Cold Takes Popular Opinions

Join us on this episode as we navigate through the intricate world of social media platforms, emphasizing the reward potential of early adoption. Uncover how being proactive and engaging strategically on these platforms can herald better outcomes. Learn why emotional attachments towards platforms can be detrimental and why attention pivoting is vital. Citing real-life company narratives - triumphs and predicaments, the episode shines a spotlight on Instagram Threads, Twitter's up-and-coming textual contender. Delve into LinkedIn's recent algorithm updates, their implications for content discovery and engagement, and address the uncertainty surrounding LinkedIn's celebratory notifications. 

Join Trevor and Ira on this episode of Cold Takes Popular Opinions as they unravel the secrets to thriving in the ever-changing world of LinkedIn. Discover the crucial elements necessary for driving traffic and visibility, while avoiding the common mistake of blindly replicating successful content strategies. Gain valuable insights on understanding your target audience to create compelling and helpful content that stands out. Dive deep into the challenges LinkedIn faces in simplifying content creation, overcoming education gaps, and streamlining the platform. Explore the identity crisis LinkedIn grapples with as it balances catering to creators while remaining a job-seeking and B2B sales platform. Uncover the struggles faced by companies and employees in maintaining control over their content and the importance of a safe and supportive environment. Delve into the impact of AI and distractions on LinkedIn's shift towards ads, hindering the creation of valuable educational content. Finally, get an insider's perspective on LinkedIn's ad campaigns, engagement levels, and the recent acquisition of Lydia. Tune in now for this insightful episode that sheds light on the challenges and potential solutions for LinkedIn's evolution as a platform.

On this enlightening episode of Cold Takes Popular Opinions, Trevor and Ira have a candidate and open conversation as they explore the challenges and triumphs faced by children with Tourette Syndrome. Gain invaluable insights into understanding the symptoms and unique difficulties associated with Tourette Syndrome.  They share and explore practical strategies for parents to support their children's education, advocating for their needs within schools. importance of communication, patience, and understanding in fostering a thriving educational environment for children with Tourette Syndrome. Help raise awareness by sharing this episode, promoting inclusivity and compassion for those living with Tourette Syndrome and related conditions.

Valuable Resources Mentioned in the Episode:

Connect with Trevor on LinkedIn:  https://www.linkedin.com/in/trevorlrobinson/

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[00:00:11] The author discusses the importance of creating content in today's AI-driven world, and how people and companies often overcomplicate the process. They suggest discussing ways to get started and what people are doing right and wrong in content creation.
[00:01:59] Creating content can be daunting, but it's important to just get started and be passionate about it, especially with the constantly changing landscape of social media. The key is to create content that stands out and gets into the newsfeed. Examples of how to launch a podcast quickly are given.
[00:05:58] Overcoming imposter syndrome is key to creating consistent content, and it's important to start creating content without putting too much pressure on oneself. Tools like Riverside make it easy to record podcasts, and there are AI tools available to simplify the editing process. Don't make excuses and start creating content today.
[00:08:50] Use Riverside to record and edit the podcast. Leverage AI by using Castmagic IO to produce transcripts, show titles, and social media content ideas in less time. Emphasize that done is better than perfect.
[00:10:51] The LinkedIn algorithm reports are pointless and can do more harm than good as they focus on a small subset of users and don't account for different audiences and variables. It's important to understand the basics of platform culture, but getting hung up on these reports can be detrimental.
[00:13:27] Reports and engagement metrics on social media can be misleading, and it's important to focus on creating consistent content that resonates with your audience and leverages your own strengths and standards. AI tools like chat and GPT can be helpful for generating ideas, but it's important to add your own spin and not rely solely on automated content.
[00:17:54] Simplify content creation by not overthinking it and focusing on getting it out to the world. Use your personal style and create content as if sharing it with a friend or family member. AI tools can help, but it's important to add a human element for authenticity.
[00:21:48] Advice for creating content: focus on what you care about, evolve your topics, share personal stories in context of the platform, and use organizational tools. Notion is recommended.
[00:25:57] Pillars don't matter, just start posting and build the muscle. Personal interests are more important. Write down ideas, choose a format, and ship it out. Feedback is important.
[00:27:54] This podcast focuses on discussing topics of interest without limiting themselves to a specific topic to attract listeners.

Speaker A [00:00:00]:

All right, IRA, welcome back to another episode. How are you, man?

Speaker B [00:00:03]:

I'm doing well, man. How are you?

Speaker A [00:00:04]:

Doing well, we got a lot to cover this week, man. I feel like this tech space is just moving at three years at the pace of like, two weeks, man.

Speaker B [00:00:12]:

They call it tech speed.

Speaker A [00:00:15]:

We got to slow it down. So I have a couple of things I want to talk about today I think people might find interesting because this is pretty relevant. And again, each of these weeks, man, we're trying to keep up with some of this stuff. I know we have some cool top topics that we want to dive into in future episodes, but yeah, the pace of this, man, is hard to keep up with things. And I want to get your opinion on a lot of this stuff. Have you heard about this new I don't know if it's a plugin, but it's with Chat GPT, the code interpreter.

Speaker B [00:00:39]:

Yeah, I saw you had sent me an article on it and I was checking it out, so just a little bit, but it's crazy stuff. Crazy stuff.

Speaker A [00:00:47]:

Yeah. So for those who aren't familiar and again, I just skimmed the article, so I'm no expert in this, and I would love to hear your interpretation of it, but essentially you'll be able now to take any kind of data, set, upload it, and then it's ultimately just going to spit out all kinds of interpretations. So for the example that they use, is somebody pulled, I believe it was a data set of all the lighthouses in the US. And they uploaded this file and in a matter of seconds, they were able to put this into charts and see where lighthouses are lighting up and get like, animations and gifs and things of that nature. So, yeah, I probably did a poor job explaining that. What's your interpretation?

Speaker B [00:01:27]:

Yeah, I mean, the thing is, with any data set, making use of the data is the key. Of course, we've talked about this in some of the past episodes, but I live a lot in the manufacturing space and dealing with different companies. And depending on where you are in there, I know there's lots of companies that have just a ton of data, and one of the biggest questions they have is I have too much data. What am I supposed to do with it? So having a tool like this to maybe try to figure out different charts and patterns and things is great. Now, with that considered, it could be jumping to conclusions, maybe, and potentially providing some trends of things that maybe don't really exist, but I guess that's true with any kind of evaluation. So I think the tool is really powerful. But how valid is information? I mean, the lighthouse example is cool, but really applying it to more general operations, I don't know. It would be interesting to see how it evolves over time.

Speaker A [00:02:28]:

Yeah, I think you have some good points there. I think the validity of it more so, I think, about things like what problems can this solve? I mean, especially in the manufacturing space, there's a ton of things, if you get the right output that you're looking for. And I think the first person I thought of was Jameson Rotts, who we had on. We'll have him back again soon. Because this is a lot of what he's doing with machine learning and the algorithms and working with companies and taking their large data sets and so forth. And so I think what he's doing is a lot more integrated in in depth. But for the general population, I think this is a good first step. Now, the thing I'm noticing with all of these tools that they're rolling out so fast, is that they are still very tech intensive, meaning you still have to understand how to use them, how to put in the custom prompts to get the output that you want, and things of that nature. What I'm actually fascinated with, though, is actually thinking at scale. I don't know what this looks like, if it's twelve months, 24 months, three years out, et cetera. But I think what's fascinating is some of the use cases of taking all of this data and having machine learning and algorithms and OpenAI use all the data to pull in to come to conclusions that could actually be beneficial to society in a good way. And I'll give you an example, is think of all the missing persons cases that are out there, right? Think of all that data if we can roll this up, these machines now, and this AI can tie those connections together, probably getting Internet access with Chat, GBT Four and so forth, and probably draw some conclusions of at least to say, hey, check out this, or here's some commonalities or correlations and so forth. That to me, is what I get excited about. This. I know you probably get excited on the manufacturing floor. I get excited just about the possibilities. I think it's going to shake up for a lot of you got families, this is going to help. But even more so, a lot of these organizations that might not have the funding traditionally to access some of these resources that could actually help them.

Speaker B [00:04:24]:

Yeah, initially, when you say that, the thing that comes to my mind is Black Mirror on Netflix and are we going a little too far?

Speaker A [00:04:33]:

I don't know.

Speaker B [00:04:34]:

Is this going to be great in the beginning and then end very cold and everything else? But you bring up a really good point and I've had a lot I appreciate that. What's that?

Speaker A [00:04:43]:

I appreciate that. I don't hear that.

Speaker B [00:04:45]:

Sorry. It was a pretty good point. Take it down to pay.

Speaker A [00:04:48]:

Okay.

Speaker B [00:04:48]:

No, it was a really good point, because when I think of whether it's a manufacturing space or I've actually been looking a lot of like the contracting space, and I've been looking at even some insurance and financial advising kind of industries and things, and there's a lot of these industries that are smaller operations, and a lot of business is smaller operations. Not everybody's frito Lay or GM or Ford, right? There's a lot of small stuff. And how do these smaller companies take advantage of these digital systems if they don't have the funding to actually go do these things? So if there's the ability to use some of these tools to generically add data to them and provide some real output, kind of like we were saying with these data sets, that could be really powerful, particularly in some areas where I would say tech has been a laggard, particularly in the contracting industries and things. I know personally, I've tried to hire a fencing contractor, I've tried to hire a concrete contractor and things and getting them to show up and letting me know when they're on their way and even paying them after the fact is sometimes a challenge. And I get it, they're busy and they're doing their craft and that's where they want to focus. But there's got to be some ways to help them from a business system standpoint. Maybe some of these data points here can help pull things together not only to give them more information, but to make their business operations better. I think there's something there.

Speaker A [00:06:17]:

Yeah, I think it's unfortunate but I think that's the subset of businesses that I think could have the easiest and biggest impact on because those local services, we'll just talk about that as a market. I'm in that space and I've had a massive advantage because I've been able to leverage tech and these things and I see the low hanging fruit now. I actually think that unfortunately it will be one of the last industries to adapt and that is just a byproduct of that personality type of business owners, they're just not focused on this. They have a craft and they might hear some buzzwords and so forth, but they're content with grinding and how they have and that's all they know. And that's very similar to my dad grew up, worked at the same company, his whole career was on the printing press, tried to tell him new things and that was his Mo. He loved just what he did and there's nothing wrong with that. And so it is interesting how the tech does favor. Those are the easiest ones to solve because it's not like manufacturing where there are all these other second order consequences that you have to factor in. This is just how do we optimize and streamline your business. But again, unless they have a third party there helping them, which most of them won't and just don't, it's going to be hard for them. And I think that there'll be the late adapters. And I have another thing I want to talk about here. Then it's a good segue. So I saw this weekend so my mom's a real estate broker, so I keep her up to date on all these things as best as I can. And I saw that Zillow is rolling out and they're actually running paid ads promoting I don't know what they're calling it, zillow GPT maybe. But it's essentially I haven't looked into the back end of it, but I'm assuming it's just a plugin that they've used now. But they have this set up and they're promoting it where you can have a conversation and we chat GPT and it's going to essentially you can say, hey, I'm looking for a single family home in this area. I want this school district, and it spits out all of this. And at first glance when I talked to my mom about this, I was like, well, it's just good for you to know that this is here. I don't think it does anything that the filtering doesn't do currently. But then I started to think about it a lot more and I was like, this is going to disrupt the industry because people are going to they already search things, but the filters are kind of they're very binary. Do you want a fence, yes or no? Right? And I think this is going to open up the ability now where the value of a realtor is in listening, right? It's in listening, understanding needs, and then taking feedback and adjusting. And I think that's going to open up a whole world of possibilities here.

