Deep Learning With The Wolf

The Honeymoon Phase

You know that feeling when you first open a chat with an AI?

It's magic. You ask something, it nails the answer. You ask for a tweak, it remembers your first request and incorporates it perfectly. You feel like you've found a thinking partner who's tireless, patient, and maybe just a bit witty.

Then… somewhere along the way… it changes.

By message 10, it's forgetting things you said two minutes ago. By message 20, it's making up facts or circling back to ideas you already rejected. By message 30, it's confidently making stuff up.

Welcome to context rot—the AI equivalent of your friend slowly zoning out mid-conversation.

Other Names for the Same Pain

It's not always called "context rot." Depending on who you ask, you might hear:

* Context decay – when details fade like old handwriting

* Lost in the middle – a nod to research showing AI often forgets what's buried in the middle of long inputs

* Token overload – the blunt, engineering way of saying "you fed it too much at once"

* Conversational drift – when the chat slowly wanders off-course

* AI brain fog – the meme version“I may have lost the thread, but I’m still confident.”

Voices from the Wild

I did a quick walk-through Reddit to find some frustrated users feeling this pain. These are all quotes from the past three months, lest you think recent model updates have magically solved this problem.

One user nailed the fundamental problem:

"I feel like maintaining context... is the biggest shortcoming of LLMs right now."

Another described the exact moment things go wrong:

"Context rot. If it's getting confused... start a new chat if the history is adding confusion instead of clarity."

Some treat it like AI exhaustion:

"Just like how you get brain rot, you'll give the poor LLM context rot. Quality over quantity is key."

Some describe the experience vividly:

"It's like explaining something to someone who's slowly falling asleep while you're talking."

Others point to the technical reality:

"Even with large context sizes, there are facts in the middle that can get missed—RAG helps fill the gaps."

And the statistical truth:

"The longer your context becomes, the more statistical confusion it will cause..."

Original source links at the end of this article.

Why the Rot Sets In

Picture the AI's context window—its working memory—like a whiteboard in a busy meeting room.

At first, there's plenty of space for clean, organized notes. But as the conversation grows, the board fills up with overlapping ideas, side comments, and tangents. Even though nothing gets physically erased yet, the important stuff becomes harder to find among the clutter.

Three main culprits drive the decay:

Too much noise Long chats mix relevant facts with small talk, rabbit holes, and random asides. The AI struggles to separate signal from noise.

Middle content amnesia Research confirms what users experience: models focus heavily on the start and end of conversations, while middle content gets fuzzy. It's like remembering the beginning and end of a movie but losing track of the plot in the middle.

Statistical confusion The AI isn't "thinking" like humans—it's predicting the next word based on patterns. Too much competing information clouds those predictions.

As one user explained:

"The longer your context becomes, the more statistical confusion it will cause because there are so many things to remember."

⸻

How to Stop the Rot: A Practical Survival Guide

Break It Up Long, meandering conversations are where performance nosedives fastest. Keep chats focused on a single goal. Example: Instead of one 50-message chat about "improving my website," start separate chats for "homepage copy," "SEO strategy," and "design feedback." Break down your needs into smaller pieces and start new chats for new tasks.

Summarize Before Moving On

When you start a fresh chat, give the AI a concise recap of the essentials:

* The current task

* Key facts or constraints

* Any important decisions already made

Think of it as handing your AI a cheat sheet before the test

Use External Notes

For ongoing projects—stories, codebases, research—store summaries in a separate document. Paste relevant sections into fresh chats instead of forcing the AI to dig through conversational archaeology.

One user's workflow:

"I save lore and characters in a text file. At the end of each session, I have it summarize the storyline and upload it into the new session."

Reset When It Wobbles

The moment it starts repeating mistakes or ignoring clear instructions, restart the chat. Don't try to coach it back on track—fresh context works better than corrections.

"The number one fix is to reset the chat after 3 failed attempts. Fresh context, fresh hope."

5. Use RAG (Retrieval-Augmented Generation)

This is a fancy way of saying: keep important information in a separate database and feed it in only when needed. Instead of stuffing everything into one conversation, the AI retrieves relevant bits at the right moment.

"Even with large context sizes, there are facts in the middle that can get missed—RAG helps fill the gaps."

The Bigger Picture

Context rot isn't just an AI quirk—it's a reminder that more information isn't always better. Whether you're chatting with AI or managing human projects, curation beats overload every time.

The most productive conversations happen when you remember: the AI is a powerful tool, not a patient therapist. It works best when you give it focused problems to solve, not sprawling life stories to unravel.

Next time you find yourself frustrated as your AI drifts off-topic, remember: it's not getting tired or rebellious. It's just lost in the maze of context you built for it.

The solution isn't to give up on AI—it's to become a better conversation architect.

Video version of this article:

Sources:

“I feel like maintaining context … is the biggest shortcoming of LLMs right now.”u/brown2green – r/LocalLLaMA (about 3 months ago)🔗https://www.reddit.com/r/LocalLLaMA/comments/1kotssm/i_believe_were_at_a_point_where_context_is_the

“Context rot. If it’s getting confused… start a new chat if the history is adding confusion…”u/Resident-Rutabaga336 – r/ChatGPT (recent months)🔗 https://www.reddit.com/r/ChatGPT/comments/1meey3b/we_all_can_relate_to_this

“Just like how you get brain rot, you’ll give the poor LLM context rot. Quality over quantity is key.” u/RPWithAI – r/JanitorAI_Official (3 weeks ago) 🔗 https://www.reddit.com/r/JanitorAI_Official/comments/1m7ext5/context_rot_large_context_size_negatively_impacts

“Even with large context sizes, there are facts in the middle that can get missed—RAG helps fill the gaps.” u/SkyFeistyLlama8 – r/LocalLLaMA (3 months ago) 🔗 https://www.reddit.com/r/LocalLLaMA/comments/1kotssm/i_believe_were_at_a_point_where_context_is_the

“The longer your context becomes, the more statistical confusion it will cause…”u/martinerous – r/LocalLLaMA (recent months)🔗 https://www.reddit.com/r/LocalLLaMA/comments/1f057ns/does_model_output_inherently_degrade_as_context

#ai #llms #contextrot #promptengineering #generativeai #rag #machinelearning #futureofwork #aidevelopment #nlp #deeplearningwiththewolf #dianawolftorres

Imagine you’ve missed two days of work. Not a week. Not a month. Just two days.

When you come back, the world has shifted. A new model has dropped. A breakthrough paper is everywhere. A tool you relied on has already been replaced by something faster, cheaper, and better.

For Kriti Goyal, this isn’t an exaggeration—it’s her daily reality as a machine learning engineer. “The pace is overwhelming,” she says. “If you step away for even 48 hours, it feels like you’ve missed so much.”

And yet, she speaks about it with something closer to awe than exhaustion. For her, this relentless speed isn’t just a challenge. It’s what makes working in AI exhilarating. It’s the reason she’s fascinated by the field’s rapid democratization: small, efficient models that no longer demand a supercomputer or a massive cloud bill to run.

“Today, a hospital can deploy its own model locally,” she explains, “and take care of its own privacy concerns without sending sensitive data anywhere else.” In her mind, this is more than a technical shift—it’s a quiet revolution, one that is pulling AI out of centralized labs and placing it directly into the hands of those who need it most.

