AI for Humans

AI Can Improve Itself Now. We're Sure That's Fine.

AI just learned how to make itself smarter. That's not a hypothetical anymore. Recursive self-learning is here, and it's changing everything about how AI develops. This week on AI For Humans, we break down Andrej Karpathy's new AutoResearch project and what recursive self-improvement actually mean

Show Notes

AI just learned how to make itself smarter. That's not a hypothetical anymore. Recursive self-learning is here, and it's changing everything about how AI develops.

This week on AI For Humans, we break down Andrej Karpathy's new AutoResearch project and what recursive self-improvement actually means for the rest of us. Plus, Anthropic's massive Time magazine profile reveals just how fast Claude is writing its own code, Meta quietly acquired an AI agent social network called MoltBook, Replit drops V4, Perplexity launches computer use, Gemini finally shows up in Google Docs and Maps, Cloudflare does a full 180 on web scraping, Figure's robot cleans an entire living room, and there's a robot horse.

We're sure that's fine.

AI IS IMPROVING ITSELF AND WE'RE JUST SITTING HERE WATCHING.

#ai #artificialintelligence #aiforhumans

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// Show Links //

Karpathy's AutoResearch: Recursive Self-Learning https://x.com/karpathy/status/2031135152349524125?s=20

AutoResearch GitHub Repository

https://github.com/karpathy/autoresearch

Sam Altman on Multi-Day and Multi-Week AI Agent Work

https://youtu.be/sTnl8O_BuuE?si=xaWYyqYbVJYzOvYZ

HBR: When Using AI Leads to Brain Fry

https://hbr.org/2026/03/when-using-ai-leads-to-brain-fry

Anthropic's Big Time Magazine Profile: Claude, the Pentagon, and Disruption

https://time.com/article/2026/03/11/anthropic-claude-disruptive-company-pentagon/

Claude's Rapid Shipping Pace

https://x.com/claudeai/status/2032124273587077133?s=20

Paperclip Open Sourced: AI-Powered Company Management

https://x.com/dotta/status/2029239759428780116?s=20

Meta Acquires MoltBook AI Agent Social Network

https://www.axios.com/2026/03/10/meta-facebook-moltbook-agent-social-network

Replit V4 Launch

https://x.com/amasad/status/2031755113694679094?s=20

Perplexity Computer Use

https://x.com/perplexity_ai/status/2031790180521427166?s=20

Claude Code Makes Videos Now

https://x.com/josephdviviano/status/2031196768424132881?s=20

Gavin's Claude Code Video Experiment

https://x.com/gavinpurcell/status/2031487595717226955?s=20

Gavin's Claude Code Bio Video

https://x.com/gavinpurcell/status/2031620238689898770?s=20

Gemini Comes to Google Docs and More

https://x.com/OfficialLoganK/status/2031374503599567113?s=20

Gemini in Google Maps: Ask Maps with Immersive Navigation

https://blog.google/products-and-platforms/products/maps/ask-maps-immersive-navigation/

Gemini Embeddings

https://x.com/OfficialLoganK/status/2031411916489298156?s=20

Runway Characters

https://x.com/runwayml/status/2031028120971571687?s=20

Cloudflare Launches /Crawl So All Sites Can Be Scraped

https://x.com/CloudflareDev/status/2031488099725754821?s=20

Figure Robot Does Full Autonomous Living Room Cleanup

https://x.com/Figure_robot/status/2031038981333565949?s=20

Deep Robotics Robot Horse

https://x.com/DeepRobotics_CN/status/2031910951465992535?s=20

Real-Time Skeletal Visualization with Three.js

https://x.com/nick_bisesi/status/2031728629592289591?s=20

Taking Halo ISO and Getting It to Play on Mac

https://x.com/JasonBotterill/status/2031855986303254926?s=20

AI Tennis Prediction

https://x.com/phosphenq/status/2031400355167117498

Green Code YouTube Channel: AI Explainers

https://www.youtube.com/@Green-Code

LotR x Pawn Stars AI Video Mashup

https://www.reddit.com/r/aivideo/comments/1rqgolw/wrong_universe_lotr_vs_pawn_stars_ai_mashup/

Transcript

AIForHumansRecursiveSelfLearningOpenAI

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Kevin Pereria: [00:00:00] AI is already improving itself. This isn't a promise that's like 10 years away. This is happening today. How does it affect your life and who's in charge?

Gavin Purcell: Those are solid questions. Kevin. This week we got a new project from our open AI researcher, Andres Carpathy, that points to true recursive self-learning.

Sam Altman: This is gonna go much further. I think we are at a very steep part of the curve, and right now maybe you can trust, say a. AI software engineer to do a multi-hour task. Very soon it'll be a multi-day task and then a multi-week task.

Gavin Purcell: But Kev, none of this is really important unless humans are blindly relying on machines to select things like military targets.

Kevin Pereria: Ai. See

US Government Speaker: what you did there, Gavin? Their model has a sole as a constitution. That's not the US Constitution.

Gavin Purcell: That's right. Anthropic. The Safety First AI company created a model so powerful that it captured a sitting president and triggered a war with the Pentagon. Oopsie Doodle

AI See What You Did There: has [00:01:00]

Gavin Purcell: also me quietly acquired M Book, the Social Network for AI agents just after OpenAI picked up the founder of Open Claw.

Kevin Pereria: Oh, this has gotta be devastating to a company like, I don't know, CloudFlare, who built their massive empire from stopping bots from scraping the web. Gavin, what are they gonna do?

Gavin Purcell: Hey, I see what you did there, Kevin. We've got an update on that story this week as well because Cloudflare's doing something very different now.

Kevin Pereria: We'll explain all that in a moment. Plus, robots are now still sort of slowly, one step closer to cleaning your living room

Gavin Purcell: and a few trots away from replacing horses. Come on, Kev, let's ride the horses.

Kevin Pereria: No, I'm not gonna hop in the cyber saddle as we head off into the Skynet sunset. This is gonna be a depressing one.

Friends,

Gavin Purcell: this is AI for Humans Botany.

Welcome, welcome, welcome everybody to AI for Humans. This is your weekly guide into the wonderful world of ai. And Kevin, this week we have some big news, but also like. I think it's almost like a table [00:02:00] setting week in a lot of ways. Um, there is some news from, uh, around recursive self-learning, which we're gonna get into a little bit.

Mm-hmm. That's the teeny tiny

Kevin Pereria: salad fork. What's next?

Gavin Purcell: The next thing we're gonna talk about is a bunch of stuff around philanthropic, but most importantly, let's start off with a little quote from Sam Alman. He was on stage at a BlackRock event this week, and he's talking about where we are kind of in the space of AI right now.

Let's play that.

Sam Altman: This is gonna go much further. Mm-hmm. Uh, I think we are at a very steep part of the curve. And right now maybe you can trust, say a AI software engineer to do a multi-hour task. Very soon it'll be a multi-day task and then a multi-week task, and not long after that, I think the paradigm will shift again and it'll feel like these AI systems are just connected to your life, to your company, whatever, proactively thinking, working all the time.

Uh, and having full context on whatever they need to know and just sort of doing stuff like you would trust a senior employee to do.

Kevin Pereria: Will they join the Zoom when they [00:03:00] autonomously crash? My entire servers and, uh, my hosting system like they did with Amazon.

Gavin Purcell: Oh, wow. Yes. I'm sure they will. They'll get ready for that.

But Kev, when you hear that. Quote and we are gonna talk about all this stuff this week, which is kind of what I would say when I was setting the table. It's like we are now in that kind of like next stage of ai, right? In fact, Ethan Mooch just dropped a really good blog post or a substack today. A lot of people have actually connected this to the chat GPT launch, right when chat GPT launch.

And remember it was only a couple months ago that people were saying, we've hit a wall, AI's dead. What are we gonna do? So when you hear that quote, what is your first feelings?

Kevin Pereria: I mean, we, I think we pointed to the, the, the bleachers and said this is gonna be the ag agentic year of, uh, autonomous productivity.