Speaker B [00:08:58]:

Now, I'm curious. I bought a house a couple of years ago and talking to my real estate agent. I believe there's laws that prohibit agents from talking about certain things, like they could tell you whether or not a house is in a particular school district, but maybe you could expand that question to which of these are a good school district. Well, that's not something they can necessarily talk about, at least as I understand it. And maybe that is something that a chat assistant could talk to you about. Or are there regulations that need to be placed on that for whatever reason, to say, well, hey, maybe that's bias one way or another and potentially prevent looking at home.

Speaker A [00:09:47]:

That's the overarching theme is how do you prevent the bias from coming in because you got the data, how is it interpreting it?

Speaker B [00:09:57]:

Because I think of that Bot perspective and you go, okay, I'm going to be moving to central Pennsylvania because I just got a job there. You don't know anything about the area. You're from Arizona and you're going to go, hey, I have two kids. I need a house that's going to be four bedrooms and I want it to be comfortable in a nice place and go to a good school. If those are your criteria. I think that's a hard thing for a lot of people to position because there's a lot of bias that goes into what I just said.

Speaker A [00:10:27]:

There is a lot.

Speaker B [00:10:27]:

Yeah, but realistically, that's what somebody wants to know, right? And they're going to ask their friends and family and people that are in the local area, they're going to get that information. Do they get it from a bot?

Speaker A [00:10:40]:

This is completely random, but do you think we're going to get to the point? Actually, we are going to get to the point. This might be by next week at this pace, but where you've got the internet as a whole, right? I think it'd be awesome if you had a chat GPT for your friends, right? So it goes out, you select the criteria of all your friends or it knows your social network. Then you're running these searches. You need a house or something in a neighborhood and then you can ask questions and it's going to go and pull data based on your circle of crowdsource. Scrap. Exactly. Yeah, I think that could be pretty interesting.

Speaker B [00:11:13]:

Well, so that means in this local area here, you're going to have like CD versus CV. And if you're not from this local area, it's two competing school districts right across a small river. It makes no sense, but in any ways they're both really good places. But you'll have strong bias one way or another.

Speaker A [00:11:27]:

Yeah, you will. And it's interesting. And the takeaway that I gave her was, hey, listen, mom, this is good to know. We're already rolling out a plan and we have a plan, so we're already leveraging some of these tools from a marketing perspective. But I told her, I said the number one thing that you can do, and I think this is what most businesses can do as well, is you got to get ahead of the curve. Meaning you already know the objections that are going to come, which is some people might say, well, why do I need a Realtor if I can just do this right? And in that case, the value of a broker and a Realtor is not in finding you homes. Right? It's not like sourcing in the recruiting world where you do have to have a skill to find candidates with specific skill sets and so forth. In the real estate market, it's all about having a pulse, what's coming on the market, knowing what's out there, maybe some statuses of things, things like that. But the real value does come in the relationship, making the transaction easy, stress free, seamless. And so that's what we're doubling down on is putting out tons of content around those things, using these tools to help us create that content and so forth. But I think this is really transitioning over to a key point here that we can chat about, which is we're seeing this in general now in LinkedIn is flooded with this in this AI content, right? And I think it's getting watered down and LinkedIn is not doing themselves any favors. Because I don't know if you saw, but LinkedIn is now rolling out their own AI pilot. Have you seen that?

Speaker B [00:12:56]:

No, I haven't. And I'm on LinkedIn all the time.

Speaker A [00:12:58]:

I have access to it. Some accounts do. It's basically AI that's prompting you on certain things to kind of help write content for you. So it's like asking for milestones and it's kind of prompting you. And I think they're already rolling out a feature to help you write your profile. So I don't know if you saw that one, but they have a new feature out now that's going to be I know I'm not seeing new feature outs beta. Some accounts have it, some don't. There's no rhyme or reason, I think, to why people get these things, but it's to help you write your LinkedIn profile, write your headline, things of that nature. And so when you've got a platform like LinkedIn, let's just talk about LinkedIn specifically. Here. What I'm seeing, curious to see if you're seeing the same thing, is that I would say, majority number one, there's more content being produced, but number two, a lot of the content is garbage. I'll just openly say it's garbage, it's AI created. And look, I'm not ever going to knock on someone for creating content. I don't care if it's good or if it's bad, it's all relative. The effort is all that matters to me. Where I draw the line is that Laziness and what I'm seeing is now there's people promoting, hey, you can start engaging more by leaving AI generated content or comments and so forth. And I think there's even a couple of tools that do it now. And so I think historically, LinkedIn has always had a major problem in the sense that they've never done a good job catering to creators and giving them the resources to create effectively. And so now what's happening is a third party did that chat GPT, right? And now LinkedIn is playing this, oh, we want to be in this space, and they haven't even curbed their own issues of like, it's all AI content, they're not penalizing it yet or things like that. Now they're only going to add fuel to the fire. I am incredibly curious to see where this goes.

Speaker B [00:14:46]:

Yeah, so I got a bunch of thoughts on this. So as someone who does create, particularly on LinkedIn, actually that's pretty much the only place I create that in this podcast here. I've always seen my creation on LinkedIn as more or less learning in public or just my thoughts, but it's typically been on very technical topics and these kind of things, but it's really been the crowdsource, other people's opinions on my thoughts and these things to help me, to help everybody else and to further the manufacturing space. And I actually just had this conversation with the group the other day and I have seen personally a lot more AI driven type things and it's making it more of a struggle to be on the platform. I do think it's making it easier to stand out on the platform, but.

Speaker A [00:15:34]:

It'S a great point we'll come back to.

Speaker B [00:15:36]:

Yeah, but it's honestly been a struggle recently. I've never had that problem. When you think about the creator landscape, particularly on LinkedIn, I've never been the creator on Twitter or these other tools like YouTube and whatnot. But you look at the back end of some of these things and they're awesome for creators. Like, you can plan out tweets, you can plan out videos, you can schedule stuff out. And I always looked at LinkedIn and I said, why don't we have something like that? Because I don't have to write it. I have to write it, save it somewhere else, and then copy and paste it in. If I'm going to archive or backlog any kind of content I want to put out there. There's no easy content management system. They have a little bit of stuff now, but I don't even know if it penalizes you for using that yet. They're going to go and enable all this AI stuff. I don't know. It seems like we jumped over a step just having the ability to kind of schedule some simple things, schedule some stuff out. It'll be immensely beneficial for a lot of creators that are creating good stuff.

Speaker A [00:16:43]:

Versus and I think it's actually going to deter the good creators because LinkedIn is kind of looking at as a play of, hey, let's just get more people out here and active, but they're not understanding the byproduct of you're putting out a bad quality experience for the users. And then that in turn, is going to be a turn off to people like you and myself and others who might put out content. And now I've seen the rumblings with some of the top creators that, hey, our views are down drastically and their quality of content that they were doing is good. However, their algorithms aren't smart enough to detect yet. Oh, this is AI versus this person actually has good original thoughts. So, yeah, I think you had great points there. It's going to be interesting to watch it play out where I will say that I'm putting all my all my I guess I'm doubling down. Putting all my eggs in one basket, though, is on the concept of originality.

Speaker B [00:17:35]:

And I secret sauce to Trevor. Here what's going on.

Speaker A [00:17:38]:

This is my game plan. You'll see it roll out, but it is an originality and creativity and having and finding your own voice. And I think a lot of people get caught up in saying, I have to talk about this niche, or I'm an expert in that, or, hey, LinkedIn polls are the flavor of the month, or carousels, and that's fine. You can ride the waves and trends all you want, but look at all those people that used to do the pointing videos. They just play a trending sound. They point to that, they're gone. They have no following. You don't even know who they were. They never spoke a word. They just put text on screen and pointed where I think the future is heading. And even if you look at the YouTube landscape again, a lot of content is AI driven now. So it's making creating content and the access and ability to do that so much easier. So where I actually think now that it's going to stand out and it's going to translate over to LinkedIn is more on the authenticity. And so there was a lot of rumblings that like, oh, daily Vlogging and the Vlog style is dead. It's not dead. What happened is the world shut down for a good two years, so people couldn't go out and get that content, so they were forced to create another element. Now that the world opened back up, that's going to be where the shift is trending back to, and I think it's going to carry over to LinkedIn, I think even subject matter experts, if you're in the manufacturing space, showing a day in the life going down on the floor, showing what you're working with, showing that. Man, I tried to build this demo and I completely failed. Here's what I'm doing. That kind of content AI just can't replicate, at least not yet, right? And so imagine on a newsfeed on LinkedIn, for example, when you have all this boring generated, like, no one needs tips anymore, no one needs the five tips, or here's the best ten, no one needs that. What they want is, and this is how I think individuals are going to grow their audiences and have a lasting impact, is getting back to that originality. You have to put a little effort into the content. And I think it makes it easier to create because people are more authentic with themselves. And that's the challenge. Whereas I find a lot of people I talk to and work with is that they're just scared to put themselves out there. So naturally, people just default to regurgitating and repurposing education or information. And while it's valuable, it's not really building your brand, your thoughts, how people get to know you. And some people aren't going to like you and your views and your opinions. And look, you got to grow tough skin, thick skin, whatever the saying is.

Speaker B [00:19:58]:

Yeah, as someone that's been a creator, even in something, I would say as well, the manufacturing space is a very niche space. It's not a huge space from overall landscape, but, man, there are definitely people that will call you on the carpet and I try to have conversations with those people after the fact, because you got to have thick skin, you got to take in. And frankly, one of the reasons I do a lot of this is not because I want followers or views or it's because I want to learn there's a reason that other people are saying different things, and my goal is to get those different points of view. I've been at the same company now for almost 18 years, and that's a long time and long time. There's a ton of positives to that. But honestly, there's some negatives to that too, to be blunt. And some of those negatives are I just don't have that necessarily that worldview. My view is from this company, right?

Speaker A [00:20:53]:

Yeah.

Speaker B [00:20:53]:

And I have my own opinions and thoughts and these kind of things. So this is a way that I have found to try to get those different points of view by trying to use, I would argue, more emotional intelligence, to try to bring in and see things from different perspectives and not just say that and read about it, but actually try to live it through podcasts and these video things and interacting on social media. That's really what I've tried to accomplish.

Speaker A [00:21:18]:

Through my and you do a great job of that. I think that's one of the biggest things is, like, you see the creators who are like, they know it all, and that's their point of view. And I'm guilty of that sometimes myself. And then you've got the different type that's like, hey, I'm learning. I don't understand everything. But it's a fine line because people do want the expert. They don't want someone who's just like, hey, I read this today. Yesterday it was this, right? I think we recorded an episode last week. And then again, with all this amazing technology, things tend to break. So this is another episode that gets scrapped.