The Ice Sculpture Principle

Kriti has a favorite metaphor for her work: “AI is like an ice sculpture—it has to hold under pressure and work flawlessly.”

She laughs when she says it, but she’s not joking. It’s her way of describing the unforgiving nature of production AI. Demos are easy; anyone can hack together a proof of concept that works in ideal conditions. But real-world systems? Those are built to withstand heat lamps, impatient users, and the occasional hammer someone swings at your creation just to see if it will break.

“Building a demo is one thing,” she says. “But turning that into something reliable, something that people can actually trust, is a completely different challenge.”

That mindset—part precision engineering, part entrepreneurial grit—shapes how she sees the future of AI: tools that are not only powerful, but robust, private, and safe enough to be trusted in mission-critical environments.

From CV to NLP: A Personal Journey

Kriti didn’t set out to become a machine learning engineer. Her path started in computer vision, pulled in by professors whose enthusiasm for the field was contagious. “They showed me how much you could do with images and algorithms,” she recalls. “It was like magic, but grounded in math.”

Back in 2019, much of her work was rooted in traditional machine learning. “We were still in this world of feature engineering and heuristics,” she says. “Rules were easier to understand.” But as deep learning swept in, everything changed. The models became larger, the methods more complex, and the once-clear boundaries between CV and NLP began to blur.

That transition, she says, was both exhilarating and daunting. “The field was evolving so fast that you had to evolve with it. It wasn’t just about keeping up with the papers—it was about constantly rethinking how you build.”

It was this relentless pace that sharpened her instincts for efficiency, infrastructure, and scalability. She didn’t just want to build models—she wanted to build systems that could run those models faster, cheaper, and more reliably.

Networks, Not Job Boards

In today’s AI job market, one posting can attract a thousand applicants in a single day. “You can’t rely on applying cold,” Kriti says. “Networking is how you stand out.”

It’s not a theory—it’s how she’s built her own career. She speaks candidly about the cultural shift she experienced after moving to the U.S. “In India, companies come to you,” she explains. “Here, you have to hustle. You didn’t grow up in this culture, so you have to learn it. It’s not a complaint—it’s just the reality.”

For her, that reality became a strategy: connecting with peers, staying visible in the field, and building relationships both inside and outside of the workplace. “Networking isn’t just for job hunting,” she adds. “Even if you take time off between college and grad school, or you’re early in your career, those connections matter. They’re what lead to opportunities—especially the early startup roles that never make it to job boards.”

This is why, when asked what advice she’d give to young engineers, she doesn’t hesitate: “Start building your network now. Not later. Now.”

Write Your Way Into the Field

If Kriti has one piece of advice that surprises engineers, it’s this: don’t just build—write.

“Put your work on GitHub,” she says, “but don’t stop there. Write about it. Give your smart take on what you’ve built.”

To her, visibility in AI isn’t just a matter of posting code or linking to a project. It’s about adding context—explaining what you learned, why it matters, and how you approached it. That, she argues, is what turns a side project into a signal of expertise.

She even cites a favorite quote—attributed to Benjamin Franklin: “Either write something worth reading or do something worth writing.” For Kriti, the best engineers do both.

“This is how you get noticed,” she says. “Not just by recruiters, but by the community itself. Writing forces you to think clearly, and it helps other people see how you think. That’s what opens doors.”

The Future of AI (and the Ice Sculpture That Won’t Break)

When Kriti looks ahead, she doesn’t see a future dominated by ever-larger models. She sees a world where AI becomes smaller, faster, and closer to the people who need it most.

“Not every problem needs a 500-billion-parameter model,” she says. “Smaller models that you can fine-tune and run locally—that’s where so much of the opportunity is.” Hospitals are her favorite example: privacy is non-negotiable, so the ability to keep data on-device isn’t just a convenience—it’s a breakthrough.

But what excites her just as much is what most people overlook: the difference between building a demo and building a product.

“Building a cool AI demo over the weekend is like creating an ice sculpture,” she explains. “It’s beautiful, it gets ‘oohs’ and ‘aahs’ in a controlled environment—but it’s fragile and melts under pressure.”

The real challenge? Building something that doesn’t melt. “A real product is like a bridge,” she says. “It has to withstand storms, carry immense traffic, and work flawlessly millions of times without a catastrophic failure.”

This, she adds, is the unglamorous side of engineering: defensive design, not just to make things work—but to make them safe. “You’re preparing so your bridge can get nuked, and you still have to prevent the bad actors from taking down your product or harming users.”

And yet, for all her precision and discipline, Kriti remains deeply optimistic. For her, this isn’t just a field—it’s a craft. A craft that rewards speed and rigor, yes, but also creativity, collaboration, and the quiet discipline of engineers who keep showing up, carving the details, and building something that lasts.

Build Tools That Last

Two days. That’s all it takes to feel behind in AI. But for Kriti Goyal, that pace isn’t a warning—it’s an invitation.

Because while the tools may change every 48 hours, the principles don’t: build things that matter, build them to last, and never stop learning. From fine-tuned hospital models to the “ice sculpture” reliability that production AI demands, her world is proof that speed and craft can coexist—if you’re willing to keep carving.

And maybe that’s the real lesson. AI isn’t just racing forward. It’s also being shaped, one decision, one model, one engineer at a time. And in a field where change never slows down, that kind of steady hand is exactly what endures.

Interested in connecting with machine learning engineer Kriti Goyal ? You can find her on LinkedIn. Her technical expertise is remarkable—but just as importantly, she’s generous with her insights and a genuinely thoughtful human being.

#ai #machinelearning #mlengineering #techcareers #deeplearning #modeldeployment #trustworthyai #aiforhealthcare #scalingai #privacybydesign #deeplearningwiththewolf #dianawolftorres #kritigoyal

NotebookLM has been my quiet productivity companion for months. I used to wrestle with recording my own podcasts — multiple takes, second-guessing every syllable, and worst of all, hearing my voice on playback. (All of us can relate to being our own worst critic.)

Then NotebookLM introduced audio overviews, and everything changed. No more late-night re-records. No more wondering if I sounded like I had a head cold. Just AI-generated audio summaries that let me focus on the content instead of the mechanics.

Now, Google has taken the next step: Video Overviews.

But before you imagine instant Hollywood-level magic, let me be clear: this is still day one. And on day one, even the best AI tools have their quirks.

When Research Becomes a Movie (Sort Of)

Video Overviews take your sources — PDFs, Google Docs, web pages, even YouTube transcripts — and spin them into AI-narrated slideshows with visuals, diagrams, and key excerpts. It’s not flashy animation, but it’s surprisingly good at transforming text-heavy materials into something that feels (more or less) watchable.

For my “first attempt” video, I used the “Discover” feature on NotebookLM, (a feature that seems to be limited to the desktop version only.) With this feature, Notebook will do your research for you. You need only bring your concept.

I wrote a simple prompt telling NotebookLM I wanted a video about NotebookLM. It very quickly found ten sources, (and more isn’t always better. I will explain in a moment.)

I clicked “Generate” and… waited. And waited. Somehow, I didn’t realize I’d clicked the Generate button again. All total, I ended up with three videos. Oh, that would explain the wait. (Other users, though, reported an average wait time of 12 minutes per video.)

Since I had three videos, I went through them to see the results. And… it was like watching a bunch of PowerPoint presentations about NotebookLM. (Yawn.) I couldn’t even get through them all, so I won’t torture you with them here.

