00:18:14] CR: no, I disagree. I think you’re, you’re calling it way too soon. Um, but, and I’ll tell you why in a second, but

[00:18:20] CR: before we get into

[00:18:21] SS: I’m not saying that Google won’t, I’m saying, I’m not saying that Google won’t go and get their LLMs and transition it. And this is their challenge, is to adapt. This is their challenge. And the reason I don’t think that they will, is because they have an entire infrastructure based on the revenue streams, which is pay per click and ads.

[00:18:39] SS: And I think the future is subscription, and thank God for that, because it might just save the internet. Because the last thing you want is ads, because it changes what you see. I think subscription is much better. I think they’re fucked. I think they’re fucking, their search is dead. Absolutely fucked. Dead in the water.

[00:18:55] SS: I’m calling it now. I’m fucking calling it hard.

[00:19:00] CR: so one of the things that OpenAI launched during the 12 days of OpenAI was the general availability of search inside of ChatGPT for free users, as well as previously it was available for plus users. So they’re going hard on that, but again, the thing we have to remember is that Google has a massive ecosystem, they’re a bit like Apple, they’ve got a massive device install base running Android, that where their LLM, Claude or whatever it is, will be the, not Claude, that’s Anthropic, um, Gemini will be the default on all of those devices, um, depending on what happens with their, um, Monopoly lawsuit, they may be able to block ChatGPT’s, uh, ability to be featured heavily on those devices.

[00:19:58] CR: But they’ve got a very strong tool, and they’re coming back really hard with a lot of this stuff. Gemini, They just launched a new version of Gemini in the last week that’s doing really well in the benchmarks. Their latest video, text to video tool looks like it’s way better than Sora, which OpenAI also publicly launched in the last week or so.

[00:20:21] CR: But Google’s tool, I think it’s called Veo, is not publicly available yet. Um, I don’t know, man, I think, you know, because of their install base, their device base, and, you know, you’ve got Chromebooks and all that kind of stuff, and the Gmail user base, and all that kind of stuff,

[00:20:37] CR: that they’ve

[00:20:38] SS: I didn’t say Google was dead. I said search, as we know it, has got fucking terminal

[00:20:43] CR: well, it’s, no, but search is just going to evolve into,

[00:20:46] CR: search is just evolving into AI

[00:20:49] SS: I’ll tell you

[00:20:50] CR: AI

[00:20:50] SS: I’ll tell you why it won’t.

[00:20:51] SS: And it never does. It won’t and it never does and I’m going to tell you why because this happens fucking again and again and again.

[00:20:59] SS: Is that companies always love their business model more than they love the technology in there.

[00:21:05] CR: Christian Clayton’s innovator’s dilemma, I agree

[00:21:08] SS: 100%. It is still

[00:21:09] SS: what can happen.

[00:21:10] CR: But!

[00:21:11] SS: They are gone on that area. They’ll still be a big, and by the way, Kodak and everyone that you’ve seen has been disrupted, had all the technology, had the footprint. Everyone said, Kodak won’t die.

[00:21:21] SS: They’ve got a footprint of 40 trillion

[00:21:23] CR: Google’s a fundamentally different business. It’s a technology business that has been at the forefront. We, like, OpenAI came out of Google. LLMs came out of Google and Google has Demis Hassabis, who’s no fucking clown.

[00:21:40] SS: Okay. I get it. But the difference has got nothing to do with

[00:21:45] CR: They take it, no, it’s about culture, but they

[00:21:48] CR: take it

[00:21:49] SS: It’s about business models. It’s not about culture. No, it’s not even about culture. It is about business

[00:21:54] CR: but it’s the culture that protects the business model. But it’s the culture of the company that protects, I mean, that’s Clayton Christensen’s whole thing about protecting the business model from era one till it’s too late to transition to era two and then you lose

[00:22:10] CR: the transition war, right?

[00:22:26] SS: Do you know what it is? Salesperson.

[00:22:29] CR: Right.

[00:22:29] CR: It’s like

[00:22:30] SS: They’ve got more salespeople than anything else in their business. You think they’re a technology company? They’re

[00:22:35] CR: the way, I love this podcast because it’s the only podcast I do where we argue. All the other podcasts I do, we just agree on everything. I love this. You and I can have an argument. I love it.

[00:22:45] SS: Fuck you, Cameron. You are so

[00:22:46] CR: No, it’s

[00:22:47] CR: great. I love it. I love it that we have

[00:22:49] SS: are fucking dead. They’re fucking dead, mate. Because everything

[00:22:52] CR: but you’re saying Alphabet’s not dead.

[00:22:54] CR: Google’s not dead.

[00:22:55] CR: Just, you’re saying

[00:22:56] SS: I’m saying

[00:22:57] SS: searches, they’re fucking dead. Now, here’s where I reckon, quickly, where I reckon they’re gonna go gangbusters and fucking slay the world.

[00:23:05] SS: with Waymo. Waymo is crazy. In every city they’re in now, they have 30 percent of ride share already. They’ve already overtaken Lyft, and they are eating into Uber so quickly, it’s not even funny. Anyway, so they’re my three, and I love that we disagree, and the beauty of it is, we’re going to talk every week and just see how this thing rolls out.

[00:23:28] SS: Now Cameron, over to your top three from this year.

[00:23:32] CR: I’ve done no prep,

[00:23:33] CR: because you

[00:23:34] SS: I love that. You don’t need

[00:23:35] CR: we were going to do like

[00:23:36] SS: were Born ready

[00:23:37] SS: born ready.

[00:23:38] CR: Yeah, that’s what I always say. Um, but, off the top of my head, I mean, it’s been a huge year, and I’ve probably forgotten a bunch of things. But, the things off the top of my head that I’m most excited or impressed about this year.

[00:23:52] CR: First is going to be Claude 3. 5 Sonnet and Coding. Now, funnily enough, just in the last, last 24 hours, O1, OpenAI’s new model, just beat Claude in the coding benchmarks. I haven’t tested O1 recently for coding because Claude 3. 5 has just done such a great job. job for me, but my ability to code stuff in the last couple of months using Claude 3.

[00:24:22] CR: 5 Sonnet has just been, um, like a magical experience. Not perfect, but just insane. Like you were saying before, like when I wrote that news app, A couple of weeks ago, I was going, Hey, can you just like build me my own news aggregator? Yeah, yeah, sure. Here it is. Boom. Like it’s, it’s, that has been an insane experience for me this year.

[00:24:49] CR: Um, the fact that you could just think of something and build it now, like it’s, it’s crazy that we can do that. Uh, with a tool that cost me, I mean, I pay for the API, but you know, and I, and sometimes I, I, run up quite a bill on it. You know, it might cost me anywhere from 20 to 50 bucks a month to use the API, depending on how

[00:25:09] CR: heavily I’m

[00:25:09] SS: What a build. Isn’t it funny on what’s quite a build these days? Go out and hire a software developer in 1992 and mortgage your house to get a shitty piece of software. It’s

[00:25:19] CR: Yeah. Or even hire one today. It’s going to be the same thing. Like to, to have somebody building apps for me for 20 to 50 bucks a month is crazy. My second one would be AI integration with apps. So we start the open AI, just released a lot of this stuff in the last couple of weeks, part of the 12 days to further and further integration today in their live stream, they announced integration with Apple Notes, which I don’t, I don’t Use any more, I use Obsidian, by the way, if you don’t use Obsidian and you’re a big note taker, check it out, Obsidian is absolutely magical tool.

[00:25:59] CR: One of the best pieces of software out there, in my opinion. But, um, we’re now at the era, I have AI integrated into, um, My code, um, app, the, the, the development environment that I use, I have it integrated in a couple of other different apps. So we’re now in the beginning of the era where it’s integrated into your apps.

[00:26:25] CR: It can see what you’re doing, You don’t have to copy and paste it from your app into the AI and then paste the result back. It’s just watching what you’re doing. It’s making suggestions as you go. It’s coding alongside you. That is the beginning of the future where AI is just integrated into everything that you do and all of your

[00:26:51] SS: It’s just in the walls. It’s just in the walls like electricity. That’s where AI is going. Ambient computing and omnipresence is when a technology has really reached its threshold. When you don’t have to go to it, it is just everywhere. That’s when you know technology has changed things.

[00:27:08] CR: By the way, this has been one of my rants for the last couple of weeks. I don’t know if you and I’ve talked about this, but let me ask you a question. Do you know how electricity works?

[00:27:16] SS: Uh, I’m gonna say no because I think my answer will be wrong even if I try it. So I’ll just go with no. Can you tell me? Don’t they look

[00:27:25] CR: Well, I think most people don’t know how it works. And it’s, it’s one of those things like, Special Relativity and the Double Slit Experiment that I need to re read myself every few years to remind myself because I forget. I need to do a refresher course on it every now and again. But I think, See, the way that you kind of get taught how electricity works in school is when you, at high school, in high school science, right, is you flick a switch and it opens the hose, this is a wire, and electrons get pushed down the wire to the filament in the light and they, and it heats up the filament and light comes out.

[00:28:06] CR: That’s not true. That’s not how electricity works at all. The electrons don’t move. They do move a little bit.

[00:28:16] SS: it’s like a wave in the ocean, which a lot of people think a wave is actually the same chunk of water. You know how a swell goes through the ocean, but the drops stay where they are. It’s the energy that

[00:28:29] SS: moves and it moves the drops in that spot. So it’s actually a hump and, and, and water. People don’t realize that you’re actually just riding energy.

[00:28:37] SS: You’re not even riding the same drops of water when you’re riding a wave.

[00:28:41] CR: but what is energy?

[00:28:44] SS: I don’t fucking know. You better tell me. I mean, I sort of know, but I, I, I’ve done the school stuff, but I kind of don’t really know. So can you please tell me and the listeners?

[00:28:55] CR: well, energy is just the ability to do work. It isn’t anything, you know, it’s what the issue I always have with new agey types, when we start having conversations, they go, well, everything is made of energy.

[00:29:05] CR: Like

[00:29:05] SS: Oh, they love that. It’s their favourite

[00:29:07] CR: is just the ability to do work. So what, What are you fucking saying?

[00:29:12] CR: It doesn’t make any sense. You, you’re just using random words. They don’t mean anything. That it’s like from Princess Bride. I do not think that word means what you think it means. Um, but here’s the, I had this conversation with ChatGPT the other day where I was going down this thing about electricity and how it works.

[00:29:28] CR: And I said, well, you know, what happens is the electromagnetic field. Field, uh, which is everywhere and it permeates everything that’s around the wire carries the energy, the field carries the energy down to the filament. And we go, but what’s, what’s the field? What is the field? And then it started going, well, think about waves on the water.

[00:29:52] CR: Don’t give me fucking analogies. I’m asking you a question. What is the field made of? And they go, well, think of this analogy. I’m going, don’t Fucking give me a na I went on with this for an hour. I’m having a voice conversation with it when I was

[00:30:03] CR: cleaning the

[00:30:04] SS: By the way, you told me you don’t swear at AIs in a previous post. You AIs, and I’m starting to sense that now that they’re

[00:30:11] CR: I was, I wasn’t swearing, I’m, I’m, I’m exaggerating.

[00:30:14] CR: I was being very polite.

[00:30:16] SS: just wanted

[00:30:16] CR: I don’t like And I was like, what is it? What is the field? And it was fudging. So after about an hour of ChatGPT, I gave up and I went to, um, Gemini, cause the new Gemini had just come out. And I said, what is the electrical field made, electromagnetic field made out of? Fundamentally, what is it?

[00:30:36] CR: And it said, nobody knows. Science doesn’t know. It’s one of the great mysteries of science. We do, we know it exists. We know how to use it, but we don’t know. What it is, we just take advantage of it. We don’t know. I went back to GPT and I said, Gemini just told me we don’t know what it is. And GPT said, Oh, well, that’s true.

[00:30:56] CR: Yeah. And I said, well, why didn’t you just fucking tell me that an hour ago, instead of giving me the same bullshit analogies over and over again, just say, Hey, listen, we don’t know what it’s about. He goes, Oh, you’re right. I should have said that. So

[00:31:06] SS: this is a key this is a key career business and technology insight for everyone. You don’t need to know how something works to make it work for you.

[00:31:16] CR: yeah, it’s like quantum mechanics. We still don’t know really what’s going on with quantum mechanics. We know how to use it. We do lots of stuff with it. No one knows how it works, or why it works the way it works.

[00:31:27] SS: It is nice to know how something works, it is nicer to get it working for you.

[00:31:32] CR: Here’s my analogy, though, with AI. We don’t know how AI works. No one knows how AI works, still, right? But we know how, we’re learning to know how to use it, and it will be like electricity, as you say. We, no one will know how it works, we’ll just do stuff with it. So, but AI integration with SMA, my third would probably be Apple Vision Pro.

[00:31:51] CR: Even though it’s had a minor, Eve, have you had the demo yet? Have you gone?

[00:31:59] SS: yeah, the demo, I’m like, how is this changing anything for me?

[00:32:03] CR: God, you’re

[00:32:04] CR: such

[00:32:04] SS: I went there and did it, and I actually meant to talk to you about

[00:32:07] CR: spiritually. You are so dead

[00:32:09] SS: I’m not seriously dead, I’m like, yeah, I get it, it’s nice and you can do all these things, and I get that it has a lot of applications. Right? I get it. I get that it has a lot of entertainment and industrial applications and it’s incredible and it’s, and it’s good, but I just, I just, it’s just a bit of a so what for me.

[00:32:29] SS: I don’t see how I’m going to plug into that and fundamentally change my life for the better.

[00:32:36] CR: Wow. Okay. Well, they’re my

[00:32:38] CR: top three

[00:32:39] SS: me why you love it though. Look, I just want to keep to make sure this is not the Mutual Agreement Society podcast because no one So I did lean into it a bit, I gave a bit of Cheryl, it was a bit of a Cheryl, and I leaned in to the disagreement. Now, come on, tell us what you love. this,

[00:32:53] CR: Well, you know, I think in terms of, I said this at the time when I did my demo, like, very few times in my life I can think of when I experienced a new piece of technology and it blew my mind and I went, this is me. A fundamental quantum leap on anything I’ve experienced before. And it’s completely reshaped the way that I think about the future and what can be done with technology.

[00:33:26] CR: For me, that was Apple Vision Pro. I had fairly low expectations going into it and the demo experience, I was like, Oh, holy shit. Like this just completely opens up new realms of what is possible. Interacting with technology can be like just, uh, the three dimensionality of my experience of the internet and photos and videos and, um, I can just imagine, it’s really just going into the Ready Player One sort of

[00:34:01] CR: space, the beginnings of that, you know?

[00:34:04] SS: and, and, and maybe it is five years from now. I mean, just keeping exponentials in mind, you know, not a huge amount of years. Mate, if, if this could transition into some kind of, Physical virtual reality holodeck style, you know, next gen Star Trek. I mean, for me that, that, that’s astounding, but look, I definitely see the applications and I think VR loosely and AR have had these applications, you know, training and pilots and surgeons and, uh, entertainment experiences, you know, being at a concert you’re not really at on the stage with Dave Grohl, all, all of that kind of cool stuff that could emerge from it, I think it’s still there, but, um, it feels like it’s a great piece of kit.

[00:34:47] SS: That hasn’t really got a home yet.

[00:34:50] CR: Yeah, no, exactly. It’s, it’s very, very early adopter y mode, but you know, I still think an amazing piece of technology, like incredible achievement.

[00:35:04] CR: What’s

[00:35:04] SS: going to go through our top five. We’re going to

[00:35:06] CR: only got one.

[00:35:08] SS: predictions. Hey, you’ve only got one. I’m going to go through my five and rather

[00:35:13] CR: I’m sure mine’s going to be one of your five. So this is going to be

[00:35:16] SS: well, interesting because I, there was, I’ve got 20 from my podcast, which everyone should do, not my podcast, my post on Substack, which everyone should certainly be signed up to and go and read.

[00:35:26] SS: Uh, tech and AI transfer 25, 2025. And I picked out the five that I think. The most interesting to me, there’s a lot that have overlaps. Okay, I’ll read them out and then we’ll just pick which ones you want to speak about. The first one is agentic AI, AI agents. That’s the top of my list and it’s not a course.

[00:35:46] CR: You

[00:35:47] SS: Oh, there you go, well said.

[00:35:48] CR: got my only one. Yeah, Agents. Wait,

[00:35:52] SS: and the, uh, well, the, it’s kind of the top tier one. The next one I had on my list was machine based

[00:35:59] SS: business.

[00:36:00] CR: move on yet. I

[00:36:01] CR: mean, are we going

[00:36:02] SS: No, no, we’re going to come

[00:36:02] SS: back.

[00:36:03] CR: Oh,

[00:36:04] SS: We’re going to come back. Okay. So one was agent AIs or agentic AI. Number two was machine based customers. I think this is going to be huge.

[00:36:12] SS: And that’s when it’s kind of an agent process, but it’s your purchaser, the person that goes and buys things, looks at things, does the research, negotiates all of that, everything from a car to whatever, goes through your subscriptions, does all of that kind of stuff.

[00:36:26] CR: just, that’s just,

[00:36:27] CR: a

[00:36:28] SS: Yes, but I think it has a specific business implication, because I think that businesses are going to get, have to get good at talking to and with AIs, and we’re going to have to get good at prompting them on that realm within that specificity.

[00:36:41] SS: The next one I had was the AI creative explosion, a Cambrian explosion of capability based on the fact now that if you can think of it, you can do it. If you can imagine it, you can do it. I don’t even know where that’s going to go, but the fact that anyone can do everything that has ever been done. is insane because I think a lot of people have ideas and have never had the capability and I think that’s extraordinary.

[00:37:03] SS: My fourth one was the global robotaxi ramp up. 10 years late but it’s finally here and I think that’s going to go global next year. The cities in the US that are doing

[00:37:13] SS: it. Yeah, I really do. I think they’re keeping that in their back pocket, and I think if Google or Alphabet are smart, this is something that they can do without any antitrust issues.

[00:37:23] SS: They can plug it in and then build out different business models based on logistics and moving people and payloads in a way that keeps some of their traditional business models of pay per click and advertising true within that logistical context. I think that’s going to be huge. And the other one is AI Eyeballs, which is the idea of holding up the video in a live moment, distilling, analysing, and helping you.

[00:37:46] SS: I did it with my PK Ripper BMX. I needed a new part on it the other day. I held it up and I said, Hey, that looks like a nice BMX there. It looks like a bit of a retro one. Is that a PK Ripper? I’m like, yeah, it is. He’s like, cool. How can I help you with it? Well, my, uh, cranks are broken. Yeah, I can see those.

[00:38:04] SS: They’re the red line flight tool. They’re not cuddler’s cranks. So they, they do break down a bit easy and I went through and I said, what part do I need? Cause one fell out when I was like, you said, what you need is this here. And then I asked it, I found a place that sells it locally that can ship it that day, gave me a link.

[00:38:18] SS: It was like insanely simple example, but this is kind of like what the promise of Google Glass was. But now OpenAI, you have live video chat, it can understand exactly what it’s saying, converse with you, solve real time problems with AI eyes. That’s huge. They’re my five, brother.

[00:38:38] CR: Well, that’s, uh, yeah. I don’t know about Robotaxis, but Elon running the White House might be interesting how he pushes that along from a Tesla perspective.

[00:38:49] SS: Well,

[00:38:51] CR: Look, I think there are some predictions of AGI as early as 2025. I’m not sure about that, but I think, you know, I think Sam Altman has been saying lately that we will get AGI and it’ll be kind of a ho hum moment. And I tend to agree because people are ho hum about AI already, which boggles my mind.

[00:39:16] CR: I still

[00:39:17] SS: for us. Except for us. Because I’m just

[00:39:19] CR: yeah. I was saying to Chrissy last night, like, AGI. Like when we’re talking about the Jetson and I was like, it’s 167 million times as powerful as the computer I had 30 years ago for a 10th of the price. Like, it’s just, my brain can’t even begin to compute what, where we’re at. You can call an AI over a rotary phone and have a conversation with it about any topic.

[00:39:52] CR: Like it’s just, anyway. Bye. I think he’s right that AGI will, when I say slowly creep up on us, I mean slowly in the sort of time frames that we’re looking at. AI is just getting better and better and better. And at some point in the next year or two, it’s just going to be better at any human, at every topic.

[00:40:17] CR: And people will just go, yeah, so what?

[00:40:19] CR: People will just

[00:40:20] SS: don’t know how many years now. I don’t know how many years now. It

[00:40:25] CR: It’ll just, people will just

[00:40:26] CR: be blasé

[00:40:27] SS: is intellectually. It is intellectually. It is intellectually. Intellectually it is, physically it’s not. On this TikTok that I was watching last night, I should have saved it. Anyway, it’ll be my history. This guy was saying that the thing that’s interesting so far with AI and robotics is that robots find hard the things that humans find easy.

[00:40:45] SS: Like standing still and walking upstairs. And if we go back to the Atlas robots and Boston Dynamics and all of that kind of stuff, but computers and AI find easy, the things that humans find hard, you know, computation, complex, complexity, all that kind of stuff. I thought that was kind of an interesting insight.

[00:41:04] SS: Um, and maybe that’s why we’re blase about AI because computers for a long time in a computational sense. a far exceeded humans, you know, whether it’s a calculator or, or anything. And so I was just going, yeah, they’ve always been better than us. You know what I mean? Like, and, and, and I don’t know if I can talk now, whatever.

[00:41:23] SS: I mean, for me, it’s really interesting because it’s language based and that’s how, that’s how, that’s the fabric of all human knowledge.

[00:41:31] CR: Speaking of which, there was an interesting paper that I saw this morning from Meta, don’t know if you’ve seen this, where the suggestion is that we should write the LLMs in a way where they don’t use language, don’t use English to think. So the way that, like if we have chain of thought reasoning with an LLM at the moment, like an O1, it uses English, language, human language, to think through the process.