Speaker B [00:21:49]:

But we should publish that one because I think at one point I just had a really weird look on my face and it was frozen.

Speaker A [00:21:55]:

I can see if I can dig that up. I'll see if I can dig it up and we'll push it out. Well, we talked about a new from LinkedIn. Speaking of LinkedIn, one of the founders, Reed Hoffman, is rolling out an app, call it I think it was Pi or Pi GPT or Pi AI or something. But the premise of it was on it was supposed to be around mental health. And I think it's a great concept. It's a little dangerous, though. But the whole premise was that you can talk to this I guess this bot will call it, and it's just supposed to be positive and like a mental health resource when you need it. And I think it's great because I think mental health in this country in general gets neglected and there's not enough emphasis on it. We, in that episode, talked about some of these risks and so forth, and I don't want to take this conversation down that path, at least not right now. But what I do think is important is that as people start to create content and leverage these things, they do have to grow thick skin. And I think the downside of social is that it's very toxic, and if you don't have that thick skin, it can eat people up. And for example, I go on Twitter and I'll leave a comment on something that I know to be true. Man, I just left one and I got ripped. People were like, you have an MBA and this is your logic? And their comment was like, you could tell these people they have the egg is their profile photo, but you just get ripped, and you have to be able to take that. You got to be able to take the if you put yourself out there, you're always going to have people. I think that's the success to creating, in my opinion, is it's not just taking the first step of getting the post out there. I think all the success or the successful creators have realized this is a learning experience. People are going to judge. People are going to leave comments. There's going to be trolls. You can't do anything about it. But that's where I think these apps, like this new Pie AI, it's needed because people get beat up online, even if they post a photo like their dog or something. You got people being like, you own a pit bull. We're just in society, and it's sad and it's a shame, but I think we're only going to see more of that now, and I think it's the sad reality.

Speaker B [00:24:13]:

Yeah, I mean, it's definitely a road we can go down. I agree with everything you just said, though. I do have a question for you, and maybe we can take this one to another podcast here, but even through this conversation, we talked about how many bots, right? How many bots are there out there now? Everybody's making a bot. Is it too much? There's a bot for seemingly everything anymore, and if there's not one now, there may be soon. Is it too much? Are we okay with talking to bots? I did one this morning, by the way. So we ordered something from Amazon and we did make a return, and it was some sort of problem. We couldn't return the product. So I had a conversation, and it was weird because it seemed like a person on the other end of the line, but it started off with saying, hey, I'm an Amazon bot. And it chatted to me even when it gave me multiple things like, hey, I'm sorry to see about your products having this issue and the end of that bubble. And then it was like, let's see if we can do something to fix this end of that bubble. Just like someone would type it or write it, and I was okay having a conversation with that bot. Trevor, I think you're okay having a conversation with that bot. But the general masses, are they okay having a conversation with a bot? Because I think even me, my head goes to the old telephone. Thing where you had to press one to get the customer service. I think it's completely different now, but I think that's a lot of people's mentality that, are we okay? Are we in bot culture now? Or where are we?

Speaker A [00:25:56]:

I think there's two spectrums to this, right? There's the companies that have bots that invest in the bots and they're amazing bots and they save time, money, amazon. Amazon. Because they invest not in the quality of the bot, they're investing in the experience on the other end. That's what they care about. And so in turn, they have to create an awesome bot before they roll it out. On the other spectrum. I've seen companies that have a little chat pop up and what they're doing is it's basically they're putting in the questions and it's basing off keyword. They'll show an answer. Personally, my take is that I've had some awesome experience with bots. I've had some terrible experiences with bots. Now, do I like chatting with them or is it too much? I look at it as a time constraint. If I can get in and get it solved quick, I would rather do that because I can multitask, I can chat with two or three bots at the same time, get it all taken care of. There's other times though, when I've been with a human and it takes way longer because they're like, well, let me look up your account. I don't enjoy those experiences, right? But to answer your question, do we have too many bots? I think it's going to phase itself out, to be honest. I think what we'll have is everyone's going to have a bot. The best ones will stand. And I think that's where the innovation will sharp happening from is those top tiers, and then everyone's going to realize either they can't support the cost of their bots or it's actually negatively impacting their company, right? And I think it's going to happen on the support side more than anything. Whereas they're going to try to save cost on customer technical support by leveraging AI. And then even though they say our data set is clean, we put all the information here, we tested it, they neglect spending and investing heavily in actually testing it from a third party to make sure that what does the end user think? Is it getting them? How long are they taking? Did they get their issue resolved? But maybe now there's actually a negative sentiment for them that they're like, I don't like this product, I want to talk to a human. So? Yeah. I don't know. I think it's certainly something to kind of watch out for over the next I would even say twelve months because I think it's going to innovate that fast.

Speaker B [00:28:06]:

It'd be funny if all of a sudden we have like a national non bot day and you're not allowed to lose any bots. We'll see what happens. Maybe the world stops spinning for a day.

Speaker A [00:28:14]:

I don't know. What I want is I just want a podcast recording app that works. That's all I want. It's not that's all I want.

Speaker B [00:28:23]:

Did this one break two times?

Speaker A [00:28:26]:

The first episode we ever shot.

Speaker B [00:28:28]:

I thought you meant this time.

Speaker A [00:28:29]:

No, this is good this time. And this is supposed to be the cream of the crop app. Yeah, but I mean, even then you're seeing these tools that I saw, an amazing tool now that somebody created with AI that goes through a podcast. And it'll actually if you use Adobe Premiere, it will actually import your multiple tracks. So, like your track and then my track, and then what it'll do is every time I'm speaking, it'll automatically split the screen or chop it there and then show yours and show mine. So it kind of takes that whole process because that's the longest part of editing. If you're doing the split screen again, though, I think people are just going to be over reliant on these and they're going to be like, oh, we've needed content. So what they should have been done two years ago, getting repurposing content, now they're going to look at this as, oh, it saves me so much time. But if everyone's doing it, it loses that mass appeal. Right. And the same thing with all these bots. If all these companies are using bots, naturally it's a selection process because the sites that aren't investing, but they think they got to be in the game, they're going to create that much of a worse experience for their brand that's going to hurt them rather than help them. And I think it's going to come back to kind of like the snail mail versus email. The companies that aren't using bots are going to stand out because there's going to be a massive advantage of saying you can talk to a human and.

Speaker B [00:29:53]:

Coming full circle all the way we were with talking about what we call them, like the local businesses and these kind of things. This could be a huge opportunity one way or another for a lot of these companies. I'm really curious, and I do wonder, with the poor implementation of bots, does it create a negative sentiment towards the whole topic until there's like a Google Type bot? I'm not saying it would be from Google, but someone that there was lots of search engines before Google. I use lots of them. And then Google came out and then it kind of like ran the show. Will that happen with bots? I don't know. Be kind of curious to find out.

Speaker A [00:30:29]:

It's a good point. I think going back to the local businesses, this is a tip. If any local business owners are listening, the number one thing local business owners can do is just answer the phone. That's it. It's not hard.

Speaker B [00:30:40]:

Pick up the phone.

Speaker A [00:30:41]:

The customer service aspect is so huge, it's incredible. And it's because they're on the job and so forth. But you got to invest in somebody to just answer the phone. That's where a lot of business is lost. I had to deal with it calling some technicians and plumbers recently, and they just don't answer the phone.

Speaker B [00:30:59]:

I got a great plumber, so we could talk after the podcast.

Speaker A [00:31:04]:

So otherwise this is a good episode. I think we covered a lot here, lots of simmer on. I think in one of these future episodes, I think it'd be awesome if we can talk about content and how to actually leverage some of these AI tools, because we do talk a lot about the Ramifications and some use cases.

Speaker B [00:31:17]:

But I think if we get in.

Speaker A [00:31:18]:

The nitty gritty and actually maybe let's talk next week about how individuals can actually leverage these tools to create better content, doesn't make them sound like a robot. So if you're down for that, I think that'd be a good conversation.

Speaker B [00:31:31]:

I'm down. Let's do it.

Speaker A [00:31:33]:

Awesome. All right, ma'am. Well, that's all for this week. So if you made it this far in the episode, thank you for listening, and we'll be back next week.

Speaker B [00:31:40]:

See ya.

All right, welcome back to the Cold Takes Popular Opinion Podcast. I'm your host, Trevor Robinson, with my co-host here, Ira Sharp. And today we have a very special guest, Jamison Rotz from Nearly Human AI.

Welcome, Jamison. Hey, thanks for having me, guys. Yeah, this is a special episode for us because you are the AI man, or at least in our circle, you are the AI expert.

So do you want to give the audience a really brief rundown of what Nearly Human AI is and a quick synopsis of your background? And then we're just going to dive into some fun AI burning questions that people want to know about. Yeah, sure thing.

I've been in technology my entire career, started off as a software dev and founded this company 12 years ago. Like it's a consultancy to start, but we quickly ended up moving into the data science and machine learning space and specifically natural language processing. So it's been a really interesting run.

We started out when there was like next to nothing available in the space. And now here we are in the new large language model era. And so it's been a really great experience.

We've seen a lot along the way and it's an exciting time. About two years ago, we kind of like we started moving from just a services company into a product company when we landed funding for our current product at Bell Cortex, and it's a machine learning platform that allows companies. To take either models that they have us create or models that they create themselves and move it out into a production deployment and connect it to their business systems.

And it takes away basically, you know, like the million dollar lift worth of DevOps that it typically takes to get your machine learning technology fielded and connected with, with your business system. So that's the space that we're in right now. And with all the natural language background, you know, we're, we're really impacted by everything that's happened in the past six months since the launch of chat GPT.

I can only imagine, you know, how much it's, you know, just drawn attention to what you do and everything like that. So, you know, before where you're probably trying to explain for days, what this stuff is, you probably still need to explain for days what it is, but at least, you know, people have heard of chat GPT and kind of want to know more. Well, the questions are completely different.

It's like, you know, what, it used to be like, what do you mean by natural language processing? Right. You know, and it's like, how do these like things roll off of people's tongues and they're like, what's going on?

What, how's this, what's happening? Right. And I remember, I remember when I, when Jamison and you and I first connected, that was one of the first things I said is like, your business probably exploded overnight.

You've got that, you know, before you're in that era of marketing, there's probably a lot of concern or questions around this space. And it just seems like in the last couple of months, everything's accelerated. Almost everybody is aware of, of at least the concept now.

So it really probably propelled that conversation forward for you. It absolutely has. And like I said, the questions now are a lot more interesting because everyone is, you know, open AI allowed people to just like get in there and touch it.

Right. So like now people have, have actually been able to. Interact with some of this technology.

And so like the thought cycles on this, like completely changed because now, you know, you see it, you feel it, you at some level of understanding firsthand. And then people are like, especially like from a business to business perspective, and that people are like, wow, how do I, how do I use this now? Yeah.