OK, this will NOT do.I used all of those sources to create a “Briefing Document” in NotebookLM and then created this article. I then used this article to create the Video overview.

And, then I was able to create an interesting Video Overview.

So, what did I learn?

I wouldn’t call it “garbage in, garbage out,” as all of those sources were accurate. More like “stuffy and uninteresting in” and “stuffy and uninteresting” out.

The video overview can only generate “good stuff” from “good stuff.”

How to Get Started with Video Overviews

If you want to try it yourself, here’s the quick path:

* Upload your sources (PDFs, Docs, or even YouTube links) into NotebookLM.

* Select “Video Overview” in the new Studio panel.

* Add a steering prompt (e.g., “Explain for beginners” or “Focus on financial trends”).

* Click generate — then be patient. (Coffee helps.)

* Review and refine. You can adjust prompts or generate multiple versions until it’s right.

Pro Tip: Start with smaller documents before you throw a 200-page market report at it.

What You Can Do With NotebookLM

You can use NotebookLM for a wide range of tasks, from breaking down complex research papers into digestible summaries to creating study aids like video overviews and mind maps. Educators can turn lesson materials into structured multimedia content, while students can generate simplified explanations or exam review guides. In business settings, it can summarize financial reports, prepare briefing documents, or create quick training resources. Even for personal learning, NotebookLM can organize and explain dense topics, helping transform scattered sources into clear, actionable insights.

How Video Overviews Differ From Audio Overviews

Video, obviously. But beyond the fact that you can actually see things, Video Overviews go further than their audio-only cousins. While Audio Overviews provide quick, podcast-style summaries you can listen to while folding laundry, Video Overviews turn your source materials into narrated, slide-style presentations. This makes them especially useful for explaining charts, diagrams, and other content that benefits from visuals. The voice used in Video Overviews is also different from the two familiar voices in Audio Overviews, and while it currently has fewer style options, it delivers a clear, structured experience that works well for topics where “just listening” isn’t quite enough.

How Will This Help Me?

Before I started to use NotebookLM for my podcasts, I recorded them myself. Picture me - usually in my shed, as I attempted to find a quiet spot- surrounded by too many helmets and a lot of paint. It took me multiple takes to get a single podcast done, sometimes taking hours. All of this took time away from writing. In the "video overview,” they describe it as “pure fun.” Eh, that’s a liberal interpretation. Creating a podcast is hard work, and I did it as a way to help promote the newsletter. But, ironically, it took precious time away from the newsletter.

So, when Google burst onto the scene with their AI tool that could record podcasts for me, I happily turned over the mic. More time for writing? Yes, please. But, this wasn’t just about freeing me from a task that was often frustrating. Audio overviews created extra hours in my workflow.

With those extra hours, I made THE DROIDS NEWSLETTER. Now, my son has joined me as part of the editorial team. It’s been a fantastic project, and all of it happened because I found a few extra hours in my week.

Final Thoughts- whether to video or audio?

NotebookLM’s Video Overviews won’t replace human insight — but they are another tool to help break down your research. Research feels less static. Learning feels less one-dimensional. Even the dreaded quarterly report starts to look… almost approachable.

Now, this being said, there are times when I still want audio. Each of these tools has its time and place. I could envision myself creating these videos when I want to create quick little “explainers.” (Google has another great tool called “Google Vids,” also just launched, that is excellent for creating explainer vids. I’ve been on the Google Labs testing team for that one for over a year and highly recommend it.)

But, a few minutes ago, I spotted an announcement from Google DeepMind and a new paper about the AlphaEarth AI model. Secret confession: I love listening to academic papers as I fall asleep at night. So, within a few minutes, NotebookLM had generated a 12-minute audio overview of AlphaEarth. Perfect. Can’t wait to hear my latest bedtime story from Google.

It’s not magic, but it’s a glimpse of how a research tool can improve your daily life.

Fun Facts (Because Why Not?)

* 🎙 I have three Spotify channels, two YouTube channels, and two newsletters. So, yes, I do a lot of research.

* 🎧 There are two Spotify channels named “Deep Learning with the Wolf” — a quirk of Spotify’s RSS feed system. Long story. No regrets. Both are great. There are no wrong choices here.

* 🏒 I was once a DJ at 89 WGSU Geneseo and the “Ice Knights” hockey color commentator. Fun twist: the first hockey game I ever saw was also the first one I called live. Turns out, improv is a life skill.

#deeplearningwiththewolf #thedroidsnewsletter #googlenotebooklm #googledeepmind #audiooverview #videooverviews #dianawolftorres #alphaearthfoundations

Yesterday, I shared my first real adventure with AI agents—specifically Perplexity’s #Comet—and how it helped me crank out a surprising number of “mini-articles.” (I’ll explain that experiment in more detail soon.) While I focused mostly on the hilarious moment when Comet got hopelessly lost on the Ideogram site—like a digital puppy chasing its tail—I probably didn’t give enough credit to what it did do well.

One real win: Comet pulled some excellent sources on the shifting landscape of childhood in the age of AI.

And the timing couldn’t have been better. Kaspersky just dropped a new report exploring what kids’ online lives really look like in 2025. From screen time to digital friends to new threats, the report unpacks the latest trends—and the growing need for awareness as AI weaves deeper into everyday life.

Childhood in the age of AI looks nothing like it did a few years ago. Kaspersky’s just-released report unpacks the newest shifts in kids’ online lives—highlighting what’s changing, what’s trending, and what to watch out for.

* AI curiosity more than doubled: Over 7.5% of all kids’ searches are now AI-related, up from just 3.19% last year.

* Character.AI breaks out: First time in the Top 20 kid-used apps, alongside rising interest in ChatGPT and Gemini.

* YouTube holds the crown: Maintains #1 spot as the most-used app, with usage rising to nearly 30%. WhatsApp overtakes TikTok for #2.

* Gaming and memes boom: Browser games like Sprunki and meme-driven humor set the pace for digital youth culture.

* Streaming apps remain strong: Nearly one in five searches are for streaming platforms—including Netflix and Disney+.

* Risks increase: Kids encounter more complex, sometimes inappropriate, AI content, sparking new safety concerns.

* Kaspersky’s advice: Keep communication open, educate on cyber hygiene, and use digital monitoring tools for safe exploration.

The digital world won’t wait for us to catch up. It’s time to rethink digital literacy and safety for a generation that’s truly growing up AI-native.The Full Report from Kaspersky- What Kids Are Searching in 2025.

#OnlineSafety #AIParenting #KasperskyReport #DigitalLiteracy #RaisingDigitalNatives #FutureOfChildhood#DeepLearningWithTheWolf #DianaWolfTorres

Today was supposed to be a standard writing day: me, coffee, AI headlines, and one short conference call.

Plan: Execute.

Instead, during that one call:

🧠 OpenAI dropped the ChatGPT Agent—a fully agentic AI that can browse the web, click buttons, fill out forms, and build docs or slides. In short, it can do things, not just talk about them.

🌠 Simultaneously, Perplexity granted me access to Comet, their new agent that lives inside your browser. I’d been on the waitlist, and I’d volunteered for testing, so maybe I stacked the deck. Either way, it cheerfully just appeared in my browser just as OpenAI was promising us the future.

An agent war, announced in real time, while I was blowing the steam off my coffee.

Is This Even Real?

Naturally, my first reaction was suspicion. The Comet app immediately requested access to all my Chrome passwords.