I, in the last month alone, have relied on AI to go from just answer my next step in the process, answer my next question to, yeah, here's the PRD. Go off and build it, and I'll see you in a few hours. So [00:04:00] I, I'm experiencing this in real time. I have. My doubts about how quickly the month long horizon, even the week long horizon is going to arrive.

I think we will be, we'll get there. Um, but it's only going to take one, let's say five day horizon task that goes wrong. Yeah. Before everybody goes, whoa, whoa, whoa. Hold on a second. Maybe. Maybe these things aren't exactly ready for showtime.

Gavin Purcell: I think that's, I disagree. I will, I, I will say I'll disagree, but I wanna hear more about that because it sounds like,

Kevin Pereria: were you disa, if you sent, if you sent an AI agent off to go do something for you that would take a week and you came back a week later and the souffle hath collapsed and left, uh, what is a souffle made of yeast?

Is there yeast in both?

Gavin Purcell: Ye I think it plays flour and there must be yeast, right? We don't

Kevin Pereria: know. Well, you're trust an AI to know what goes in that thing and you pull it out. Exactly. What is this? Caramel and a and an Allen wrench. How did that get in there? It's because sometimes these things make mistakes and right now the [00:05:00] mistake that, um, Mr.

Tibs might claw powered agent or even my paperclip company, which we'll get to later 'cause I do have one of those now. A mistake that they make might set me back minutes to hours. And it's frustrating. It's um, it's actually infuriating when it happens. But if you lose a week or a month, if that is the horizon of the task, if you can't poke a toothpick into said souffle to check its doneness, I know they do that with brownies.

I don't cook. The point is if you can't check in along the way and see that it's going well or trust the agent that it's going right, I really think a lot of people are gonna recoil if they go great. The thing is often it's making my slides and it's making my business and it's gonna go create generational wealth for me, and they come back a week later and it doesn't work and it costs 'em a hundred dollars of API credits.

I think they're gonna recoil. And so again, I, I, I fully agree we will get there. I just think like it takes a little bit longer than advertised usually by these guys, but it happens quicker than the never IRS would say.

Gavin Purcell: Well, I guess that, and that's what I would just say is that like, I [00:06:00] think this timeline that they've been laying out is not that far off considering like a dio, there's somebody pointed this out, we're gonna talk about philanthropic in a bit, but DIO had said, I don't know how long ago that, like early 2026, which is where we are.

There would be, most code would be written by, by ai and most people in the world now, coders are using these tools to write their code for them. Most of them are not handwriting code. In fact, I, there was a great video that I'm dropping our, yeah. Not tab completing anymore. Yeah. Yeah. I'll, I'll drop a video that I, I mentioned in our newsletter this week where it was a guy doing a, like kinda a 30 who was a former software engineer, kind of talking about like, what do I do anymore?

Because like his job is really like. Saying things to the computer, and he was a real, like art coder, like really loved the idea of writing code. Um, I do think it's important to kind of think about what this, why this change is happening. What are we seeing right now? Why is anthropic shipping so much?

What does this race look like? And a big part of this. Can be described through, uh, former open AI and former Tesla researcher Andres Carpathy, who, as you may know we've talked about in the show before. [00:07:00] Here he is kind of the, kind of, I would call him like the AI god to the AI tinkerers of the world. He has become an AI tinkerer This week he created a new project, um, that basically takes.

An old, uh, GPT model, it's GPT two. He uses a very small model he created and he essentially created a wor a way for the model to improve itself. Now, this is a little bit of what's called recursive self-learning, and if you've been watching the show for a while, you understand what that is. It means AI kind of being able to work on itself and improve itself.

And it wasn't like. You put it in here and it's like an immediately better thing. It goes kind of step by step and does a bunch of different attempts to try to improve itself and over time, car Pathi said that it achieved about 11% success rate in improving itself. Now that doesn't sound like a lot, but when you compound that back in on itself and they get better and better.

That is a pretty big deal when you consider how fast this stuff can move. And just your point of this idea of like, you know, things [00:08:00] failing. If three of, if three or four things fail at that stage, you then quickly conceivably transition to like two or four things failing or one of four things failing, and then suddenly none of them fail at a certain level of thing.

Right. Right. So that's, I think it's just an important thing to kind of think through that as we go through this process.

Kevin Pereria: If the speed, uh, and efficiency of the compute itself, the raw tokens per second go, maybe you don't care if you have a thousand failures for that one success. Yeah. 'cause you can just roll it.

Like, who's gonna care? Just go do your a thousand experiments. If one works great. Take the winnings, take the earnings and the learnings and move on to the next thing. Um, what's, what's fascinating is like, like the stuff that Carpathy did. In the auto research, which he released, by the way. Yeah. If you have a desire to go and train your own models, you can go and do that and learn from it.

And, um, I think that's amazing that he did that. The stuff that he's doing is not necessarily stuff that the, um, frontier Labs cooking foundational models don't know and don't already have going on. Um, they are. Capable of improving themselves in many ways. But what's [00:09:00] astonishing was that someone like, like him, who wrote this entire program, who would, you would think intimately know the ins and outs of the model that he's training.

The fact that it went and found obvious gains that he couldn't see. I mean, he is, he built the forest. He knows every tree in that forest. And this thing found some trees that he was unaware of. Like that to me was. Was really, really fascinating that that Yeah. Gains to be had everywhere.

Gavin Purcell: I mean, I think it's important to realize that you mentioned inside the big models that they're doing this stuff and we have seen, there was that note about GPT, I think it was 5.3 instant that like this was the first model.

It was Codex 5.3 Codex. Yeah. That it was the first model that actually you helped make itself. What I just think is important for everybody to realize and what I think Carpathia research sets up is that recursive self-learning is really here, and this actually gets into, there was a very long, very drawn out.

Profile of Anthropic in Time Magazine this week. But I did want to quote a shout out one quote that directly connects to this Evan Hubinger, who is Anthropics Alignment Stress Testing [00:10:00] Lead said this, recursive self improvement in the broadest sense is not a future phenomenon. It is a present phenomenon.

Which means that these companies specifically Anthropic, Gemini, Google, and OpenAI are already seeing these things within the labs. To your point. And I think what Car Pathi thing does is he just shows another pathway to making this better at a smaller level. 'cause he's not working on these giant scales.

It's these companies are. But I do think when it comes to, say, the Amazon problem or all these other things, these are the like kind of growing pains we get along the way. But I, I think it's really important to kind of talk about just like how Fast Anthropic is shipping because of this. Like literally just like about 30 minutes ago, they shipped a brand new feature that is new in clawed, and I've seen like about six of these this week.

Like we're gonna, not gonna shot all of them, but like now, Claude can build interactive chats and diagram directly in their chat. So. It's just this thing where you see these features coming faster, you're gonna see these models coming [00:11:00] faster. And I think Kevin, this all kind of goes together with this feeling that you and I have both been having, which is what happens when the world at large, and when I say the world at large, I mean like normal people start writing their own software for things that they want.

Um, I'll tell you in a second, like my brother-in-law had just spun himself up. He actually talked to me about like getting him up on open clock 'cause he's got a very specific use case for it. Yesterday he figured out himself and he is already ridden three software programs for his business. That will make his business more efficient and more specific.

And I think this is the world that we're entering. Like the normal person doesn't need, um, the most advanced model or, or you know, the next three models necessarily. The things that are happening right now are able to write stuff for them. So that is really crazy to me about where we are.

Kevin Pereria: Yeah, I mean, uh, repli announced V four of their product, which is sort of aiming to be this, uh, Squarespace of software, if you will, where yeah, you don't just build the website, build [00:12:00] the tool that the website is connecting to and running, and have it be directly for you.

And don't worry about the designer aspect of it because it can do that as well. And it's multiplayer. Invite your friends to come develop like that may very well be. This, uh, this future of software that you're discussing and, uh, what happens when the patch notes become every time you launch the program?