And we'll dive into a lot of questions that we have around this. I just want to know off the bat. I mean, if I were in your shoes with AI and how fast things are evolving, it seems like every week there's a new tool.

And then, you know, in the next week that, that previous new tool is now extinct because everyone's building on top and developing so fast. So given the fact of your building in this space and you're building a pretty big problem and solving a big problem, does this, does this give you anxiety in general at the, at the speed of development or anything of that nature? You know, it's funny.

I think that like maybe six months ago, a little bit more so than now, even though it's moving faster now than it was six months ago, we are sort of in a fortunate space where we're building platforms that enable all kinds of models, including the large language models that are coming out now. From our business perspective, like we're actually able to like move with the latest technology. So I'm not building something that is in danger of like immediately being replaced by exactly what you said.

I mean, it's been, it's been really exciting because I've never been in a space like this before where it's like, this is almost like a business strategy all of a sudden where it's like, you, you just, you see where we are and you imagine where we're going next. And like the next week, there's a headline about how that technology now exists. Right.

And so it's going so incredibly fast. And I really thought that, you know, when I, when ChachiPT first came out, I really thought that we were going to see a ramp in a plateau, right. Because that's, that's typically like how this works.

If you think about like, you know, automated vehicles, for example, right. Like, like the 10 years ago, right. Like the Tesla S took us to like 80% of like where we are now.

And now we're 10 years on still trying to solve that final 20%, because these are really complex problems or safety considerations, the whole thing. But what's different now is that in this, especially in this natural language space, and we can talk about like some of the special sauce that open AI has really cooked up that's, that's launched this forward, but in this space, when, when GPT-4 hit, I had this like revelation that this one's not going to slow down quite the way that we saw before. And the reason why I came to that conclusion is because GPT-4 leveled up so dramatically from like the GPT sort of 3.5 that was running behind ChachiPT.

That it was astounding. And, and I don't have the inside knowledge of open AI to know exactly like what the vintage of what ChachiPT was running versus GPT-4 to know exactly what that timeline looks like. But it was astounding.

It, it surprised me the level up that they took and what's going on with GPT-4 now as they get ready for GPT-5 is not only do we sort of like expect, you know, kind of like a similar leveling up, but now we actually have like the LLMs writing algorithms that are going to fuel the next generation of LLMs. And so I think that this like, this continues on a pretty steep path going forward. But that being said, like, I think what quells my anxiety is that we're seeing a lot of first use that is the media is really fast on this cycle right now.

So, there is some value to just kind of like taking a breath, holding back and watching what happens a bit so that we can understand like where the real business value is, and that's where we at Nearly Human are at. Focus where the rubber is going to meet the road, right? So a lot of this stuff is cool and interesting, but that last 20% needs to be solved before businesses can start to rely on it to actually like change their business models.

Yeah. What I find fascinating is that you do have a lot of tinkers out there that are, that are kind of leveraging this, but the fact of how far, like you said, the advancement came with chat GPT-4 and the fact that I don't even know what percent of the API tokens have been deployed yet, because I know they have a really long beta list and I've been on it since day one. I know some people have gotten it.

And so it's scary to me to think that it's probably not even 10% yet have been released. Right. Think of the evolution once that can get in the hands of, of many others.

I think we're going to see that, but to your point, I think you're building something on the, on the, on the roots or the backbone of a really, you know, long-term sustainable use case. Versus some of these other innovations that are popping up are solving, some are solving problems, some are just really, you know, interesting where I'm fascinated and where I, when I talked about this, you know, in previous episodes is that just the possibilities, right? So I'm going to put you on the spot, Jamison.

So what do you think is probably one of the simplest benefits that you just say AI in general can, can do for people on a daily basis. And then what's something that you think, you know, is the most exciting thing for you, for people on a daily basis, and then what's something that you think people aren't thinking about that could be a bigger use case, you know, in the future, if that makes sense. So on a day-to-day basis, I think the most exciting thing for me, and it's like, you know, this is kind of a way that I use it personally.

I don't know that I see people explicitly talking about it in this sense, but what I do love about it as it sits today is from an ideation perspective, it's it as a reinvent the wheel preventer, right? Because like every time you come up with an idea, you can sort of like go to chat TPT and in 30 seconds, understand what the consensus of the internet is around that idea, right? And you can even tell it short bullet points, right?

So the TLDR even goes away. And, and so what that does is provides this really interesting baseline knowledge for everything that you're working on. And I love that because, you know, I think every like innovators, it falls into this trap of like wasting cycles on solved problems just because they're new to them, right?

And like washing that out right out of the gate and leveling up your thought process on the problem that you're trying to solve to like, okay, now I understand sort of like consensus. There's all of these bits and pieces that were actually out there that I wasn't aware of. Now I am.

And then I can take that to the next step and say, okay, well, like what thought cycles are actually novel in this and where can we launch off from here? And I think that I think that's a valuable way to look at it. I do think that the content creation side of things that people are like actively using it for now is a little like underwhelming when you look at it long-term because I feel like that's just essentially going to like whitewash the internet with pontification.

So right now what's running rampant is you can see comments on LinkedIn are just AI generated. And the big problem is they're too long. There's too much stuff and it's just not natural in how a human does it.

So I think, you know, this is a little thing I'm noticing. And it's very same-ish, right? So it's like as if your feed wasn't mind numbing enough, overwhelming enough to begin with.

Right? Yeah. And the way people are, I'll give you a little inside baseball here of what the smart people are doing on LinkedIn to really stand out is, you know, in the current state of the algorithm is really living in those comments, right?

That's something that's picking up a lot of steam. However, to stand out now, a strategy is really, you know, a few people are doing effectively, they'll catch waves is actually recording loom videos as responses to comments so people can see your face, they can see you and then you're not lost in was this AI generated? Was this not?

Because I think a lot of people are just going out AI and posting it out there. And like you said, I think it's just going to saturate the internet with like garbage content and originality and getting your face and voice out there is going to stand out a lot more. And you put your finger right on the spot of something that I think is a 100% bet going forward when I look at this.

And that is that as all of this happens, right, like human authenticity is going to become more and more valuable as it becomes less and less of a percentage of what's out there, right? And so right now, like those lube videos are generally more authentic because it's proof of life, right? That's exactly how that's not going to last long, right?

Because now if you go out with a 30, 40 second recording of your voice and a picture, you can deep fake a video of you saying whatever you've told chat GPT to say, right? So as that, because that technology is like pretty good. If you look at some of these things, like it's, it's pretty compelling already.

So once we lose the proof of life on video takes, then that problem becomes more interesting. And I think one of the things that we have to solve going forward is this proof of life issue. Like, and I think about that in terms of like, well, what do we do?

What do we implement? That's like unscalable in nature and like connects directly to a person so that you do have an understanding of this. And you know, this is a very deep psychological need.

I think that we have like as humans that regardless of what happens in AI, we're not going to evolve away from. And, and so I think that like, as we think about business models going forward, like the actual, like, like the actual person to person interaction, like what we're having right here is something that will remain valuable no matter what happens. Yeah.

Mommy, I generated, so I don't know what you're talking about. So, so, you know, on the content creation side, I agree. I think it'll become, I believe it'll become evident who's doing what.

I mean, it's already kind of out there and, and it's going to become more and more. It is interesting because the whole idea is that this AI becomes, you know, you, it becomes, you know, your bot, you know, and, and so I dream of the day that I can take the mountains of notes and, and flow them into a learning model. And then I can just query for stuff that I've learned over the past 18 years or 20 years and be able to get the responses that I forgot.

It's going to be awesome. But I am curious on this whole topic because I know in some other countries, even they're starting to like either outlaw it or try to figure out how to govern it. And, you know, I don't know how I feel about that.

I feel good because, you know, when you look at some of these language models, obviously open AI, for example, was taken in tons of information. You know, it's a big reason they're making it an open platform because they can collect information from everybody. And that's a huge security risk.

That's huge IP risk. But like the answer can't just be turn it off or over govern it because there's going to be people that advance it regardless of what anybody does. So it's an interesting spot because I feel like we've opened this box and I don't know how I feel about it.

Like, should you close it and put it back in the closet and forget that it's there? I don't think you can do that. But like, should you evolve it?

Because then it'll become something maybe you didn't expect it to be because things are advancing so fast. And yes, people are using it for content creation and that's great, but people are also doing it to develop some sort of script to try to spoof IP addresses of the biggest state actors that there are to cause national damage. And it's a bit of the early days of the internet right now with this whole AI stuff.

It's kind of crazy. Even on that, Ira, really quick is that you got these situations, like, I don't know if you guys have seen, I think it was Drake and The Weeknd. Drake and The Weeknd, somebody created an AI song with both of them on it and it went viral on every social media platform.

And it sounds super realistic. And it's like, what do you do if you are those artists? How do you stop this along with the Joe Rogan AI experience?

If you guys saw that, that was crazy. Yeah, there's all these layers. So what are your thoughts on this, James?

Well, first, Jamison, before you go, I hadn't heard that. So can you sing it for us, Trevor? Yeah, let me know.

No, no, no. No, so in the past two weeks, I've seen some really promising things happen, and I think I can see my way through it now. And this is new for me, so it's exciting.

I have like waffled back between from extreme optimism to extreme pessimism. And now I'm optimistic again, which is my nature, full disclaimer. So, you know, you're not.

Is that in the context of a day or is that like? Yeah, for perspective, that's probably in the context of like the past two months. When it first came out, I was like, oh, this is this is great.

This is really, you know, and then it got really dark for me because I started seeing like some of what was going on. But here's the thing, and I think that like to your point, like this whole talk of like, oh, let's slow down and wait for regulation is like first off insane. When has that ever worked?

Right. So like doing the same thing and expecting different outcomes. Right.

And and secondly, to your point, like even if certain organizations or certain countries decided to take that approach, like you would never get worldwide consensus on this. And and if you're if you're most responsible entities are the ones slowing down the most, then that automatically means that like your least responsible entities are the ones that are going like mad. And and that's not a good balance either.

So what's what's good about this, OK, is in the past past month or so. Right. It's become very clear that so open AI, you know, what these large language models do is is like is very mundane.

Right. Like they're just predicting like the next thing to say. And it's based on this massive amount of data that they've trained on.

And there's a lot of costs associated with it. Why it took open AI, you know, billions of dollars worth of Azure credits to like to train this thing. But but what gets interesting is like what what open AI did was that they figured out like this.

I mean, this large language model thing has been going on in research for, you know, for 10 years for sure. We we lack the processing power to really like get after it in a meaningful way until maybe like the past five years or so. In theory, this is you know, this has been around since I forget.

I mean, some of these early like theoretical large language models are from like back in the 40s. Right. So like the but what open AI was able to crack in a very interesting way was how you like tune these predictors over all of this language that gets it to like act creepily human.

Right. Even though what it's doing at the root of it is is really mundane. So they solved that problem and like created the art of the possible when they launched chat GPT and got this in the minds of the world.

Right. But since then, and this is like this is an absolute theme in machine learning, right? Like is that when you get cute with machine learning, it always allows you to kind of like skip steps.