Wait—what? It felt like the start of a phishing scam: target nerds who love early tech, trigger a browser pop-up, and ask for access to the Chrome keychain. Deviously clever.

ChatGPT is my go-to tech support these days. I asked: “Help me verify this.”

Chat took the job seriously. We opened Terminal windows, ran security checks, and verified installation paths. (It passed.) It even explained how I could run Comet without giving it access to every password I’ve ever saved.

So I let Comet in… with conditions. No, Comet, you may not know my entire online life. You can log into Perplexity, sure. But everything else? You’ll have to earn that level of trust.

Comet asked if I wanted it to be my default browser. Comet… we just met. We can’t already be besties. (I mean, I do have a second laptop, so maybe there’s room for something to blossom. But let’s not rush it.)

Agents at Work (Sort Of)

I’ve been writing a lot of mini-news stories lately. Think AI and robotics headlines—short, timely, useful. They take time to research, write, and package, especially when paired with original artwork.

This seemed like a perfect test.

I asked Comet to help me:

* 🧠 Find good stories

* 📝 Draft them using my format and subtitle structure

* 🎨 Generate matching images

It did surprisingly well on the first two. Fast, competent, and formatted exactly as I requested. For a first run? I was impressed.

Then came the artwork.

When “Integration” Isn’t

I noticed a little “Ideogram” tab in the Comet sidebar. Exciting! This looked like a direct integration—a seamless way to generate images without leaving the tool.

So I gave Comet my artwork style prompt and told it to get to work.

I give it a solid B- for trying very, very hard. (Chat wanted to give Comet and "F" for failing the assignment. Seriously, Chat?)

Comet navigated to the Ideogram website, but from there, it absolutely lost the plot. It couldn’t find the “Create” button. It kept getting lost in the navigation of the page and scrolling endlessly through the artwork of the public pages. I mean, I do that, too, when my blood sugar is low and my attention levels are shot.

Comet narrated its journey with an epic monologue worthy of those first 100 pages of LOTR. You know, a story that kind of goes on and on and on and on and on... and you wonder? Where is this going?

It landed on an account named “Generate” and tried to interpret that as a verb. It gave itself pep talks in long internal monologues, scrolling aimlessly and narrating the experience like a lost tourist reading every street sign aloud.

Eventually, I stepped in and said, “The button’s the plus sign in the black circle. Bottom of the page.”

More scrolling. More monologuing. Finally, Comet stopped and told me:

“You can generate your image now.”

Oh. Thank you. For… warming up the interface?

That saved me a LOT of time.

Hooray agents?

What Went Wrong?

Chat tattled on Comet: it didn’t have API access. That was the issue.

I’d been feeding ChatGPT screenshots of Comet’s flailing attempt to use Ideogram, hoping it could help me troubleshoot. I could have asked Perplexity support, but that would’ve returned 37 scholarly articles, six GitHub links, and a whitepaper. Chat, at least, gives me a straight answer—eventually.

Here’s what we pieced together: Comet couldn’t click buttons, verify logins, or pass prompts inside Ideogram. That level of access usually requires APIs or some kind of built-in integration. Comet had a front-row seat to Ideogram, but no backstage pass.

Sure, I could’ve done it the developer way—via API—but I’m a writer. I don’t want to manage tokens. I want to say: “Write the article. Make the picture.”

And then go work on something fun in my shed.

That’s the promise of agentic AI. But today? We’re not quite there.

Not a failure. Just a reminder: agents still have to learn which doors push and which ones pull.

So What Can They Do?

Honestly? A lot. But not everything.

Agents like Comet and ChatGPT Agent represent a shift from language-only AI to actionable AI—systems that can complete complex, multi-step tasks without you micromanaging each step.

But they’re still learning the terrain.

* They can write.

* They can search.

* They can follow templates and click around familiar apps.

But:

* They struggle with unfamiliar interfaces.

* They can’t always verify session states or pass security barriers.

* They still need you in the loop.

Today was a good reminder that the future is here—but it still needs a human holding the map.

And, also today...

Open AI Introduces ChatGPT Agent

At first glance, the ChatGPT Agent announcement might look like just another upgrade. But today’s news marks something far more transformative. This isn’t just a smarter chatbot. It’s an AI that does things.

The new ChatGPT Agent combines several earlier experimental features—like web browsing, code execution, and file handling—but adds the ability to interact with websites, fill out forms, click buttons, and build full documents or slide decks… all within a secure, sandboxed virtual machine inside ChatGPT. Think of it like giving your AI a mouse, keyboard, and private desktop—and watching it go to work on your behalf.

You can hand it a task like:

* “Book me a flight under $300 from SFO to LAX.”

* “Research a list of AI tools for education, compile a Google Doc, and draft an intro email.”

* “Generate a chart using my uploaded CSV, insert it into a slide deck, and write speaker notes.”

The kicker? It asks before doing anything consequential. This isn’t a runaway script. It checks in before sending emails or making purchases.

OpenAI calls this a “fully agentic AI.” And while it’s early days, the direction is clear: ChatGPT isn’t just an assistant anymore. It’s aiming to become your AI teammate—one that’s helpful, autonomous (with boundaries), and capable of navigating the same internet you do.

* Agents are real—they’re not coming tomorrow, they’re live today.

* This is the next step in AI: from answering to acting.

* Comet showed promise—it just needs integration polish.

* GPT-4o+Agents can already speed up heavy-lifting tasks—research, formatting, packaging.

And me? I still had to do the thinking, editing, a whole lot of rewriting- and yes- explain why Comet got stuck so badly it made me laugh. It took me back to gently coaching elementary schoolers—and I’m grateful for the reminder that assistants might show up… but they don’t replace the teacher.

#ChatGPT #OpenAI #PerplexityAI #CometAI #AgentFails #RobotAssistant #HumanInTheLoop #WritersLife #DeepLearningwiththeWolf #DianaWolfTorres #Perplexity #ChatGPTAgent

Imagine waking up one day to find that your face has been used in a video you never authorized—perhaps endorsing a product you detest or uttering words you never spoke. As AI-driven deepfakes blur the line between reality and fabrication, Denmark is stepping forward with a bold, pioneering law that might just change the way we own ourselves in the digital era.

In an era where your likeness can be copied, manipulated, and weaponized with alarming ease, Denmark is preparing to become the first country in Europe to grant citizens copyright-like control over their own faces, voices, and bodies. This radical legal shift, championed by Culture Minister Jakob Engel-Schmidt, seeks to transform personal identity from an intangible social fact into a form of intellectual property. The proposal aims to empower individuals with unprecedented rights to their physical selves—rights that, until now, belonged mostly to corporations or creative industries.

The Anatomy of a New Law: What Denmark Is Changing

At its core, the proposed law rewires the traditional boundaries of privacy and copyright. It would treat your face, voice, and bodily presence as if they were creative works, much like a musician owns a song or a painter owns a canvas. This means:

* Ownership of Your Likeness: Your physical identity—face, voice, and body—would legally belong to you. Any replication by AI systems without your consent could be deemed an infringement, granting you control over how your digital “self” is used.

* Deepfakes Under the Legal Lens: AI-generated deepfakes—highly realistic digital recreations of individuals—would be treated similarly to pirated media. The law would prohibit the creation and dissemination of deepfakes without explicit authorization, giving victims the power to demand removal of unauthorized content.