[00:42:04] CR: And they’re saying that uses tokens and it’s slow.

[00:42:08] CR: It would be faster just to let it do it in its own way, in code, and then push out the answer in language, it doesn’t, it shouldn’t have to think it through, so that, and that would reduce the level of compute and the level of wattage that was required and all that kind of stuff.

[00:42:24] SS: is really interesting. And that’s where, uh, our favourite linguist, the guy did Esperanto. What’s his name again? He’s one of your boys, the linguist, Chomsky.

[00:42:35] CR: He didn’t do Esperanto. It was a

[00:42:37] CR: different guy, but

[00:42:37] SS: Did he do Esperanto? He was a linguist, wasn’t he,

[00:42:40] CR: Chomsky is, yeah, he’s, he’s one of the, you know, major linguists, yeah, in terms of understanding

[00:42:47] SS: I thought he did Esperanto. Who did Esperanto? Do you remember? Wasn’t

[00:42:50] CR: Uh, no, I can’t remember his name.

[00:42:52] CR: Different

[00:42:53] SS: It was Billy Espo. It was Billy Espo. And he put Ranto on the end of it. Anyway. So Billy Espo, the thing with language that, you know, it’s What I think is interesting is that it has nuance in it, which I think enables all of the things that we would do creatively be possible.

[00:43:13] SS: I think in the computation sense, it definitely would waste tokens. But I think at the output level, probably has to do it in that language. And as someone who speaks three languages, how’s that for a flex? Um, there is something in languages that, Makes it impossible to transliterate exactly. It just can’t be done.

[00:43:34] SS: And the only way you can truly understand the language is to kind of understand the culture and the way of life and even be in that country, because then the words start to make sense because of the physical interactions and they become a function of that. And you just, some things you just can’t translate.

[00:43:52] SS: And when you understand both languages really well, you can explain it to somebody and say, look, we say this word, but it really doesn’t mean that. And that’s the only one that we’ve got to kind of translate. But it’s kind of like this, and you have to go into that. And I think that if the LLMs were doing it in computation, their capacity to give us the optionality of all the things that they can do would be lost in that translation process.

[00:44:13] CR: Esperanto was invented by L. L. Zamenhof, Ludwig Laser Zamenhof, a Polish Jewish ophthalmologist, in the late 19th century. He published the first book outlining the language, titled Unua Libro. First book. In 1887, under the pseudonym Doctoral Esperanto, which means Doctor Hopeful, the pseudonym eventually became the name of the language itself.

[00:44:37] CR: Zamenhof’s goal was to create an easy to learn, politically neutral, and culturally inclusive auxiliary language that could foster international communication, and Understanding. Esperanto’s grammar is highly regular, its vocabulary is derived mainly from European languages, and it was designed to be phonetic and logical.

[00:44:57] CR: Despite being a constructed language, Esperanto has developed its own thriving global community of speakers.

[00:45:05] CR: There you go.

[00:45:06] SS: I’m gonna learn Esperanto late at night tonight after a couple of Campari’s at 1am.

[00:45:11] CR: like that idea. Maybe we should do our next podcast in Esperanto.

[00:45:15] CR: We’ll

[00:45:15] SS: Esperanto!

[00:45:17] SS: Well, Cameron, given that you’ve got one, do you want to give us your thoughts on agents and why they matter? And I’m getting the sense, and I kind of, when I look through mine, it kind of is a capstone thing that really trickles through all of the others to an extent. So why don’t we kind of get your view on agents, what they are and why they really matter.

[00:45:38] SS: And that, that might even be a nice way for us to kind of round out the, the pod. Cause we have to do one before the new year as well, by the way. Yeah.

[00:45:47] CR: Yeah, so look, this isn’t an original prediction. Pretty much everyone in the space is saying 2025 is going to be the year of agents, and the way that most of them describe agents, it’s when you can give your AI a complicated task made up of uh, uh, A number of sub tasks that have to be done, some of which might take a bit of time and effort and they will just go off and do those things and come back to you when it’s done.

[00:46:23] CR: Now, trying to come up with Examples of this is tricky. Like the one I heard Sam Altman use the other day was pretty mundane. He was like, well, you know, you could use, ask it to find a restaurant to make you a booking. And it might go off and ring three restaurants and find out what their availability is and then come back to you.

[00:46:51] CR: And. When it’s got a booking and check your friend’s calendars and do all that kind of stuff and interface with all these different things and come back to you with a result. And he said, that’s pretty, that’s interesting, but not that exciting. He said, but what if you got it to go and speak to a hundred restaurants and find out what all of their offerings were?

[00:47:12] CR: And, you know, if they catered to, you know, You know, uh, what pricing they could do and if they could cater for a particular, I don’t know, vegans or whatever it is. And then he said, well, you might think that’s a lot of wasting people’s time, but it would probably be your AI talking with the AIs of all of those restaurants and having a negotiation and a conversation and then coming back to you.

[00:47:33] CR: And, you know, it reminds me of, um, talks. I was giving at Microsoft circa 2000, 25 years ago, something like that, when I was talking about Web 2. 0 and it was the early days of Web 2. 0 and the vision that we had for how that would play out back then was that If I wanted to build a, um, you know, a TV, if I wanted to buy a TV, I would say to my browser, I need a TV, and it would go off and not just find the best price from a bunch of TV retailers for me, It would talk to the retailers and the retailers would use their own back end systems to do a just in time build of that TV and would go out and speak to all of their suppliers and negotiate the best pricing that they could get for all of the components and it would be built on the fly and I would get the best price based on the best negotiation that the best retailers and manufacturers could get with all of their suppliers, come back and give me the best price.

[00:48:54] CR: Not dissimilar to how Tesla, in a way, will custom build a car for you these days. One of the problems that we had, this was all part of the idea that there would be interoperability between all of the backend manufacturing systems, and they’d be able to have schemas that could talk to each other, and XML was going to be the basis of that, or NET as Microsoft called their platform back then.

[00:49:21] CR: And what. What happened was the, uh, technical logistics and the management logistics required to get all of those schemers to interoperate and interface with each other was way bigger project than anyone really wanted to do just to reduce their margins by having more competition. And it kind of all fell apart and it didn’t quite get there.

[00:49:46] CR: But I see we’re heading into a world where every system, and I remember you and I talking about this at the beginning of this series, like a year or two ago, about agents that sit on the front of every business’s website, that can speak with their back end manufacturing systems, and ultimately I think we’re heading into a world where my Agent will go out and be able to speak to the agents of all of the retailers and all of the manufacturers and negotiate on my behalf.

[00:50:19] CR: You were talking about, what did you call it, machine based shoppers or

[00:50:23] CR: something before?

[00:50:24] SS: Yeah. Machine based customers.

[00:50:26] CR: So agents is basically really complicated processes that software Well, your AI will be able to do on your behalf. And I think Sam’s point was, we tend to think of it in things that we, in terms of things that we already do today, that it might make easier, but he’s saying there are things.

[00:50:45] CR: That we haven’t even thought of because they’re not practical or possible today. That we will be able to do in the future when everyone has intelligent software that can talk to other pieces of intelligent software. And often, in some cases, it’ll be the same software. It’ll be my version of ChatGPT talking to your version of ChatGPT talking to another ChatGPT.

[00:51:12] CR: It’ll just be ChatGPT or whatever it is. It’s talking to itself, uh, cause it’ll be front ending a lot of these systems, but that’s the world of agents, complicated scenarios done completely by software and it’ll, it’ll happen slowly. I don’t think it’ll happen all at once. You know, it’ll, it’ll start with small iterations, but will gradually become more and more sophisticated over the next year or two, but definitely I think 2025 is where we’re going to start to see the beginnings of software, really.

[00:51:51] CR: This is where software as a service becomes real. These things will do services for

[00:51:57] SS: the, the current software as a service gets eaten up by an overriding agent style thing. And the agent is multimodal because it’s not like software at the service now is set in little verticals with functional tasks. But because it’s language based and this is the, this is why language based software LLM is so important is that it’s multimodal.

[00:52:20] SS: It can do any task with any set of directions and it eats up every little piece of software as a service. App that there is. And, and just on that, it’s interesting how technology has a way of building another layer to circumvent the problems. And the problem with the backend speaking to each other is that people have, companies have proprietary systems, don’t want to open them up.

[00:52:43] SS: They want to keep them closed on purpose because they have an incentive. And then technology sits above it. So, okay, you’ve got your two different backend logistics or supply chain systems. Well cool, now we’ve got the agent that just speaks English, or Hindi, or Spanish, or Mandarin, or both. Actually, it speaks all of them, sorry.

[00:53:02] SS: Mainly Esperanto. Look, supply chains in Esperanto has always been what I’ve hoped for. So, it can speak in all of those supply chain levels. So it doesn’t matter that it’s not all in NET or some system in the back end that has this ability for software to kind of, Interact because you get the language layer on top.

[00:53:23] SS: And that brings me back to what that paradox that I was trying to think of before it’s Jevons paradox

[00:53:30] CR: Who?

[00:53:30] SS: and, uh, Jevons paradox, Jevon. And it was by, um, coined by William Stanley Jevons in 1865. And it refers to the idea that as technology improves, the efficiency of resource use, the overall consumption of that resource often increases and Instead of decreasing, for example, more efficient fuel engines lead to greater fuel consumption as travel becomes cheaper and more accessible.

[00:53:58] SS: It’s the same kind of, with ai, it’s the AI becomes better and more useful and, and I think it kind of leads into. Unexpected use cases as well because it becomes more omnipresent. It goes on further and it says in a broader sense this could also be linked to the idea of emergent utility. As we refine or cleave off parts of a material resource or concept we discover new ways to use or repurpose what remains.

[00:54:23] SS: And so it kind of feels into this and it says this reflects on the recursive nature of innovation and while refining or breaking down something often leads to greater complexity rather than simplicity and reduction. So it kind of adds, and for me, Jevon’s paradox relates to the idea that we don’t need a UBI because there’s all of these unexpected things that just layer out.

[00:54:44] SS: So I just thought that that was interesting and a guy was talking about it on my TikTok last night.

[00:54:50] CR: Yeah, well I, look,

[00:54:52] SS: At 2am,

[00:54:53] CR: oh man, I didn’t get any sleep last night, Fox was in our room sick at 3. 30am and

[00:54:58] CR: throwing up all

[00:54:59] SS: Fox, what are you doing?

[00:55:01] CR: then I had to record a podcast at 9am, so I just got up, I had to make bread. Yeah, me too, so, um, yeah, look, I think, we can’t even begin to imagine the ways that we’re going to use this stuff in the next year or so, Steve, and just to wrap up, I had one last thing I wanted to say to you.

[00:55:17] CR: was great

[00:55:22] SS: Can I guess? Something, how are you going, um, have a happy new year, something in Esperanto. I know that much.

[00:55:31] CR: fun. Let’s do it again next week in Esperanto. Thanks, buddy. Have

[00:55:38] CR: a good week.

[00:55:38] SS: Thanks, champion, great chat.

Cameron explains his MANIFESTO FOR AUSTRALIAN AGI, Steve explains why he supports the Australian government’s ban on social media for kids, and they discuss NVIDIA’s downloadable local LLM.

FUTURISTIC 33

[00:00:00] CR: Welcome back to Futuristic. It is episode 33. It’s the 29th of November 2024. Steve Sammartino, welcome back.

[00:00:16] SS: Reilly.

[00:00:19] CR: We have, uh, some big things to talk about, Steve. Big ideas that I want to get into today about the future of AGI in Australia. Social media bans, personal AIs from NVIDIA, but before we do that, why don’t you tell everybody how you have been futuristic since our last conversation.

[00:00:44] SS: One was with VUT and the brief that I got was, you gotta help convince university that we need to embrace AI more, which is kind of crazy and interesting. You know, they’re still using it a lot to stop people cheating or using the tool in some capacity. And I just had two things to say.

[00:01:11] SS: I said, not using it is insane. And I said, I don’t know the answer, but I know the question. And the question is, how do we help our curriculum rise above the AI? Because that’s what we do with every tool. You’ve got to rise above it so that you’re working on top of it. Now, of course, you need to know what good looks like.

[00:01:30] SS: So there’s that. So that was the one thing that was interesting. And I did a workshop with CBUS. Which is a big building company, Seabus Property, who owned the superannuation in the building. It went really well. Incredible Workshop was on MVP’s, Minimum Viable Products, and I want to say that for any company trying to innovate, Or a startup.

[00:01:50] SS: MVP’s are still the ticket. That is still the secret sauce. And it’s really, really hard to do. You know, I really had to thin up some of the ideas for these guys that just cannot think small enough to get momentum. And that was an insight that that’s been true for 20 years. And I can’t see it ever changing.

[00:02:09] SS: Is that if you do something small, you can find a path to success and iterate. And I was really driving

[00:02:16] SS: that home.

[00:02:17] CR: Think small.

[00:02:19] SS: Think small.

[00:02:19] CR: 2024. Well, I’ve done a lot of coding, uh, as usual, just coming up with ideas and coding stuff. Um, just trying to automate a bunch of things. Like, I’m still trying to automate the, um, investing checklist that I do each week. So it’ll be one click button and off it’ll go. I had some success with that this week.

[00:02:39] CR: Did a first phase of it that worked. First test worked. Now I’m trying to expand. And again, think small. So it’s like, I wrote all the scripts around one stock. That I had the data for. I said, right, generate a score for this stock. Got that working. Now I’m like, trying to give it a list of stocks and get it to do scores for a list, like 10.

[00:03:01] CR: And then I’ll give it 200 and see if it still works. But it’s just, yeah, starting off building it piece by piece. But, um, Yeah, I think that’s, that’s mostly it from a technology perspective. Just a lot of using the latest coding tools and it’s frustrating. You know, I’ve been using Claude 3. 5 Sonnet, which a week or two ago was freaking amazing.

[00:03:28] CR: The last couple of days just really sucked. Uh, and I see people talking about that on Reddit. It’s this constant frustration where these tools, uh, have weeks where they’re just like genius level, amazing one shot solutions for everything. And then all of a sudden they’ll just be dumb and, you know, like they’ve had half their brain removed.

[00:03:50] CR: They’ve been lobotomized.

[00:03:51] SS: Why do you think that is? What do you think

[00:03:53] SS: causes that?

[00:03:55] CR: I think they’re. I don’t know. I see lots of theories, but it seems to be some version of, they’ve got a certain amount of GPUs that they’re using to build their frontier models, maintain their existing models. They’re quantizing things. They’re trying to, um, Save money at different stages. They’re moving the, you know, we’ve got 50, 000 GPUs applied to this.

[00:04:23] CR: We’re going to take 10, 000 and move them over to this thing. And so this thing becomes dumber. I don’t know. They’re just messing around on the back end as they’re continually building new models, training new models, trying to save money, trying to, I think, reduce The algorithms as well, like, okay, if it’s costing them a dollar to give you an answer that they’re charging you a cent for, they’re trying to figure out ways to reduce the cost of that by optimizing things, and it doesn’t always work, there’s a lot of experimentation, like, a lot of people get really shitty on Reddit, Um, I’m paying you my 20 a month and this service is terrible.

[00:05:06] CR: And I’m like, dude, you have an artificial intelligence for 20 bucks a month. Like shut the fuck up.

[00:05:12] SS: Hunched a year with excitement, the greatest tool ever invented you have for less than the price of a

[00:05:19] SS: pizza?

[00:05:20] SS: Look, let’s complain here. We’ve got the most incredible AI, mostly free, or the super version for 20 bucks a month. You should so be complaining. Your lot in

[00:05:29] SS: life is

[00:05:30] SS: horrible.

[00:05:30] CR: Yeah. Shut the fuck up and stop complaining. Yes. Yeah. It’s going to be up and down. I just accept it. It’s going to be good days and bad days, but you know, the good makes up for the frustrating things. Um,

[00:05:42] SS: plausible ideas. The one that, uh, all of a sudden, let’s say, a few people get onto the new version, there’s a couple of tabs open, next thing you know it’s amazing and there’s thousands of tabs open and the machine slows down. I mean, that’s highly plausible. The idea that, you know, GPTs are generative pre trained transformers is a big one because one of the things I see on Reddit is often a new version has, let’s call them scary capacities, where they do things that are a little bit, Oh my God, wow.

[00:06:11] SS: And they throttle those back or change those to an extent, which knowing the way the algorithms work that they’re imperfect and it’s not an, if this, or then that protocol that could infect other parts of the system. Uh, the answers that it gives. So they were like really plausible and the cost one, the third one that you’ve mentioned, that’s another great one.

[00:06:31] SS: Gee, this is great. We want to launch and show everyone how amazing it is. But now that everyone knows how amazing it is, let’s just, we’ve launched the plane, let’s pull back there and save a bit of fuel in the, in cruise mode.

[00:06:45] CR: a couple of other things that, uh, I know you introduced me to an AI. There’s a video editing tool this

[00:06:52] SS: Yeah.

[00:06:53] CR: uh, that can take your video and just turn it into TikTok clips and give you ratings on how engaging it is. I ran my investing podcast through it and it gave it all very low engagement ratings. So I didn’t, didn’t post any of them, but it’s an interesting, uh, tool.

[00:07:12] SS: I’ll, I’ll, I want to talk about that because one of the things that, you know, I noticed on, it’s called clap. app for listeners and it is a really great way to get shorts. It’s also can be used just to generate one of the most accurate forms of, uh,

[00:07:31] SS: captions that I’ve seen.

[00:07:32] SS: It’s really

[00:07:33] SS: good. And it actually has an editor. it, yeah. It has an editor inside the browser. So if you haven’t got the software like the iMovie or the Apple software, it actually is a pretty handy little piece of software to do the

[00:07:44] SS: editing on it. Bye. Clap with a K, by the way, like Klu Klux Klan, clap on your own there, Cameron. Clap with, I’ll just go clap with the guy.

[00:07:55] SS: Uh, I, what I noticed is that it does a generic version of it. It gives a summary when you write something and it’ll say, uh, whether or not it thinks it’s, uh, A viral clip and it gives it a score out of a hundred and it’ll say this is viral because it’s got a good hook or it’s quite funny or it’s and so and it actually does get it contextually.

[00:08:15] SS: What it doesn’t take into account is your audience typology, which it doesn’t really know the context of where you’re hosting it. And I’ve had a couple that had ratings of 25 out of a hundred that did better than ones that had ratings of 75 out of a hundred that I posted on my TikTok, uh, which I thought was interesting.

[00:08:34] SS: So. And it also, it chooses some that are good, but you’re better off, I still think, having a look at it, and seeing the chunk that it chose, and going, actually, I’m gonna extend this a bit, cut that a bit, and make it start earlier or finish earlier. Still needs a bit of a human eye of it, but I tell you what, it really can save you an hour and a half going through a live

[00:08:54] SS: video to find good bits.

[00:08:57] CR: Yeah, and I think it’s just a good example as to where we’re heading with these tools where, you know, it will just do all of the editing for you. It’ll be all done on the fly. The AI will do all of the editing, puts editors out of a job. It just makes it easier for everyone to produce more and more engaging content.

[00:09:19] SS: Yeah, so we’ll eat our own dog food on this one cam and we will see what it picks and we’ll see if it picks itself. We’ll see how smart this AI is. If this AI is smart as it thinks it is, it should pick itself and show clap as exactly. Let’s, this is the test of tests cam. Might be the greatest thing we’ve done

[00:09:39] SS: on The Futuristic to date.

[00:09:42] CR: I think that’s when it becomes self aware, when it starts to pick stories about itself to promote. Um, on our last show, I said that I thought Elon Musk was going to be Trump’s AI czar, and that he would be, um, you know, determining the future of AI. Story came out after that, he must have been listening, because a story came out saying President elect Trump is considering naming an AI czar.

[00:10:05] CR: Czar in the White House to coordinate federal policy and governmental use of the emerging technology. Trump transition sources told Axios, Elon Musk won’t be the AI czar, but is expected to be intimately involved in shaping the future of the debate and use cases. The sources said. Now, uh, I didn’t expect him to actually be appointed the official AI czar, but I do expect him to have a lot of influence over how that runs and the policies that they implement.

[00:10:40] CR: And, uh, this goes on to say that, um, Musk, who owns a leading AI company, XAI, has failed. Feuded publicly with rival CEOs including OpenAI Sam Altman and Google’s Sundar Pichai. Rival’s Wari Musk could leverage his Trump relationship to favor his companies. By the way, I listened to, um, do you know, um, Diamandis, Peter Diamandis?

[00:11:07] SS: I do. The, uh, he’s a Singulitarian from the Kurzweil School. He does the, uh,

[00:11:11] SS: Abundance 360.

[00:11:12] CR: Hmm. Do you listen to his podcast at all or watch his YouTube?

[00:11:16] SS: No, I don’t. I’ve seen a lot of his

[00:11:17] SS: YouTubes and his talks.

[00:11:20] CR: I saw two things of him this week. One was a chat with Musk from a Singularity conference in Riyadh that he was hosting just before the election. And that’s where Trump said he thinks we’ll have AGI by 2025, 2026 at the latest. And he also talked about a future of abundance. He said if we get this right, it won’t be a universal basic.

[00:11:46] CR: income. It’ll be a universal, uh, a universal luxury income. You’ll basically have everything you need. It’ll be full abundance. But then I also watched, uh, Diamandis do an interview with the Mooch, Scaramoochie.

[00:12:03] SS: Karamuchi.

[00:12:05] CR: And it was the first half of it was really good. The Mooch was talking about the fact, he says, he said, I have a Trump Dakota ring.