And the way that you skip steps is like is finding the signal in the noise. Right. So you see like the coon to come out from Facebook and all of a sudden it's just like very small, like large language model that you can train effectively and cheaply.

And then the idea of like the reinforcement training that comes into play with these things. And all of a sudden you start seeing more and more large language models come into the space. And so I think the way that we should handle this going forward is that we expect instead of like a fight to the death between open AI and Google, right?

You know, who's going to take over the world. You know, they're going to move in the AGI, the generalized artificial intelligence space based on a lot of information and a very broad scope of what they're trying to attack. But the fact that we've got these smaller models, and this is an area that like nearly human is leaning hard into is that they're going to hit a wall and they're going to be up against smaller models.

The training mechanisms that we use for these models are going to become like orders of the magnitude more efficient. There's already approaches that people are starting to take to say, okay, well, if open AI is like training this way, you know, how do we tweak that and like reduce our costs by 10 or a hundred times? And, and then it's actually working with, you know, maybe not like the exact same results, but 80% of the results, which is by far good enough for a lot of applications.

So I think if we take this approach where we like give the court systems in our countries, like the, the power and the authority to sort of like govern these human acting models, the same way we govern humans. So that if one of them like breaks a law, you know, the people involved are able to be prosecuted. It gives some interesting legal teeth to the actual deployment of these things.

And then we allow it to continue, but we support all of these different large language models coming in. And then now you start to have competition in the space. And that does two things.

One, it creates this little interesting nuance for the large, the big players, the AGI players in that once companies like what Bloomberg did this, right? They took all their financial data and they trained a private LLM. This one, much higher quality data in a narrower scope.

And if you think about that in terms of where this goes, you have different companies in different spaces that have access to this, to this data corpus that they've built up over years. They're going to close that off, right? You're already seeing like, you know, Cora and, and then Reddit, like closing down their APIs to keep, you know, large language models from just sucking all this information out.

And that's in preparation for some of the, their own things that they're going to start doing. So if we get more of these LLMs out there in place competing with one another, then you have options. So if one of them does something that we don't agree with on a legal or ethical basis, like you have a court shut them down and while they're under like investigation, and that gives their competitors the ability to come into that space.

And that's real capital market motivation for companies to become more careful. So I'm really hopeful about like where that ends up going. But I mean, do you really think it's possible?

I mean, I agree, you know, there's extreme value in getting these small language models and these kinds of things, but if they're exposed at all, which if you think they're not exposed, they probably are exposed just because, you know, there is no such thing as an air gap system and things. Don't you think that there could be something built to interconnect them, you know, to learn from each other? I mean, you're already seeing that with, what is it, auto ML or something like this, where GPT, yeah, where it's, you know, it's whole idea is to destroy the world or something.

That was chaos GPT. Chaos. We've gone auto GPT.

Yeah, yeah, yeah. But I mean, despite what it is, I mean, that's that just did like it's all moving so fast. And then if you look at governing things, it's just I see it being very, very difficult.

And I think we're all saying the same thing, but it has been done with like medicine, right? We've done it with like, you know, peace treaties with nuclear bombs and these kind of things. I don't know.

I look at this and I go, is it to that level? I tend to think that it kind of is. It can be right.

And I've just, everybody that I've talked to, I encourage, especially the, there's a ton of responsible AI chatter out there. Right. And that needs to become more than chatter.

And I've just been encouraging folks that are like working in that advocacy space to bring the lawsuits. Like it's the only way to force the issue. Just like Sue.

Everybody's got to start getting this into the court system and forcing the courts to like make opinions on this. That's going to be a long process, but not as long as waiting on regulators. Is that a U S centric thing though?

Like, does that matter if you're another, it's going to be the ones, right? Like, because that's, those are the, the, like the sort of like democratic spaces that have these port systems that can absorb this kind of stuff and get to work on it. If you look at like autocratic regimes and stuff for one those, you know, if you look, so you look at China, right.

And China is already starting to like wrap their arms around it in a pretty substantial way. But the other thing is from like an information perspective, China is pretty isolated from the rest of the world because they're not getting stuff in, but none of this is, I mean, like, but if you could have pipes, I'm sure, I mean, they know what's going on a Facebook. Like you may not be able to look at Facebook there, but they know what's going on on Facebook.

A hundred percent. And that's where it gets a little funny. And I don't know that, like, I do know the good part about this is also like from a worldwide perspective, like, because of the way China's because the way China has operated, like we can see the data going in and coming out of like China's like, you know, state firewall essential, essentially.

So that can be monitored and, and it may, it may come to the, I mean, you know, this is, this is a whole other geopolitical thing. Right. Because as tensions rise between China and Russia and the rest of the world, you know, like cyber warfare and information warfare is absolutely going to be a thing in the future.

And that's something that's going to develop alongside of this. And like the US and EU and other like free nations are going to have to like sort of treaty up around this. I think, do you feel that the, the government in general is probably gonna have to hire, I mean, to, to gain the competence around this.

I can't imagine that the current government and state has the competence of the experts that actually truly understand, you know, the impacts of this technology. Like, do you think that that's going to be a big, a big wave in the future here of them having to level up? They're already, they're already hiring.

And quite frankly, there's two things that there's two things that are happening in their favor right now. One is the massive Silicon Valley layoffs. Yes.

And that coupled with the fact that like venture capital is all sideways right now. So like company formation in that area has just like slowed down by orders of magnitude. Right.

So there's that going on, which is freeing up talent. And the other thing is just the social backlash around sort of like the VC frothy fraudulent stuff that's just like making headlines left and right has created a generation of technologists that want to do some good in the world. And so I think, you know, between the government, like leveling up on their hiring and offering some more competitive salaries in the place.

And I've heard stories, you know, there was a, there was a podcast from the head of the FTC that was stating that like, they have been hiring top tier technologists at a rate that he's never seen. And they don't care about the money. They're like, I feel passionate about like making the world a better place and thwarting some of the potential risks around technology.

And I'm here for it. Right. But, but doesn't even matter.

I mean, like seriously, because you got to think top tier technologists, you're hiring them into the government, you're trying to regulate all this, but you can learn out of the cliche of your parents' basement and the best, the best Silicon Valley tech company started out of various garages. Right. So why couldn't you be in the middle of Russia in a basement, learning all this stuff to figure out how to be the bad actor?

I think it's there. Right. And it's absolutely there.

And it is absolutely there. And that is the biggest risk that we face. It's like, it's the auto GPT thing, right?

Auto GPT is, is an amazing concept. There's not sort of the, this kind of like creeps into your world, Ira. There's not sort of the interconnectivity between all of these services to allow that just like run rampant and like spiral at scale yet, but it's coming fast.

Right. And so those are the things where again, right. Like the, these, the, the free market governments and court systems like need to be able to like get after this stuff as they see it happening and, and call attention to it because we, you know, one of two things is going to happen.

Right. Like, and, and this is like, this is the, the weird thing about it, right. Is it like, we don't want to slow down because that seems counterproductive, but if we don't proceed with caution, there is going to be some event that causes it all to stop because it's just too bad.

Right. I think that's what we're hearing from a lot of these vocal guys. I mean, lover, Haiti, Elon Musk, you know, he kinda, you know, he's been out there pushing that narrative, you know, whether there's a hidden agenda behind that or not.

I'm all on my fields on this one. Everybody slid out in six months. Why launch three more companies?

Yeah. Point is valid. I want to shift gears here.

I have two questions that, you know, Ira and I here were debating in some past episodes. We'd love to get your opinion on here. So the first one here would be when you look at this and you look at the, the, we'll just say for lack of better words, the impact and the benefit that companies can have, you know, from the just, just AI in general, right?

Let's just not even go chat, GPT or whatever, just AI in general. What do you feel right now is like the window of opportunity that companies have to get their act together, to start investing in this. Whether that's bringing on new people to leverage something as simple as chat GPT, or whether it's, you know, hiring a company like yours to come in and implement it and so forth.

What do you realistically think that window of opportunity is before they just get left in the dust and then they're kind of fighting and kind of like they lose the competitive advantage, right? The first mover, what do you think that window is? Well, I think it really depends.

So from to your point earlier, I think if your strategy is to simply implement like the latest technology, you know, by the time like you get that in place, like just the fact that you have that latest technology, it's not going to be the latest technology and like that value just like goes downstream, like immediately. Right. So I think that's a bit of a fool's errand.

I think that like the two things that I recommend companies really look at, one is leveling up your workforce in terms of like their skills and exposure around this, right? That is something that like you, the investment in the exposure to this technology won't go away because you do risk, you risk getting left behind very quickly if you don't spend some time just kind of staying up to date with what's happening because it's going to continue to accelerate. That being said, like don't freak out, right?

Because like if you don't have the exact like right strategy or you feel like, oh, I'm already behind the eight ball, like you're not because something's going to come out in next week or next month that's going to like negate 75% of what you thought you needed to know in November of last year. Right. So, so I mean like that, that introduction and the, and the awareness of this technology within your workforce in general is a really good thing to invest in.

The other thing that really, I think defines that like window of opportunity gets back to what we touched on a little bit before, and that's like your domain knowledge in your business space and the data, this corporate knowledge and the data around it that you have collected. And the, the size and quality of that corpus is going to be directly related to the length of your runway in terms of corporate advantage, because that's the thing that your competitors cannot recreate simply or easily. So it really comes down, it's going to come down to who has the best information and has the most forward thinking approach to leveraging that within their company.

Yeah, and it comes in, it's very, you know, relatable to when I work with a lot of companies and marketing teams, there's a million options that they could do. And the first thing I always see is we need to launch a podcast. We need to run ads.

We need to do, and, and it's slow down, right? Just because everyone else is doing it. There's always going to be a new flavor of the week, right?

We have to understand, and this gets hard even in this sense sometimes for them of like, what is your goal? Let's look at the resources you have, the assets, where are there gaps? Because the strategy could change.

And to be honest, in most cases, the best strategy for most of these companies are just the most basic ones. It's getting the foundation in place before hopping into that shiny object, so to speak. And it sounds like this is going to be very similar parallels where they have to bring in somebody or have that domain expertise that can kind of guide them to say, we know when to sit and watch, we know when to dip our toe.

And then, you know, with full confidence, we know when to lean in, but then even when to pivot or kind of like those like safety valves, so to speak. Does that sound accurate? Yeah.

And I think the other thing that like companies need to reshape their thinking on and really like challenge their mindset around it is the one thing that I think is happening, right? Is this, in the tech industry, there's this idea of like a 10X developer, which is basically means, right? Like these are these like cream of the crop developers who like their knowledge and their methodologies like just make them 10 times more productive than maybe the like the typical developer in their field.

But I think that like bringing this technology to bear and the ability for LLMs to be writing code and like implementing again, right? Like you can see what the consensus implementation of virtually anything is right now by just telling it to like write the code, whether or not you can cut and paste it and deploy it, which in some cases you might, or you look at that code and say, okay, this is what everybody else is doing. And here's where I add my special sauce.

Challenge companies when they're thinking about like prototyping things and like dipping their toes, like you said, you know what? Go out there and look for firms and developers that look 10X because there's going to be more and more of them as they learn to leverage this technology. The 10X developer is going to become like the new normal.