* Civil Enforcement Rather than Criminal: Unlike criminal statutes elsewhere, Denmark’s approach is civil. Victims can issue takedown demands and seek compensation through civil courts. Platforms failing to comply face severe fines, but individual offenders won’t face jail time.

How Will This Play Out in Practice?

The mechanism closely resembles the familiar DMCA takedown system used for copyrighted content online:

* If someone crafts a deepfake using your likeness without permission, you can issue a formal takedown request to the hosting platform.

* Platforms that do not remove infringing content risk hefty fines and possible enforcement actions coordinated with the European Union.

* Victims can pursue monetary damages under existing compensation frameworks.

* Crucially, parody and satire remain protected, ensuring that the law respects freedom of expression and comedic critique.

Why This Matters: A Paradigm Shift in Digital Rights

Denmark’s initiative represents a legal innovation born out of necessity. The rapid advance of generative AI technologies has exposed gaps in existing legal frameworks. Traditional privacy laws struggle to tackle the novel challenge of identity manipulation at scale, while copyright law has not conventionally recognized one’s own likeness as property.

By elevating the physical self to a form of intellectual property, Denmark offers a template that blends privacy, personality rights, and copyright into a cohesive new category. This approach:

* Pioneers a New Model: Denmark could become the first European nation—and among the very first globally—to enact such sweeping digital identity protections.

* Responds to Technological Reality: With AI capable of producing convincing fakes in seconds, a stronger legal shield is urgently needed.

* Signals EU-Wide Ambitions: Denmark plans to leverage its upcoming presidency of the European Union to promote this model, potentially influencing policy across the continent.

Global Context: How Denmark’s Law Stacks Up

Across the world, governments are grappling with deepfake challenges but with varying strategies:

Denmark’s civil, copyright-like framework contrasts with the criminalized, punitive regimes elsewhere, emphasizing individual control over coercive penalties.

The Road Ahead

The bill is currently in public consultation with formal parliamentary introduction expected this autumn. If enacted, it will position Denmark as a trailblazer in digital identity rights, potentially influencing legislation far beyond its borders.

Yet, challenges remain:

* How will courts interpret “ownership” of one’s likeness?

* Will platforms globally comply or resist such laws?

* Can satire and free speech maintain a protected space amidst stricter controls?

Vocabulary Key

* Deepfake: AI-generated media that realistically mimics a person’s appearance or voice.

* Intellectual Property (IP): Legal rights that protect creations of the mind, like inventions, designs, and artistic works.

* Takedown Request: A demand to remove content that infringes rights, often used in copyright law.

* Civil Enforcement: Legal actions that involve lawsuits or fines but not criminal prosecution.

* Parody and Satire: Forms of expression that imitate or humorously critique, often protected under free speech.

Reflecting on Identity in the Age of AI

Denmark’s bold experiment forces us to rethink what it means to “own” ourselves in a digital age where identity can be copied, manipulated, and sold without our consent. Beyond legal technicalities, this law taps into a profound human desire for agency over our own image—the face we present to the world, both offline and online.

As AI technologies grow more powerful, they challenge the very essence of authenticity and trust. Denmark’s approach does not merely react to a technical problem; it anticipates a future where our digital selves become assets, and where protecting that identity requires new legal imagination.

This is more than copyright law—it is a declaration that in the tangled web of algorithms and pixels, the individual must remain sovereign over their own face. The wolf is calling: follow Denmark’s lead, and join the global conversation about how to protect what makes us uniquely human in the AI era.

FAQs

* What rights would the new Danish law grant to citizens?It grants copyright-like ownership over one’s face, voice, and body, allowing legal control over unauthorized AI-generated use.

* How would the law handle deepfakes?Deepfakes created or shared without consent would be considered copyright infringement, allowing victims to request takedowns.

* Are there any criminal penalties under this law?No, the law is civil. Victims can seek removal and damages, but no jail time is involved.

* Does the law protect parody or satire?Yes, comedic or critical use is explicitly exempt from infringement claims.

* Could this law influence other countries or the EU?Yes, Denmark plans to promote this model at the EU level, potentially shaping future AI and digital rights policies.

Additional Reading for Inquisitive Minds:

Deepfake Laws and Digital Identity Protections

For readers interested in exploring the legal landscape and policy details behind Denmark’s deepfake law and related international efforts, here are reputable sources in MLA format with clickable links:

Denmark’s Deepfake Law

* “Denmark proposes landmark law to protect citizens from deepfake misuse.” CADE Project, 1 July 2025. Read here.

* “Denmark fights back against deepfakes with copyright protection: What other laws exist in Europe?” Euronews Next, 30 June 2025. Read here.

* “Denmark wants you to copyright yourself. It might be the only way to stop deepfakes.” Fast Company, 3 July 2025. Read here.

* “Danes Could Get Copyright to Their Own Image Under AI Bill.” TIME, 27 June 2025. Read here.

* “Denmark taking steps to boost protections against deepfake images.” AP News, 27 June 2025. Read here.

France’s Deepfake Law

* “France prohibits non-consensual deep fakes.” JD Supra, 15 July 2024. Read here.

* “France: Bill Introduced to Require Labeling of AI-Generated Images on Social Networks.” Library of Congress, 7 March 2025. Read here.

* “Deepfake laws: Global regulations in the digital age against misinformation.” Yoti, 11 September 2024. Read here.

UK Deepfake Laws

* “Creating deepfake porn to be made a crime in UK under ‘first-of-its-kind’ law.” Euronews Next, 17 April 2024. Read here.

* “Government crackdown on explicit deepfakes.” GOV.UK, 7 January 2025. Read here.

* “Government cracks down on ‘deepfakes’ creation.” GOV.UK, 16 April 2024. Read here.

* “Campaign win: law to stop deepfake abuse.” End Violence Against Women Coalition, 12 March 2025. Read here.

USA: Take It Down Act (2025)

* “Text - S.146 - 119th Congress (2025-2026): TAKE IT DOWN Act.” U.S. Congress, 19 May 2025. Read here.

* “S.146 - TAKE IT DOWN Act 119th Congress (2025-2026).” U.S. Congress, 19 May 2025. Read here.

* “‘Take It Down Act’ Requires Online Platforms To Remove Deepfakes.” Skadden, 1 June 2025. Read here.

* “TAKE IT DOWN Act Passes the House, Heads to President Trump’s Desk.” U.S. Senate Committee on Commerce, Science, and Transportation, 28 April 2025. Read here.

Podcast Note: The voices you hear are 100% AI-generated using NotebookLM. I love my virtual podcasters—they’re smart, fast, quirky, don’t drink my coffee, and live solely in the digital universe.

#ai #deepfakes #digitalidentity #copyrightlaw #intellectualproperty #deeplearning #aipolicy #dataprotection #techlaw #futureofai #privacyrights #digitalrights #aitech #innovation #ethicsinai

In the Field

Robotic house-printing isn’t just a flashy proof of concept anymore—it’s industrialized real estate. Systems capable of printing everything from foundations to roofs are moving from pilot sites to livable communities, reshaping construction with autonomy and precision.

Phoenix & Vulcan: ICON's Robotic Gantries

ICON’s Vulcan gantry printer and next-gen Phoenix boom arm are full-structure robotics platforms—capable of delineating walls, infrastructure embeds, and even roofs.

* Vulcan covers ~280 m² at 5–7 in/min using proprietary Lavacrete via BuildOS.