[00:12:11] CR: He was talking about Elon. They were talking about how long Elon’s going to last with Trump. Something we also talked about in that last episode. And Scaramucci famously, when he was Trump’s communications director in the first term, lasted 11 days. And he said, he calls that one Scaramucci. So the amount of time that you last, Working for Trump is, is a Scaramouche, it’s, it’s counted in 11 days, you gotta love, it is genius, and he said,

[00:12:40] SS: that. more than Moore’s Law. That’s how much I

[00:12:42] SS: love it. Wow. he said he thinks Musk is

[00:12:45] CR: going to last 30 Scaramouches, so it’s about a year, but then they were having the question about if and when Musk and Trump have a falling out, who survives, who is the more powerful of the two, and I think We all probably know the answer to that question, and it’s, uh, not the orange demon.

[00:13:06] CR: I think Musk is probably the one who comes out on top, so it’ll be interesting to see what that looks like. But anyway, he was saying, he was talking about the fact that, uh, Musk is already on the outs with Trump. And he said you can tell that because he didn’t Make Musk the head of the DOGE, the Department of Government Efficiency, by himself, it’s him and Vivek Ramaswamy.

[00:13:29] CR: He said so, he’s already, Trump is already starting to white ant Musk’s power by putting two guys in charge. Now the way I’d read that is that Musk wasn’t, he doesn’t have time to actually run this thing. He’s just going to swing in. Probably via Zoom calls once a week and say, yeah, fire this department, fire these 50 guys, and then let Vivek actually implement it.

[00:13:56] CR: Uh, Mooch, who’s got the Trump Dakota ring, is interesting. He said, there are 40 senior ranking members of his first administration that hate his guts now and want nothing to do with him and don’t think he should be president. What makes you think the new people in his administration are going to have a different experience?

[00:14:16] CR: To the first administration who mostly all hate his guts, including his former vice president, want to see him in jail. Um, yeah, he’s like, it’s, it’s going to be exactly the same experience. He’s going to, you know, shit all over everyone, piss everyone off, not listen to anyone. Anyway, it was pretty fake. But then the second half of the chat was them, all of them, Diamandis and Mooch and the other guy pumping Bitcoin as the greatest investment known to man.

[00:14:45] CR: And. And Mooch was plugging his own, his new book on Bitcoin, The Little Book of Bitcoin. Now I, uh, am well on record for five years, longer actually, but since I did the QAV podcast, I’m saying that Bitcoin is just nonsense as an investment. But I got his book and read it just to see what his arguments were, and he doesn’t have any.

[00:15:07] CR: Um, there were no arguments, just the usual thing. It’s going up, so therefore it’s a good investment. Um, and the usual

[00:15:16] SS: really interesting. Really on that, just on the Bitcoin investment. Here’s my rule with investing is that just because something is going up and you can make money out of it,

[00:15:25] SS: doesn’t make it a good investment. That is, That is,

[00:15:28] SS: the fundamental

[00:15:29] CR: Doesn’t make it an investment.

[00:15:31] SS: even an

[00:15:32] SS: investment. Exactly.

[00:15:33] CR: not investing. It’s

[00:15:34] CR: gambling.

[00:15:35] CR: Yes.

[00:15:37] SS: And I will die on that hill. And, and people have got rich gambling. On sheets and on all forms of speculation, no doubt. And it will

[00:15:47] SS: continue, but I would rather, I would rather, I would rather get

[00:15:52] SS: rich slow and get rich

[00:15:54] SS: surely.

[00:15:55] CR: Yes. And be able to sleep at night.

[00:15:57] CR: Like I, What I’ve learned from Tony over the

[00:16:00] SS: I was going to ask you

[00:16:01] SS: Tony’s opinion. Yeah,

[00:16:02] SS: on it.

[00:16:03] CR: same as Charlie Munger’s and Warren Buffett’s. Charlie Munger, before he died, used to call Bitcoin rat poison squared. Like,

[00:16:12] SS: That’s such a

[00:16:12] SS: Charlie.

[00:16:13] CR: yeah, such a

[00:16:14] CR: Charlie, love Charlie. Um, like the conversation Tony and I have talked about a lot, you know, it’s always the basic premise of investing is to buy something for less than it’s worth and wait for the market to readjust.

[00:16:30] CR: And to value it correctly. Uh, so you need to do that. You need to know what the intrinsic value of something is to know if you can buy it at less than its intrinsic value. So the question I always have for Bitcoin people is explain to me how you calculate the intrinsic value of one Bitcoin today. And then I can tell you what it’s worth.

[00:16:50] CR: And they can’t do that because it has no intrinsic

[00:16:52] SS: Well, it’s the same with all currencies. And this is the point. And yes, people speculate on currency and have done for millennia, doesn’t, and no, no investor would tell you that currency is an investment. Even people in Wall Street, they say, well, it’s a speculative tool and we use it and we can make money out of it.

[00:17:10] SS: And we’re happy to click tickets along the way. But Bitcoin is not a currency nor an

[00:17:15] SS: investment because it doesn’t pass the six rules of

[00:17:16] SS: a

[00:17:17] SS: currency.

[00:17:18] CR: And neither’s gold.

[00:17:20] CR: They always say Bitcoin is digital gold. And gold, you know, again, Buffett and Munger say gold isn’t an investment. It’s, it has no intrinsic value. It’s just a pretty

[00:17:30] SS: be a store of value, as can be grain, as can be a barrel of

[00:17:34] SS: oil,

[00:17:36] CR: least you can eat grain.

[00:17:37] SS: that’s right, and You can

[00:17:38] CR: burn

[00:17:39] CR: oil,

[00:17:40] SS: really, gold has some micro uses, you know, small electronics and other bits and pieces in jewelry, but it’s, it’s, it’s, again, it goes back to the Nobel Harari thing on money is a myth that we all collectively buy into because we need a tool for trade.

[00:17:57] CR: Anyway.

[00:17:59] SS: Moving on.

[00:17:59] CR: Let’s move

[00:18:00] CR: on.

[00:18:01] CR: Steve, I wrote a manifesto this week.

[00:18:04] SS: think you

[00:18:04] SS: write enough

[00:18:05] SS: manifestos. What is it

[00:18:07] SS: on? one thing I’ve always, listeners.

[00:18:10] CR: one thing I’ve always said about myself is I don’t write enough manifestos. I need to write more manifestos.

[00:18:15] SS: to as well. Are you going to go live in the shed in the woods? I’m just

[00:18:19] SS: asking. And do you

[00:18:21] SS: know how to,

[00:18:22] CR: got the crazy

[00:18:23] CR: hair, I just need to,

[00:18:24] CR: grow the crazy beard and I’m good to go.

[00:18:27] SS: and, and the post office now, you know, is only two every second day Cameron, just to let you know for when you’re mailing off

[00:18:32] SS: the, some universities.

[00:18:36] CR: Um, you know, Chrissy’s nickname for me is already The Wiz because she says I have crazy wizard hair. So, uh, yeah,

[00:18:43] CR: the Wiz. She’s like, hey, hey Wiz. Um, let me, let me read the preamble. Across Roads, Australia stands at a pivotal moment in history. The rise of Artificial General Intelligence, AGI, and robotics offers an extraordinary opportunity to build a future of abundance where work.

[00:19:05] CR: As we know it becomes optional, technology eliminates scarcity, and everyone has access to the essentials of life. But, who will shape this future? Who will decide how this technology is used? It’s been over two years since the release of chat GPT by open AI in November, 2022. And since then, AI models have continued to improve at a rapid rate.

[00:19:33] CR: Many senior industry leaders are predicting a GI could appear as soon as 2025. Leaders in the field of robotics are predicting that by 2040 there could be a billion bipedal robots in society and they will cost roughly the same as an entry level. Motor vehicle does today. In the last two years, our government and corporate leaders have done very little to prepare Australia for what’s happening.

[00:20:00] CR: If we leave the preparation to governments and corporations, we risk walking into a nightmare. The same governments that failed to prepare for the COVID 19 pandemic, despite decades of warnings from scientists. We’ll fail to prepare for the AGI revolution. During COVID, we saw the consequences of short term thinking, poor planning, and a political system more focused on protecting profits than saving lives.

[00:20:27] CR: Hospitals were overwhelmed, supply chains collapsed, and millions of people were left to fend for themselves. Now imagine the same incompetence larger scale, with AGI and robotics disrupting every job, every industry, every industry. and every aspect of society. Corporations, driven by profits above all else, will use AGI to maximize efficiency at the expense of workers.

[00:20:53] CR: Entire industries will disappear overnight, with no safety nets in place for those displaced. Housing, healthcare, education, and even food could be controlled by algorithms designed to extract wealth, not serve humanity. Without intervention, this technology will deepen inequality and concentrate power in the hands of a small elite, while millions of Australians are left behind, struggling to survive in a system that no longer values their existence.

[00:21:22] CR: But there is another path. A path where we, the people, take control of our future, where AGI and robotics are used to empower communities, not exploit them. A society where technology guarantees universal access to housing, healthcare, education and sustainable energy. A society where every person’s dignity is respected and every community has the tools to thrive.

[00:21:49] CR: Governments are shown as time consuming. and again that they cannot be trusted to act in the public’s best interest. If we leave this to the politicians and the corporations, we know what will happen. They will act too late, too timidly, and in service of the powerful. It is up to us to seize this moment and take responsibility for shaping the future.

[00:22:10] CR: We envision an Australia built on dignity, Equity and Abundance. A society where the benefits of AGI and robotics belong to all of us, not just the few. But this future will not happen by accident. It will only happen if we organize, act, and build it ourselves. The stakes are high. Could not be higher. The future is ours to create or ours to lose.

[00:22:36] CR: Let us rise to this challenge together.

[00:22:39] SS: By the way, I very much liked it. It was getting a little bit Unabomber until the end when he said there is an alternative. And then I breathed. I breathed, I said, I’m on a podcast with a guy. I’m not gonna have to explain in some true crime documentary letters. And

[00:22:54] SS: that’s a good thing for me. I

[00:22:56] SS: may, I really, Or is it? really liked it and I wrote a couple of notes when you were reading the first half that sprung to my mind.

[00:23:05] SS: Based on what you

[00:23:06] SS: were writing, would you like to hear them? Cameron?

[00:23:09] CR: That’s why we’re here, Steve.

[00:23:10] SS: Okay. The first thing that I wrote was that the real question is, can and will all have access to these tools of abundance? And then when I wrote that, I thought about, uh, the abundance that we have now, right? Because you could argue, and I’m just about to go to ChatGPT now and ask it, and you might even be able to do this for me if you’ve got it open, Cameron, is how much Wealth is there in the world per person.

[00:23:43] SS: I think it’s around about a hundred grand and in America, it might even be over a million. Can you check out those two numbers? Because we could argue, despite it not being as well distributed. And a lot of people in underdeveloped parts of the world, the food and the wealth and the electricity and the clean water, they don’t all have that yet.

[00:24:06] SS: So that’s one thing. Um, but we already have incredible abundance now where there is more than enough calories, energy to feed everyone. Everyone can be housed. There’s, there’s enough. Uh, homes, certainly in Australia, there’s a lot of empty homes, uh, there’s an incredible number of resources, uh, and they could be distributed if we had some sort of a system which was not capitalist, you know, potentially some sort of a communist system or where wealth is distributed, so everyone has dignity and access to the resources they need to live a healthy and, you know, moderately Well off life, but I feel like the monopoly on violence that governments have and the rules and taxations that government put in place, even though they redistribute some of the wealth, really is just part of the capitalist system where capture and control of resources is already there.

[00:25:02] SS: And if we didn’t have capture and control of resources, we could already feed, house, clothe, educate, And give medical care to everyone because we’ve certainly got the resources. And while we had corporate control, now we’re just going to have another form of algorithmic control. And the legal system might thwart people from having true control over their robot, like an Apple phone, where it can be bricked if you break some of the laws.

[00:25:28] SS: Uh, it seems as though we’ve got an oligopoly of Companies that control the AI, and even though the AI could potentially lead us to abundance, it’s controlled by the same corporations, and I can’t see them distributing their wealth to create this level of abundance in the back half of your essay, as much as I’d like

[00:25:44] SS: that to be the case.

[00:25:47] CR: I’ll answer that in a second, but let’s go to GPT.

[00:25:49] CR: The global wealth per adult averaged approximately USD 84, 718. However, this figure doesn’t reflect the stark disparities in wealth distribution worldwide. The median wealth per adult, a more accurate indicator of typical individual wealth, was around USD 8, 360, highlighting significant inequality. In Australia, the average wealth per adult stood at USD 546, 184, with a median wealth of USD 261, 805, indicating a relatively equitable distribution compared to global standards.

[00:26:31] CR: These figures underscore the vast differences in wealth both between and within countries, emphasizing the importance of considering median values to understand the economic reality of the average person.

[00:26:42] SS: than medians here, Cameron, and the reason is we’re talking about if we distributed it evenly. Right? So, so, so the averages are more important than the median in this case, because the median is more about how, how well distributed is it? This is a question of if we split up the resources and gave everyone access to abundance.

[00:26:59] SS: I’d love to know what the American number is. I reckon it’d have to be over, it’d have to be over a million per person, surely. Wealth per person in America would, because if Australia is,

[00:27:09] SS: you know, 500, yeah, you’d have to think America would

[00:27:13] SS: be at least that, maybe more.

[00:27:16] CR: Um, interesting, getting back to the, getting back to the,

[00:27:20] CR: the chat that Elon was having with Peter Diamandis, um, they were talking about it being the end of capitalism. And Elon, which I thought was fascinating, the richest man in the world, was saying, yes, this is going to bring about, if we get this right, this will bring about the end of capitalism as we know it, because everyone will have everything that they need, uh, for no cost, everything will just be provided to you.

[00:27:45] SS: are we talking robotics, creating things and extracting resources, or are we talking about nanobots creating a BMX bike

[00:27:52] SS: from scratch, organizing things at the molecular

[00:27:54] SS: level? He didn’t get into that level of detail, but yeah, all the stuff that Kurzweil talks about and Diamandis talks about in his books. In my, um Manifesto, I refer to it as Universal Basic Services, which isn’t a term I came up with, but it’s something that has been growing, I’ve been seeing people start to talk about it.

[00:28:16] CR: UBS instead of UBI. I wrote, We envision a society where everyone has access to the essentials of life, guaranteed as human rights. It should be a future of dignity, equity, and abundance. Now, I agree with you, and Tony and I have had this debate. For the last six months, his view is that the establishment, the powers that be, won’t allow this future to happen.

[00:28:43] CR: They won’t allow AI and robotics to achieve this vision because they won’t give up control. And I agree with that in part. I think that’s basically, this is what I talked about in the psychopath epidemic to a large extent. If you’re in a position of power and wealth and you don’t want to give it up, You’re going to use your power and wealth to keep your power and wealth.

[00:29:07] CR: Uh,

[00:29:08] SS: construct, mostly, was what I

[00:29:10] SS: took from the book.

[00:29:13] CR: what, what, what’s an emotional The idea of keeping wealth and power, because you’ve got abundance, and you’ve got way

[00:29:21] SS: more than You need in a lot of those circumstances.

[00:29:24] CR: You know, why would you give it up willingly? You’re not. You’re going to fight to keep it. And you’re going to use it to maintain control by manipulating or influencing the political system, the legal system, the system of media and education and all the things that influence the people because, you know, the 99 percent are always more powerful than the 1%.

[00:29:48] CR: The 99 percent can rise up at any time and overthrow the 1%.

[00:29:52] SS: And the 1 percent

[00:29:52] SS: know

[00:29:53] SS: this, they know

[00:29:54] CR: And they know this and they need to The 99 don’t though. The 99 actually don’t. You know, 5 percent of the 99 know it.

[00:30:03] CR: because the

[00:30:04] CR: 1 percent have spent a fortune telling the 99 percent that violence isn’t the answer.

[00:30:09] CR: Such a, such a graha, non violence, think about Gandhi. Gandhi was a great man, he was non violent. Did Gandhi get rid of the British from India? No, not really, it was the violent Sikhs who rose up and got rid of Britain I didn’t know that, but there’s a great show that I’m going

[00:30:27] SS: to sit down and watch called Mr. Inbetween. I haven’t Oh, oh my god,

[00:30:32] CR: the greatest show ever to come out of Australia by a landmile. Oh I’ve never heard a bad report you haven’t seen it. Now I’ve seen clips and I love it. Don’t, don’t spoil it for me because It’s when I have my last gig this week, I’m going to sit down joyously and just, and

[00:30:51] SS: just binge the whole

[00:30:52] SS: thing. man, But there’s one scene that I saw, I’ve seen a few of the scenes enough to have a taste that I know I’m going to love it.

[00:31:00] SS: And, uh, in one of the scenes, he’s sitting around in some round table, um, so he doesn’t have to go to jail. And he’s talking about a situation where he had an altercation with someone and was violent towards them. And the, uh, person sitting with all of the attendees to help with their violence, he said, can you give me an example, Ray, of a time where violence has actually worked?

[00:31:25] SS: And he said, World War II? I mean, he said, you know, we didn’t just negotiate with the Nazis. I don’t think they would have left. And I’m like, Oh yeah.

[00:31:37] CR: It, like, the story, do you know about the story behind it?

[00:31:40] SS: I do. And I’m watching, I’m

[00:31:41] SS: halfway through, uh, The Magician. I’m halfway through that. Oh, where did you find that? on YouTube.

[00:31:47] CR: find that. No, really? Yes. And I’m halfway through and I’m loving it. And I know the story about how he made the five minute film, then the longer version at the St Kilda Film Festival. And then some Australian kind of actor, one of the guys, I forget his name, sort of put some money behind it.

[00:32:04] SS: And then it got

[00:32:05] SS: picked up in the

[00:32:05] SS: US. Yeah. so, for people who don’t know the story, I know this is by the by, but fuck it. Um, it’s,

[00:32:12] SS: media, and it’s new forms of media, and it’s all that,

[00:32:14] SS: Cameron, just a great story. So Scott Ryan, the creator and the star of the show, is a um, oh man, like.

[00:32:24] CR: The story is, Don’t ruin it

[00:32:26] SS: for me, no, not the story of the show, the story of

[00:32:29] CR: him.

[00:32:30] SS: of the thing,

[00:32:30] SS: yeah. Um, he has never done anything in his life. I’ve seen him talk about it.

[00:32:37] CR: He grew up in, grew up in Melbourne, um, Richmond, um, and didn’t really do well at high school. Um, you know, they think he had sort of some disorder, oppositional defiance disorder or something like that. Um, mental health declined at 17. He had agoraphobia. And basically lived as a recluse, never left home, didn’t do drugs, but lived with people who did a lot of drugs, and, you knew this world a

[00:33:12] SS: bit. a bit.

[00:33:14] CR: but, you know, he basically just didn’t leave home for 12 years, didn’t have a job, didn’t study, didn’t do anything, practiced as a recluse.

[00:33:21] CR: Yoga and Tai Chi and meditation, didn’t drink, didn’t do drugs, just did nothing. And then he started to think about, he goes, Oh, I got to do something. And the only thing he ever enjoyed it at school was writing. So he tried to write something and he was like a fan of the Sopranos and things like that. So he tried to write a Film about a, you know, criminal.

[00:33:47] CR: And he made The Magician, um, then he did start studying filmmaking at RMIT, shot it, I think he spent like 3, 000 on it, 2003, low budget, and it got attention at the Film Festival, noticed by Nash Edgerton, Joel Edgerton’s it, I knew it was one of

[00:34:05] SS: the Hollywood Aussie

[00:34:07] SS: guys. They helped re edit it for a theatrical release, and it was released as a film.

[00:34:14] CR: And then, um, nothing happened. with it. He said, we’re going to, we’re going to get this, you know, we’re going to get a budget for it. We’re going to get it picked up. We’re going to turn it into a series. This is like early 2000s, right? Nothing happened. They couldn’t sell it. They spent like 15 years trying to sell this to get it picked up.

[00:34:37] CR: No one would touch it. And so he did nothing again for the next 15 years. I Yes, because I’ve noticed how young he is in the movie, and it’s like, what have, I actually calibrating.

[00:34:49] CR: so, uh, he just does nothing for another 15 years. Finally, they’re able to sell the show. To a US, uh, network. I can’t remember which one. Oh, FX, picked it up. Yeah, in 2018. And they make this series, which he writes and stars in. Nash Edgerton directs, and they have some other directors, but Nash, and Nash Edgerton appears in it as well.

[00:35:16] CR: He plays a minor character, and his daughter, Nash Edgerton’s real life daughter, plays Ray’s daughter in it, and she’s fantastic. But it’s just, it is like the greatest, this guy, he, he is a fan. Fucking genius. The writing is brilliant. The stories are brilliant. The acting is, he’s terrifying. He’s basically a hitman, low end hitman, enforcer.

[00:35:40] CR: He is just fucking brilliant. But he’s never done it. This is the only thing he’s ever done. And then he did like three seasons and said, I ran out of stories and he stopped. And they’re just like, and the Good. Stop.

[00:35:54] SS: Good. And the final episode, like the final scene of the final episode, Chrissy and I still talk about, it was just, it was like Perfect. my boys. Scott Kilmartin. Scott Kilmartin is a massive fan who

[00:36:06] SS: got me onto it. Big Scotty. Oh, really? Yeah. Wow. that’s, that’s my, Yeah. Tony Kynaston got me onto it too. Oh watch it next Thursday night.

[00:36:15] CR: I’m je I’m jealous, man. You gotta,

[00:36:17] CR: uh, it’s like, That’s actually one of the great things about any form of content or, you know, discovering a band or a movie or whatever. And you say,

[00:36:25] SS: I’m jealous. Cause you get to

[00:36:27] SS: experience it again For the first For the first time.

[00:36:30] CR: Yeah. Wow. That was a pivot, wasn’t

[00:36:33] SS: it?

[00:36:34] CR: How did we get onto that? Um, were talking about violence Violence. on violence that, uh, and in that, in the interim, I did look up what the U S is really, really similar to Australia in terms of the amount of wealth per person.