And that's exciting for figuring out how you're going to leverage your business advantage based on like the data and the knowledge and the expertise that you have. So yeah. And I agree with all of that.

And I think about this from a company perspective and there's the 10X developer and there's that tech approach, but you know, this is not going to sound good, especially as this podcast comes out, but I see it as eliminating jobs. And that's kind of the goal of it, right? But I don't really see it as eliminating people from working, but eliminating jobs.

So for example, if you had 10 people working in an HR department, maybe you don't need 10 people in the HR department. Maybe you can have one person that satisfies that with the augment of AI and utilizing this. Now it doesn't mean those nine other people lost their jobs, but they could be utilized for something else in the organization.

And I think as we move forward with this, it'll allow companies to better utilize resources while investing in this type of technology to make it better and better. So just like the 10X developer analogy, I think you can do this so much with so many different things for like onboarding people and all these other tasks. And I see it no different than looking at the industrial world.

And you looked at, okay, going from a standard manufacturing line where you had a line of people assembling a car, and then you removed a lot of those people when you augmented them with robots. It doesn't mean those people lost their jobs. They were just redeployed to other types of things to further increase their productivity and ultimately the ROI and profitability of organizations.

I see this as happening from an information age. Maybe this is like the next industrial revolution for just information. Information and creativity.

I completely agree with you. We've seen this time and time again. It is true.

Both things are true. There's going to be this huge transition period where we're just going to redefine what it is that you need to run a company. And that is going to have huge workforce composition changes on a national and worldwide basis.

But I think that the way I look at it, and this will become clear as time progresses, but to your point, Ira, this touches everything. I guess as a business owner and thinking about it in terms of the C-suite of companies everywhere, it's just that like, well, okay. If you think about 10Xing your information staff, whether that's marketing or whether that's coding, where you have these opportunities, you just step back and say, okay.

To get through the thought process on that is like, all right, so let's pretend that it's five years from now and this technology has reduced my IT spend and my marketing spend and down to 10% of what it is right now. So if I just assume that that's going to be the case, what would I spend those dollars on? What's the special sauce in my business that I know if I had that extra budget, I could elevate and destroy my competition with?

And I think that just right there defines your five-year strategy, right? Because it's going to be a glide path to those kinds of savings. But if you think about it in that terms, it's going to help you come to the conclusion of what jobs those are going to be.

I guess back to the domain knowledge, right? If you're able to reposition your staff who has a bunch of domain knowledge into this new strategy that you see once you have budget for things you don't have budget for today, that's probably a winner, right? Yeah.

So it's a great segue into my second question. I want to get your opinion on. So all the rage right now is these prompt engineers.

And you see these popping up with insane salaries. I already know, I talked a little bit about this. I think personally, I think it's a short-term trend in the mass.

Cash those checks. Cash those checks. Okay.

Because here's how I'm thinking. I actually disagree on this one. I think it's- Let me explain my view and then I'll let you have your shot here.

So my take on this is that prompt engineering, it's common sense to me. I think it's just, if you want to get an answer to something, you got to give a detail and it's a feedback loop. Not giving you what you want, get more specific, right?

But I think, and again, I don't know much about these machine learning modules and so forth. But let's just take a company example for, you bring somebody on that's just onboarding HR. You could have a prompt engineer that helps do all this stuff.

Or is it going to get to the point quickly where machine learning understands exactly what you're trying to ask? Kind of like Google, right? Because when you Googled 10 years ago, it was essentially prompt engineering.

When you Google now, Google knows what I want before I even want it, right? It's getting to that level because of all these data points and with the algorithms and that machine learning in the background, I guess. That's my take on it.

Ira, what's your, I know you're very passionate about this. Well, so I actually think Googling is still a skill. It's a skill.

Yeah. And yes, you can Google when you can find things, but you can find things and then you can really find things. It depends on what you're looking for to how granular you can get.

And I think the idea of prompt engineering, if you think of chat GBT, I think a lot of people use it like Google right now, but that's not really what it is. So if you're thinking about it in that context, that's, I agree with you. But, and if you, and then if you add in like the general templates where you're like percent pretend you're this or consider this and act like this and then do this kind of thing, I agree with you.

But when you really think about prompt engineering and you think about the massive datasets that are out there to really, and I, and I see this being something that lives on to really be able to get the data out that you truly want, you need to really be an expert in your field and really understand what it is you need to articulate. And in crafting that kind of prompt is not just as simple as Googling, you know, it's, it's really looking at, well, Hey, can you consider this, this, and this, and then look at these kinds of things here. It almost becomes programming.

It's almost a new form of programming through natural language. It doesn't mean other people can't do it. Doesn't mean people won't be successful at it.

Just like Googling. I mean, you know, people that can Google and get information and then you Google and get information and you can probably do it more efficiently than other people that you know. And you probably know people that can do it more efficiently than you.

There's like this scale. And I think prompt engineering is that on steroids. So just like, just like you, you know, you have these massive datasets and things.

I do think it'll continue to be a trend and the best people at prompt engineering and they may be niche in particular industries will continue to be very, very good. That's awesome. It's quite niche.

But then I'm curious what your thoughts are. I think just the machine learning after, you know, it's going to understand what you're looking for. So you're not going to have to get as complex in the answers.

I don't know. What do you think Jamison? Well, the reason I think it's going to become commoditized and the value of it is, is going to be reduced is because so this, and actually this gets into like, we just released version 1.12 of our system on Friday.

And what's included in that release is actually a system to provide prompt engineering automatically. So what our system does now, because, because we saw this exact, this exact issue, right, is that it's, it's, it works. So you can set up like models that your company, that we can train to understand like the domain of what you're working in.

And then instead of calling GPT directly, you call the endpoint on our system. It will automatically make the prompt engineering calls out to set up the context and then it'll pass your question through. And so it creates these guide rails, these, these subject matter guide rails into these, into these large language models that will allow someone who, again, to your point, like still the ability to like articulate your question in a way that you know is going to get the proper response is still valuable.

But I think that like, there's going to be like a leveling effect within organizations where, where people can relatively quickly learn how that should work, especially with some support mechanisms in place by third party providers, like what we're doing, what others do as well. And then couple that with like what we talked about before, where you end up getting like domain specific LLMs. So now, you know, I think the AGI might actually look more like, so when you like, you call our platform, it might run a model to like, to like set up the prompts with your LLM to ask the question as well as like watch for like proprietary data stuff and like pull that out.

So you're not just spilling your guts to chat GPT, but also, you know, but, but like, as this goes, like, it doesn't necessarily just have to go like specifically to GPT, you know, it can know that, Hey, if I have this intent coming through, I have this, like, Oh, you know, like I'm asking a business question, this should go to my subscription at Bloomberg's LLM, right? Or I have this hearing question. And I have all I have an engineering body of knowledge that's either within my company, or maybe I outsource that to an industry leader that has the corpus of data, and I pay a subscription there to be able to like use their models.

And so the AGI then starts to feel is more of a network of providers of choice, as opposed to just trying to go to a one stop shop that's like relying on the like cesspool of the internet to figure out what it's talking about. Yeah. So I don't know.

I don't know who the who the right answer is there. I guess we'll have to put a reminder to follow up. I'm right.

I'm right. So yeah, so that that is a lot of information today that we we went over. Jamison, we would love to have you back again, because I'm sure we'll have tons more questions.

One that I really want to hit on next time is what you mentioned about, you know, how this data flows through with proprietary data. We saw the whole thing. I think it was Samsung.

We have, you know, all the ethics around data and what's good data, bad data. So those are all topics that yeah, so those are all topics I want to talk about a whole separate episode. In the meantime, let us anyone who's listened to this, where can they find you?

What's the best way to get in contact with you? And I guess, you know, give a plug for nearly human AI. Absolutely.

You can find us online at nearly human.ai. And if you get on there, you can read about us, sign up and we can answer any of your questions or reach out. I'm on LinkedIn, LinkedIn slash Jamison rocks.

And you'll find me out there talking about all these things as well. So you can always message me there and I'll be happy to get back to you as well. Awesome.

Well, I appreciate you coming on Jamison. Any final words, Ira? I know.

I just, thanks. Thanks a lot, Jamison. It's always great to talk to you.

And yeah, I look forward to having you on again and continue in this chat and about all things AI. So it's, it's always a good, it's always a good time. Anytime guys.

This is great talking to you. Yeah. Now I got a lot of things to go and think about.

All right. See you guys. Thanks.

See ya.

All right, welcome back, Ira, to who knows what episode this is. I don't know. A lot of these get corrupted and lost.

And with all this A.I., you know, we think that we'd have this down in by now. But regardless, we're back, man. How are you?

I'm doing well. And we'll look back at those times and we'll say, you remember all that now B roll that used to be a roll. This is B roll.

Yeah. This is B roll. So I don't know if this will get released or not.

So I have a question off the bat. You came across a pretty interesting study on prompt engineering. It's all the rage here, right?

So fill me in on that, man. What did you find? Yeah, so I mean, it was it was a variety of different articles and other topics that I was reading about it.

But prompt engineering, I mean, I don't think it's really a new thing. I mean, it's it's kind of like the evolution of Googling. But prompt engineering is is really becoming a major topic.

I would even say above and beyond this whole A.I. craze of chat GPT and prompt engineering. What it is at the core is, you know, that if you've played around with the tool and if you haven't definitely recommend it, you know, chat GPT or any of these these tools is the better prompt, better thing.

You can give it to to query on, to respond to and these kinds of things, the better response you get. And there is a bit of an art to understanding how you can input this stuff. And it's it's less about the tool and it's more about the subject matter.

But if you're an expert or a pretty proficient person in the in the topic, you can really make some really good prompts and get some solid information back, particularly if you're giving it some context. So prompt engineering is, I think, one of the really big things that will continue to really maybe even outpace some of the buzz happening with just the general A.I. topic.

Yeah, I agree. But at what point is this common sense? Yeah, I mean, it's like it's it's getting ridiculous.

I see the the LinkedIn carousels like how to. And I'm like, this is common sense. It's a conversation like I'm just blown away that like, what were these people using to find their information before?

How are they Googling things before? Like, I don't know, maybe just because I'm in that field. But at some point, it's got to be common sense that if you want to get information, it's almost like having a conversation with somebody like, yeah, maybe maybe there's an art to it that I'm just not seeing.

But but Trevor, and this is even, I think, what separates it on LinkedIn or Facebook or wherever you're seeing these carousels. But, you know, the idea of prompt engineering isn't just asking the right question. I think it's also giving it the context, because if you're just asking it the question, OK, I mean, that is good.

That's powerful. But if you provide it, say, the transcript of this video, right? And maybe all the other videos that we've done.

And then you ask it various questions about that in context with other resources that are out there to get some sort of solid output. I think that's really where the value comes in. So the prompt engineering is as much about giving the tool, giving the platform, whatever it may be, the the research, the background, what you want to pull from, plus the other resources you want to pull from, plus asking the questions in the format that you want and to get that output.