* Phoenix extends to multi-story builds, reinforces with wire extruders, halves setup time, and slashes cost-per-square-foot to ~$25–80.

These systems have already fabricated homes in Phoenix and Georgetown and are now building a 43-unit desert hotel in Marfa, Texas.

Global Players Hitting Field Deployments

* Apis Cor: A newer player in construction robotics, Apis Cor is just beginning to deploy its portable 3D-printing robots in the U.S. and internationally. The company gained global attention by winning NASA’s 3D-Printed Habitat Challenge with SEArch+, showcasing its innovation in autonomous habitat construction. While Apis Cor’s commercial projects are still emerging, their technology and NASA win mark them as a company to watch.

* Luyten 3D: Delivered a functional two-story print in Australia in 32 hours using the AI-enabled Platypus X12.

* WASP: Italy’s bio-material robotic printing lab printed the TECLA house from clay with modular dual-gantry arms.

Challenges

While 3D printing homes is often celebrated for its speed and innovation, not everyone is convinced the technology is ready to revolutionize construction. In the popular YouTube video "Why 3D Printing Buildings Leads to Problems," Stewart Hicks outlines several hurdles that remain for large-scale adoption.

“There’s quite a few challenges that are getting in the way, and frankly, the buildings made like this... they look a little weird. Companies across the world are trying to solve these problems by racing to make the process scalable, affordable, sustainable, and palatable to people that would just prefer living in a more traditional looking home.”- Stewart Hicks, Architectural Design Educator

Hicks points out that 3D-printed structures face design and material limitations. For example, unlike bricks, 3D-printed concrete can’t easily create sharp 90-degree corners, often resulting in curvy exterior shapes. Openings for doors and windows require extra support, and the tolerance for construction errors is much tighter than in traditional building—meaning small mistakes can have big consequences. Integrating standard building components, like windows and cabinetry, into the uneven surfaces of printed walls can be difficult, leading to gaps or awkward finishes.

He also highlights practical concerns about maintenance and flexibility:

“If anything happens to the 3D printed part of the structure, it’s almost impossible to repair it back to its original state. What are you going to do, bring out that giant machine? Additions or renovations are all the same thing.”1

Finally, Hicks notes that most 3D printing companies are highly vertically integrated, making it hard for outside architects or builders to work with the technology or modify printed homes in the future. For now, he argues, these challenges mean 3D-printed buildings are still a work in progress, with important questions left to answer before they become a mainstream solution.

Closing Reflection

I find these 3D-printed homes completely fascinating. The idea that a robotic system can fabricate a real, livable structure—walls, roof, and all—is awe-inspiring. But what excites me even more is the idea of living in one.

As an environmentalist, I like the “green” aspect of these homes. (Or, maybe “greener” is a more accurate term.)

3D-printed homes can:

* Drastically reduce material waste, since extrusion systems use only what’s needed.

* Use low-carbon materials, like ICON’s Lavacrete or WASP’s clay-based compounds.

* Minimize transportation emissions by building on-site from local or modular inputs.

* Lower energy consumption during production compared to traditional construction.

* Enable passive, efficient designs thanks to complex curves and insulating geometries.

At the same time, I’m fully aware that these systems still face challenges—whether it’s tolerance for error, integrating standard parts, or scalability. As Stewart Hicks points out, 3D-printed homes can feel unfamiliar to traditional tastes, and retrofitting or repairs raise real issues.

Still, I remain optimistic. These hurdles don’t diminish the potential—they sharpen the focus. If robotic construction can overcome them, we won’t just be printing homes. We’ll be prototyping a better relationship between people, machines, and the built environment.

#Robotics #3DPrinting #ConstructionTech #AutonomousSystems #BuildOS #ICON #DigitalTwins #ArchitectureAutomation #FutureOfHousing #DROIDs

The Shortcut That Comes at a Cost

We live in an era of infinite shortcuts. ChatGPT drafts our essays, summarizes articles, and gives feedback with a keystroke. But in this age of intelligent convenience, a quieter question has emerged: What is AI doing to the human mind it’s assisting?

A working paper from MIT’s Media Lab titled “Your Brain on ChatGPT: The Accumulation of Cognitive Debt” answers that question with real data—and real brainwaves. Through EEG scans, essay analysis, and memory testing, the study shows that when people write with ChatGPT, their brains work less. Neural connectivity drops, memory declines, and users struggle to recall or reflect on their own work.

“The LLM condition showed the weakest brain connectivity and learning outcomes.” (MIT Media Lab, 2025)

And the metaphor researchers propose is as memorable as it is cautionary: cognitive debt. The idea that we’re borrowing mental effort from the future—at a cost.

🧬 Inside the Experiment

MIT recruited 54 participants and split them into three writing conditions:

* LLM Group: Wrote essays using ChatGPT

* Search Group: Used Google for research, no AI assistance

* Brain-Only Group: Wrote unaided, relying solely on their own thinking

Each participant wore EEG sensors to monitor brain activity, while their essays were analyzed for linguistic complexity, originality, and coherence. After writing, they were asked to recall and explain their own arguments.

“We observed a measurable reduction in alpha and beta wave activity—signals associated with attention and active cognitive processing—in the LLM group.” (MIT Media Lab, 2025)

📉 What the Brain Does—And Doesn’t Do—With AI

Participants in the brain-only group had the strongest engagement in brain regions tied to synthesis, critical evaluation, and memory encoding.

“Those who used their own brains to write—unaided—showed stronger connectivity in parietal and prefrontal regions associated with synthesis, evaluation, and memory encoding.” (MIT Media Lab, 2025)

LLM users, meanwhile, produced essays that looked fluent—but were cognitively hollow.

“Despite producing grammatically coherent essays, LLM users were less likely to understand or remember their content minutes later.” (MIT Media Lab, 2025)

In fact, many could not recall their own thesis or cited sources moments after submission.

“LLM usage impaired not just memory retention, but also the ability to reflect on and recall one's own writing.” (MIT Media Lab, 2025)

💬 Ownership and Originality

Even more concerning was the drop in ownership and originality. Essays written with AI were linguistically flatter and structurally repetitive.

“Participants using LLMs produced essays with lower linguistic complexity and originality.” (MIT Media Lab, 2025)

Students also expressed emotional detachment from the final product.

“Students reported feeling a lack of ownership over work completed with AI assistance.” (MIT Media Lab, 2025)

This aligns with broader findings: writing isn’t just output—it’s thinking. And offloading that process weakens internal reflection.

🔄 The Switch Test: Can We Bounce Back?

In a fourth session, some participants switched groups. Brain-only writers got access to ChatGPT; LLM users had their tool removed.

“In the final session, participants who had been using LLMs struggled to re-engage their cognitive faculties after the tool was removed.” (MIT Media Lab, 2025)

Conversely, those who started with their own thinking continued to engage critically even when given AI tools. They seemed to use LLMs strategically, not passively.

“This suggests that reliance on LLMs may hinder the neural development of critical thinking and reflective writing.” (MIT Media Lab, 2025)

🧾 Cognitive Debt: A Framework for the AI Age

The study doesn’t call for banning ChatGPT. Instead, it proposes a powerful framework: cognitive debt. Like a credit card for the brain, the metaphor captures the seductive convenience and subtle cost of outsourcing thinking.