[00:36:48] SS: It’s, uh. over here, was it? It’s

[00:36:54] SS: 579, 000 USD. there you go. That’s probably about 700, 000 AUD.

[00:37:01] SS: Yeah.

[00:37:03] CR: So anyway, getting back to the side. So my basic idea is that I think we need to start a movement. Really? Like, are you serious when you say

[00:37:12] SS: that?

[00:37:12] CR: yeah, because I don’t have any confidence that our governments or our business leaders are going to manage this, Well, let’s, let’s think about it as well, because I think, and I do this a lot in my career, and it’s, it’s, it’s 20 years, is that we have so often been here before. And I think it is fair to say that the industrial revolution has brought about significant abundance and possibility. We just went through the numbers and we could have fed everyone.

[00:37:54] SS: We could have housed everyone and we could have given everyone access to healthcare with the industrial revolution. And we can now, we’ve just seen those numbers and yet we haven’t. And I would be flummoxed because in the transition, it’s not like you arrive at UBI day.

[00:38:13] SS: We don’t, we don’t arrive at abundance day.

[00:38:16] SS: It kind of creeps up. It’s a, it’s, it’s a little bit like Billy Gibson, you know, William Gibson. It’s like the future has already arrived. It’s just not equally distributed. Well, that’s kind

[00:38:25] SS: of, they’re the members, they’re the guys in ZZ Top, Billy Gibson. oh, is it a William Gibson, Billy Gibson? I didn’t know that. Fluffy guitars, give them a spin. Who

[00:38:35] SS: knew? Uh,

[00:38:37] SS: Yeah, so I Billy Gibbons? No. Billy Billy Gibbons

[00:38:41] CR: is uh, is easy. Tough

[00:38:43] SS: Oh, there you go, I didn’t know. Well, William Gibson, I was pretty sure I had William Gibson right, but anyway, uh,

[00:38:49] SS: so,

[00:38:49] SS: I just can’t see it.

[00:38:51] SS: I can’t see it happening

[00:38:53] CR: so here’s my, my without a revolution, without a real revolution, and I think blood would need to be

[00:38:59] SS: spilled. Okay. So maybe, but my, the, the way I mapped it out is what we need to do. First of all, am I

[00:39:11] SS: mapped out the revolution.

[00:39:13] CR: No, no, I haven’t mapped out the revolution.

[00:39:16] CR: I basically see us building together, putting together a movement. Where we bring together the best and the brightest from around the country and we build a shadow government, basically. So we figure out, we put together a vanguard,

[00:39:36] SS: Is it bad that I’m laughing at this? Is it bad that I’m laughing at this? Keep

[00:39:39] SS: going.

[00:39:42] CR: first person I’ve talked to about this, man, like, I need you on board.

[00:39:47] CR: We put together a vanguard of experts in public policy, technology, urban planning, economics, community organizing, voices from marginalized communities to make sure it’s inclusive and equitable, and then we create portfolios. We have ministers or working groups that focus on figuring out the vision for using AGI and robotics in things like housing, healthcare, education, energy, technology, and do we develop detailed, actionable policies for implementing universal basic services, develop a strategic blueprint that could be picked up and rolled out by a future government because they won’t be doing this effectively.

[00:40:36] CR: by themselves. Somebody needs to be building this out. Somebody needs to put the blueprints into place so they can be rolled out by a future government, whether it’s one of the existing political parties or one that we create ourselves because the, there’s no longer any faith in the Existing parties to guide us into this future.

[00:41:01] CR: Like this is, we’ve talked about this for the last year on the show, but we’re, this is the biggest thing that’s ever happened to humanity. AGI robotics, the AGI revolution, the artificial intelligence, and people say it’s the last human invention and they’re probably right.

[00:41:15] SS: I agree

[00:41:16] SS: too.

[00:41:17] CR: This could be

[00:41:19] CR: the greatest time for humanity, or it could be the end of humanity, or anything in between, right, in the next 10 years.

[00:41:28] CR: I don’t trust our politicians to run it effectively. I don’t trust our corporate leaders or our religious leaders or, you know, any of our institutions to manage this process, policing, legal, etc. We need to put together the best and the brightest from around the country. to lead us through this. And there’s plenty of really, people way smarter than me out there.

[00:41:52] CR: I, I’m not smart enough to do this, but I think we need to bring together the smartest people who actually know how housing and healthcare and education and energy and technology, whatever, work at a ground level, what the challenges are, what the implications of things are, so AGI in robotics? and Nanotech to solve all of these problems.

[00:42:18] CR: What are the practical realities of trying to solve these problems? Um, then we need to secure the resources. You know, we need to secure funding and support to drive this thing. We need to, you know, some combination of crowdfunding, major donors, ethical investors, In kind contributions of people who want to donate land and technology and expertise to support pilot programs around the country.

[00:42:44] CR: How do we, how do we solve the housing crisis? You know, how do we start to build cheap, uh, housing that can house people that are sleeping in tents? We’ve got tent cities and caravan cities growing around Australia. How do we solve that problem starting with the people that are urgently in need? For their children of having housing, uh, near places where they can work and go to school.

[00:43:12] CR: Somebody needs to be, our governments aren’t addressing the housing crisis. Somebody needs to

[00:43:17] SS: we have abundance, do they need to

[00:43:18] SS: be near anything?

[00:43:22] CR: Well, you need to Well,

[00:43:23] SS: to

[00:43:23] SS: work? Well, wait a minute, you

[00:43:24] CR: no, right,

[00:43:25] SS: right now,

[00:43:26] CR: now, yeah, so this isn’t like a, the, you don’t flip a switch and you have abundance, right? We need to

[00:43:32] SS: It’s a

[00:43:33] CR: figure out how to use to, yeah,

[00:43:35] SS: the shadow government would need significant funding before you even did anything. That would be pretty

[00:43:40] SS: significant funding. Good organization. You know, it’s kind of like, it’s not even a think tank. It’s yeah, shadow go, it’s, it’s pretty, it’s a pretty involved

[00:43:51] CR: well, not really. Not from day one.

[00:43:54] CR: You’re building, you’re, You’re building strategic blueprints first. You’re pulling together experts, building strategic blueprints. Then, as that’s progressing, you’re figuring, okay, how do we do pilot programs? How do we find some land where we can build cheap housing using the latest cutting edge technology to design and construct 3D printed houses interesting. So my farm, 000 people?

[00:44:17] SS: I’ve got 110 acre farm. Do you know how hard it is for us to get approval to build a second dwelling on it, because the law says only one house per 80 acres. And like, yeah, but we’re trying to build another house to prove our technology so that we can build houses 50 percent cheaper.

[00:44:31] SS: Do you think the local government is going to help

[00:44:32] SS: us? You wouldn’t believe it,

[00:44:34] SS: Cameron. Yeah, said on the Diamandis interview. He said, it takes longer. To get approval to build a new rocket than it does to actually build the rocket

[00:44:49] SS: I think that’s also the case with housing and many other things. One point that’s really interesting, actually, when you mentioned the segments, obviously healthcare, housing, one of them was

[00:45:02] SS: education.

[00:45:04] SS: And I would start there, and I’ll tell you why. I’ll tell you why I would start with education, because we already have the technology, and it’s not AGI, but it’s good enough in every category to have educational abundance

[00:45:18] SS: Right now.

[00:45:19] SS: Like. Gentlemen, we have the technology to build him better, stronger, faster. Do

[00:45:31] SS: E Boston, a man, half man, half machine, let loose, to come and help a society, a society in trouble. I’m just

[00:45:40] SS: making that up.

[00:45:43] CR: people that weren’t around in the seventies, dunno what we’re talking about, or the early eighties you missed the, it was the 6 million dollar man.

[00:45:50] CR: Yeah, 6 million. Like can’t even get a house in Brisbane for that now. Yeah, no.

[00:45:56] SS: think Education so right

[00:45:57] SS: now,

[00:45:57] CR: Yes, would say that we have, I would say, let’s call it relative abundance with education. I once spoke to RMIT University and they said, the future of education, we want you to come in, we want you to rip the band aid off, tell us everything you think, no holds barred on what the future is, right?

[00:46:20] SS: The executive there were out in the Yarra Valley and I said, okay, the first, they said, I said, so you, you really want me to, they said, yes. I said, the first thing you need to do is to get rid of the ATAR and let everyone study. Any course they want to study, regardless of the course that they got, or the score that they got.

[00:46:41] SS: And they said, oh, we can’t do that because they might not be able to pass the exams. I said, well, that doesn’t matter. And they said, we won’t be able to fit them in the building. I said, okay, if you didn’t get the full score, you can do it from home and do the same exam. Well, we wouldn’t be up that, that every reason I gave them, we couldn’t afford it.

[00:46:58] SS: I said, I had to look at your endowment. It’s 5 billion. You’re a hedge funds disguised as an educational institution. Like, what are you here for? Before I did that, I said, why do you exist? They were for the betterment of society, for the education of people. And then I went, get rid of the HR and let everyone in.

[00:47:16] SS: No, no, no, no, no. That’s just not going to work. Seriously. They hated me so much over the next two hours. We had a family photo where we all lined up at the end of the session. And when I stood there, everyone stood two meters to the side and I’ve got the photo of me on my own, right? Crazy. And when we had lunch afterwards, I sat down at a table and everyone got up and changed tables.

[00:47:40] SS: This is a hundred percent

[00:47:42] SS: the truth. Oh, that’s gold, We could do abundance right now with

[00:47:47] CR: what’s ATAR what’s ATAR is the score, which really

[00:47:51] SS: is a false limitation on the

[00:47:53] SS: amount of Your university, your entrance score, Your entrance score, which mattered when you can only fit 30 people in the building, but no one goes to the lectures anymore. No one goes to the building and we don’t need it.

[00:48:05] SS: So that’s

[00:48:05] SS: Just that is just false

[00:48:07] SS: scarcity.

[00:48:08] CR: Yeah. Just stream them online. You’ll give them an AI.

[00:48:11] SS: want to do it now. So, so already the challenges here are political, not, as you say, you need a movement because

[00:48:18] SS: we can do it right now with education today,

[00:48:19] SS: globally. Yeah. So we go, fuck universities, we’ll start our own university. Anyone can study any subject, anywhere, anytime. And we’ll get the world’s preeminent experts or experts in

[00:48:31] SS: this country. Here’s your engineering guy. Here’s your whatever, here’s your whatever.

[00:48:34] CR: we’ll just get the AI to do most of it, Yeah,

[00:48:36] SS: exactly. within a year.

[00:48:38] CR: Yeah. And we’re going to build a system for how you start from knowing nothing about medicine to being a doctor with AI teaching you everything, you know.

[00:48:48] SS: and, and so, and, and the AI robotics. So the robot will show you how to do the surgery and the, all of that sort of stuff. And Cameron will, he will donate his body to science. He’s that type of guy, but you don’t only need a shadow government. You actually need shadow systems. So then you build shadow education.

[00:49:07] SS: And you almost. It’s kind of almost like any form of industry disruption, but it’s happening category at a time. It’s kind of like what happened with media. They all went across to digital and legacy media is a rounding error with Murdoch’s just hanging on

[00:49:21] SS: somehow at 93 years of age.

[00:49:24] CR: One of the other low pieces of low hanging fruit is mental health. Access, you know, um, down in the pilot program section, I’ve got deploy AI powered mental health platforms offering 24 by 7 free on demand support for depression, ADHD, anxiety, and crisis intervention. Pair AI solutions with community hubs staffed by local volunteers and visiting professionals.

[00:49:47] CR: You know, trying to get kids diagnosed with ADHD in Australia at the moment, as everyone’s heard. Takes forever, costs a fortune, depression, anxiety, trying to get people into, uh, be able to see a therapist is absolutely ridiculous. And you know, it’s deliberately manipulated by the industry bodies to make it as expensive and as difficult.

[00:50:12] CR: I read a, there’s a big article on this in Australia a month or two ago that I read, you know, the, The GPs are trying to get permission for the GPs to be able to diagnose kids with ADHD and the psychiatry or the psychology industry bodies are trying to stop it from happening because it’s, some, some of their members are getting paid 900, 000 a year and I’m not just making that up, 900, 000 a year for to work in AI, sorry, ADHD diagnosis specialty clinics because people are willing to pay a fortune to get their kids diagnosed so they can get them on medication and it’s just a massive payday for psychiatry and psychologists.

[00:51:05] CR: Yeah, I’ll send you a link.

[00:51:06] CR: It’s insane.

[00:51:09] CR: But we need to build solutions for this sort of stuff. Education, mental health, uh, et cetera, et cetera. But it’s not gonna, like, here’s my, my, my realization was that it’s just, we, we, this is too important. We can’t allow business as usual to shepherd us through this period.

[00:51:28] CR: It, they’re not gonna, they’re not gonna do a good job. We need to put together. A shadow government to prepare the, prepare the ground for this stuff.

[00:51:39] SS: It seems to me very much like a, you know, a modern revolution. I don’t know if you would know this better than me, that if the world has had relative peace for the last 50 I don’t know if that’s a bad statement or not, uh, since World War II, I don’t know if this, when you have large tech upheavals that results in war and resources and new systems of governance, not sure, but it certainly feels as though nothing other than a revolution Would make this possible unless we somehow managed to second resources to build out these things. And I just can’t see the donors being there because the donors are typically those with the wealth who are beneficiaries of the

[00:52:33] SS: existential system.

[00:52:34] SS: Saudis love

[00:52:35] SS: to tap into Look, I agree with you. That’s going to be a challenging aspect of it, but, um, you know, you’ll find some of them out there that, that are thinking about their children and their grandchildren and want to see a better world built for them. Um, I think we’ll, we’ll be able to find. We’ll be able to find people to fund it.

[00:52:54] CR: They may not even be domestic. Uh, you know, they may be international, tapping into sources of philanthropy.

[00:53:00] SS: that do some, some brand washing. They like to do some sort of greenwashing

[00:53:05] SS: on their brand. The Saudis are big on

[00:53:07] SS: that. Well, it’s not only that, they know that crude oil has got a shelf life, man, of uh, how long they can make money out of it. Don’t know exactly how long it’s going to be, but they need to prepare for, they need to prepare for the days when they’re not able to sell oil anymore. What are they going to do next?

[00:53:27] CR: Well, I had a final thought on this. It’s just, it’s just that, um, I started this process by, by thinking about what I call techno communism. Um, you know, I, I’ve said on the QAV podcast recently that I’m a communist and, um, people sent me some emails, surprised that a guy hosting a podcast about value investing is a, And what I’ve always said about myself and communism is that if I think about the world that I want my children to live in, it’s a world where everybody is looked after, everybody has their needs taken care of, everybody, um, can have, Abundance and happiness and peace and prosperity and get to live their best life.

[00:54:20] CR: Which system of socio economic cooperation that I’ve heard about or read about over the course of my life do I think is, has the possibility of delivering that? It’s not Capitalism

[00:54:33] SS: Possibility is a good word too, because we’ve never really

[00:54:36] SS: achieved it yet. I would say that’s a

[00:54:38] SS: fair statement. Not on a large scale, not

[00:54:41] SS: on a large

[00:54:41] CR: system has achieved that. And capitalism, see the difference between capitalism and communism is that communism has a vision that it’s aiming towards, and it’s a vision of a better world where everyone is taken care of. Capitalism doesn’t have a vision. There’s no vision for capitalism apart from the capitalists control everything.

[00:55:03] CR: That’s the only vision. There’s no I’ve read Milton Friedman. I’ve read all of the foundational books on capitalism. Um, and there’s nothing. There’s no great vision for a better society.

[00:55:19] SS: but there is one book that defines what it is. I can’t remember who the author is, but it’s called Finite and Infinite

[00:55:25] SS: Games Right? and Finite and Infinite Games talks about the two. It’s a really weird book.

[00:55:32] SS: It’s from the Stuart Brand School of

[00:55:34] SS: Crazy Books in Oh, I love Stewart

[00:55:36] CR: Brand. Yeah. And so Uh, Stuart Brand, for listeners, was someone who, he ran the Whole Earth catalogue, is that right?

[00:55:45] CR: Yeah, real sort of Techno

[00:55:48] SS: utopianism, you know, in the early computer era. And he was part of that, that movement, and he’s done some really interesting things. And he also was famous for saying, information wants to be free. But he also said, information also wants to be expensive. And it’s the balance between those

[00:56:02] SS: two things is sort of where we are.

[00:56:05] SS: Uh, Finite and Infinite Games by James

[00:56:08] CR: P. Kass, an American academic who was Professor Emeritus of History and Literature of Religion at New York University. A review of the book summarizes Kass’s argument. There are at least two kinds of games, finite and infinite. A finite game is played for the purpose of winning, an infinite game for the purpose of continuing the play.

[00:56:29] CR: Finite games are those instrumental activities, from sports to politics to wars, in which the participants obey rules, recognize boundaries and announce winners and losers. The infinite game, there is only one, includes any authentic interaction from touching to culture that changes rules, plays with boundaries and exists solely for the purpose of continuing the game.

[00:56:52] CR: A finite player seeks power. The infinite one displays self sufficient strength. Finite necessitating an audience. Infinite ones are dramatic, involving participants.

[00:57:06] SS: so it’s interesting. I would put capitalism as an infinite game because the people who are playing it just want to keep playing and just want to keep the power. When you read it, it’s kind of clear. And to me, communism seems like a finite game. The game is, is that we distribute and find a system to distribute the resources so that we all have them.

[00:57:27] SS: And more resources come in and out, but the game has an end. An end is everyone has access to everything they need. Whereas Capitalism is this infinite game where I just want to win, and I will manipulate and change the rules to keep playing the game. And I want to be seen as, In front of everyone else and maintain that power structure.

[00:57:45] SS: For me, it was the clearest thing. And I obviously had my economics head on it when I read it. But, um, for me, that was one of the ones that really defines economic systems. If you read it with that context in your mind, you can really see certain patterns. Uh, but I, I think you’re right. I think capitalism, uh, is, is, is about the game itself.

[00:58:06] SS: Whereas communism is about a sense of equality, which could or should be achieved, they feel like two different types of games.

[00:58:13] SS: And hence, I think that’s why there’s a tension

[00:58:15] SS: there. And people will always say, well, we tried communism, it didn’t work. And my response to that is,

[00:58:22] CR: my response to that is threefold. Well, no, we’ve never had communism. That’s another point. We, we, communism is the end point. You have to go through socialism to get to communism and the so called communist countries then and now didn’t get past socialism.

[00:58:40] CR: Um, But the other three, the main three points are number one, capitalism hasn’t worked either. It’s brought the world to the brink of destruction. Um, and, and there’s greater economic inequality, et cetera, et cetera, than we’ve ever had before. Right now, there’s consolidation of wealth in the hands of the 1 percent or the 0.

[00:58:59] CR: 1%. So, okay. So that’s a, that’s a nil argument. It, we tried and it didn’t work. Um, but the key reasons why I, as a historian who’s studied 20th century communism for decades, if I had to put down the two main reasons why communism didn’t work, actually three main reasons why communism didn’t work in the 20th century, they are as follows.

[00:59:26] CR: Number one, the countries that tried it Skipped a step. The countries that all tried it were all, um, mostly pre industrial revolution or barely industrial revolution countries. Russia, um, China, uh, Cuba, Vietnam, Korea, North Korea. These are countries that had been either oppressed by colonials like Indochina and the French, China had had their century of humiliation under the British and, you know, their emperors hadn’t really adopted the Industrial Revolution, had their own Industrial Revolution in a way, but it wasn’t the same as the British Western one.

[01:00:10] CR: Um, and they tried to, and the Russians had the czars and all that kind of stuff that were very late to the Industrial Revolution. And by the time they started their, Socialist slash communist experiments in the early to mid 20th century, they were in a desperate situation. They were starving. They were being attacked by capitalist countries that were far wealthier and far more powerful militarily as well as economically.

[01:00:41] CR: And they tried to Speed up the process. Now, if you go back and you read Marx and Engels, the process that they envisioned for a feudal society, getting to a communist society, was you had to go from feudalism to capitalism, then to socialism, then to communism. And the capitalist period was important because that would build literacy, uh, and infrastructure.

[01:01:08] CR: You can’t really have a society where the people control the means of production unless the people are literate. And you’ve already invested in the means of production. You have, you know, you have roads and to get to that. and it’s almost like capitalism leads you through the innovation and the incentive process to get the resources and infrastructure required

[01:01:30] SS: to have an abundance for

[01:01:32] SS: all, Exactly. And then you evolve beyond capitalism into socialism, and then you evolve beyond socialism into communism, and the difference, main difference, the way I break it down for people is, socialism is where you have a state, you still have a state, that is controlling the division of, uh, Money and responsibility and power and monitoring it, a vanguard.

[01:01:55] CR: When you get to communism, you no longer need the state. Everything is just functioning by itself in communes, little communities. They’re running everything. The people have taken control of the means of production and everything just runs by itself. We never got there. And what, and what the problem, one of the problems, Russia and China and Cuba, et cetera, et cetera, had is when they tried this, their populations were mostly illiterate.

[01:02:18] CR: They hadn’t had an opportunity to build the infrastructure. So they tried to do a speed run in five year time windows to catch up because the capitalists were trying to destroy them while they’re doing this experiment and threatening them with nuclear weapons, et cetera, et cetera, the invading them, et cetera, et cetera.

[01:02:38] CR: And they, and, and the speed run didn’t work generally, which is why Dong Xiaoping is the great genius of China, because in the 70s, Dong said. we, we went, we tried to go too fast, too hard, we need to take back a step, we need to reintroduce some capitalism into the country, but we need to manage it.

[01:02:59] CR: Carefully manage it so they don’t become too powerful, but we need capitalism to invest in the infrastructure. And then after we do that for 50 years, we’ll be the most powerful country in the world, and then we can go get back to where we were. And that explains the rise of China since 1979.