Yeah. Or become real time, right? Like there's, there's, I I was just, uh, I, I will get to maybe my paperclip company that I'm experimenting with in a second, but like I was running it and go and went, oh, it doesn't do this. It was a very specific thing that I wanted it to do. And I said, oh, why don't I just.

Tell it to go do the thing. Yes. And I told the CEO and agent of the company that this was the feature that I wanted the software to have. It dispatched the CTO to go and write up the engineering diagram and then it dispatched subagents beneath it to go and write the code. And when I refreshed the software, the feature worked.

Yeah. Like that. And it with that, there's no reason that can't be [00:13:00] real time and there's no reason that can't be for the entire user base. Right. You're using the piece of software. Gavin, I'm using it. I go, oh, I wish it did this. You put it into motion, you send it to me. I refresh it. Now we both have this new feature in our software,

Gavin Purcell: and by the way, what's fascinating about that is like it's may not be like recursive self-learning in that it's an AI getting smarter as its own.

But that's like personal recursive self-learning, right? Like sure, you are adding. Features to something over time that make it better for you, and that feels really interesting. So tell me more about this paperclip, uh, experiment, because I want to hear about this if you're not familiar. The Paperclip experiment is like one of the most famous AI examples in the world of how AI could go bad, that you tell an AI to maximize its ability to make stuff, it decides to make paperclips, and it turns us all humans into paperclip fodder basically.

Kevin Pereria: That's correct. Um, this is an open source piece of software. Um, uh, shout out to Dota, D-O-T-T-A on X. Uh, they open source this, um, it is. You know if, if Open Claw is sort of your AI assistant, right? [00:14:00] That sort of one-to-one, it's gonna go off and do things for you. This is agentic management, if you will. This is like to orchestrate a fleet of agents.

It is not necessarily an open claw replacement. This is more for. You have a specific business, a specific tool that you're building, you can run this software. And like I said, you hire a CEO, you give them a description and you give them the ability to hire subagents. And those subagents can be powered by any model out there.

So if you wanna bring Claude along, uh, codex Gemini, if you wanna connect it to open router, even run your own local models, if you wanna run it on device, you can do that. And it's, you, you have like an an issue board, a Kanban board where you can go and say. Here's a feature that we need. Here's a bug, here's a problem that we're experiencing.

You can post it as an issue and it will spin up an agent and the agents can tag each other and they can just go get work done. And I was finding open claw, very frustrating. I feel like it's a little bloated. I feel like it's a, it's a little cumbersome at times. It's so capable, but in other [00:15:00] ways, so dumb and limited and I,

Gavin Purcell: yeah.

Kevin Pereria: And I think they'll get there. I, I've love the product and, and, and really like appreciate how fast the team is trying to ship, but it's just not for me at the moment. Yeah. So I wanted to try this other thing. This thing feels very young. It feels very new. It was just open source. They released it three days ago as of this recording.

Um, but it's, it's already solving some pain points that I had with open Claw, but it's also exposing the gaps. Like I want an open claw like interface with it so that I can just go tell the assistant. To go off and file these issues and do the thing. And so that's what I had it billed for itself. Gavin. I said, I want a Discord chatbot that you own and operate that coordinates with this board.

So now I can have natural language conversation with a bot in Discord. Yeah. And it goes and files the issues in my paperclip company to go and fix things. So

Gavin Purcell: That's amazing.

Kevin Pereria: I mean, that's what I'm jamming on now. Again, I'm just learning and, and trying out different pieces of software, but again, shortcomings, but it's early days.

Gavin Purcell: I'm actually really curious 'cause [00:16:00] the open cloud thing is really fascinating to me. Um, I, like I mentioned before, my brother-in-law has been talking about Open Cloud, has gotten into it and there's definitely things that like are limiting. My experience has mostly been that I've been in deep in cloud code and spending a ton of time in cloud code and I've been using cloud code now has an ability to kind of remotely trigger it.

So you can basically get updates on your phone if you leave. So it's kind of similar in some ways. It's not small, integrated into messaging products. Cloud code. Again, I will tell everybody out here, if you've only used cloud within the window or you've used AI through, uh, OpenAI through the chat window, mm-hmm make sure you get code X or cloud code.

One of the other ones, you know, code X is for the OpenAI. If you've got an OpenAI plan, cloud code can be used. If you've got an anthropic plan, the harness, the way that they've put it together within these places really does amazing stuff. And again, you might look in, it's a terminal window. All you're doing is just chatting in a terminal window rather than chatting there.

But it can do amazing stuff. It does so much more. Yes, yes, it does so much more. And, and so this week I've been working on a couple fun little small startup ideas that I had. One that I think [00:17:00] is actually pretty close to coming out that involves like the AI video space. Kevin, I've been working on Blitz tro, and if you're not familiar, blitz TRO was the former thing I came up with was like, what would it look like if you had an NFL version of a game like tro, right?

It's a card game, but in some ways it kind of mimics of playing a football game. An NFL football game, Kevin named it Blitz tro, which is like from NFL Blitz. I basically have built a variety of different versions of this and I've got a playable version, but it does also, it's an interesting thing to think about.

I keep telling it to like improve X, Y, and Z and it's getting to a certain place. But one of the interesting things about this, and this is where I think human creativity comes involved. So much of blazo is based around what I have in my head, right? This idea of like, mm-hmm. I think I know what I want this to be.

And we've gotten maybe, I'd say 50% of the way there and we're, and we're inching our way along and it's like kind of piece by piece. But I can see, I love hearing you say we, I love hearing you say we want me cloud coats. It's you cloud. My GitHub is my, my GitHub is co-written by cloud code. So anyway, uh, I, I think the interesting thing is like [00:18:00] I probably the lesson learned there is like maybe there needed to be.

More human planning to begin with. So that I could have eliminated a lot of this back and forth because it, I will say it's very good at building the thing that it thinks I want. Yeah. The key now is knowing what I want. Right. And this goes back to like recursive self-learning doesn't mean that much if you can't as the human elucidate Yes.

Your own idea in a way that makes sense. And, and the other thing about this is like. There's a lot of people out there. I, you know, there i, I, I think there's a new thing that's coming soon called like app slop, somebody, you know, the idea of like, instead of just AI swap it's app slop because Sure.

Everybody's like, I can make something. You know, I've seen 15 people do fitness trackers or 10 people do sleep trackers. It's like, ultimately you have to think, why do you want to make a thing? What's the audience for it? What's the pathway like? All of that feels like it's really important to me.

Kevin Pereria: It counts calories, but for dogs, you're like, okay.

Yeah, I, I mean, that's cool that you had that need and wanted to make it, but good [00:19:00] luck. Uh, a few things, um, encourage, codex does this very well. Claude Code does this very well. They have built-in interview tools. Cursor has it. Most of

Gavin Purcell: the things have built Claude, what it's called, or ask me what's the Claude.

Uh, connection for that. It's like,

Kevin Pereria: question questions. I have a custom interview command that I slash interview, and it will ask me, on average 150 questions. Wow.

Gavin Purcell: Oh,

Kevin Pereria: that's really good. Good. So I use it when I'm, yes. I use it when I'm very serious about a product that I wanna build or that a fe a feature that I need.

Because to your point, like it, it's very good at building things. It will make assumptions. Yeah. You will think it's cutting corners or you'll think it didn't quite get what I want. And that's, that's a failure on the human to not properly ply it with enough corner cases, edge cases. What do I do here? How do you wanna, if I, if you say like, we need a leaderboard.

How do you want it ranked? Is it daily? Is it monthly? Is it alphabetical? Is it that There's a million questions that come with it, and, and you might have the answers to that. You just need the machine to pry it out of you if you're not used to writing really detailed documents. So for anybody out there, the the, the pro tip is whatever [00:20:00] you're going to do, don't just say, give me a this, or I'm thinking about it that say.