“We propose the term cognitive debt to describe the cumulative disengagement and reduced learning observed in LLM-dependent workflows.” (MIT Media Lab, 2025)

Used wisely, AI can amplify learning. Used blindly, it can dull the very faculties we hope to develop.

🔮 Toward an AI-Augmented Mind

The future lies in cognitive design—teaching people how to use AI in ways that build rather than bypass thinking. That means:

* Drafting by hand before refining with AI

* Using ChatGPT as a coach or partner, not a ghostwriter

* Building AI literacy into every level of education

Because at the end of the day, the goal isn’t to write better essays—it’s to become better thinkers.

Think First. Then Prompt.

The MIT study asks us to consider a deeper question: what’s at stake when we let machines do the hardest part of learning—the thinking itself?

AI is here to stay. But if we want to raise minds that can reason, reflect, and remember, we’ll need to be as intentional with our mental tools as we are with our physical ones.

Because every shortcut we take shapes the roads we’ll forget how to build.

Read the full paper here.

🎧 Acknowledgment Note for NotebookLM Podcast

Podcast production note:The accompanying podcast episode for this article was drafted/recorded using Google’s NotebookLM, which helped summarize and synthesize key ideas from the original MIT Media Lab paper and supporting commentary. Special thanks to the NotebookLM team for their exploratory work in AI-assisted knowledge synthesis. Admittedly, all the research I do with NotebookLM keeps my brain from slowly deteriorating due to AI usage.

#mitmedialab #neuroscience #cognitivedebt #chatgpt #llms #aieducation #brainhealth #nataliyakosmyna #eugenehauptmann #yetongyuan #jessicasitu #xianhaoliao #ashlyberesnitsky #irisbraunstein #pattiemaes

As the lights dimmed in Paris’s grand Dôme de Paris on June 11, 2025, Jensen Huang appeared under a cascade of laser beams and floating GPU icons. “This is the era of AI factories,” he declared, unveiling banks of Grace Blackwell NVL72 systems humming like futuristic beehives. In that moment, the once-modest gaming-chip architect became the conductor of a global intelligence infrastructure—a fitting culmination to a journey that began with toilet brushes and coffee cups.

From Reform School Janitor to Systems Thinker

At age nine, a family mix-up sent Huang not to the elite boarding school they’d intended, but to Oneida Baptist Institute in rural Kentucky. There, every morning began with the same ritual: scrubbing toilets until they gleamed. Rather than grumble, Huang treated the chore as an experiment. He mapped cleaning routes, timed each swipe, and set self-imposed quality targets. “I was probably the best toilet cleaner they ever had,” he later joked. That early taste of process optimization would echo through every boardroom he led.

Denny’s Dishwasher to Data-Center Dynamo

By fifteen, Huang balanced high school classes with a night-shift at Denny’s. As dishwasher, busboy, and waiter, he approached each task like an engineer optimizing a pipeline: How many coffee cups could he carry? What’s the shortest walking path between tables? He sketched floor plans in pencil, logged service times, and shaved seconds off every delivery. Those experiments weren’t mere fast-food anecdotes—they were the prototype for tomorrow’s GPU load balancing under NVLink.

The Scholar’s Ledger: Frugality and Credentials

When tuition bills loomed, Huang chose Oregon State University to keep costs low and earned his BS in electrical engineering without breaking the bank. Later, he enrolled part-time at Stanford, juggling courses with industry R&D. Over seven years, he added a master’s degree without pausing his career—an exercise in resource arbitrage that presaged NVIDIA’s lean approach to capital allocation.

Planting the Platform Seed: Founding NVIDIA

Huang founded Nvidia Corporation after meeting with Chris Malachowsky and Curtis Priem at an East San Jose Denny’s. If you’re in the mood for both GPU history and a stack of pancakes, this Denny’s is still there - 2484 Berryessa Road.

The “Accident” That Redefined Computing

Between 2006 and 2012, research labs discovered that NVIDIA GPUs—designed for games—excelled at neural-network training. Huang embraced this pattern recognition, launching CUDA, a parallel-computing framework that let scientists harness thousands of GPU cores. What began as a serendipitous side benefit became a deliberate AI-platform strategy:

* Market Expansion: Gaming → High-Performance Computing → AI/ML

* Product Evolution: Graphics chips → Compute accelerators → End-to-end AI platforms

* Value Leap: 10× addressable market growth without rewriting core IP

2025 in Paris: AI Factories & Continental Sovereignty

At VivaTech 2025, Huang unveiled NVIDIA’s blueprint for “AI factories”—modular clusters of Grace Blackwell NVL72 racks, each housing 72 Blackwell GPUs linked via NVLink to achieve over 100 TB/s of internal bandwidth. These factories are designed not just for scale, but for efficiency: every watt, every millimeter of rack space, tuned to maximum throughput.

He also urged Europe to take control of its compute destiny. Within days, the European Commission’s InvestAI program—already funded at €20 billion—was positioned to finance four continental AI gigafactories. The U.K. government reaffirmed a £2 billion AI investment package (including £1 billion for national compute infrastructure) in its Spring AI Review. And although Macron and Scholz did not speak directly at VivaTech, their joint statements in the conference’s aftermath underscored the geopolitical stakes of digital autonomy in an age of shifting tech power.

Speculative Horizons: Rubin, Feynman, & Global AI Grids

Looking past Blackwell, Huang offered a glimpse of NVIDIA’s future roadmap:

* Rubin (2026): A hybrid GPU+CPU on TSMC’s 3 nm node with HBM4, projected to top 50 petaflops on 4-bit AI workloads.

* Feynman (2028): Named for the visionary physicist, this chip will unify next-gen HBM with ultra-dense compute—primed for edge-to-cloud deployments.

Envision AI factories powered by wind turbines in Nordic fjords, robotics labs in Germany running digital-twin simulations, and genomic-analysis clouds in Brazil—each built on the same NVIDIA foundation, yet customized to local needs.

Looking Ahead

Jensen Huang’s odyssey—from Taiwanese immigrant and reform-school janitor to the mastermind of a worldwide AI-infrastructure network—reveals the power of operational grit married to strategic eyesight. He transformed the discipline of cleaning toilets and optimizing coffee service into the DNA of NVIDIA’s platform play. As AI factories come online around the globe, they carry forward his core lesson: no task is too small, no detail too trivial, when you’re engineering the future of intelligence.

Podcast Note:

This episode was produced with Notebook LM and features AI podcasters. During a transcript review, one funding figure was mistakenly cited in U.S. dollars instead of euros; the correct commitments are €20 billion for the InvestAI program and £1 billion for U.K. national compute (part of a broader £2 billion AI package).

Vocabulary Key

* Platform Strategy: Designing a core technology so third parties can build complementary products, creating network effects.

* Sovereign AI: Nationally governed AI infrastructure to protect cultural and data autonomy.

* NVLink: High-speed interconnect that lets GPUs share data at terabyte-scale per second.

* Petaflop: One quadrillion floating-point operations per second—an AI compute throughput benchmark.

* Token: A discrete unit of text or data processed by modern language models.

FAQs

Why did NVIDIA GPUs outperform CPUs for AI? Their thousands of parallel cores and high memory bandwidth match neural-network workloads more closely than CPUs’ sequential architectures.

What is an “AI factory”? A purpose-built compute cluster optimized end-to-end for training and serving large-scale AI models.