[01:03:19] SS: Although that’s now a pending disaster. There’s a video I watched last night on China’s economic

[01:03:27] SS: future and it is super, super,

[01:03:29] SS: super bleak.

[01:03:31] CR: I’ve, I’ve been hearing those stories for No, no, no. I saw some numbers that blew my, this, this blew my mind. We’re going to talk about it. Next futuristic and we’re both going to watch it and it’s crazy. That said, we call that the Jack Ma clause.

[01:03:43] SS: We don’t want anyone to get too much power. Uncle Jack, listen, you’re coming on a little holiday with us. We’re going to, uh,

[01:03:50] SS: we’re going to reprogram your brain. But also you’ve got Xi Jinping, who is. becoming incredibly,

[01:03:56] SS: he’s an interesting cat,

[01:03:59] CR: Man, Lee Kuan Yew, when he was still around, said that Xi Jinping was the most impressive human he’d ever met. I mean, and Lee Kuan Yew was loved in the West for what he did in Singapore. And he said He said that Xi Jinping was a Nelson Mandela level leader of a country who was going to completely reshape China.

[01:04:19] CR: You get a lot of, you get a lot of, it gets a lot of negative press over here, but anyway, I don’t know you’ve got Chinese family and all that kind of stuff.

[01:04:25] SS: we’ll go to that another time, I mean the fundamental anyway, Alright

[01:04:28] SS: quickly because we’ve got to get back to a couple of other

[01:04:30] SS: topics on the

[01:04:30] CR: well, techno communism, so they tried to move too fast, but also, the technology wasn’t there to centrally manage hundreds of millions of people and their economic and business and social affairs, right? We have the technology now to do that, and we centrally manage Western economies all the time. You know, the way we roll out COVID vaccines is all done by technology, right?

[01:04:54] CR: And our economies are run centrally managed. Um, the RBI. Centrally manages our economy by tweaking levers. So this vision of techno communism is how I started with this. So anyway, that’s my view. That’s my movement. This is going to be the next 20 years of my life. Well, the next two years, because it’ll all be over in two years, whether we win or we lose.

[01:05:16] CR: So,

[01:05:17] SS: Well look, um the idea that abundance for all i think is, Just wondrous. And, and, and, and, and if that is, I believe that the technology could provide abundance, absolutely. And I agree with you that the challenge is the power structures around that abundance and the distribution of it, not whether or not it’s technologically

[01:05:36] SS: capable. So I agree with the

[01:05:38] SS: capability. the third reason communism failed is that psychopaths fuck everything up. That’s one of the big

[01:05:45] CR: yeah. You need to have

[01:05:48] CR: frameworks in place, whether it’s capitalism or communism or religion or police, whatever it is, to stop psychopaths from being able to take complete power, because they will. That’s what psychopaths do.

[01:06:03] CR: So part of all of this is how do we go through this process and don’t let the psychopaths Infiltrate and fuck it up. Psychopaths have their purpose and they have their uses, don’t get me wrong, but you need to carefully manage the psychopaths, because there’s one in ten people that are psychopaths, and if they can get, if they can get access to power, they will, they’re very good at that, the functional ones, and they’ll fuck everything up.

[01:06:30] CR: So that is another problem we had with communism, is the psychopaths got involved. And capitalism’s fatal flaw is that power structures emerge. And its fundamental flaw is that inequality over time, you need a redistribution of wealth. That’s the number one problem with it.

[01:06:46] SS: Capitalism, I

[01:06:47] SS: think. wealth and the power that the wealth

[01:06:50] CR: buys. Yeah, exactly. Yeah, it facilitates that and it needs to be circumvented. Moving right along, right along, Cameron, to uh, social media

[01:07:00] SS: in Australia.

[01:07:03] CR: People, man, I’m getting, I’ve seen a lot of, a lot of people are very angry for our international listeners. The Australian government has just passed legislation that says they’re going to ban social media for anyone under the age of 16 in Australia. TikTok, Facebook, Twitter, Snapchat, I think is included in there.

[01:07:22] CR: Um, doesn’t include some things like online gaming for some reason. Um, there are some things that are. Not going to be, uh, included. How are they going to do it? Not really clear at this juncture.

[01:07:37] SS: I’m gonna write a manifesto on how easy it is to police. It’s so easy. It’s embarrassing as to how easy it is to know exactly, nearly exactly how old a person is on social media. Uh, there’s been a lot of talk, and this is a classic example of

[01:07:54] SS: techno, uh, utopianism,

[01:07:56] SS: and this is, you say, name this theme song. Da da da da da da da da da da da da. You can’t answer it? Okay. You, you’re obviously underage. Get off your band.

[01:08:08] SS: that’s actually a good one. That’s fun. That’s actually a fun one. Name this theme song. We’ve got enough 80s stuff that we can really throw out there until they start memeing on 80s songs and then tell everyone what they are and they use it as an, a stealth

[01:08:20] SS: education process in pop culture. Yeah, right. Sorry. What’s your policing system?

[01:08:25] SS: well, let’s just go for the listeners first.

[01:08:28] SS: A lot of people have come out and said that, uh, it’s thwarting free speech. You can imagine Elon came out and all of the

[01:08:36] SS: complaints. Look, I think it’s, I think it’s super clear that it’s absolutely dangerous for young minds. I think we’ve spoken about it before. I’m really for this law. In fact, I wish it was 18 years of age.

[01:08:46] SS: Because I just cannot see any good coming from social media with kids, you know, young girls and self harm and bullying and all of these expectations on life, reducing their attention spans. The negative, and I’ve seen it personally with family members, where it’s incredibly damaging. And I’m all for this law.

[01:09:07] SS: And I think within a few years, it’s going to go up to 18. Now, The fine corporations can be fined up to 49. 5 million Australian dollars for systemic failures to implement an age limit. Well, first of all, what is systemic? Which means, can they just do it all year and they go, Oh yeah, about that and fight in court a year later after they’ve made zillions of dollars?

[01:09:33] SS: 49 million is nothing for big tech, even in Australia.

[01:09:38] SS: It’s, it’s not even a parking

[01:09:40] SS: ticket.

[01:09:41] CR: Why is

[01:09:41] SS: give you the

[01:09:42] SS: numbers.

[01:09:43] CR: 5?

[01:09:44] SS: Sorry?

[01:09:45] CR: Why is it 49. 5? Is that like 90, you know, 99 cents instead of a dollar? Is it

[01:09:50] SS: nice to make it feel as though they really considered it and didn’t just didn’t throw the round number of 50 is what that is, Cameron. So let’s just be clear on the psychology of

[01:09:59] SS: governance.

[01:10:00] CR: Right, of marketing

[01:10:02] CR: a fine.

[01:10:02] SS: yeah, exactly. So Facebook’s revenue in Australia is 1. 26 billion, right? So it’s what 4 percent of revenue, something like that.

[01:10:12] SS: Uh, Alphabet’s revenue in Australia is 7 billion. It’s not even 1%. Again, parking ticket. The only one that it could affect in Australia, whose revenue is growing, but last reported was only 375 million in revenue. So it’s reasonably impactful on TikTok’s revenue. So, we have a bunch of companies here where the fines are inconsequential.

[01:10:39] SS: Another mistake they made is, underage users, nor their parents, neither of those will face punishment for violations. However, if I’m caught underage drinking or I’m supplying someone underage drink, I get a fine of 2, 000 to 10, 000. Why wouldn’t they do the same thing if they’re serious about it? And I do think that social media is more dangerous for children than underage drinking or driving a car.

[01:11:03] SS: I really do. Uh, now here’s how they can know. I actually wrote like a 30 point plan on the ways that you can know exactly how old someone is on social media. The first one

[01:11:14] SS: is.

[01:11:16] SS: Yes, Cameron.

[01:11:17] CR: before before you go on, I just wanted to point out, what did you say Google’s revenue was in Australia? Do

[01:11:22] SS: Alphabet

[01:11:23] SS: in total is 7 billion.

[01:11:26] CR: you know how much of that they paid tax on?

[01:11:28] SS: Oh yeah, I know they pay about 20 million

[01:11:30] SS: tax a year or something ridiculous. Almost

[01:11:31] SS: nothing.

[01:11:33] CR: 90 million in tax they paid based on income of 1. 892 billion because they claimed that around 80 percent of their income is not taxable.

[01:11:46] SS: That’s right. Because you know what they do? They lease their brands and their assets off themselves, which is the easiest loophole to close in the

[01:11:54] SS: world. That’s like me saying I’m gonna put my brain, I’m gonna put my brain in um, a zero tax haven and I rent my brain from my, this is insane. It’s just

[01:12:04] SS: insanity.

[01:12:05] SS: It’s a joke.

[01:12:07] CR: took 6. 3 billion from Australian customers during fiscal 2021 2022, told the ATO that 93. 6 percent of their income was not taxable.

[01:12:18] SS: allow that. But this is why to remove multinational tax avoidance, it’s so, so simple. And again, Cameron, we’ve been here before. Land tax. Why was land tax introduced? Because people were finding ways to say, yeah, but I had to put the fences up and the cows and the this and the that.

[01:12:34] SS: And then they said, yeah, we’re just going to put a value on your land and send you a textbook. Congratulations. You’re my newest taxpayer. We do the same thing. It’s called revenue assessment tax for any international company. We put a valuation on your company. You did 7B in revenue. Here’s your 10 percent tax on that.

[01:12:48] SS: Congratulations or leave. We

[01:12:49] SS: don’t care. It’s real easy. You

[01:12:51] SS: need his courage. yeah, we’ll just nationalize all of your assets and

[01:12:54] CR: you can fuck off.

[01:12:57] SS: I’m not joking. This is exactly what

[01:12:59] SS: we should do. It’s so easy. It’s an

[01:13:01] CR: Same with mining companies. Oh, you don’t want to pay tax on your mine? Then fuck off. We’ll, we’ll nationalize your take it with ya. Well, we should nationalize the mines anyway, but that’s another part of our communist plan. I agree. That is insane. Zero value add. back to, how do you, how do you

[01:13:16] SS: error. It’s a rounding error. Um, now, here are some of the ways.

[01:13:22] SS: I won’t list them all because it’ll bore listeners, but I’m going to write a manifesto. First one is Despite what they say, they are looking at the face of every single person who is on social media, every single time. They are doing that. And when you’re posting, you’re taking a photo, and they can very accurately with AI, guess your age.

[01:13:38] SS: That’s number one. Number two, finger size. They know exactly how big your finger size is. Number three is the tone of your voice, whether or not you’ve been through puberty or not. If you haven’t been through puberty, they can tell in your voice whether or not you have been through puberty. There’s three.

[01:13:53] SS: We haven’t even

[01:13:53] SS: started. Which room you are in.

[01:13:56] CR: bio authentication. BioPrints. There’s about 20, right? I’ve just given you three. Location, Geo. All right, let’s go with location. The first one is, Which bedroom are you in in the house? Every single house is on Google Maps. Every single house which has been sold, sold in the last 15 years, would have a map of that house and the address knowing where the bedrooms are.

[01:14:20] SS: If the phone is next to a bed which isn’t the main bedroom, you know how old they are. You take that phone, if that phone is in a classroom, we know the classroom and the ages of the people in that classroom. Here’s another one. The most common message on social media is Happy Birthday. Happy Birthday, Steven.

[01:14:39] SS: Great, hope you enjoy your 14th birthday. You can cross reference this with all of your contacts lists who are the same contacts where you can do a triangulation test on the same things on them to work out exactly how old they are. Like, what about the content that they look at? What about the things that they share?

[01:14:55] SS: There is an insane number of indicators and I actually asked ChatGPT and it gave me more than 50 and they said we don’t know if these They actually have access, but it is highly plausible and probable that they do have access to all of this information. They know exactly how old the person is. And here’s what we need to do. Find someone who is on there, who is younger than you. We’re going to come for you. And the fine is 5 percent of your revenue. Your fine is 10 percent of your revenue. Congratulations, here’s your fine. Or we’ll take your directors and put you in an orange suit. It’s real easy. Either way, parents who give it to their kids should risk a fine of 10, 000 as well.

[01:15:37] SS: Because we need to treat it the same way as drink driving, as driving on the road illegally, and alcohol if we’re serious about it, and tobacco. If we’re serious about it, it’s easy to define who is on the phone. So easy. I’ve just given you a whole bunch

[01:15:53] SS: of reasons that you can cross

[01:15:55] SS: reference those. Well, there’s a difference. You’re talking about the ability of the technology companies to determine the age of the participants, but how do you police it? How does the government police what the social media companies, how well they’re monitoring and managing the process? That’s a way you police it is, yeah, so you find people. Who have broken the law. So this is the needle in the haystack. You got to show the

[01:16:25] SS: needle. If How do you find that? You get 15 year olds to confess to the government, go to a confessional with a Catholic priest and after he finishes touching them up just mentions that they’ve you make the fine, here’s, here’s what I think too. If you make the fine and the downside significant enough, you’ll get an incredible amount of compliance from corporations. Cause they’re, they’ve only got one

[01:16:47] SS: motivation,

[01:16:48] SS: Cameron. Yeah, but I’m not talking about the corporation, I’m talking about how does the government police that the corporations are doing it? How do they monitor it to make sure they’re doing the right job?

[01:17:04] SS: I think they will do the right job if the risk is high enough for them financially.

[01:17:10] CR: Yeah, I get that argument, but that’s That’s my argument.

[01:17:19] CR: It’s like talking to my wife. Um, okay, so

[01:17:24] SS: What does that mean? You really love me,

[01:17:25] SS: Cam. Thank you. Well, you know

[01:17:27] CR: that’s true. Um,

[01:17:30] SS: well, there would be

[01:17:31] SS: ways that you could do it. Let me, let me

[01:17:33] SS: digest that and in the you can just you can just say I don’t know.

[01:17:37] SS: not yet, but I’m sure there is a way. I don’t know yet. I

[01:17:39] SS: actually I don’t know. So you don’t have a policing strategy at all, real. Well, You’re talking about compliance strategy, not a policing strategy.

[01:17:48] SS: yeah, a compliance strategy, I think we have, the policing I think is, I mean, you could do the same way you do things with cars.

[01:17:57] SS: You could do random

[01:17:58] SS: checks. Yeah, that was where I was

[01:18:00] CR: going to go with it. So random checks and how do you do that? We’re just going to rock up to Facebook’s offices and

[01:18:06] SS: But you could do that. You, and also, well, wait a at people’s profiles and then determine whether or not they’re. Of age,

[01:18:14] SS: Well, well, if you’re gonna have a law. Maybe, maybe you could determine whether or not people are of age on their profiles, but maybe you take phones out of kids hands in the same way that you get someone on the street, uh, in a car, in a public place. Maybe that’s it. In the same way that it’s what’s in your, I don’t know.

[01:18:31] CR: cops just randomly tap kids on the shoulder on the train on the maybe, Yeah, maybe, maybe, that’s it.

[01:18:39] SS: Why, what’s wrong with that?

[01:18:40] CR: look, cause that sounds very police statey.

[01:18:44] SS: Well, we’ve already got police state with alcohol and, and cars. What’s the difference?

[01:18:49] CR: I don’t want more police statey. I want less police statey, but look, let me, let me throw some. I do, and look, I’ve had a number of people in the last couple of weeks, including my boys, uh, who are 24, say this is just ridiculous and it’s bullshit and it’s never gonna work and kids will find a way around it, they’ll, they’ll find a way to hack Like they do with alcohol and like they do with driving cars

[01:19:10] SS: illegally. Yeah, that’s what they You know, the most important thing though on it, for me, the most important thing, yeah, and, and, and I know that people laugh at me for this, but in my mind the most important thing that this does is it gives parents a reason to say it’s against the law and we are

[01:19:29] SS: not doing it. You’re not

[01:19:31] SS: having it. And I think, and I, and I do think that in countries like Australia and parents who care about their kids. In the same way that they don’t give their kids alcohol, well you hope that they don’t, when they’re young, uh, this becomes like that. And a large part of it is really about parenting, but this gives the parents tacit approval and legal approval to come and say, hey, wait a minute, no, we’re not breaking the law.

[01:19:58] SS: I think that’s the most powerful

[01:19:59] SS: thing on this law.

[01:20:02] CR: I’ve had, so I’ve had a range of conversations and I’ve seen a lot of stuff online about this over the last couple of weeks. Um, one of the arguments that I heard against it from a friend was that what about LGBTQ kids in rural towns that, uh, the only source of support that they get is from social media, being online in communities of other LGBTQ people.

[01:20:30] CR: They’re going to be cut off. Uh, it’s going to be bad for them. Do you have a response to that?

[01:20:37] SS: No, because I was just, um, typing into ChatGPT, uh, ways that it could be policed, because it might have a better answer

[01:20:45] SS: than ours. Sorry, can you ask me again, please, mate?

[01:20:48] SS: Was doing So one of the arguments that I heard against a ban is that what if there are LGBTQ kids in rural towns where social media is the only place they get any sort of community and support and they will now be cut off from that.

[01:21:05] SS: Yeah. Look, that’s a concern and people, uh, who need social connection for a variety of reasons, whether they’re mental health or their personal status or all of those. Things like you’ve mentioned. Um, we should be able to, as a part of this, provide some kind of a forum where they can find each other that is outside of the realms of traditional social media.

[01:21:33] SS: I don’t think that would be incredibly difficult to build a forum. As far as I understand, WhatsApp and a few other messaging groups are still available and Reddit and other places. I think that there is still places for them to connect and communicate. But if it is that government needs to invest in this.

[01:21:51] SS: Then they should, and they should get the money off big tech to do it, right? So build a safe place for people of that ilk to be able to connect with each other and communicate, and that’s actually even more of a healthcare issue than a social media issue, if you want my honest opinion on it, and that there should be services that the government is investing in to help people with specific.

[01:22:13] SS: Um, needs for socialization and connection

[01:22:16] SS: who, you know, don’t fit into the

[01:22:20] CR: Yeah, we already have Kids Helpline. According to Guardian, four hours ago, uh, the laws will apply to Facebook, Instagram, Snapchat, Reddit, and X. Exemptions will apply for health and education services, including YouTube, Messenger Kids, WhatsApp, Kids Helpline, and Google Classroom. So there are, uh,

[01:22:44] SS: Y.

[01:22:45] SS: Ha ha ha Ha There are going to be avenues and platforms for kids.

[01:22:50] CR: Um, so look, I think we’ve talked about this before, but this is how I’ve articulated it to people in the last couple of weeks. I am personally against censorship as a general rule. I think in a, in a free society, you want to keep the government out of censorship as much as possible. You also want to keep them out of interfering with what people can do in their private lives, their personal lives.

[01:23:13] CR: I disagree with bans on tobacco. I disagree with. Uh, Duties on Tobacco, and all that kind of stuff. Oh, right. That’s said,

[01:23:24] CR: watch what surprises you.

[01:23:26] SS: to hear that you disagree with that. I, I think in a free economy, if something’s legal, you should be able to use

[01:23:31] SS: it, but

[01:23:31] SS: yeah, it’s either

[01:23:32] SS: legal or it’s I’m happy for

[01:23:36] CR: there to be restrictions on where you can smoke in public, but, I, I’m not able to buy cigars to smoke for myself at home on my deck. Because the price went up from like five bucks a cigar to 60 bucks a cigar on the things, right? So

[01:23:55] CR: that kind of stuff, um, I, I take offense to,

[01:23:59] SS: Yeah, No, I agree but here’s the

[01:24:00] CR: thing. I disagree with that. I, and I think they should be limited. It should be a tool of last resort. That said, I do believe governments have a responsibility. of care, particularly for, uh, minors and minorities and, and people that, um, get the rough end of the stick in a society where they’re on the fringes and the margins.

[01:24:25] CR: And if, We, we know there’s increasing evidence that social media is just bad for everybody, generally speaking, but particularly for kids because their brains aren’t fully developed. They don’t have the control, the executive function to know what’s good for them, what’s not good for them. We know that there’s a lot of bullying, there’s a lot of suicide, there’s a lot of horrible stuff that happens just in terms of self esteem and all that kind of stuff that comes from what, looking at Instagram that kind of stuff.

[01:24:56] CR: That, um If corporations know this, but aren’t doing enough to stop it, if parents Know this and aren’t doing enough to stop their kids being on it that there is a point in time Where governments do have a responsibility of care to step in and go enough’s enough We’re gonna have a generation or generations of kids that are more fucked up than they need to be.

[01:25:23] CR: We need to Put an end to this. We need to stop this. We need to step up. It’s difficult. Um, I’m, I’m, I’m in a sort of mixed position on it. Um, I don’t trust governments to do this stuff well. Um, but I do understand the impetus to protect the most vulnerable in society if the, if the forms of protection that exist outside of that aren’t doing a good enough job to protect them.

[01:25:58] SS: Yeah. It was interesting when I put into ChatGPT some of the policing. I mean, the, the most obvious one, which got thwarted because of privacy concerns, which is insane by, I think the coalition was, uh, to put in, um, verified digital ID systems, which would be the easiest way, some form of ID to prove that you’re over the age of 16, whether it’s a learner’s permit or whatever.

[01:26:22] SS: And you can do that end to end encryption, which, which actually

[01:26:24] SS: has zero privacy

[01:26:25] SS: issues as well. All right. So, everyone’s like, oh, they want to get all your ID, yeah, they know who you fuckin are exactly. And they know that as well. So they should have had that. And that’s the easiest way to do it. And I would envisage, I would envisage that at some point that’ll come in. I do think that, like a lot of laws, you put them in for good reason, but there probably will be an amendment.

[01:26:47] SS: Um, some of the other ones was device level restrictions, built in settings. Um, Guardian Approval, all those

[01:26:53] SS: kind of things as well. Um,

[01:26:56] CR: Now, there’s also the argument that this has all been orchestrated by the Murdoch media as, and the other big media, Kerry Stokes, et cetera, and

[01:27:08] SS: it may well have.