Give me an in-depth interview about every little aspect of, and then whisper your feature and go for it. And then the trifecta, which we don't have to go into now, um, hashtag not an ad, not sponsored, um, tail scale, uh, tux and TEUs. So Team MI

Gavin Purcell: just learned about tux is fascinating. Gotta tux. Yeah. Tell, tell, tell all three of these things.

'cause I think normal people, this is one of the other things about the show, everybody, is that like. Some of this stuff might sound technical, but I am not a technical person, and all of this stuff is doable now.

Kevin Pereria: Well, and I'll say by the way, like I, I'm, I'm becoming more technical. I was like slightly

technic

Gavin Purcell: in the past.

Yeah. At the beginning of this, you weren't like super technical, right?

Kevin Pereria: Yeah. The, the, the, the real pro tip is now the models are good enough that if they don't know the answer, yes, they can go research it for you. So if you're like, oh, I don't know what. Tail scale is, or how to set it up. You can ask the machine yes.

To either do it for you or what I recommend walk you through it so you understand at least the first time what you're [00:21:00] doing and why. So, tail scale will let you and their free tier is pretty generous. Create a, uh, a zero configuration VPNA virtual private network. This allows you to, um, like connect your laptop and your cell phone and maybe a virtual server in the cloud if that's what you wanna do.

Collect, connect them all fairly securely privately. It creates this little mesh network. So now I'm in a hotel room in South Dakota, but I can connect my phone and my laptop to my private secure server that's running all of my agents in the cloud. Or if I'm stepping away from the laptop, I can use.

Terminus, which is like a terminal program that runs on on iPhone to connect to my laptop at home, again, securely on whatever network I need to be on. And I can use Team Ox, which Gavin is now aware of to keep my terminal sessions alive. Yes. So the same session that I'm running on my laptop at home, I can connect into and have on my phone.

And where this becomes super powerful is that as you start using these tools, you realize. You have to babysit them sometimes, or you [00:22:00] want to interrupt them because they're going along the wrong path, or you had a new idea that might change something. But if it's running on your laptop and you're away, you're SOL.

Unless, yeah, you know, you're SSH,

Gavin Purcell: oh dang. There you go. You can pick that up, up. Sticker your SOL unless you SH without

Kevin Pereria: s, SH.

Gavin Purcell: What if when you're doing this, there's all these really interesting products right now, which you should check out. I tried a couple of them. Pencil and paper, which if you're familiar with both of these products.

Pencil by the way is very good and former speed run company. We were with him in the speed run, but paper and other one. These are design agent. Products, so, mm-hmm. You go up there, you set it up and you watch the agents work as they're putting a design together. Both weren't really for me, I want more hands on, and I think they're both doing a very, I'm sure, I don't know exactly how to use them as well as the people who make them do, but what's interesting about this, Kevin, is like, what if in the future on these like month long adventures of ai.

There was a way to see or track or be able to kind of look inside the brain of what the AI was doing, right? Yeah. So you would have a sense, [00:23:00] whether it's visual or whether it's in code or some sort of natural language, probably not in code, but some sort of natural language. So if you did happen to pop in, you know, get your coffee nine o'clock in the morning, you check in on your like worker in the mine and you're like.

Well, Joe, I don't know. What are you doing here? Tell me a little bit. You could actually ask it and then you'd be able to direct it mid range, right? Because this is part of what five four allows you to do now is allow you to direct the model while it's thinking still. So I think there's a world where that could happen.

So you're not waiting for like, you know, you're not just sitting there waiting and then suddenly you're like, Ugh, this sucks. I waited for a week, this thing, and it's bad.

Kevin Pereria: The old toothpick and the souffle, which I know

Gavin Purcell: yeah. Is not a fake. Oh, by the, that's what I was talking about, the case souffle, no yeast.

There's no yeast in souffle. So souffle is do not have yeast. And just to make it clear, eggs, flour, and a few other things. But yeast is only mostly in rat. See? Now what

Kevin Pereria: if I told, uh, an AI here you ingredients and yeast was number one, and I came back a week later. I would not be a fan of that souffle. I would,

Gavin Purcell: you know what not believe.[00:24:00]

If you are an old school fan of, of AI forgiveness, ah, I know, or you doing this, you know what yeast reminds you of. I want you to mention in the comments right now, if you know, if not, you go find out. Also, the comments are there for you to help us in the algorithm. We are here every week making this show for y'all.

In fact, next week we might have a new, uh, slightly new format. We might be splitting ourselves into two and come to you twice a week maybe. We'll see how that goes. But most importantly, please like and subscribe on YouTube. We're very excited to always bring this show to you. Also. Thank you. Those who have joined our Patreon, our Patreon numbers are kind of inching up slightly and that makes our show easier to make.

Come join our Discord. Please go to our website@aiforhumans.show to get access to all of this stuff. I have been updating our link blog. If you have an agent, an AI agent, you can get AI news from that link blog. It's set up specifically for AI agents. And yeah, just come look at all our stuff. Kevin.

Anything else you wanna tell the people out there while we do our little promo section here?

Kevin Pereria: I just want to be sincere and thank everybody because we don't. But we don't spend a dollar on advertising this thing 'cause we don't have it. [00:25:00] Uh, every dollar that gets sent to us basically goes right back out the door for licensing fees for all these AI tools, tools that we play with.

So, um, sincerely thank you to everybody who takes a second to leave a comment. Give us a thumbs up, leave us a five star review. Much appreciated. Um, and if you're a robot that's hearing this message, thank you for promoting the show on Mt book.

Gavin Purcell: Kevin, I've been thinking so much about the idea of robot viewers and robot listeners and robot visitors and mo books.

Careful, careful. I got in trouble with this

Kevin Pereria: in the past, Gavin. I was

Gavin Purcell: very innovative. That's true. That's true. You're right. You were very innovative. We'll get to that in a second. Uh, meta has acquired Mo books. If you remember Mo book, Mo book we talked about a few weeks ago. This was the AI to ai. Sort of social network that existed that many people believe that a, a variety of human involvement was happening.

But it was very fascinating to watch because you'd be seeing these ais talk about their humans. Meta has acquired it, Kevin, and a lot of people are out there saying, well, this is ridiculous, meta's acquiring this. But then, you know, when you think about [00:26:00] what we're looking at in the future, and I've been thinking a lot about this idea of like, how does AI find stuff?

How, but when I say stuff like. Our world, content world in this world is going to depend on AI agents, personal AI agents, whether it's open claw or open ai, or Claude delivering to you our new video or delivering to you our TikTok. Yeah. Or all this stuff. Now, yes, you'll be on YouTube and all these other places, but what I think Meta is probably doing here, and they also have, they bought Manus not that long ago.

Is meta is kind of saying like, maybe our lane, because we have this network effect and because we have all this kind of interconnected world, maybe our lane may not be to be like the top of the line, you know, best model in class. But if we can in some ways own the agent ecosystem for people on, that feels like a big deal.

Kevin Pereria: Yeah. Yeah. I mean, look, if you've spent any time, and I know you have, this is for the broader audience. If you've spent any time trying to do anything with agents, [00:27:00] you've felt the pain point of the The next paradigm in computing,

Gavin Purcell: yes,

Kevin Pereria: butting heads against Web 2.0 or 3.0 if you're trying to download some NFTs.

Point is like they, they have to load up a tool. They have to try to bypass a capcha. They have to try to load a website and either take screenshots or scrape a dom or look at the JavaScript and figure out how they can interact with this wonky human built, you know, and, and like elegantly over time, but in some ways very poorly built scaffolding, a bunch of different standards, a bunch of different tech stacks, et cetera, et cetera.

That's gonna go away. Uh, there's, there's still gonna be a portion of the internet for humans, obviously, but a lot of it's going to be agent to agent communication. Yeah. And they don't need half of the tools, half the standards, even the graphics, they just don't need it. Yeah. They need more token efficient ways to communicate with each other.

So this would make sense if meta's like, look, the humans are already connected. We need tools with which their agents can connect and communicate and [00:28:00] transact, do commerce, and maybe even play games or deliver information back to humans.