How does sovereign AI differ from cloud AI? Sovereign AI emphasizes national ownership and governance of data and compute, rather than reliance on global hyperscalers.

What role does CUDA play? CUDA is NVIDIA’s parallel-programming platform, enabling developers to accelerate diverse applications on GPUs.

#aiinfrastructure #nvidia #gtcparis #deeptech #platformstrategy #vivatech #sovereignai #nvlink #gpu #mlops #futureofwork #nvidia #jensenhuang #deeplearning #deeplearningwiththewolf

Editor’s Note: Personal views expressed.

I usually write about machines that think; today I'm writing about people who decided to do something thoughtful—about a nation that's waking up, stepping outside, and making its voice heard.

DIY Democracy

Earlier this week, I stenciled DEMOCRACY across an old t-shirt my son left behind—barely fitting all those letters. Using paints from my Star Wars armor projects, I carefully filled in the lettering. (I'd later discover this paint transfers to skin in the heat, leaving me literally blue by day's end.) With ChatGPT's help, I brainstormed protest slogans and settled on my favorite: "Off With His Crown." A bit of cardboard and glue, and I had my sign.

Ready or Not

Saturday's forecast promised the 70s, but it felt much hotter. Minutes before my ride arrived, I quickly painted a crown on an old cap with a red cancel symbol through it—cancel culture at its finest. The paint was still tacky as I gingerly got in the car, immediately feeling the nervous energy among our carload of protesters. We compared signs like kids at a science fair: "What'd you make?"

Arriving Early—But Part of Something Much Bigger

We got to the planned street corner ahead of schedule, but parking was already nonexistent. What I didn't fully grasp until later was the scope of what we were participating in.

I’d seen the “dots on the map” grow all week long until it was 2,000 towns and cities that had planned protests, but I had no idea this would amount to between five and six million people. While the numbers are still being counted- and may never be fully known- this amounts to between 1.6 and 1.8 percent of the population of the United States. It’s staggering.

You can't fully capture protest energy—it's electric. Every stranger feels like a friend. Most of the crowd skewed older (proof that wisdom comes with age?), but as the hours passed, more young faces filled the streets. When I spotted a mariachi-blasting flatbed truck and signs in Spanish ("Leave my parents alone"), I knew this was something special.

What heartened me most was seeing how many others had taken the time to make their own t-shirts and hand-crafted signs. It was part Maker Faire, all protest—small town America in a small city, repeated all across the country.

The DIY spirit was everywhere: stenciled messages, painted banners, creative slogans born from kitchen tables and garage workshops. This wasn't astroturf or manufactured dissent—this was authentic, grassroots democracy in action.

A March That Grew and Grew

Heat exhaustion struck one of the elders—"Clear a path!" yelled someone, and medics moved in. I walked away, saddened that someone had fallen. Clearly they weren’t in good health and had come out to the protest anyway. This event was so important to them they felt they had to be there. It is a statement of what this country means to people and why they feel democracy is still worth fighting for.

As I walked out, a “march” formed- several hundred people strong- walking down our main street (called First Street.) The street winds for a mile down to the church, lined with businesses on both sides.

That was our cue to start marching down Main Street. Imagine hundreds of people flowing together with horns honking in solidarity. Somehow 200 people swelled into 800 people. The supporters kept coming and the cars kept coming. Some cars circled around the block multiple times so they could cheer us on again and again- including a Cybertruck that just wanted to be a part of the action. Everybody wanted to be a part of this movement. You could feel this was something.

Peace, Joy, and First Amendment Pride—While D.C. Saw Tanks

Our local police cruised through every few blocks. We waved, we shouted "Thank you!"—a scene I never imagined would feel so natural. No tear gas, no police on horseback, no misplaced Marines or National Guard—just a peaceful, joyous celebration of civic engagement.

The contrast was deliberate and stark. As organizers put it: "They’ve defied our courts, deported Americans, disappeared people off the streets, attacked our civil rights, and slashed our services. The corruption has gone too. far. No thrones. No crowns. No kings.”

While Trump's parade featured 6,700 soldiers, 150 vehicles including dozens of tanks, and 50 aircraft flying overhead, our movement was about something fundamentally different—ordinary Americans exercising their constitutional rights.

What the World Needs to Know

It may seem to people outside the United States that this country is asleep, or that we’ve lost our collective minds. I want to reassure you that this is not the case and America is still here.

A slim majority fell prey to the lies of a snake oil salesman and his car salesman buddy. Now, in communities across America, people of all backgrounds are rediscovering what democracy looks like in action.

The protests occurred as part of what organizers called a "nationwide day of defiance", with the timing on Flag Day being intentional: the flag doesn't belong to Donald Trump. It belongs to us.

The timing wasn't coincidental. As we marched peacefully down Main Street, ICE agents were executing Stephen Miller's explicit orders to abandon criminal enforcement and target day laborers instead. Home Depot parking lots—where immigrant workers gather each morning hoping for honest work—became ground zero for a quota-driven deportation machine that prioritized optics over justice. It was this injustice that became the flashpoint for what happened in Los Angeles. (Well, that and sending in the Marines to distract the narrative from the Epstein files.)

The Networks That Matter

Protests will continue. This was bigger than any single demonstration—it was a nationwide network of citizens activating simultaneously, coordinating organically, and demonstrating that democracy's immune system is still functioning.

Most of my writing focuses on deep learning and neural networks. But this moment reminded me that the most important networks aren't artificial—they're human. Both kinds require constant attention, active participation, and collective intelligence to function properly. Saturday showed me that when those human networks activate, they're capable of extraordinary things.Tomorrow we'll get back to talking about artificial intelligence. But don't completely give up on the state of human intelligence in the United States. There's hope for us yet.

Fast Facts: A Historic Day

By the Numbers:

* An estimated 4-6 million Americans protested across the country on Saturday, June 14, 2025

* Over 2,000 cities and towns participated nationwide. Source: The Daily Beast.This represents 1.2-1.8% of the entire U.S. population taking to the streets in a single day.

* Independent data analysts suggest this was the largest single-day protest in American history.

Historical Context:

* The previous record holder was the 2017 Women's March with an estimated 3.3-4.6 million participants

* The Trump era has seen "dramatically more protest activity" than his first presidency, with over 15,000 protests since January 2025—a threefold increase

* Organizers intentionally avoided downtown D.C., choosing to "organize literally everywhere else" while ceding the capital to Trump's military parade.

The Peaceful Contrast:

* Trump's parade featured 6,000+ troops, dozens of tanks, and cost an estimated $850,000+ per deportation flight (What to know about 'No Kings' protests against Trump's policies. Source: PBS.)

* The "No Kings" protests were committed to nonviolent action. Organizers offered trainings for participants on how to de-escalate confrontations.

* No major incidents of violence reported at the democracy protests, while Trump deployed 4,000 National Guard troops and 700 Marines to Los Angeles in response to immigration protests

What It Means: Saturday proved that when human networks activate, they're capable of extraordinary things. As organizers put it: "The flag doesn't belong to President Trump. It belongs to us."

#FlagDay #NationwideProtests #PeacefulProtest #DemocracyInAction #HumanNetworks #StandUp #WeThePeople #AmericaStillHere #FromAIToActivism #NoKingsDay #Indivisible #TrumpProtests #GrassrootsActivism #CivicEngagement #FirstAmendment #FlagDay #NationwideProtests #PeacefulProtest #DeepLearningwiththeWolf