[01:27:09] CR: against Google and Facebook for, you know, refusing to, um, be bribed in order to let people have access to the news. And I think that’s probably right too.

[01:27:24] CR: I’m sure I think there’s a high

[01:27:25] SS: chance of that. Doesn’t make me

[01:27:26] SS: against pushed hard for this. Exactly. Both things can change my mind on it. If it came from people who have done

[01:27:33] SS: nefarious, iniquitous things

[01:27:35] SS: in the past, it And are doing it for nefarious

[01:27:38] CR: reasons.

[01:27:39] SS: exactly, for their own power and wealth, doesn’t make me against it. Um, but I think that, um, Yeah, the law will have to be adapted, but putting it in is really important and it gives parents something really important. The policing of it, random checks it, uh, was another one that was suggested by ChatGPT with the companies providing the services and it said the fines would need to be significant enough for them to enforce it.

[01:28:08] SS: I mean, it’s a classic algebra of, do you make more money by not doing it and paying the parking fine? I mean, it’s really simple algebra, right, uh, on

[01:28:15] SS: that. It’s the seatbelt recall argument from Fight It is the Fight Club. It’s exactly that. And that’s all they need to do. I think there are ways that the easiest one is proof of ID on the device. Uh, big tech, absolutely no. If you make the fine big enough and do random checks, then, uh, and if they’re smart, they would comply with it and shut people off because then they can, oh man, I was actually, I’m, I was going to say then they would maybe thwart the laws in other countries by not drawing attention to themselves Hmm. because they would not

[01:28:50] SS: want it in other countries,

[01:28:51] SS: surely. Anyway, I mean, I’m doubtful that this will actually get implemented.

[01:28:59] SS: When you say implemented, passed

[01:29:01] SS: in the Senate, or, no,

[01:29:03] CR: actually, executed. It’s been passed in the Senate, I think. Yeah. Um, I’m, I’m way, this quote, it says, if they can target you for advertising, they can use the same technology to know exactly who you are and verify the age of a child. We know that. It’s whether or not we can police it, like you say. The enforcement is the, is the hard part, but I think that parents, they need to be, it needs to be the same as alcoholic driving.

[01:29:26] SS: But I’m, I’m for it.

[01:29:29] SS: Gee, this has been the longest podcast we’ve ever done in

[01:29:30] SS: history. nah, my, uh, my guess is when Trump is in power, uh, he and Elon will make a couple of phone calls to Albo, or whoever our government is at the time, and it’ll all be, it’ll all disappear or get watered down with some sort of bullshit excuses. That would be incredibly Or, it’ll be, you can do it to Facebook and Google, And TikTok and Snapchat, but you can’t do it to X.

[01:29:59] SS: Because X is really important for journalists and news, and it’s more of a news forum.

[01:30:04] SS: Platform for free speech

[01:30:05] SS: and news, so, Did you want to talk about Nvidia or have we run out of time?

[01:30:09] SS: I can do it, we might as well. We’ve gone this long, anyone who’s here, thanks for staying with us, and send us a little note, an email, a tweet, an X, or something on LinkedIn and say, I, I stayed with you, the whole way, JP, I’m talking to you, James Peterson, I know you stay true, and Jon Yo.

[01:30:28] CR: Johnny Yo.

[01:30:30] CR: Used to work with John at Microsoft like 20 years ago. Okay, get into it. NVIDIA, what’s NVIDIA doing that NVIDIA has launched an AI chatbot. And what I love about this is that it runs locally on your PC. ChatRTX. And I feel like we’ve spoken about this before. A custom chatbot which is trained on your own local data, including documents, videos, and more. For me, this is like the start of digital twinism, which isn’t a word, but I’ve used it.

[01:31:01] SS: And it’s kind of like, I feel like this is what Apple missed.

[01:31:05] SS: This is what Apple should be doing. They’ve got the device with all of the stuff, your voice, your print, everything. You know, I, I feel like this is, I haven’t tested it, but it feels like the first move towards digital twins, local client learning on, on your device about you and what you believe.

[01:31:22] SS: Uh, I don’t know how that would integrate when you’re offline. Cause it can work when you’re offline as well to a chatbot. Um, how much data you would need and whether or not it can work without access to the web. For me, this is kind of like gone under the radar. It’s really significant, and it’s also significant as well, because NVIDIA has teamed up with OpenAI to do the Figure 1 and Figure 3 robots, humanoid robots, which I get the sense that this will go into that local version as well.

[01:31:50] SS: So,

[01:31:51] SS: your thoughts Cameron?

[01:31:54] CR: well, um, to run this, look, I think Apple are doing this, this is their vision, um, but they’re rolling it out slowly. I mean, one of the challenges, I can’t run this, because it only runs on Windows 11. And you need an NVIDIA GeForce RTX 30 or 40 series GPU, or an NVIDIA RTX Ampere or ADA generation GPU with at least 8GB of VRAM.

[01:32:21] CR: So, I don’t have a time machine to get a Windows operating system as well. That’s the other thing you need,

[01:32:26] SS: is Yeah Yeah So, um, But! I do think this is, um, I think this is great stuff and I do think this is a hint of where the future is. So the point of this is it can read all of your own docs and notes and all your own data on your machine and you can chat with it about all of your data on your machine and you’re not sharing it with, uh, something outside with the greater world can chat with your files.

[01:33:00] CR: Um, and developers can use it to build their own rag based applications for RTX. It’s sort of a demo, I think, of how to do this. NVIDIA, uh, NVIDIA are trying to build their own tools, like they’re building their own robotics, um, operating system, their own LLM operating system. Uh, you have, you have the. LLM platforms like OpenAI and XAI talking about building their own chipsets because they can’t get them fast enough from NVIDIA.

[01:33:31] CR: Then you’ve, they want to go down the stack. You’ve got NVIDIA going, well, we can go up the stack too. We can both play at that game. So they’re going to be building more and more. I mean, most people had never, including me, had never really paid any attention to NVIDIA two years ago. NVIDIA,

[01:33:49] CR: I mean, I had heard of

[01:33:50] CR: them, but course. Yeah. Yeah,

[01:33:52] CR: They were guys that built gaming chipsets for Xboxes and shit, like it was, or high end gaming computers, right? Um, so now Nvidia are going up the market stack. And these other, the LLM companies are trying to go down. I, I think Nvidia’s play is probably easier, seeing as they’ve kind of been the partners of all of the LLM platforms in the building of their platforms in the first place. I think they understand the software layer better than the software guys probably know how to build chip fabs.

[01:34:26] CR: But, um, I expect to see more of this out of

[01:34:29] CR: Nvidia. who could encroach into the other person’s

[01:34:31] SS: space easier is a really good point.

[01:34:33] SS: Right. Yeah. A little bit I expect to see NVIDIA rolling out more of these sorts of tools, generative AI, enterprise level, as well as consumer level, uh, full stack ecosystems built on top of their platform, and start to develop more of a consumer slash business brand on the software level of the stack as well, and just, and doing it for free, because they make money out of The backend tech, you know, they can give it away.

[01:35:04] CR: It’s a bit like,

[01:35:05] SS: like what Google did with the search, right? They made money in a, in a different

[01:35:08] SS: way. And, and Facebook as

[01:35:10] SS: well. Um, pools. I did a deep dive on an American swimming pool company, actually the world’s biggest swimming pool company on QAV this week. It’s called Pool Corporation. And guess what percentage of their revenues comes from pool sales? 13%.

[01:35:28] SS: I have no idea.

[01:35:32] SS: What The rest of it,

[01:35:34] CR: maintenance on your pool. It’s the razor blade model. You get the pool cheap. Hey, take a pool. Everyone gets a pool. You get a pool. You get a pool. You get a pool.

[01:35:47] SS: You get a pull!

[01:35:49] CR: We make money off you for the rest of your life by paying for maintenance and maintenance products. They own the whole ecosystem for pools, including in

[01:35:57] CR: Australia. But did Pool Corporation. And I love a company that’s called Pool Corporation and say, what do we do here? We make computers. We’re called Computer Corporation. We make sunglasses. Therefore we are called Sunglass Corporation. We make BMS bicycles. Therefore we are called BMX

[01:36:14] SS: Corporation.

[01:36:15] SS: Okay, Cameron.

[01:36:17] CR: Yeah, I love it. Branding 101. Just, that’s why I called the, hey, Cause why are we did I call my, what we’re a body of people. Corporate, as in body, Latin, people, corporation. That’s what we are,

[01:36:28] SS: Cameron. By the way, today is the 20th anniversary of my first podcast actually coming out, being published today, 29th of November. Published my very first podcast, G’day World Number One. Um, what did I call my podcast network when I launched it a couple of months later?

[01:36:48] SS: The Podcast Network.

[01:36:51] CR: Yeah, because I’m with you on that. Just call it what it is. It’s Especially if you’re early, especially if you’re

[01:36:56] SS: early. It’s Bauhaus, Steve. The principles of Bauhaus, the design movement into war period in Germany. Form follows function, and just, just call it what it is. Don’t fuck around, don’t put frilly things on it, just say what it is. It’s a podcast network, we’re gonna call it the podcast network.

[01:37:13] CR: It’s a pool corporation, we are the pool corporation. Let’s not, let’s not pretend. Anyway, congratulations I like it a lot. Um, there you go. Well,

[01:37:23] CR: If anyone out there is downloading NVIDIA Chat with RTX and running it, uh, let us know. Tell us what you think. All right, we done? We’re done. That’s uh, an hour and 38

[01:37:37] CR: minutes, Steve. might be the

[01:37:39] SS: longest one ever. Wow. are you going to join my

[01:37:41] CR: movement?

[01:37:42] CR: Are we starting a movement together?

[01:37:43] SS: was, I was stimulated. I was really intellectually stimulated and

[01:37:48] CR: I put you down? Put you down for a contribution?

[01:37:51] SS: put me down, put me down. I, uh, am very interested in reading. Well, I’ve heard the manifesto,

[01:37:57] SS: but You can be Engles to my Marks. sure. Engles was actually the, he was the smart one. He well then I can’t be that. You don’t need to be that. You wonder, you wonder.

[01:38:09] SS: Your breath of knowledge.

[01:38:10] CR: just had the beard. I mean, Engles had a

[01:38:12] CR: beard too, but Marks had the better beard. That’s really. All right. Cheers. Thank you everyone.

[01:38:20] SS: Thank you. That was, uh, I really liked that techno utopian thing that we were, cause it’s, it’s really, really interesting and important. Like, nah, like, well, I, I kind of agree. It’s like, stop.

Is Elon Musk going to be Trump’s AI Czar? And, if so, does that mean he has all of the US’ AI plays – OpenAI, Google, Anthropic, Meta, etc – at his mercy? We think so. And it’s going to make for an interesting few years.

Futuristic 32

[00:00:00] CR: Alright, give me

[00:00:06] SS: two, three, Cameron Reilly, Steve Sammartino, tuning in to the Futuristic Podcast. This is the time, we are the people, and we are so happy to have you here.

[00:00:15] SS: Yes.

[00:00:19] CR: episode, uh, 30, what, 2, I think? Yes, 32, according to my notes. Recording this on the 18th of November, 2024, Steve. We’re, um, we’re back in a new era, back to the future. A new era of a upcoming Trump era. Presidency in the United States, and the main reason I wanted to do a show, uh, there’s a lot of stuff going on, but I haven’t seen enough talk about this in the interwebs of late, is the fact that, as far as I can tell, essentially this means Elon Musk is now The AI czar of the Trump administration.

[00:01:13] CR: They’ve declared that he’s going to be co running the DOGE, Department of Government Efficiency, with Vivek Ramaswamy. But, uh, like you absolutely got to be certain that Elon is going to be running Anything to do with AI, AI regulation, AI investment, and I’d fucking hate to be Sam Altman right about now, because

[00:01:41] SS: The Funk Soul Brother. Check it out now. The Funk Soul Brother. It’s over, brother.

[00:01:49] SS: It’s right, about now. That’s that

[00:01:50] SS: song.

[00:01:51] CR: right, uh, we know that Sam and Elon have got a longstanding beef, um, Elon sued Sam and OpenAI last year, or this year, I can’t remember, Um, over his involvement in OpenAI, uh, uh, uh, and, you know that this now means Elon is gonna be determining the future of, uh, of AI, of AI regulation. I, uh, uh, fuck, what this means for the future of AI.

[00:02:23] CR: And, my big, like, I’ve got a lot of concerns with the Trump Presidency. But one of the biggest I had in this election was, fuck, if Trump wins, what does that mean for the future of AI? Because he’s a loose cannon and he could fuck shit up.

[00:02:38] SS: yeah. He’s not

[00:02:39] CR: my entire life for

[00:02:40] CR: artificial intelligence and the singularity and I don’t want

[00:02:42] CR: it to get fucked up by some orange, uh, moron.

[00:02:46] CR: But then, and like, all right, there’s a lot of things we can say about Elon Musk. And his support for Trump and all those sorts of things. But Elon is max AI, even though he signed the whole AI slowdown thing early on, we all know that was kind of bullshit. Since then he’s invested gajillions of dollars into building XAI.

[00:03:11] CR: We know he’s all about humans and Neuralink integrating AI into our brains and AI helping the human race survive and all this kind of stuff. If Elon and Trump don’t have a falling out again, which I give that better than 50 50 odds,

[00:03:33] SS: 50, at least 50, 50, at

[00:03:35] CR: at least.

[00:03:35] CR: 50, yeah, I’d say 90 10 that they’re gonna have a falling out, maybe even before Trump takes office.

[00:03:42] SS: yeah, Trump’s really impetuous. He can change his mind in a heartbeat on something because someone else gets his ear or something else is relevant to him, which, there’s more to it. And I think that Musk made the investment because he knew there was complexity and risk. I mean, one of the simple ones is Tesla and China, right?

[00:04:04] SS: So that’s antithetical. Trump’s interests and Elon’s don’t overlap there. So there’s a number of things, which I think is why Elon invested so heavily. And while we’re on the topic, can we just say for all the entrepreneurial things that Elon Musk has done and done so well. Including SpaceX and Tesla. His greatest investment of all time was the 119 million.

[00:04:32] SS: He invested in the Trump presidency, which is about 10 percent of how much was raised. The day after the election, the market capitalization of, Companies that Musk’s owns went up by 15 billion. So that’s 126X return on investment in six months. So that’s his

[00:04:55] SS: greatest

[00:04:56] SS: ROI.

[00:04:58] CR: Well, you know,

[00:04:59] SS: And that excludes, that excludes, uh,

[00:05:01] SS: SpaceX. Which you would have to

[00:05:04] SS: imagine,

[00:05:06] CR: for the last couple of years, everyone who said he was an idiot for buying Twitter, and he’d fuck Twitter up, and he was a moron, you’ve heard me say this a million times, we could say lots of things about Elon Musk, but he is not an idiot,

[00:05:20] SS: no, he’s definitely not an idiot. He’s interesting and strange and I don’t like lots of what he does.

[00:05:25] SS: But

[00:05:26] CR: if he bought Twitter, he did it for a reason. Now I don’t think he bought it to get Trump elected because when he bought Twitter, I don’t think anyone thought Trump had any fucking chance of running again and getting the nomination. But yeah, it was. Clear to me from the get go that he bought Twitter because he wanted a platform to get shit done that he could, you know, use it to market his own services and products and that kind of stuff.

[00:05:55] CR: But he obviously has now used Twitter to help get Trump elected, which basically makes Elon and Peter Thiel in charge of the United States government. He and Peter Thiel just bought themselves

[00:06:10] SS: yeah, I, I think he has a lot of attention across every platform because he’s so newsworthy with everything that he does. I think he could have done it without Twitter or X because every feed that I see, and I can promise you, I don’t go onto X at all, uh, these days and I am still filled with musk. News and content because he’s always on, on, on the edge and, and controversy

[00:06:37] SS: works

[00:06:39] SS: in

[00:06:40] CR: Yeah, well I did a big show on the Bullshit Filter a week or two ago about why he threw his weight behind Musk, the China thing is part of it, but he also had about 20 or 30 lawsuits that the Biden administration were going after all of his companies for regulatory issues, And he had, my take, my read on the whole thing is he had just decided that he was going to destroy the Democrats for the, for, as payback for all of the investigations they were doing into all of his companies for labor practices and environmental regulations and all sorts of things, you know, he has that classic laissez faire capitalist mindset, which is, hey, I’m shaping the future and shaping the economy and doing all this good stuff.

[00:07:32] CR: You should just be supporting me and getting the hell out of my way and letting me do whatever the hell I want. Not trying to slow me down. And so he just decided to weaponize Twitter and his attention and his money politically. Citizens 2010, means that there’s no holds barred now for billionaires that want to buy an election in the And he and Peter

[00:07:55] SS: great idea. It’s a great idea

[00:07:57] CR: Oh, fantastic for

[00:07:58] CR: democracy.

[00:07:59] SS: for billionaires.

[00:08:01] CR: Americans keep telling me, we have to save the democracy, and I’m like, what democracy? You have a plutocracy. You don’t have a democracy. It’s

[00:08:09] SS: I prefer kleptocracy. Kleptocracy is good.

[00:08:12] CR: that too.

[00:08:13] SS: Tech

[00:08:14] CR: So anyway, let’s talk, Steve, about the future of AI for a little bit. Um, how we think this is gonna play out with Elon in control.

[00:08:26] CR: And again, this is with the caveat that That Elon and Trump don’t have a massive falling out at some point and then it could all go awry. Let’s say that somehow those two egos can sit in the same room and manage to make it work for four years.

[00:08:47] SS: I, I,

[00:08:48] CR: AGI with

[00:08:49] CR: Elon Musk in control

[00:08:51] SS: I think he’s too far behind. I don’t think he can catch up. Uh, I think that the other players are doing so incredibly well. And when I say the other players, I mostly mean Microsoft and OpenAI. I don’t think he can catch up and, and I think that even though, even though he’s got the year of the president, I think he’ll get advantages given to him in terms of laws and regulations and decision criteria.

[00:09:27] SS: But I don’t know that enough of that is going to thwart Microsoft and Amazon and Google and all of the other players. It’s because. They’re, I think, already a bar ahead, uh, in terms of consumer use, AI tools, not Neuralink, that’s, that’s a separate thing, uh, and ChatGPT at the moment, seriously, absolutely crushing it with its latest improvements.

[00:09:57] SS: So I actually don’t think it’s going to make, in my view, a big difference to the AI race, because I don’t think inside that four years, the others can be thwarted enough. Now, I do think that regulation and laws will be shaped towards Musk’s preference, but I don’t think that You’re going to make up the last eight or 10 years just because you’ve got some regulatory advantages or decisions that are to your advantage. Yeah, really? Well, what I would like to hear is how, because is anyone using any of Musk’s AI products? Like if we look at robocars, way behind. Alright, now he might get some laws placed where his non LIDAR form of, uh, autonomous vehicles might get approved by the Trump administration, uh, he’s got his robots which are way behind the figure one and other robotics, uh, neural implants I think are still a fair way off because that involves humans and it’s very difficult to get that approved.

[00:11:09] SS: In terms of having a consumer based AI like, uh, Anthropic or Gemini or OpenAI, I don’t know anyone who uses that. And if you look at all the usage charts, his is, you know, Grok is way down and functionality in terms of functionality testing is nowhere near it. So that’s not to say that a lot can’t happen in the four years, but I don’t see how, and I’m happy to have you change my mind because you’ve done that before

[00:11:34] SS: and you’re pretty good at it.

[00:11:36] CR: That’s what I’m here for. It’s my job. Look, ahem, Um, let me preface this by saying some news broke in the last 24 hours, uh, that something bad seems to have happened at XAI. Uh, it’s all just rumors swirling about on X, uh, aka Twitter and Reddit at the moment. So We know that you can’t put a lot of stock in that, but somebody tweeted, a guy called Aidan McLeod tweeted yesterday, Elon lost the mandate of heaven, the cosmic rays weren’t on his side, RIPXAI, the GPU looking data center was cool, look out for departures.

[00:12:18] CR: Somebody asked what happened and he said something bad. Now We don’t know what that means, um, this guy, Aidan McLeod, according to his, uh, ex biography, is just, uh, some sort of an AI guy. Um, I don’t know if he actually works there, I don’t think he does, I’m not really sure. Ha ha ha!

[00:12:47] SS: You hear things. Janitors hear

[00:12:49] SS: things.

[00:12:50] CR: Um, but, you know, I had been, uh, Following the sort of XAI thing, I know Elon was on Lex’s show and he’s been talking about this, uh, with, uh, I’ve also heard Jensen Huang from NVIDIA talk about this, but they’ve just built this massive, uh, data center, um, massive, massive, massive data center with NVIDIA chips that was going to be built Bigger than Ben Hur, the biggest AI data center, um, there was another story just in the last day or so that he was raising up to six billion dollars to purchase another hundred thousand NVIDIA chips for the data center in Memphis.

[00:13:31] CR: Um, And there’s this rumor that something really bad has happened. Something’s not working with the, with the training. But I believe that this guy Aiden has got a reputation of posting a lot of shit on Twitter, so I’m not taking any of it seriously, but we’ll see. But that aside, my guess, knowing how brutal Elon can be, did you see the emails that came out over the

[00:13:58] SS: No, you better, you

[00:13:59] SS: better give them to me.

[00:14:01] CR: Emails were released in the

[00:14:03] CR: last 48, 72 hours. From 2017, there were emails from Ilya Sutskever and Greg at OpenAI to Sam and Elon in 2017. They were, so Elon was still involved with OpenAI. There were management meetings happening around funding and executive structure and shareholding moving forwards.