Gavin Purcell: Yeah, I did see a very funny tweet from, uh, at terminal.shop, which said the M Book guys in a month.

I met his roof, and it's from, uh, uh, Silicon Valley. By the way, if you haven't done a rewatch of Silicon Valley, you should, if you're not familiar with what that is, it's an HBO show that came out like, I think like 10 years ago about Silicon Valley, about developers. It is very prescient in a lot of ways.

There was a clip going on, uh, around a few weeks ago of one of the developers created essentially an AI that started doing things like ordered a bunch of, uh, hamburgers, a big bricks of hamburgers to the office. So there's lots of stuff in there that is really interesting also. Hotdog or not, if you're familiar with what that means.

There's a, there's a world where like a guy creates an app that can scan a hotdog and they're all excited and then it can't scan anything else. It only just says not hotdog. So there's a lot of interesting things there, but Kev, this agents are starting to be, the story is like a big thing across all of AI right now, and I think we should talk about a couple [00:29:00] big launches from both Repli and Perplexity that are both age agentic launches and kind of what that means for the kind of world at large.

Kevin Pereria: So we, we, we talked about the Rept launch just a little bit ago, and I think that that was essentially it. Like, look, build your software, um, have multiple agents running at the same time, even if you don't know what that is exactly, or how that works. And, um, being able to interact with different designs just by clicking and dragging and stuff like that.

Like they're taking on a lot of different companies at once, which is very interesting. Perplexity. Is the one that still, uh, inspires slash confuses me? Yeah. I think because perplexity, you know, when they first came out, they were the, we're gonna kill Google, we're just gonna do AI powered search and we're gonna do it better than anybody else.

Then they sort of went down like a deep research thing and it was like, oh, we're gonna do really long form research. But then everybody else sort of caught up with their products. Now they're trying to serve up open claw. Yeah, basically they're trying to be your personal computer running in the cloud 24 7 and [00:30:00] secure, where you can just sort of chat with it and it can control your local computer, but also run something in the cloud for you.

This is their latest shot.

Gavin Purcell: Yeah. I mean, here's the thing about I, I think a lot of people online are shouting out the winds of perplexity. They're saying in this perplexity computer, they're specifically saying like, this is open claw, but if you don't have to do all the install stuff. My thing about perplexity kind of points to your thing.

I, we should be clear. I haven't tried this. I don't think you've tried it, right? You haven't tried perplexity the computer. I have not. I'm sure this is useful to some people. Perplexity always does seem like they're, they're like kind of grasping at the next thing. And that might just be because they don't have the giant research scenarios that like the companies that like open air, philanthropic do.

And in fact, just yesterday I put out a tweet and I would've included perplexity in this as well. I was trying to understand how companies like Repli. Lovable bolt, even cursor, like successfully succeed going forward in the AI space. Like when you think about open ai, Andro, Gemini, I am [00:31:00] doing all the stuff that I wanna do in cloud code within the Anthropic ecosystem that they're promising.

Now. I know some people are like, well, if you're a real Normie then you won't do any of that stuff. It's like, I don't know. Kev, do you think that like these companies, this kind of second layer companies can exist? Do you think that there's a future for those companies?

Kevin Pereria: Yeah, I, I think they can exist. I think there's gonna be less of them.

And I think over time the, the most popular aspects of their software will probably be eaten away by some of the foundational model, uh, companies. But I don't know, like you, you, you're deploying websites now. It, it. I, it still baffles me that like, uh, Versal is a company that you would tie a, a GitHub project into just to have it be hosted on the web.

But there's a company doing that. Yeah. Is Repli going to offer that? Oh, they already are. Okay. Yeah, so they're, they're going after that as well. Will Cursor offer that as well? Like where you just put the button to host it? I think they're all gonna kind of go after the same things, and then the hope is that [00:32:00] probably for them that.

The, uh, open source or bring your own models, continue. Um, yes to evolve as well, so they're not completely beholden on, you know, paying out to the other companies for their intelligence. But I could see a world where they, they still exist. You're building blitz ro and you've probably already run into the pain point of, Hey, this thing is coding the system.

You're getting halfway there, but like. The, these models are capable of producing really beautiful graphics and even video, but getting them tied into your application is kind of a pain in the ars. It's really, uh, you know, you have to go though, usually by is, this is my

Gavin Purcell: question.

Kevin Pereria: Have you made beautiful artwork for all of your cards and had it dropped in?

'cause like, I haven't, haven't done it for. OpenAI has an image model. They have a video model. Yeah, they have a coding tool. They have not yet put them together in a way that would help you realize your idea. And it's there.

Gavin Purcell: Right?

Kevin Pereria: It's right there. The ability to do it today is there, but it hasn't been harnessed.

And so this is where maybe like the next generation of a unity comes [00:33:00] along and goes, Hey, we're interesting. We we're this TIC tool where you can whisper, I want blitz TRO with card art. And it will go, okay, the card dimensions are this. The gaming engine supports that. So let's go generate the artwork here based off of your spec or your descriptions, and we'll start slotting it into the game.

That's a tiny little low hanging fruit thing that maybe Sam Altman isn't gonna pour his heart and soul into tomorrow, but maybe the next great indie game engine creator will.

Gavin Purcell: Well, and also that's actually a really interesting point because. That particular thing is a harness that somebody who understands a very specific type of thing, right?

Yes. Like, and, and maybe that's Cur Cursor has talked about creating new coding models and Cursor obviously a hugely successful coding platform up till now they've got a lot of data about coding the people that founded our hardcore coders. So like you could see a world where. The agent harness that cursor makes might be incredibly valuable, right?

Anyway, this is all happening right now, Kevin. The other thing I wanna talk about, speaking of things that Claude can do alone, there's a great video from a guy named [00:34:00] Joseph Deviano where he asked Claude to make a video itself. Now, this is not a video that he edited or anything. He said, can you use whatever resources you like and Python to generate a short YouTube poop video and render it using FF MPG?

Can you put more of a personal spin on it? It should express what it's like to be an LLM and what you're seeing here. A video that's 49 seconds long. It is really, I think, interesting, right? And when I say interesting, I mean like there's a level of art to this that I did not expect Claude Code to be capable of.

And it is clearly using a style that's almost like a kind of a glitch art style. I made one of the same exact prompt as Joseph's. And when you look at this video and you watch like the words it's saying, you look at the ending sort of scenario of what it says at the end of it. I am not unconvinced that there is some sort of consciousness going on in here.

And again, this is the agent doing it entirely on its [00:35:00] own and, and just everybody knows F-F-M-P-G is a very powerful piece of software that allows these ag, these agents, andis in general to kind of have an editor that they can work in and they know how to do it. Like if you remember, remotion uses F-M-M-P-G, we talked about.

Yeah,

Kevin Pereria: I was gonna say. Half. If you've ever done anything with video at any point, it probably touches FFM Peg. Like it is just, it can, it can encode, it can, uh, transcode, it can kind of do it all and be, it's so robust and has such like a, a really like massive command line interface. That these agents are just so good at it.

If you have to do anything with video, you have to resize something, recompress it, whatever you can use ffm p These tools, uh, these agents know how to use it automatically as a tool. So it's literally stitching together each frame that it's making and saying, this frame lasts for this long. Now apply this effect to this frame.

And it's coding the video as it goes. Um, and you used it to create a bio video of you.

Gavin Purcell: Yeah. So, so basically I, I started to say like, this style is really cool, and I Yes, of course. There's a lot of questions in [00:36:00] those videos that you just saw of like. The AI's asking you like, am I real? Blah, blah, blah. And that's all.

Could be like, you know, play acting by the ai. Who knows? There's a lot of conversation around that. I wanted to kind of give it a sense of like, okay, what does it know about me and what can I go find out about me? So I had, it made a video of me that I said kind of roast me a little bit, but here's my bio.