It's like programming without programming. You don't necessarily need to have the you don't have to need to know how to do like Python or C or any of these other programming languages. But I think you need to think a little bit like a programmer if you want that kind of output.

But that makes sense. Do you think it's more about the prompt or do you think it's about the individuals just don't really know what they want? Right.

Because like, here's a great example. If I let's just assume you and I are going to lunch, right? I look at this and I'm like, Ira, where do you want to go to lunch?

That's kind of like a basic prompt. I'm going to get a pretty, you know, generic output. But then if I know that, you know, you love Mexican food and you love it and I want to kind of see, I'm going to I'm going to kind of probe you with some context around that.

Right. So I think that's the bigger the bigger issue is that because if I want to really get some research, right, let's just say I want to find some research on, you know, whatever it may be. I'm probably not just going to go put a basic prompt in and expect it to read my mind.

Maybe this is common sense. Maybe I'm way off base. I'd love to know what people think about this.

But I mean, I think what Chats GPT is shown in all these other tools is really it's scary. It's just the lack of like, I think it's lack of common sense. It might sound harsh, but like, I don't know.

But these people are paying big salaries. What was the number that you threw out? Like two hundred and fifty grand or something?

Yeah. The the salary of a solid prompt engineer. Some of the numbers I've seen floating around is two hundred fifty to three hundred fifty thousand dollars.

And, you know, I think some of that is because it's new, you know, and sure. These kind of things. But, you know, Trevor, I get it.

Like if you're talking about where you want to go to lunch or these kind of things. But first of all, if I ask Siri, she's going to ask me seven times what I said, because, you know, she's just not a good personal assistant. But that's a whole separate conversation we can have.

I mean, I love her. I have her on my phone. You know, I'm an Apple fanboy, but man, she needs some work.

But, you know, when it comes to Chats GPT, you ask about where you want to go to lunch. Yes, it's you know, but you need context about, OK, maybe go figure out where he's been before, whoever you're going with. But it's that background.

And that's where I think the prompt engineers that you're seeing, these big salaries, it's not just them doing the query, it's them providing the research. And if you really look at what's done, like I've heard reports that especially with coding and there's so much available out there and coding that you can pull from resources is I've heard of people downsizing significantly on their coders and reducing it down to one, two, three coders, and they're able to produce the same amount of work with fewer people using Chats GPT or other tools like it to help generate the code. Now, you have to be a subject matter expert.

So like going back to your example of food, like you have to know the person. Hey, this person likes Mexican food. They don't like Italian or, you know, whatever it is.

You go down through the list and maybe it gives you a better recommendation than if you're just going in cold. And the same thing with coding, like you need to know what's outputting is the right context, is it the right information? It's probably not going to give it to you in a perfect silver platter.

You're going to have to go through and edit it. But going through and having a generate a significant amount of code could save you a ton of time. That's my guess.

I just think it's like not even the prompt as much as knowing what you want. Right. So if I want to say I want to write a website and I'm not going to say, hey, write me a website, you know, write me a copy for my website.

I'm probably going to say, OK, what do I want? I want a website that's, you know, focused on high conversions. Right.

I want a website that's using, you know, modern copywriting formulas. So I might say to it like, hey, act as if you're a copywriting specialist or something, then I might go even deeper and say, act as if you're, you know, Dan Kennedy, the copywriting legend. And then I would ask you, like, do you understand his his frameworks for, you know, headers and stuff?

And then just have that conversation. To me, it seems like common sense. Maybe it's not to the masses, but I think it stems from like users having to understand what they want.

Now I can see 100%, you know, in your context of like coding. Yes, you have to have some background knowledge and like understand how to ask follow up questions and like, you know, rearrange things to get what you want. But like, I think this notion of just like, I can't fathom that this is going to become a mass scale thing in terms of like prompt engineering, because you could just ask chat GPT to help write the prompt, which we're starting to see now.

Currently. Yeah. And I think that it depends on how you're using it.

So if you're talking about it from a general user perspective, first of all, I do think there is a skill in Googling as well as in chat, if that's a word, probably will be if it's not already. Um, but you know, cause you got, you got to know how to do that dialogue. Cause I know people and I'm sure you do too, that you're like, how could you not find this?

Like seriously. Um, but, but that's why there's a site. Have you ever seen the site?

Uh, let me Google that for you. No, I haven't. It's awesome.

It's called let me Google that for you.com. And so what you do is you go there, you type in the search result and then it'll give you a link and then you send the link to the person that asked you. And when they click on it, it like pulls up Google on the homepage.

And then it's like typing in whatever it is that they just ask you and then it pulls up the results for them. So that's awesome. Yeah, that's great.

But you know, on this prompt engineering thing, so I think it's more of a data science thing. Cause, cause I agree with that. I agree.

Cause yeah. Cause if you look at it from like the data, yeah. If you look at it, okay.

So just give me a website, whatever it was, but think about it as a company. Right? So if you're a company and you have a couple of employees and you're going to onboard somebody, right?

So an onboarded person, they're gonna have a bunch of questions about the company. You know, what are my HR policies? Where do I find the 401k stuff?

Where do I, who do I go talk to about this particular topic? Who's the, who's the SME on that subject matter expert, or who, who do I, you know, put my time off request to all these general questions, there is no reason that couldn't be laid or provided in some sort of context, I'm sure it's written down somewhere and even the best organized companies, it's hard to find this information, but if you just put it all into some sort of database and then you were able to query that database and more of a general kind of way where the prompt engineer could potentially make sure that the prompts that a general person could put in will give them the right results. That's gold.

I mean, think of the time savings there. That to that point though, that to me gets a little bit away from prompt engineering and more into, uh, and that use case, cause you're in a container here working with a very specific set of data, right? Company, you know, their, all their data.

To me, that just seems more along the lines of like an algorithm, machine learning, et cetera, right. More so than a prompt, because if, if, uh, and we have a guest that we're going to bring on soon, Jamison Rots, who he can really enlighten on this, because I mean, he knows way more than we do, but it's interesting. I think it's interesting.

I don't know where these salaries are going to come from. I mean, it's like, at what point today, I think it would be a good time to. will be really in the backend building it for like maybe internal data sets.

But like, I can't see companies at, at scale going out here now saying we need prompt that a prompt that is incredibly important. I do agree, but like, I just can't see companies hiring people for this. When the whole premise of what they're using, meaning like open AI and chat GPT is constantly learning and evolving and can essentially write the prompts for you.

And it's just, I don't know the whole thing. It's, it's interesting. If there are no right or wrong answers, I'm just kind of fascinated by this statistic.

Yeah. I think it's a great statistic and you know, it is kind of interesting and that's kind of the whole point of this podcast, right? We can kind of get two different points of view on it.

Cause, cause I can completely see the salary ranges of this. Now, will everybody hire these kinds of people? No.

Yeah. Um, but maybe there's, what type of companies, what type of companies you think would hire this type of person? The logical thing is any kind of big company, any kind of company that has, um, maybe more than a hundred employees could use this internally from an onboarding perspective.

And then if you look at anybody that does any kind of, um, there is doing anything with data and they, people need to extract that data in some way, shape or form, which pretty much be anybody, whether it be business results or production results or financial results or whatever it is, I think all these things are good and you're, you're right. I mean, it's as much as data collection and making sure the data is available. As it is, you know, doing the prompt engineering, but I think the prompt engineering position is so important because having the data available as part of a model.

Yeah, that's just piece of it, but making sure that if you query it in a particular kind of way, like a normal person would, and not thinking necessarily as hierarchical point of view, and you actually get the right result. Okay. Well, that's, that's where the real value of that person comes in.

And if you can eliminate a ton of phone calls, you can increase the productivity of a company exponentially. Yeah. Yeah.

That's, that's where our buddy Jamison Rots at Nearly Human AI is going to come on and he's, he's working on that for companies, so it's going to be interesting to hear his perspective and more details. Cause you know, I know what he's working on, but not to the extent. So I think he's going to answer a lot of these questions.

He's he's knows so much, man. He starts talking and then it's like, what's going on? Yeah.

Yeah. We'll try to keep them at a general level, but yeah, it's, I think it's fascinating, you know, there are apps out there that do it, so I know a lot of people probably use the Chrome extension. I'm going to I flip over and I just use the chat GPT, you know, I'm so it's called, um, we got it policies.

So my company computer, I have a hard time installing some of these Chrome extensions. So, okay. It's called, I don't, I don't know how to pronounce this, but it's AI P R M.

And it's essentially chat GPT prompts. And there currently are 2,500 of these in the database. And so they work really well.

And it's a Chrome extension. And then when you open chat GPT, what it does is you can just search anything you want and it's pre-written prompts already. And some of them are pretty incredible.

They're, they're really detailed. Now that's a great starting point because you can start there and then ask those follow-up questions. Uh, but yeah, I don't know.

That's pretty incredible to me. These salaries, I'm not surprised where I actually think the bigger, more alarming issue is going to be is, you know, and this is kind of in like the business, you know, corporate world is like how companies create content. And I'm going to give you a couple of examples here where I think is happening is that tools like mid journey are, you know, they're creating some of the best graphics and it's not going to take them that long to, to further develop that.

So I think companies that are having, you know, I don't think graphic designers are ever going to be replaced, but I certainly think there's going to be a more of a use case now for those types of roles that are like almost like in that thin layer on like, you know, the fence of saying, this is what the goal is. You know, here's on the other side, we've got, you know, all this technology. I'm the one that understands how to get them that image pretty quickly.

And we can do it at scale though. I think that's going to be one case that we're going to start seeing. I think the more interesting thing though, that, that this technology is really opening up and I'm seeing this all the time now is that like, let's be real 99% of companies content is self-serving and boring.

Right. So I think this opens up the gate and gives them the opportunity to really not only produce content at scale, but also this is kind of that lifeline. A lot of companies have needed in terms of, okay, well, maybe you didn't have the resources before, or maybe, you know, you didn't have the creativity to think about this.

This, this blows everything out of the water now, because it's so easy to have somebody go out there and do tons of research and find, you know, different headlines, different talking points, different sub niches of things and craft, you know, a content calendar and start putting out content where the real challenge is going to come. And this is where most companies I think will fail unless, you know, they're really embracing this is just in the delivery of the content, right? Because my LinkedIn newsfeed is just flooded right now with just garbage.

It should be called LinkedIn GPT. That's what they should name the site too. Cause it's either post about chat GPT or, and you know, the irony here is we're talking about on the podcast, but it's just completely AI generated, by the way.

This will probably be in a LinkedIn newsfeed. So if I had any credibility, it's not the window, but the idea here though, is that it's, it's never been easier to stand out online because you have the ideas, but I think where we're hitting the point now is for originality. And I think we're kind of getting in this space where, you know, it's always been human to human, but I think now we're seeing it more than ever.

And this just kind of accelerated it. You know, when COVID first hit, we started to see this evolution of companies stepping out saying, okay, we've got to try different things because the newsfeeds are getting more crowded because everyone's locked at home on these digital platforms. So a lot of companies that had success before with like company pages and like traditional posts, those are now getting buried because of the algorithms.

And now content really needs to be educational. It needs to be entertaining or it needs to be really aspiring. Right.