[00:14:29] CR: And Ilya and Greg sent an email. together to Sam and Elon talking about concerns that they had about Elon’s position and Sam’s position about the company moving forwards. And basically the insinuation in the emails was that Ilya and Greg believed that Elon wanted to have dictatorial control over the company and they weren’t sure that was in the world’s best interests if OpenAI developed AGI. They were also concerned about Sam’s motivations as well for running the company and AGI etc etc. They also said a lot of nice stuff about Sam in it, and the email was very diplomatically worded, it was like, listen, we’ve been scared to bring this up, but we feel like we have to bring this up, or we’ll regret it later on, we have to have an open, transparent relationship with you guys if this is gonna go forwards, and they put their position there.

[00:15:32] CR: And it was very, very carefully worded, very diplomatic. Elon’s reply was basically, fuck you guys, deals off. Literally two lines. And then,

[00:15:43] SS: fuck yourselves. Do you want me to say that again?

[00:15:46] SS: Go

[00:15:47] SS: fuck yourselves.

[00:15:49] CR: and the timestamp on his email was like 10 minutes after the timestamp on theirs. Then he sent another one an hour later, which basically said, just to be clear, This isn’t an attempt to negotiate for my current, my former position. That deal is now completely off the table, deals over, everything’s off.

[00:16:08] CR: And he left OpenAI a couple of months later, completely severed his relationship. So that’s the kind of Elon slash. OpenAI relationship, and it’s never recovered from that. It’s basically, I’m going to take my bat, my ball, and my money, and you guys can get fucked. And I’m going to build, and I’m going to build a competitor inside of Tesla, Slash, now, XAI, wherever that sits. So, here’s my take on what could go down. I think Elon is out to destroy OpenAI. And Google. One of the things that came out in this email thread was that Elon’s concern when he created OpenAI was that Demis Hassabis at DeepMind Google was going to end up running all of AGI and he didn’t think that was going to be good for the planet.

[00:16:59] CR: So I think Elon is going to do everything he can do to make sure that he wins the AI race, either by hobbling OpenAI and or Google and or Microsoft’s. and Anthropic’s efforts through regulatory hurdles that they’ll be able to put in place. Keep in mind too that with, Trump now has no guardrails whatsoever.

[00:17:30] CR: He controls the, all three branches of, of the exec, executive, right? Uh, all three branches of government. The White House, Congress, the Supreme Court. He’s got everyone terrified. He can do anything that he wants, pretty much. He doesn’t give a shit about the rule of law. He doesn’t give a shit about tradition.

[00:17:50] CR: And neither does Elon, for that matter. So they can throw any hurdles that Elon wants at OpenAI and the rest of them.

[00:18:02] SS: So I agree with that,

[00:18:03] SS: but I just don’t see what you

[00:18:05] SS: can do in

[00:18:07] CR: oh, he owns, he, he ends up owning OpenAI, is what he can do.

[00:18:12] SS: Okay.

[00:18:13] SS: All

[00:18:13] CR: It’s okay, guys, I can, I can

[00:18:16] CR: either throw so many regulatory hurdles at you that you’ll never ship another fucking product or I take you over and all the regulatory hurdles go away, Sam can fuck off, I now run OpenAI, I bring

[00:18:32] SS: we’re dealing with, but we’re not dealing with open AI, nice little startup. We’re dealing with. Two of the other most powerful organizations in the world. So you’re dealing with Microsoft, you’re dealing with Alphabet, you’re dealing with

[00:18:49] SS: Amazon. Well, like

[00:18:52] SS: I still, I, okay. If he could, how do you just,

[00:18:55] CR: in the, in the Trump administration?

[00:18:58] SS: sorry,

[00:18:59] CR: How many of those have an official

[00:19:01] SS: you’re right. Well, the only way I see them catching up. Is the

[00:19:06] SS: takeover, because it’s certainly not going to do it with

[00:19:07] SS: product.

[00:19:09] CR: Well, I don’t know. I mean, again, it depends on this data center. Like, we know that OpenAI have been struggling to ramp up their data centers as quickly as they want, partly, I think, because Elon has bought all of the Nvidia chips. Um, you know, it, it, it depends on whether or not they actually have problems in their data center, how quickly they can ramp up all of their stuff, because at the end of the day, I mean, yes, there’s a certain level of expertise with training and your RAG methods and all that kind of stuff, but I get the feeling right now everybody in the AI space knows what they’re doing.

[00:19:44] CR: Everyone knows what everyone else is pretty much doing. Google, Anthropic, OpenAI, Microsoft, they all know the basic play here. It’s just who can throw the most amount of money at the biggest data centers. There’s, you know, a little bit of fine tuning and tweaking for the algorithmic approach to this, but really it’s just Who can buy the most amount of Nvidia chips and get them up and running as quickly as possible that’s going to win the day, to a large extent.

[00:20:13] CR: But anyway, I see Elon just throwing everything that he has at making sure that he wins, and if Man, if there’s one thing you gotta say about Elon,

[00:20:22] SS: Yeah, I agree with that. He’s very good at winning. He’s very good at taking over companies that he didn’t found. And taking all the credit that kind of goes with it. Uh, and he’s good at, no he is, he’s done that. And he’s very good at that. And there’s a chance that He could do, I just think that it’s not going to be that easy.

[00:20:42] SS: And if he does try and do that, you’re going to have pretty significant court cases. But as you say, it could go all the way up to the Supreme Court on, on certain, uh, certain things. If anything, Elon could use antitrust to his advantage. Advantage. We know that there’s a multitude of court cases against all big tech.

[00:21:03] SS: Lena Connan and crew and also in the European Union. If there was something that Elon could do quite stealthily is that he could claim that he’s not part of big tech. In that traditional sense, and if I was to, you know, think about a playbook that he could use to get control of some of these companies, is getting to Trump’s ear that it’s dangerous to have Google, Microsoft, and Amazon, already the world’s biggest technology companies, controlling AI, and that should be separate, uh, separation of state, and they should be spun off, And in some way he could get himself involved in that spinoff and take a different form of control.

[00:21:45] SS: He could also say, I’m the only one that has real manufacturing, which has large manufacturing bases in America. And if I have access to the AI and put that within Tesla, we could also use that with Ford and GM and open up robotics and manufacturing back in this country and feed it into humanoid robots, so there’s a play there.

[00:22:06] SS: And that, that would be a plausible trajectory. For Musk to gain control of AI by trying to take it out of the hands of corporations, which already have too much power and use an America first kind of manufacturing regime and

[00:22:25] SS: not giving big tech too much power.

[00:22:26] SS: That could be a smart way to do it.

[00:22:28] CR: And I’ll build your robot fascist

[00:22:30] CR: armies to make sure that, uh, you, uh, remain in power forever.

[00:22:34] SS: Underrated, universal soldier,

[00:22:38] CR: Mhmm.

[00:22:39] CR: Mhmm. Mhmm.

[00:22:41] SS: army is a great name for a punk rock.

[00:22:44] SS: album. And I know we’re on a good podcast when we come up with names for punk rock albums, Robot Fascist Army.

[00:22:52] CR: Mhmm. Mhmm.

[00:22:53] SS: And maybe we can get Gary Neumann to do some of the first songs

[00:23:00] SS: with an industrial punk kind of overlay.

[00:23:02] CR: early 80s Gary Neumann, man, it’s good shit. Um, look, I firmly believe that, um, Trump is gonna try and position himself so he never loses power, uh, as a result of this, because he can’t afford to lose power. He nearly went to jail the last time he lost power,

[00:23:22] SS: And you would think that his megalomania proclivities would have only increased now that he got back in with A Told Ya So. And I would imagine that he’s Even looser with his executive orders and pushing really hard. And this sounds crazy. This is gonna sound so crazy. I really worry about Trump having his finger on the red buttons.

[00:23:46] SS: But I’m kind of interested to see what he could do to Shake and break America. I think that’s probably why he got voted in. I wouldn’t have voted for him because I just think he’s a pretty scary dude and not thoughtful. And you need a thoughtful person that role. I don’t know.

[00:24:07] SS: Your thoughts, Cameron, you’re

[00:24:08] SS: more politically.

[00:24:11] CR: I did a two

[00:24:12] CR: hour show on it last week, man, I’m

[00:24:14] SS: I’ll tune into that. I’ve got a four hour plane ride tonight. So that’s my listening on the

[00:24:18] SS: plane ride.

[00:24:19] CR: Yeah, look, I think it’s a very, very bad time for America and for the world, um, on that respect. I think it’s just going to be a complete mess over there. I’m about to start a series on fascism on my bullshit filter show to sort of explain where this fits in to the history of fascism and the modern form of, like, fascism 20th century was very much, uh, shaped by the inter war era.

[00:24:47] CR: Period. And you had a lot of mostly young men who were rootless. Um, they’d lost friends and family and meaning and purpose, and they’d been

[00:24:57] SS: And we have that now.

[00:24:59] CR: different sort of thing. But yes, and there was an article in the New York Times over the weekend about social media and its contribution to loneliness, young men, uh, all people, but a lot of young men who are lonely, social media has sort of disrupted, uh, even further their ability to make.

[00:25:19] CR: social con social, um, connections over the last 10 years. Anyway, yeah, look, it’s, it’s a very, very dangerous period that we’re moving into, but with a lot of commonalities from the interwar period, a lot of economic inequality, a lot of people feeling betrayed, a lot of people feeling ripped off, and for genuine reasons, in America,

[00:25:41] SS: I agree. I

[00:25:42] CR: has gone overseas, blue collar working

[00:25:45] CR: classes, people are doing it tough, they’re angry, and they’re right to be angry.

[00:25:49] CR: They’re angry at Washington and the big political parties and with good reason. But if they think, born with a silver spoon in his mouth, Trump, who’s driven many, many businesses into bankruptcy and fucked the economy the last time he was president, but they don’t know that because they don’t understand

[00:26:06] CR: economics.

[00:26:07] SS: Yeah, he’s, he’s a, he’s a, he’s a classic confidence man, really, in, in, in, in the greatest sense of the word, he’s, he’s a, he’s a confidence man in, in, in, in every sense of the word, in terms of the businesses that he’s had, he’s basically an economic failure. Uh, if you had invested the wealth he inherited in S& P 500 index, he would be more well off than he is now.

[00:26:28] SS: He’s probably not nearly as well off. As he makes out, he’s been broke. He’s had a number of failed dodgy businesses. He’s just a really dodgy guy. He’s, he’s a monorail man. He is taking the monorail to Springfield, and Springfield had the monorail and then they saw it in a monorail and they’re back and they bought the monorail a second time around in Springfield.

[00:26:49] SS: Like seriously, Trump

[00:26:51] SS: is the

[00:26:52] SS: monorail,

[00:26:53] CR: He’s a classic con man. And anyway, getting back to Musk and OpenAI. Um, I think it’s, I think it’s going to be a really interesting period. And I’m in two minds about it. I think I wouldn’t trust either of the big administrations to manage this next five years as we move into AGI. Uh, but with Elon there, I think he will actually, if he stays in good stead with the Trump administration, will push it in the right direction, but it will be in his direction.

[00:27:29] SS: I think. I think he has good intentions for a GI in terms of humanity, but I think he has. A malintent in that he wants to have absolute and financial control within that. So it’s kind of weird. There’s this dichotomy of him wanting power control and all of those things. But I do think that he does have, and maybe I’ve been sold as well, uh, humanity’s interest in terms of AGI and multi planetary species.

[00:28:00] SS: They seem somewhat altruistic, but he does want power and control while he provides.

[00:28:07] CR: mmm,

[00:28:08] SS: Is, is my sense. Uh, okay. But Big Tech, I think. Strategically, they need to be, have an America First viewpoint. If they appeal to Trump’s viewpoint on National First, uh, the move towards de globalization, bringing manufacturing and robotics back home, making sure you win the AI race.

[00:28:34] SS: If they appeal to that proclivity, they’ll, they’ll do pretty well and probably won’t be split up. with antitrust. And I think the biggest issue is going to be how Musk tries to move those chess pieces to gain more control and power over AI

[00:28:50] SS: himself, as we’ve discussed.

[00:28:53] CR: yeah. Bottom line is, I think Musk will be, slow everyone else down until he can catch up. And or take over what they’re doing, but we’ll see how it plays out. Speaking of open

[00:29:06] SS: AI, yeah, let’s keep going because I’ve

[00:29:07] SS: got some stuff on that.

[00:29:09] CR: well, there’s a rumor that’s just come out today. Uh, again, rumors on X, so take it or leave it. But, uh, rumor is that the O1 preview ends next week, that the results have been good and they’re getting ready for the full. launch. Um, rumors are also that five members of the team left due to disagreements over readiness.

[00:29:37] CR: But, uh, It looks like we’re going to get full 01 and what that means, how that compares to the quote unquote GPT 5, it’s still not very clear to me. I, I don’t use 01 much. I did use it a bit for coding when it came out, but I found that Claude, 3. 5 Sonnet for coding right now, and I’ll tell you about one of my coding projects a little bit later, my recent ones, but Claude is just killing it with coding right now, just killing it.

[00:30:13] CR: Far better experience than O1 for me, but, um, yeah, we may be getting a full O1 launch in the

[00:30:22] SS: I’m still using, O1 is really good for, for reasoning and thought patterns and, and that memory enhancement. I’m finding it’s really good for that when I’m having an elongated bunch of work I’m doing with the AI. Um, I’m still using 4. 0 at the moment. I still find that’s the best when I ask it to create things it can’t do.

[00:30:42] SS: One of my favorite things is when it says I can’t do that, I’m like, can you write some code so that you can do that and give me a client to do the thing? So my view is that it can already do anything because whatever it can’t do, I ask it to teach itself how to do it.

[00:30:58] CR: Right.

[00:30:58] SS: Uh, one of the things that, uh, I’m finding incredible at the moment, and I, I haven’t used Google in more than a week. Because lately since, and I don’t know when the update happened, but going to live web while you’re in ChatGPT is now extraordinary. And I’ll ask it, I’ll say, I want you to combine what you’ve got in your database and go to the web to find the latest live information on X, whatever I’m working on. And it’ll give me that information.

[00:31:29] CR: Mm mm-Hmm.

[00:31:30] SS: I’m just finding the difference that I’m seeing, and this for me feels like the next paradigm. of search, and I guess we’re moving away from search to AI, is give me an answer, don’t give me options. It gives me answers, And it will flag where it got it from, reputable sources, and no doubt it’s using Bing in the background, so Bing is back baby, it’s made the comeback.

[00:31:53] SS: A really stealth back ending of Bing inside to chat GPT by OpenAI and Microsoft, really smart play. finding live web with AI on ChatGPT, I’m finding that’s so great. I was doing an investment portfolio for my daughter, uh, and so one of the things that I like to do with my kids to teach them about investing is you don’t start with investing, you start with what they like. And I did this with both of them three years ago. I said, I want you to write down your favorite products or services. And I just wrote a list. The best companies were in that list. I’m like, who makes those? And I told them the companies and then you give them 10, 000, just a number. It doesn’t have to be real money.

[00:32:37] SS: All right. Allocate these around. And I was just updating my daughter’s portfolio because she changed her mind on some of the things that she wants. in her portfolio and she gave me so many great updates. I went on to ChatGPT 4, asked her to download a spreadsheet with live feeds to the web and do some code so that we can update it at all points.

[00:32:58] SS: Um, sits in a Google Doc with a little macro that will pull the live prices. I just did that in ChatGPT. I didn’t have to ask or go anywhere or code anything and it gives the live updates. All of a sudden I don’t have to go to Google and find, like Google has so many SERPs, the search engine, um, panels and now I can just get that stuff and not go to Google.

[00:33:23] SS: I did some homework on it and research hard to get the exact numbers, but research says anywhere where between 5% and 12% of Google searches are now in chat, GPT

[00:33:36] SS: and open ai. I dunno what, which is massive. Five to 12 percent

[00:33:44] CR: mm mm-Hmm.

[00:33:45] SS: right now also has expanded the work portfolio of what you do. And there’s also some, some risk now because what it does is in a stealthy way, it kind of makes the Microsoft suite of products, Microsoft Office, more compelling and live now because it integrates with the live web.

[00:34:05] SS: So it’s really interesting to see that open AI can really eat into

[00:34:12] SS: search.

[00:34:15] CR: Well, I know that Google is also obviously, uh, integrating their own search results into, or their own AI results into their search. They’re trying to, you know, back end around that.

[00:34:30] SS: Yeah, they are. But I think that. I’ve seen some statistics on data on, uh, the usage of OpenAI and ChatGPT versus the other brands. And it’s, it’s, it’s kind of like Google versus AltaVista.

[00:34:45] CR: hmm,

[00:34:47] SS: it’ll be really interesting to see how important brands are in people’s minds from a tech perspective. Because technology has always had this idea that the utility is always more important than the brand.

[00:35:00] SS: And I think we know that that’s true. And if a product has exceptional utility, the brand grows underneath that utility. But it does make me wonder if people’s mindset now that they had their first experience with open AI, it’s still probably a bit better than the others in my view, in most things on average.

[00:35:18] SS: And I think all of the reports show that at this point is Google just become that old thing and we don’t use that now. And we gravitate across because we’re talking about the large majority of the people. population who aren’t analyzing use case like we are. And they might just go, Oh, well, I want an AI for this and to integrate the web and AI.

[00:35:37] SS: I just don’t use Google for that. Even if Google builds that capability because it’s sort of second or third, you know, first to mind, first to market and you get that transition of consumer behavior across, it will be a really interesting use case. And I don’t think we’ll have to wait long, couple of years to see whether or not Google starts to decline because it’s seen as a search.

[00:35:58] SS: And I don’t want. Answers. I want

[00:36:01] SS: one answer. I don’t want options.

[00:36:04] CR: My sense is a little bit different to that. It gets back to the Apple intelligence conversation that we had a while

[00:36:11] SS: We need to

[00:36:11] SS: have that again.

[00:36:13] CR: I think again, depending on all these other factors, like how Elon, um, changes the game over there, I’ve always felt that The people who actively use AI products today is a very, very small percentage of the population.

[00:36:33] CR: And, uh, so therefore the people that have got any sort of brand loyalty to OpenAI, as I do, despite the fact that I use Claude for all my programming, um, It’s very, very small. And at some point over the next couple of years, AI won’t be a category. It’ll just be part of the built in functionality to whatever your device is.

[00:37:03] CR: Apple will use it with Siri. It’ll, people who don’t use AI will just keep saying, Hey Siri, can you do X for me? Or Siri will say, Hey, Steve, I noticed that you’re trying to do X. Would you like me to help you with that? And that will just become how you integrate with AI. And if it’s on an Android device, it’ll be Google’s option.

[00:37:22] CR: If it’s on an Apple device, it’ll be Apple’s option. And OpenAI and Microsoft will be out in the fringes unless A, they come out with their own device, and I know Sam’s been talking about doing that with Johnny Ive, uh, or B, uh, they managed to shut up for fuck’s sake, Siri. They managed to

[00:37:48] SS: me you were nice to your

[00:37:49] SS: robots.

[00:37:51] CR: except Siri. Yeah, I’m nice to all the good ones, Siri can fuck right off. Um, or, they managed to do something that is so incredibly compelling and so far ahead of the game that they do get everybody, even the laggards. And it’s not even the laggards, it’s mainstream. The mainstream people. Using it. You know, I still ask people all the time, um, are you using OpenAI, are you using AI for anything?

[00:38:19] CR: And they’re like, nah, haven’t, haven’t even touched it, haven’t even looked at it, like just, shh, nah, it’s not even on people’s radars. They’ve, they’ve heard about it, but they haven’t even looked at it yet, which, um, Still blows my mind. I think the device manufacturers that own their own operating systems will integrate it in, and from all intent, for the stuff that the majority of people want to use AI for in the next couple of years, it’ll just be seamless.

[00:38:45] CR: Built in to the background and they won’t even know that they’re using AI. It’ll just be, well, this is what Alexa does. This is what Siri does. This is what, whatever Google’s version. What’s Google’s version called? I don’t even remember.

[00:39:01] SS: Gemini.

[00:39:03] CR: No, No, On the, on the,

[00:39:05] CR: Uh, operating system right now. If you ask, if you ask

[00:39:08] CR: it

[00:39:08] SS: know. I don’t I don’t,

[00:39:10] CR: Yeah. Okay.

[00:39:12] SS: know.

[00:39:12] CR: Hmm. I think it’s just, Hey Google, right? You just say, Hey Google, and it does stuff for you. I think it’s just that, if you have like one of those, like, little devices, little speakers in your, sitting in your house. We used to have one. A Nest! Is that what they call it? A Google Nest?

[00:39:29] SS: Yeah. Google Home,

[00:39:29] CR: to have

[00:39:30] SS: Google Home.

[00:39:31] SS: Just, Hey Google. I think it’s

[00:39:32] SS: just, Hey Google.

[00:39:33] SS: pretty much.

[00:39:33] CR: That’s, that’s what I said. Yeah, it’s just,

[00:39:35] CR: hey Google. I, I think that’ll be the way that most people interface with their AI. It’ll just be built in

[00:39:43] SS: Yeah.

[00:39:46] SS: Potentially.

[00:39:48] SS: Yeah, I probably will. That’ll be your personal AI. I just had a look that apparently the traffic is 180 million per

[00:39:55] SS: month of unique

[00:39:57] SS: users, ChatGPT, and

[00:40:02] CR: That sounds

[00:40:02] SS: that was, that was based on

[00:40:04] SS: Semrush,

[00:40:05] CR: Yeah, right.

[00:40:07] SS: No, no, let me, no, sorry, more than that now, 207 million, according to November 2024, which is pretty small, Google something like 3.

[00:40:16] SS: 5 billion. But if you look at, but if you look at that, if you’re getting 5 percent of search, or 12 percent of search,

[00:40:25] SS: you’re eating it.

[00:40:26] CR: yes.