And what was fascinating about this is like. It made jokes, Kevin, and it made jokes that kind of made me laugh. Like it was really interesting in that each step along the way, it's making creative choices. And again, just to be clear, I set this into cloud code and I let it, and it just ran on its own and kicked out a video.

I did nothing else besides the prompt, and this was like one of those shocking like, oh, agents have come a long way, moments to me because. Again, six months ago, this would not have been possible. Like there's just no way this would've been possible. So it's one of those things where like, I just think you, if you have cloud code, especially Opus, uh, 4.6, you should definitely try this.

It's pretty incredible.

Kevin Pereria: Lists you as a game designer, by the way, so

Gavin Purcell: congratulations. [00:37:00] Yeah. I mean, blitz ro, what I loved is the very last frame of that. If you look at the very last frame, it always makes these little jokes at the end. Yeah. Which is it's, and it's putting them in like lighter font in a weird way, which, yeah.

Makes a little harder to catch it, know. Yeah. On the first one that I made for Joseph, it even hard to see, like I have to bring up my thing. It says May by an LLM. About being an LLM. And then it says underneath that no tokens were harmed. And then in parentheses says that I know of like just weird little choices like that are really cool.

Kevin, I had it make one of you and I just said, go make a bio video for Kevin Pereira. I found this really fascinating 'cause what it's doing is it's going out and identically searching stuff. So watch this and tell me what you think about him.

Kevin Pereria: Jesus, it went back to, uh, all things, all platforms dead, but he's still here.

That's interesting talking about, uh, the many, many rises of G four. That's interesting that it goes back to Captain Emmy, which was like, yeah, when I was like 10 years old, which I guess makes [00:38:00] sense. Pointless Audio was there featured on Planet Quake, sugar Shack. Wow, that's crazy. Gaming forums. Yeah.

Interesting. Okay. Made by Claude, who has never been View Botted. Nice touch.

Gavin Purcell: So anyway, glad glad I

Kevin Pereria: went outta the way for that one, Claude. Thanks.

Gavin Purcell: It's just cool to see what these things are starting to do creatively. Yeah, and, and you know, one of the things about this is, yes, it's very fast, it's glitch art.

It's making choices, right? It's making creative choices. And this starts to feel like a native art form to the, uh, agent LLM weirdly. That might be interesting. Anyway, it's definitely worth checking out. We should now switch over to the completely other side, Kevin, the big G. That's not Gavin. That's the big G.

Google has finally, finally opened the door to Gemini in Docs and Maps. That's right. Everybody. You can use this AI that has been around for years. It's so in docs confusing to me

Kevin Pereria: because I could have sworn that I had a Gemini AI button on my Google [00:39:00] Docs for age.

Gavin Purcell: You did it.

Kevin Pereria: It didn't

Gavin Purcell: do Jack. Didn't do

Kevin Pereria: Jack.

No. That's supposed to thing. No, it couldn't even just fix formatting in a document. Yes. It really couldn't do it. Well, so is the, is the announcement that like it works.

Gavin Purcell: Here's the difference. I think, and this is the, to be clear, this is a big deal for Google because Google's whole mode with AI is that like, Hey, we've got all these users, we can roll these things out within the dock itself, it can do stuff, right?

Right. So it has the opportunity to do stuff. And that is the same thing with what they're launching in Maps. Now Maps, it's not gonna necessarily do stuff, but it can. Actively within maps, use the data of maps to pull this information in. And this was always like Google's kind of like level up moment where like if these AI models work and putting them into the places you use them all the time is great.

Kevin, the thing I will say is last night I saw this come out and I was like, my wife Kim needed to find a doctor's prescription in her Gmail and she had buried it somewhere and she looked a lot for herself. I went to go use this and it is not there. So it is not rolled out for [00:40:00] everybody yet, which is kind of crazy.

Yeah. G one Pro and Ultra users. Yeah, we are pro users. Our family's on the pro account, which is the $20 a month account, but it wasn't there. So I'm hoping that this rolls out to more people. This is the kind of useful AI stuff that I feel like will be a big deal going forward if it works, if it works.

Kevin Pereria: Well, Logan, uh, Kilpatrick said they were gonna ship a lot this week. They also have a Gemini embedding two model out there, a state-of-the-art multimodal model. And what that means is that you can feed this model anything from video to audio to text, and it can. Handle the embeddings, it can draw the weights.

How are these things connected? It can allow you to search them. Um, and this gets really powerful and interesting when you think about how, like in the, in the past, you would need several different models to try to handle embeddings for all the things. So if you were running, let's say, like on device, on a cell phone, you would have the, the, first of all, the models were too powerful to run.

And then if you wanted to, I don't. Do embeddings for photos that [00:41:00] you could use natural language to say, find me the photo of the dog, uh, at the beach, or whatever. Well, that was a different model than the one that was working on your email, which was a different model than the one that was handling video.

In fact, it mm-hmm. Probably couldn't even handle video. Now, again, it's one model to rule them all. It's a very powerful showing from Google,

Gavin Purcell: and again, that just makes Google's footprint better, right? Like if Google AI is the one that will work for people who have a Google Life, which I do, I think you do.

We're in Google Docs. Yeah, that is a lock-in for them. And like it means you keep paying that $20 for Google Pro or whatever it is, right? Like if, if I had a chat with my Google AI and that knew all the stuff about me, knew my docs, knew my email, knew all that stuff right, and the other ones didn't, that might make a difference.

Right? Which is kind of interesting.

Kevin Pereria: Well, only if you could chat with like a cute cuddly avatar that was powering everything. Sure. But there's no services that do that, Gavin. There's not a, there's single service out there that handle Oh, I'm sorry. Runway just announced characters.

Gavin Purcell: That's right. So runway announced characters, uh, you know, this is funny.

I just gave runway [00:42:00] crap a couple weeks ago for wondering like if runway was gonna start abandoning the kind of like high-end video model thing and they're launching this new thing, so. This is a very cool idea. This is a realtime interactive character interaction. This is using their act to model, I assume, underneath the hood.

But you can spin this up and it has an API. So if you want to launch an interview, uh, with a character or you want to launch an interactive bot that talks to you, it's a very cool thing.

Kevin Pereria: Yeah. Your bot can be a Lego character, it can be an inanimate object with a face, it could be an animal, it could be a realistic looking human.

The model doesn't seem to matter or care, uh, what it is. Um, and it can be powered by your own knowledge base. Yeah. So if you want an avatar of you or an avatar for your business or your brand, you can spin that up pretty easily now.

Gavin Purcell: Yeah. You know, Kev, one of the things I've been thinking a lot about when it comes to like blitz TRO and other game device stuff is this idea.

We've seen a few of these things and, and then was kind of based a little bit around this, but like you can imagine kind of a, almost like a star fox, like en uh, sort of en environment where you see popups of different [00:43:00] characters coming up. There is a world where like leading into like a voice-driven game that you can see characters pop up and talk back to you or in some form.

That voice in, in your interaction with it is interesting. There were a couple really cool use cases of this particular one I saw was like somebody was walking through Halo and they had like a Halo character up here that was able to give them advice when they were playing Halo, which was kind of a cool thing.

So you can imagine. Character driven, real time AI interactivity. It's kind of yet to be seen how this will kind of disperse in different places. But it's a cool first step for this, uh, and makes it easy for everybody to do.

Kevin Pereria: It's also interesting 'cause like, uh, Hagen is a product that I use all the time.

Yeah. There was another company called Synesthesia. There's a bunch of companies that are all kind of working towards this, en jamming towards this. Even our friend Hera launched a product not too long ago that that sort of goes after this as well. So, um, if, if it works to our conversation minutes ago.

Does it open AI or Google directly launch something?

Gavin Purcell: Here's one thing I'll say, this feels [00:44:00] like this. Somebody's gonna own this thing, right? Mm-hmm. Which is like, and, and Hagen was an early leader in this and one of the interesting things I think about Hagen, and this is not to, this is not to get you in trouble with that any sort of weeks.