And where. Kind of what I'm seeing is that we're on this fine line now, like edutainment, it's working people that are educating, but in like a unique and creative style, but even that gets burned out pretty quick. And so where I think companies are going to stand out is leveraging this AI, you know, to get ideas and help it accelerate the process, you know, and that, that can be whole downstream of this content creation too, that could be getting the transcripts that could be, you know, telling you how to repurpose it, help and write some, you know, summaries and snippets and all that stuff, but where the value is going to come.

And, and again, this is my intuition speaking here, and I think we'll see this in the next six months is that those in the, in the corporate space, or, you know, if you own a business and are listening to this, that want to win, I think it's going to come down to doubling down and going all in on your originality and creating content that is, you know, original and creative, that's not necessarily, you know, trend jacking or hopping on trends or, you know, things of that nature, but it's more, I'm thinking more like, I don't want to say cinematic, but more like if you go to YouTube and watch some of these YouTubers, they have their own feel and their style of how they're presenting this content. I think that's what we're going to start seeing standing out a little bit more in the news feeds.

And the caveat of why that works is because it actually takes time and it takes creativity.

And what we're going to start seeing then is when the masses are on these platforms like LinkedIn, for example, and every post in the news feed is some regurgitated chat GPT prompt, that's, you know, trying to educate their market. What's going to stand out is those that actually have a personality and a heartbeat, whether it's an individual or whether it's a company that's actually creating that and sharing the story and things of that nature. So that's what I'm doubling down on.

You know, I hear you say that, and I actually completely agree with you. I completely agree, but at the same time, I don't think anything's changed. I just think the bar is moved.

So while I look at it and I think about content, right. And you can think about LinkedIn in particular, corporate content is always struggled. Why?

Because it's typically not that exciting. Okay. Maybe if you're a super, why do you think it's not exciting?

It's not, it's not exciting because a lot of, a lot of the companies post a lot of companies posts are 100% self-serving. So unless you're super interested in a particular product, like, look, if I'm following Apple and Apple's just giving me stuff about their product, I'm good. Because I really want to know about that, but the majority of companies, it's not really what you're looking for.

Right. Yeah. Because it's because it's the delivery.

Yes. So I do think these tools will make that be a little bit more edutainment or, or trendy or whatever else, because it's very easy to create that it's another known. So you can go from, you know, your subject matter really, really, really well.

How do you apply that to the, to other areas, these kinds of things? Well, that's application and that's a little different. You know, I think these AI tools will, will just like you said, you can go type in a prompt, Hey, how does this particular product work in industry?

Or what is a big problem in this particular, and then you just copy and paste that, and that gives you, it makes you appear as a subject matter expert. And I think that that line has now moved to what you said, where there is an element where you can still use these AI tools as a subject matter expert to even further you even more. And that kind of goes back to what I was saying originally, where I use the AI tools, I use them as a, as a marketing professional, and I also use them in generating stuff for my posts, but I'm not going there and saying, Hey, write me an article on XYZ.

I'm using it for research or, you know, what are the big topics or whatever else? Or if I'm in a brainstorming meeting, it is fantastic. Fantastic.

Yeah. To have a neutral party sitting there right next to me that I can literally ask anything to, and it'll feed me information back. And, uh, and I use mid journey in the same way, if I'm doing creative design, like, Hey, I really want a logo that does blah, blah, blah.

You know, it's really, really easy. nice even if it's not exactly what you want, it can help your brain wander in different ways from a creativity standpoint. So I am a big one on brainstorming.

I like to have those kinds of meetings and try to fulfill these objectives. But I do think, to your point, the people that can really leverage this tool to enhance their content game, to enhance their own knowledge, and really, frankly, what things to research, it's gold. But it's a slippery slope right now, man.

It is. It's scary. I think we need a little Sheba in you next to valid posts.

Sorry, another trend topic. We do. Look, if Elon buys LinkedIn, that's going to be the new logo.

That would be Doge, right? Yeah, yeah. It's true.

Yeah, Doge. So I kind of look at it as maybe two phases, because what I heard you say and how I understood it is that companies now at their arsenal have the tool for unlimited research. Now, whether they use it or not, that's going to be a whole different story.

I imagine most won't, because they're so stuck on that this is what we have to put out versus what you said is that they could use this to add more relevant context. And so that's going to help them, because the more relevant something is and the more it speaks to an audience, whether the company thinks that that's what the audience wants or not, if that's what the audience wants, you got to give it to them. Right.

Where I think, though, that that'll have a very short lifespan is that every other company is going to start doing that. So now you still have the problem of distribution. And in this context, it's how do you get that post that is very specific and relevant because you've done the research, you know, your audience cares about it.

How do you get that to stand out on the platform when you've got individual creators out here just blowing you away with their content? And even if you look at the carousels, we're seeing all these people now have to put more effort into them in terms of like the look, the feel, because you've got to stand out in the newsfeed. So that's where I really think it's going to come back to not the content, the context will be there.

It's going to help companies rein that in and get a little bit more relevancy with their audience. But you've got to present it in a manner that's entertaining or interesting or has a unique flair to it that doesn't look like all the other content that you see in your newsfeed. Like they have to be able to say when they see you, oh, I love his look, his feel, his style.

And I think that's where we're going to get to. And I just think it's never been easier for companies right now, but it's never been harder because it's a big shift that they have to make and they have to invest in the resources and the mindset. And I see a lot of companies just over-investing in the wrong skill sets for where things are.

Yeah, it is interesting. And I know we're running long on this podcast. We could probably talk about this for quite a bit longer, but I have a decent following on LinkedIn, right?

And I am a smeeh in particularly areas of like industrial and IOT, but everything you're saying is the things I should be doing. And I guess I do do some of these things, but I guess I post for the wrong reasons just in general. Because I post because I'm researching a particular topic or I'm learning a particular thing.

And I like to add my context. If people like to read it, awesome. If they don't, I don't mind it.

But I would argue that that is what makes you stand out in the newsfeed because your posts are always out there. And I know when I... Here's what I know.

I know when I see Ira's post, I expect... I like the fact that I don't know what I'm going to get, but I do know what I'm going to get. I don't know what the topic's going to be, but I know I look at Ira as someone who's very curious and he's learning and you're not building in public.

You're learning in public as you go. Where there's others who I know when I see their content, oh, he's the carousel guy. Okay.

I've seen two or three of these. I know that there's not much value there unless the topic's interesting. But when I see your content, I'm like, oh, this is interesting because I know how you present it.

And if you look at YouTubers, there's a ton of these. There's YouTubers I follow that I don't even like the content. I like their style.

I like how they present things and so forth. And so I would argue that you're actually... You have a great case of that.

I think for you, it's just a matter of... And this podcast is going to help with that, doubling down and really enhancing your voice to reach more people now. Yeah.

And again, you know me. I like to talk, like to have conversations. I like to explore and I like to learn, right?

Because while I think I'm right about everything, trust me, I'm not. I'm not a lot. You remind me of that all the time.

So it's okay. We'll wrap this one up, but I guess we'll... Let's make up a new segment here on the fly.

Okay. So this is... Let me get your hot take on this.

Okay. Do you feel that... We'll go...

We'll really generalize this. In general, right now, do you think chat GPT is a shiny object or do you think it's actually something that people are sleeping on despite the buzz it has in the world right now? Do you think it's overkill or do you think it's...

Do you really think that people are still sleeping on it even though there's all this noise? This is a good one. So I 100% think that people are sleeping on it.

I don't think it's a shiny object. I think it is a shiny object that is actually shinier than people think. Do you think companies should be having emergency meetings about this right now?

Yes. I mean, frankly. Do you think they should be opening up budgets to find ways to either...

If they're even... They got to be allocated towards it? If you're considering any kind of digital strategy, anything, whether it be content, whether it be internal, committed to be whatever, I think you need to strongly be considering this and researching it and making it part of your plan if you didn't yesterday to make it today.

It's just that big. And... And what would you name that line item on the budget?

ChatGPT? Because ChatGPT is just an example. It's more of the idea and the concept of it.

So whether you're using... There's just so many models out there. And there's going to be many more to come.

But natural language processing in some way, shape, or form that you can have a conversation and get valuable information out. How is that not at the top of your list? Because of the productivity gains that you can get from it.

So how do you teach it? How do you utilize it? How do you integrate it?

If you're concerned about privacy and these other things, I get it. Figure out how to do it in private ways. And I'm sure there'll be lots of things coming down the pike.

But I think that companies should definitely be having strong meetings about this, emergency meetings. And I would consider it the future of the company as far as HR and data. Yeah, I agree.

So we'll end on a follow-up question. And all I need is just one word answer. I don't think I can do one word answers.

Two words, actually. It has to be two words at the middle, I guess. When we look at this, and this keeps me up at night, this is random, but I think about this a lot.

What do you think is the window of opportunity right now for companies to hop on this and really adapt? Because the window's closing. Every day, more and more things are coming out.

You've got that first mover advantage. And yeah, it might not look the same in six months, but there is an opportunity right now that's very small that the right people and the right companies can hop on and make millions, whether it's in revenue or pipeline, whatever, just by making those things before the competitors do. And then it becomes a, oh, we're going to hop in this as well, type of a strategy.

What do you think that is? One word. How long?

Oh, okay. Well, I can't give you a word. All right.

You're five words on it. Yeah, I can't give you one word. I told you I can't give you one word.

Because, well, here's the thing. Here's the thing you just asked, right? So how long?

So I think if you're going to be a consultant or something like this, I think you need to move moderately fast. And I know that's kind of goes against what I just said, but look, companies got to figure out- What's moderately fast mean? We talking 30 days, 60 days, six months?

I think six months to a year. Yeah, I do. You think that long, I think 60 days.

I think 60 days. But see, here's the thing. Who's going to integrate it in 60 days?

So you need the companies to have, that aren't going to be developing. Well, I'm going through the consultant, the individual- They need to get up to speed and things, but they're not going to get projects for six to 12 months. I mean, companies don't move fast.

So you're looking at enterprise- Exactly. More layers of tape and division. Yeah.

If you're looking at larger enterprise, the people that can really leverage this, they're not moving fast, right? So they need to be having meetings now so they can get a decision in six to 12 months so they can hire the consultant in 13 months. I know it sounds like a long time.

And in this world, it is a long time, but- That's like dog years. I get it. But there's a reason the government has websites from the 90s and the 2000s, right?

It just takes a long time to move a big ship. And it's not saying necessarily it's a bad thing. It just is a thing.

So that's my two cents. Yeah. Hopefully this will speed it up.

I think this is going to really change a lot of companies. Maybe that's a question we should query. We should go, should large enterprise consider chatGBT and say it in some sort of weird voice and see what it says.

Yeah. Yeah. Yeah.

We'll talk about that next week. And then yeah, we'll have Jameson on maybe next week or the week after. Hopefully he can answer more of this.

But yeah, otherwise, man, great catching up with you today. Good episode. A lot to think about, man.

As always, man. Appreciate it. I love this conversation.

I love the general nature of it. So yeah, let's keep on doing this. All right, man.

Awesome. Chat soon.