[00:40:28] SS: It’s

[00:40:28] CR: how many people,

[00:40:29] SS: eating. So it’s a clear

[00:40:31] SS: substitute.

[00:40:33] CR: I mean, to be fair though, I’m not sure how many people are still, are already using it as search. More and more will, of those existing users. I, like you, now use it, but it’s only been in the last, you know, week or two since the live web stuff

[00:40:47] SS: Yeah, since the live web, that’s what I’m saying. This is the moment. This is the moment. And I’ve told so many people, and I’ve shown, I’ve demoed it to a few people. Like I did a talk for the CEO Institute, uh, last week, and I did a couple of live demos of talking to it,

[00:41:03] CR: Mm.

[00:41:03] SS: and, this is an interesting one for listeners.

[00:41:06] SS: It’s easy to think that others in positions of power in life know more than you, and I can promise you they don’t. And that’s not to say that they’re not intelligent or haven’t earned their position, but they are so in their world doing their thing. I had a multitude of companies from logistics, manufacturing, finance, all in this room.

[00:41:28] SS: It was a board presentation to a bunch of CEOs running. Companies had to be worth more than a billion dollars, right?

[00:41:33] CR: Mm.

[00:41:34] SS: So you know, serious executives. they’re just so busy managing their business and their people. They’re not across tech the way that you would be. There’s this really big lag. And I showed them how ChatGPT can go live to web.

[00:41:48] SS: I showed them how you can speak to it and have a conversation about an issue. And, uh, and, and even live video feeds and analyze this data. They, they hadn’t used it. They hadn’t, you know, the lag between capability. And people using it and understanding it is where opportunity lives. And right now in the last couple of weeks, since we’ve gone to live web with ChatGPT, and if people are using 5 to 12 percent of its use case with search, you’d have to say it’s, and there’s only 207 million people on it versus Google at 3.

[00:42:19] SS: 5 billion, it’s going to eat it. It’s going to eat it real big as soon as people find out, because we don’t want a bunch of answers or blue links to go and click and do another five or six Pieces of transaction. I just want a singular transaction with a singular answer from a reputable source and then get it to manipulate the data on the screen as opposed to just getting served up something and I just get the ingredients and I’ve got to cook the dish.

[00:42:43] SS: It doesn’t just give you the ingredients, it cooks

[00:42:45] SS: the dish up for you as well.

[00:42:48] CR: But we should pull those numbers back substantially because the search functionality is currently only available to ChatGPT Plus subscribers and team users. They’re rolling it out to Enterprise and EDU in the next few weeks, and then they say they’ll roll it out to all free users over the coming months,

[00:43:12] SS: It’s going to be extraordinary because that, that will be disseminated really quickly first in companies, people working in jobs and then they’re going to come home and talk to their kids and, and it’s, it’s, it’s, I think this is a really seminal moment. Gee, I’m gonna say it could be a Kodak moment for Google.

[00:43:29] SS: Don’t forget the beauty that Kodak invented all of the technology that put them out of business. I mean, and here we are. Your history is

[00:43:39] SS: certainly rhyming, if not repeating.

[00:43:43] CR: Yeah, although they say they’re rolling it out in the next coming months, which we know from experience with OpenAI can mean any time in the next year, and in the

[00:43:52] SS: Or tomorrow, of course, because sometimes they just bring it

[00:43:54] SS: forward.

[00:43:55] CR: and in the next coming months, Elon Musk is going to be in control of

[00:43:59] SS: About that. About that, Sam. Hey, Uncle Sam. Now I’ve got Uncle Sam, because I’m in Uncle Sam’s office.

[00:44:07] CR: I am Uncle

[00:44:08] SS: it after my fake coin. I am the Dogeman of the Dogecoin. I am Uncle Sam, and goodbye Sam Altman. Elon is in town, and I’m taking OpenAI

[00:44:18] SS: back.

[00:44:19] CR: Yeah. Yeah. Look, um, well, so we’ll see how that all plays out. Um, but let’s go back a step, Steve. Uh, we normally start the show by talking about things that we’ve done recently. Um, tell me about what you’ve done with new tech or, or AI, uh, since we last spoke that

[00:44:39] SS: I’m really Extraordinarily interested in using OpenAI. I’m going to say almost as like a desktop partner now. So now that it’s got web capability, I’m building things inside it. I’m doing my documents inside it. Uh, whether it’s a PowerPoint, whether it’s a presentation, whether it’s writing some code to build something that it can’t do, uh, adding in logos, visuals, giving it bunches of instructions and asking it to put things together for me and then just download them straight to my desktop.

[00:45:12] SS: That’s how I’m using it now. And I’ve only started doing that since it’s had live web integrations because I need to get information and data that’s live. So I’m doing that and adding its capability to build things based on instructions and put three or four ingredients together and to cook me up a recipe of what I want.

[00:45:30] SS: It kind of reminds me of the old IFTT, If This Then That protocol, the IFT, which was a really solid idea. It does that really well now. And so I’ve done a number of Presentation and, and, uh, work tools, you know, creating work tools that have given me really good results. So that’s been the biggest tech usage that I’ve done.

[00:45:54] SS: I’ve also been asking it to troll Google maps to find things for me. One thing I did for a client that I have. I was developing a leads list of manufacturers that are big enough to have electricians. I work for a really big electrical wholesaling company. They’re about a 700 million firm, um, who wholesale electrical goods and solar panels and all that kind of stuff.

[00:46:16] SS: Uh, and they’ve got 113 branches and I just got it to do some real basic stuff that would just be a bit laborious without an AI. I asked it to give me, uh, 10km of radiuses of manufacturing outlets. And hospitals, and uh, educational institutions, things that are big enough. To have in house electricians, uh, things that have been opened within the last six to 12 months to use Google search and give me parameters.

[00:46:46] SS: And it just gave me lists and then I overlaid it and gave my logins for LinkedIn to go in and find the people who have those roles and then get the phone numbers. And I just got these beautiful leads list. And for each branch, I got about

[00:47:00] SS: somewhere between 60 and 80

[00:47:01] SS: leads.

[00:47:03] CR: How did you get it to

[00:47:04] CR: log into LinkedIn

[00:47:05] SS: So I had a window open and I put in the data from window. I didn’t get it to log in. I did a search on that and then dumped that data in there and got it to troll through all of the click throughs rather than me doing it and looking for the data and the patterns. But it would be great actually, that would be actually, that would be super if they, if you could use your logins with

[00:47:34] SS: it so that it could do grunt

[00:47:35] SS: work with

[00:47:37] CR: Well, you can, and I do

[00:47:39] SS: please tell,

[00:47:42] CR: So here’s my story from the last couple of weeks. Um, you know, I run the QAV podcast and I run a bunch of

[00:47:47] SS: super nerdy. We’re getting deep and nerdy on

[00:47:49] SS: this now, today.

[00:47:51] CR: I run a bunch of, uh, portfolios on that. There’s about a hundred stocks in the portfolios that I manage. And one of the problems that I’ve had in the last couple of months is one or two of those companies were acquired and delisted.

[00:48:07] CR: But I didn’t find out about that for a week or two after they’d been delisted because I don’t have time to read the news feeds for a hundred different companies about what’s happening with them and all that kind of stuff. So I, I, I was trying to figure out a solution for this. And, um, what I came up with a week ago was this realization that, I could go into Google News Alerts, which I’ve been using for 20 years, and I could create news alerts around the stock codes for each of these companies, ASX colon BHP, ASX colon FNG, whatever it is, and it would produce, it would follow the news and give me news alerts.

[00:48:53] CR: But, I don’t know. I didn’t, usually you get those as an email, and I didn’t want to get hundreds and hundreds of emails every day that I had to troll through. Then while I was in Google News Alerts, I saw that you could create it as an RSS feed instead of an email, and I thought, well that’s interesting, I could create them and drop them into my RSS reader, but still I’m going to get hundreds and hundreds of emails.

[00:49:16] CR: News stories every day and there’s always lots of duplications of those because five sites will carry basically the same story or the same press release and there’s just a lot of content to have to go through looking for the important stuff. And I didn’t want to have to manually create a hundred, uh, you know, uh, Google News Alerts and copy the RSS feeds and all that kind of shit.

[00:49:42] CR: So I had this idea. I wonder if I can write a script. that will log into Google News Alerts for me and create those RSS feeds and then save them all into an OPML file, which for people who don’t know what that is, it’s basically a format to collect a whole bunch of RSS feeds. So, I wrote a script using Claude to do that and basically it opens a browser session using a Python tool called Selenium, S E L E N I U M.

[00:50:15] CR: Selenium will run a browser session for you and you can give it your login details and it’ll log

[00:50:21] SS: okay.

[00:50:22] CR: You put it in the script, so it’ll log in to Google for me and then it will, um, just do whatever I need it to do in the background. Um And so I created that and it, it, it, I gave it a, um, I copied and pasted all of my stock codes from a spreadsheet, dropped it into the script, and it just created all of that, that OPML file from all the RSS feeds for me.

[00:50:49] CR: But then I was still thinking, I don’t want to have to read all these fucking stories every day. So then I had this bright idea, why don’t I just write an app? That analyzes all of the news stories for me. So the next step was to get Claude to write a script that every day downloads all of those news stories, then sends them to ChatGPT using the OpenAI API, and then it reads all of the stories and prioritizes them for me based on importance.

[00:51:23] CR: Well, first of all, it removes all the duplicate stories. So we can analyze them and go, okay, well, these are all duplicates of that one. So let’s just get rid of all of these and keep this one story. Then it will analyze them for importance based on a set of criteria that I’ve given it, which is like anything that mentions an acquisition or a change to the CEO status or the CFO status, or it mentions a merger or it mentions a,

[00:51:50] SS: So you’re asking it

[00:51:51] SS: what to

[00:51:52] CR: or downgrade.

[00:51:53] CR: Yes.

[00:51:55] SS: So essentially, you’ve created, you’ve coded an agent with a specific end goal in mind, which leads us into, you know, where we’re going. So you’ve built an

[00:52:06] SS: agent.

[00:52:09] CR: I’ve built an

[00:52:09] CR: agent and the bottom, the end point is every time I run this script, it writes a report for me. Which categorize, it scores all of the news stories from, uh, from 10 down to 1.

[00:52:23] SS: Beautiful.

[00:52:24] CR: Important

[00:52:25] CR: down to very low, high importance down to low importance. And I can just read those then and see, okay, here are the highly important stories each day.

[00:52:32] CR: And it basically analyzes all of the news for a hundred companies for me. Tells me what to pay attention to and what to ignore. But the, the key thing for me, the turning point in that whole process was realizing Hold on, I can just code my own. It’s this build your own mentality that my brain has, doesn’t go to first yet, but it was just a brain fart in the middle of the night.

[00:52:54] CR: Holy shit. Why am I trying to do all of it? Why don’t I just build my own? Just tell it to build something for me. That’ll do exactly what I want. And then it did it, you know, it was a little bit, it took me probably an

[00:53:06] SS: This is, you know, this is so

[00:53:07] CR: but it just did it.

[00:53:08] SS: This is so important for a couple of reasons. And why don’t we just talk about the fact that on the next news, one of the news pieces we had was that OpenAI is planning to launch an agent

[00:53:20] SS: early next year. Right?

[00:53:23] CR: rumor.

[00:53:24] SS: Yeah. And, and what you’ve just described is an agent that you’ve built.

[00:53:29] SS: For me, this is important for a couple of reasons. Is that the mindset that you have to, why don’t I just?

[00:53:36] CR: Mm

[00:53:37] SS: Which we all can do now and I did a far less complex version of that with the finding leads and prospects for a business. That why don’t I just thing with agents is actually going to be potentially one of the most important things.

[00:53:55] SS: All of us doing our work, certainly white collar work, is putting together pieces of the puzzle that would never be arranged until you arrived. Because you have certain needs and your ability to direct an agent with AI capabilities to organize the digital factors of production and present them back to you in a certain way upon your needs is actually a really important and new

[00:54:21] SS: type of creative skill that we need

[00:54:23] SS: to develop.

[00:54:25] CR: Yeah, and, and, like, that particular app that I built, probably no one on the planet has that exact same need

[00:54:31] SS: that’s the point. And that’s the exact point is that everyone keeps saying, well, what will we do? Well, we all have really different needs based on our geography, based on our, uh, health, based on where we live, based on what our kids needs are, based on our finances, based on where we work. And so all of us are going to be creating all of these unique agents based on what our needs are.

[00:54:57] SS: Personally, and from a work and a financial and health perspective, and our job is going to be literally working with the AIs. To build these agents, but we’ll probably be doing it more verbally than building some of those pieces or asking it to do the code like you and I have and go to external places.

[00:55:15] SS: And that’s where the integration of Apple AI, if they get it right, where it can log into certain things. And if you have the right trust and security protocols around it, uh, all of a sudden we all develop these amazing superpowers.

[00:55:30] CR: Yeah, it’s, uh, you know, I just did a podcast this morning, um, to commemorate my 20 years of podcasting, which

[00:55:36] SS: Congratulations, by the way, mate, you’re the OG

[00:55:38] CR: Thanks, man.

[00:55:39] SS: That’s how we met.

[00:55:40] CR: but one of the OGs. OG in Australia, but there are other OGs.

[00:55:45] SS: no, you’re the

[00:55:45] SS: OG. I don’t care what anyone says, mate. You are the OG and you reached out to me with an email from the podcast network and I was stimulated. I was like, I’m going on a podcast. I was very

[00:55:56] SS: excited.

[00:55:58] CR: Uh, 20 years ago this month, I did my first podcast and Ewan Spence, who was one of their first hosts on the podcast network a few months later, um, he and I did a show together, but he, he was, we were talking about the role that podcasting has played in society in the last 20 years, of course, including helping get Trump elected, um, this time around being on Joe Rogan and that sort of thing.

[00:56:20] CR: But Ewan positioned it as the democratization of Um, many to many. conversations. Like pre podcasting, if you wanted to interview somebody for an hour and put it out there as a live thing, you had to have a TV show or radio show. You could do pirate radio or that kind of thing, but the, the technical hurdles for all those things were very high or the cost hurdles were very high.

[00:56:52] CR: Podcasting came along and all of a sudden anyone could talk to anyone Pretty much no cost. You just needed a microphone and a recording device, and then you could upload it and get it to the entire world at almost no cost. Uh, so it was the democratization of, of. That kind of content. And you know, I, I talked about the fact that when I started my Napoleon show, I could teach people the history of Napoleon.

[00:57:18] CR: We did like a hundred hours of Napoleonic history. No one had ever done that. And no one ever in history had talked about Napoleon for a hundred hours in a public format like that, like we did. It was You know, probably no one gave a shit either, but it was like a turning point. My point is that was the democra 20 years ago, it was the democratization of audio content.

[00:57:41] CR: We’re talking, this is like the democratization of computer programming, of coding, of being able to write computer programs. Anyone will be able to write a computer program that will do whatever they need at that particular moment. It might be a use once app. I just need to do this thing. Once, like, when I was doing this thing, I needed to get all of these stock codes and build RSS feeds into an OPML.

[00:58:08] CR: It was a one off thing. I don’t need to do that again because it’s done. But I wrote a program that did that and then I can throw it away.

[00:58:15] SS: That’s a strong point, Cam, because what happens now is many of the things that we would like to do, we would look at The cost of doing that, and when I say cost, time, effort, potentially money, and say for the one time I’m going to use it. It’s just not worth the effort. But now with democratized AI where that can be built verbally or just by writing it down and anyone has that capability, many things that never get done all of a sudden might get done and can get done and new value can be created because it’s not too intensive for the one time effort and to then throw it away because it comes down to a efficiency thing.

[00:58:57] SS: And your point, and I say this on stage, I say, Congratulations, everyone in this room is now an AI developer, because if you can type or you can talk, you can do it, and I am not mincing my words. All you need to do is have the wherewithal and the will to try, and to just get on there and use your imagination and ask it to do the thing, and you can do it.

[00:59:16] SS: And I, I just don’t think everyone has realized how powerful that is. Like podcasting has incredible power and you were way ahead to more than 10 years ahead of everyone. And now it’s what is your favorite podcast? It’s like, what is your favorite TV show? Like that is there and deep and ensconced. And, you know, I imagine three years from now, people are saying, Oh, what AIs have you built lately?

[00:59:40] SS: What have you built? Like, what did you get your agent to do lately? Oh, I should have seen what I got my agent to do. Like, that’s going to be cool. We’re going to be saying, oh, I just got my agent to build this. It’s so, it’s so

[00:59:53] SS: amazing. And everyone’s

[00:59:55] SS: going to be excited.

[00:59:57] CR: And that’s an interesting point. So after I built this news app, it was one of those sort of light bulb moments for me. And I was like, fuck, why didn’t I think of this earlier? And what are the other things that I should have done already that I haven’t done just because I haven’t realized that I could do it?

[01:00:12] CR: And I went looking in Reddit for people talking about, here’s the app that I built this week. And I couldn’t think of anything. Find that platform. And I think that kind of needs to exist is a place where we just share ideas. It’s no point me sharing my code with you because my code is specific to me and my login and all that kind of stuff, but just the idea.

[01:00:34] CR: Hey, I built a news app. That filters the news that’s important to me and it’s, um, and, and customize, you know, one of the things that I’ve bitched about for fucking a long time with the internet is why the internet isn’t already filtering all of the news and telling me what I need to know. Like, Spotify does a pretty good job if I’ve, if, if it knows I’m a Nick Cave fan, it’ll go, Hey, Nick Cave’s got a new album out.

[01:01:01] CR: You might want to listen to it. I’m like, fuck yes. I do want to listen to that. Thank you, Spotify. But if Vince Jones is Coming to Brisbane and doing a gig? Which app is telling me, Hey, Vince, you love Vince Jones. You’ve loved Vince Jones for 40 years. You’ve got all of his albums. You’ve seen him live a hundred times.

[01:01:22] CR: Vince Jones is going to be in Brisbane next week doing a gig or a month from now. You should get a ticket and go to the gig. There’s no app that does that for me. Maybe I should build my own that says. You know, just keep an eye out for any news involving any of these artists or businesses or products that I’m interested in and just make sure that I’m aware of it.

[01:01:43] CR: You

[01:01:43] SS: could. You can also, with what you’ve done, say, here’s what I build for, uh, my investment portfolio. I’ve built this agent. Here’s a link to it. Just ask the

[01:01:56] SS: agent to re ask your

[01:01:57] SS: agent to reconfigure that

[01:02:00] CR: Yeah.

[01:02:00] SS: the things that you want. So you kind of like, it’s a little bit like your phone. You have a template and then someone reconfigures it.

[01:02:08] SS: So you can take someone else’s, uh, Software that their agent built, that they guided their agent to build. And then you say, well, I want it now for my kids’ investment portfolio. I’m gonna adapt Cameron’s one, but take these changes to Cams and add this, this, and this for me. Uh, so you will sample your agent to a friend who then reconfigures that agent for their needs.

[01:02:31] SS: It, it does make me think another thing, cam, when we move to this agent based AI environment. And you mentioned that you go to Reddit and different places to get ideas and ideas become a really important currency all over again. I do wonder if we’ll rebuild our websites, not for SEO and search engine optimization, but AI optimization.

[01:02:56] SS: And because the AIs and the agents will be trolling websites to find certain things and to pull that back in. The only difference this time is that It’s not for clicks to people come and do commerce with you. The entire shift takes the person to the AI. So they come and scrape you. It’s going to be interesting to see where the value lands in this chain.

[01:03:20] SS: If I’m extracting information from various sources, does it become extractive in a way where value gets all pushed into the AI and those Creating the ingredients to cook up the dish, get nothing.

[01:03:36] CR: Hmm.

[01:03:37] SS: That’s going to be an interesting shift.

[01:03:42] CR: Well, we’re over an hour, Steve. We should probably, unless you have something else you want to squeeze in, we should probably call it

[01:03:48] SS: I think we got into some deep stuff, but there’s some topics I think here that are on our list that there’ll be more bits on those that

[01:03:55] SS: we can reconvene

[01:03:58] SS: on.

[01:03:59] CR: But the big thing for me is what happens now that Elon’s in charge. We’ll have to wait and

[01:04:04] SS: In Charge! He’s giving him straight to the In Charge. Let’s just say he’s in the house, Ali G style.

[01:04:14] CR: Have

[01:04:15] SS: Talk to you soon, Cam.

[01:04:19] SS: That was cool because we were just fucking talking. I don’t know how it’ll go for everyone else, but

In this episode of Futuristic, Cameron and Steve debate the idea of a Universal Basic Income (UBI) amid economic shifts driven by AI and automation. They address cost reductions and market disruptions caused by automation, the future of personalized AI-driven content, and public sector roles as potential solutions for unemployment – critical conversations needed to shape a future where AI and humans coexist.

FUT 31

[00:00:00] SS: Just an ease.

[00:00:05] CR: Okay, I’m recording. Turn on my backup record. Give me a one, two, three.

[00:00:13] SS: One, two, three.

[00:00:17] CR: Welcome back to the Futuristic Sammartino episode 31. Uh, we’re recording this on the 25th of October, 2024, two weeks before the U S election, January. Um, one year before the Singularity, um, one year before Elon Musk releases RoboTaxis and RoboVans and robots to the world or two or five, depending on Elon’s timeline, just before we came to where I showed Steve the Tesla stock chart, they released their earnings today, share price.

[00:01:00] CR: Bumped 22%, their biggest day in 11 years for all of the Elon haters out there that were shitting on the RoboTaxi launch a week or so ago. Have you been Steve? How’s the future treating you these days?

[00:01:13] SS: If you’re just treating me okay, when you said one year out from RoboTaxes, I was like, I said 2015, because wasn’t that when he made the promise? This is like,

[00:01:21] SS: we’re 10 years in to coming soon. Jeez, I’ll tell you what, you’d be

[00:01:25] CR: As he himself,