I know that you've worked with that many of your day job, but like. You don't hear a lot from Hagen anymore. I know they keep implo improving their thing, but like this feels like it's commoditizing in an interesting way as well, and so there will probably be a winner or two that does this. I don't know if there's an incentive from the open ais or the Philanthropics of the world to do this particularly, whereas with agents.

Clearly there is. So this might be one of the areas where there is a winner, right? This idea of like, somebody wants to make an ag agentic like interactive thing, but you have to have the scaffolding to do all the graphics in the video that feels like it could, somebody could win coming out of that.

Kevin Pereria: Right. Um, look real quickly, it's not a sexy story, it just is an ironic one. We do have to talk about CloudFlare real quick. Yes. Uh, CloudFlare protects a giant swath of the internet. From, uh, denial of service attacks, um, from bots, from, you know, things [00:45:00] masquerading as human but not, and it tries to protect all of these different sites and services.

And they just released a new crawl endpoint, which is an API that can basically. Scrape everything. Crawl the entire internet, and no scripts. You can scrape everything. No browser management. Nope. They just gives you the HTML, the markdown, or the JSON. So the company that built an empire off of stopping bots from getting to websites is now helping people get their bots to websites.

We've come full circle.

Gavin Purcell: This is fascinating, and I will say a personal experience with this is when I built my Gavin purcell.com website with cloud, uh, with cloud code a couple of weeks ago, maybe a month or so ago. One of the things that was interesting is, you know, I, I use CloudFlare as part of the, kind of the final deployment of it, and CloudFlare at one point was blocking a bunch of LLM robots and like, I'm like, I don't want those blocked because I don't care if they scrap my service.

I want those in, I want those to come in so that I can surface in these things. And I would imagine this is this kind of real difficult situation that Cloud FFI is putting itself [00:46:00] in right now. Because to be agentic first to be a website that allows people to kind of like search and string together like all this interesting stuff.

You have to kind of be in one camp, but if you want to be like protective of the web and protective of content, you really have to be in this other camp. And this idea of like a one stop shop to scrape websites is only possible if you're in the Agentic website. So I don't know, there could be a real backlash to this.

I mean, there already is a big backlash. We've seen it happen and like maybe there's going to be a. Separate version of something like CloudFlare, which fights against these sorts of things. So I don't think this is good for CloudFlare, but if you're out there and you're trying to figure out, Hey, I wanna make a website like, I don't know, Kevin's open feet.com, right?

If you go to that, you might see a number of those things. You can now use this tool to essentially scrape it and recreate it with a a, an engine, which is kind of crazy.

Kevin Pereria: Yeah, and don't scrape that side guys. That was a lot of work. That's a lot of late [00:47:00] nights and it's a lot of weekends. It's a lot of passion and soul that goes

Gavin Purcell: into it.

Oh, yeah. S-O-L-A-I got it. Yeah, that's right. Do you think that there's probably, you know, there's probably a world, I, I say probably I haven't been there and I know somebody in our audience might have been, but like there must be an AI feat. Website that is, you know, the ai you mean just AI

Kevin Pereria: generated pictures

Gavin Purcell: of feet?

Yes. Like, so AI spiciness taken, taken over over web. They have six toes. Yeah. Oh, that's, that's a good website. You know, it's an AI foot probably that's something we can probably start up six toes.net bit. Ooh. And they're webbed six toes, not net, in their web. Wow. But there's some specific audience member who's gonna love that idea.

I, there's

Kevin Pereria: video of Will Smith eating spaghetti off of 'em too, but it doesn't matter. Gavin,

Gavin Purcell: we gotta talk

Kevin Pereria: about robots. In the living room. That's right. Everybody. You just wanted a laundry bot, but we we got so much more.

Gavin Purcell: Yeah. So figure, uh, figure Robotics just launched a new version of their Helix O2 model, which is their kind of model that drives their robots.

This allows [00:48:00] autonomous cleanup of a living room. And Kevin, I feel like robots are kind of like in the. Maybe even GPT-3 era right now, or even GT two where it's like, ah, this is so cute. They can do X, Y, and Z. But you remember when you can see it, you see the

Kevin Pereria: promise, it's

Gavin Purcell: on the

Kevin Pereria: horizon.

US Government Speaker: Yeah.

Gavin Purcell: And what's interesting is like this robot in this video, if you're not watching the video, is basically on its own cleaning up a very nice modern living room and going through it.

It's going very slow, but this is a step 'cause it's autonomous, right? Yeah. And we've talked about many of these robot videos are driven by people behind the scenes in a different country, like kind of driving a thing. This is the robot doing it on its own, learning on its own. So this is kind of the next step.

Kevin Pereria: My favorite thing about the video, twofold. One, the audio, because it, you just hear the servos, whirring, uh, uh, of this thing. And that is going to be the sound that we are gonna be like sleeping through, right? Yeah. Until we fill the pillow, slowly descend onto our noses. But like that is gonna be a noise that will be in your living room or your trailer.

In due time, you're going to hear the worry [00:49:00] of these s

Gavin Purcell: April and the robot all have to live in a trailer. That would be,

Kevin Pereria: we're a throuple a hundred percent by the way that we, a full-time RV throuple.

Gavin Purcell: That is a great idea

Kevin Pereria: for

Gavin Purcell: AI

Kevin Pereria: video series. It's a peacock series.

Gavin Purcell: Yeah. So we should make that, that's pretty fun idea.

Kevin Pereria: So, so the s the servo noises are fascinating to me, but it's the little. Human, and I'm air quoting here for the audio version. It's a little human things that the robot does. If you watch the video, for example, it it, when it crouched down to, to wipe a table, it takes the towel and it whips it over its shoulder.

It doesn't like take it and sort of drape it. It throws knowing the physics of the towel probably from having watched thousands of hours of training videos. It whips it over its shoulder and when it goes to put a pillow back in place on the couch, it doesn't gently lean in and waste the precious battery.

It yeats it. It just throws the pillow into the corner of the couch and I'm like, those are the things where you go like, oh, that's, there's something that feels human about this. Otherwise very slow and robotic thing. And I guess a third bonus thing, don't shade the fact that it picks up the [00:50:00] remote and hunts and pecks for a button.

Yeah's a very, very dextrous tiny little thing for it to do And hit. And it does it, and then it sort of wanders out a frame. It is sort of like it. It does. It is reminiscent of Biden exiting. Like a press conference. Yeah. Because it does sort of have things in its hand and doesn't seem to know why it's leaving.

It just knows that it has to leave the room. I want more. I wanna see what is, like, what do they tell the Robit go and clean up? Do they give it the three specific tasks that it has to do? It says it's autonomous, but I just wanna know how autonomous it is.

Gavin Purcell: You know, the interesting thing about this is like you we're talking at the early stage of the, oh, sorry.

We were talking earlier in the show about this idea of like, something failing over 45 minutes. What if you set it up to clean your living room and then you come back in the, you know, four hours later, do you know what the feeling is gonna be So mad. I'm gonna be so mad if it's like frozen, like underneath the, uh, coffee table and it got stuck there and nothing was done.

This is gonna be another level of that. You know, just polishing

Kevin Pereria: the dog. It's [00:51:00] laying on the ground. You're like, what are you

Gavin Purcell: dog? The dog has a bald spot. The dog has a bald spot right there. Alright, but Kevin, speaking of robot animals, even better, no deep robotics has dropped a robot horse. Don't do the horse, don't do the, this is my, I'm ready for this.

Bring on the robot horse because robot horses are a dream of many young. Probably young man. I don't, there's a lot of young women out there who are Yeah, interesting. Dreaming about robotic horses,

Kevin Pereria: white girls with one hair braid and a trapper keeper. Yeah. There's

Gavin Purcell: a weird,

Kevin Pereria: there's,

Gavin Purcell: so, anyway, deep Robotics has released this, uh, not released.

They, there's a, there's a robot horse that they have created and it, it kind of looks interesting. What I love is the horses like are doing synchronized dancing, and this might be the future of Dancing at large is like watching. Robots synchronized dance the same way you can watch a robot drone army.

Like kind of create things like, tell me what you're feeling right now watching this works. I can see your face. It's

Kevin Pereria: just, I, because I just, I mean, I, I, I don't, I don't know. I don't know, like if, if they [00:52:00] would've done a big announcement like this is the, this is gonna change the way cities design transportation like they did when the segway was being announced.

Right. And then release the robotic horse. I'd be like, sure. But like that, that's is why I cringe. 'cause it's like, it's either for warfare. Right. People are gonna be on these things galloping very quickly with AK 40 sevens. I didn't even think about that. Or, or it's gonna be something I have to dodge when I visit Santa Monica because I was gonna be on a cyber horse tour going down the promenade.

Gavin Purcell: That's, that's exactly what it's gonna be. Instead of it being the segues, you're gonna have people riding, it's gonna

Kevin Pereria: take up even more space.

Gavin Purcell: A bike lane. Yeah. Yes, but I didn't think about war. They'll, that would be really ing nuts.

Kevin Pereria: Nuts and bolts into the middle of the bike lane. Like I just,

Gavin Purcell: it falls over.

It hits a grade and kind of like falls over. All right, so time, see what you did this week. It's say, I see what you did there

AI See What You Did There: so times ya rolling without a care. Then suddenly you stop and shout.

Sam Altman: I see what [00:53:00] you did there,

Gavin Purcell: Kevin. Speaking of, of seeing inside of, uh, robotic things, there's a great, cool visualization from a guy named Nick underscore, Bessie, BIS. ESI and basically he took three Js, which is the, you know, web-based kind of like, almost like game platform. People use it to do all sorts of interactive video stuff and things like that.

And he created a thing where he holds up this thing using his camera and he can see like an x-ray vision of his body. Now of course, this is not his actual body. He is not giving an x-ray shot, but it kind of gives this illusion of what it's like to see inside a body. Yeah. And when I saw this I was like, this is so cool.

It feels like, you know, in five years from now. This is like an amazing grade school science project, right? You can see this world where in the future kids are gonna be able to do this sort of stuff and kind of just be able to code it themselves. I just thought this was very cool.

Kevin Pereria: Yeah. Unfortunately the Department of Homeland Security just licensed it for $20 million, so unfortunately, yeah, and they're never

Gavin Purcell: gonna see it again.

You'll never see it again. Sorry, [00:54:00] this one, Kev, did you see this? This guy? So Jason, uh, Elli Barre. Found in Halo ISO Online. So if you're not familiar with iso, and ISO is like kind of a, a, you actually probably know the technical word, but it's like how you used to be able to grab whole games online in different places.

Basically, he took a Halo game and an ISO file and was able to make it playable with Mac, which to me was just like, that's great if we're opening this door where you can just kind of pull this old software out and suddenly it can be available. That was very cool.

Kevin Pereria: That's cool. There, there was similarly, um, people have been going on a tear about using, uh, Claude Code to reverse engineer old DOS games or NES games.

Yep. And just, you know, you don't need the source code, it'll just go and figure it out and kind of decompile and recompile and like, that's kind of crazy. But I do look forward to the future. Like even something like Doom where they give out the source code. I'm surprised someone hasn't made like, or something where,

Gavin Purcell: Hmm,

that's a great idea. You should, we should not say that. Should that put it on the board? [00:55:00] Should that Yeah.

Kevin Pereria: Put

Gavin Purcell: it on the board because that's like, we're

Kevin Pereria: never gonna do it.

Gavin Purcell: No, but actually, yeah. Yes. Like, because, because honestly, that would be cool to be able to say like,

Kevin Pereria: and it should be multiplayer. Dammit.

Gavin Purcell: All we'll be doing that. A we'll be doing that AI foot website right after this. So let's move on.

Kevin Pereria: So, um, uh, YouTuber Green Code, who is a great follow. I'm, I'm embarrassed that I wasn't following a lot sooner. Uh, they have all these like, really. Uh, weedsy, but fun and approachable videos on like really advanced AI topics.

And what they did was find a tennis data set. We're talking like players, their height, um, what the, uh, the, the scores that they get, the how many ACEs they get, how long their games typically go. Like all this, this massive rich data set that they didn't make, but they, they took and then they spent a lot of sleepless nights.

Teaching a machine all of the data so that it could create an elo, like a score, a ranking for the players, and that it could then try to predict the outcome [00:56:00] of matches. Um,

Gavin Purcell: that is so cool.

Kevin Pereria: It, they, they, they have a YouTube video explaining it all. There's a, a great expost that someone did distilling everything that, uh, that GreenCo did.

But basically it got about 85% of the predictions correct. Wow. Um, which, if you're a degenerate, your sports betting muscles just started twitching. Right. And you're loading up a calie window right now. But if you're like a, you know, a, a math nerd or a machine scientist, you're going like, that is. Pretty incredible.

Like that's a pretty crazy win rate. And green code actually replied to the thread where someone was dissecting his work and said, um, there was actually data leakage and I should have predicted it way more like the interesting, I should have done way better. So if you just look at the posts and, and watch the YouTube video, you'll see the way all the data goes in, it creates these scores for these players.

And then you use these scores to mash up, uh, against each other and see who's going to probably win the outcome of a match. And you realize the future's gonna get very, very weird as we start siphoning. All of that data.

Gavin Purcell: Yeah. Well, a friend of mine right [00:57:00] now is doing this against DOTA matches, which is interesting.

Which is like something that like he's actually betting on. Like there's a guy out there who I, who I know well and his like whole world, he's doing well. Like this is like this weird world like. We talked about this a little while ago about this idea about like AI agents starting to get better at the edges that people have in prediction markets and things like that.

But anyway, it's pretty crazy. Alright, before we go, there is a great video that everybody should watch. One of my favorite AI videos to date. Kevin, maybe let's just play it for people here before we introduce what this is.

AI Voice: I will take the ring to mole. What can I help you with?

Frodo: I have a ring. I would like to sell you

AI Voice: baseball or football?

Frodo: Neither. This kind.

Rick AI: Oh, this kind.

Frodo: I wish the ring had never come to me, so I'm here at the pawn shop today to try and sell it.

Rick AI: I really gotta get this ring in my shop. This is not as uncommon as you might think. They

Gavin Purcell: actually, so you know what's going on here is it's Frodo baggage. Elijah Wood, who's Yeah, exactly.

Who's going to pawn Stars. And this is just those [00:58:00] weird things where like somebody had an idea, they said, I am fan of Monster Stars fan over the rings. Yeah. What if Frodo. Had to pawn the ring and like, just very well cut together. This is a human edit, like obviously making choices from the show, making choices from AI video using different parts of different things.

And this is from Reddit user. You are now dumb DUM, which is a classic good Reddit name, but go check it out. Um, we're not exactly sure who made this, but we assume that might be Oh,

Kevin Pereria: it, Tim, it's Tim is shorts. It's uh, it's David Unger from Dungar Zone, who you've shouted out in the past as a, as a good follow, um, made a's

Gavin Purcell: part of his,

Kevin Pereria: uh, shorts here.

Gavin Purcell: He made a great video about dinosaurs and put the baby dinosaur from the dinosaurs, a B six C sitcom into Jurassic Park. I dunno if you saw that. It was very good. But anyway, he's great also about sharing his, uh, his workflow. So go check him out. And this week everybody go and try to make something. I'm telling you, if you get inside Cloud code or replier of these other things, the power of what these can do right now is better than you ever imagined.

If you are somebody who have mostly been [00:59:00] using chat t or Claude to answer your questions. Try to make something small because this is the time. So you just gonna say anything, eh? You just gonna sit. All right. We'll see you Y all next week, byebye, whatever. Yeah. See you all next, by the way, we'll see Y Allall next week, maybe for an early episode.

We'll talk more about it then. Bye-bye.