Astra Ends Math, 1 Person $1M Companies, Hank Green Is Absolutely Right | John Gruber, Shaun Maguire & Isaiah Taylor, Justin Lopas, Beau Gaston, Ron Arel

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Today's Monday, August 3, 2026. We are live from the TVPN Ultradome, the Temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com time is money save both easy use, corporate cards, bill pay, accounting and a whole lot more all in one place. How was your weekend, Jordy?

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My weekend was good. My weekend was a little hot here

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in Southern California, but all more reason to get to the beach, enjoy the nice weather.

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It's been a good summer on a boat.

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That's nice.

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What more can you ask for?

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That's nice.

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We got a great show today. Unfortunately only one venture capitalist and I think that's because it's August.

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Oh yeah.

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You're going to see us really struggling.

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It's going to be hard to get those VCs.

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To get those VCs every other month.

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It's hard.

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They're happy to jump on same day moments notice, you know, it's important. We got one today.

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Yeah, we got 1.

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Sean McGuire coming on with Isaiah Taylor announcing a $1 billion Series B led by Sequoia. Very excited for that conversation. We got Justin, co founder of Base Power, another one billion dollar round Series D. And then we have the very the founder of the demon robot.

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Yes.

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That you may have seen last week. It's a centaur with horns, Bo Gastar. And we're very excited to talk with Bo and get a sense for what went through his head when he asked a robot like that, can you stop?

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Can you not?

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Can we pull up a picture of the robot? I want to. There it is. There it is. So this is the friendly robot that Beau is excited to get into disaster zones to help rescue people.

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And apparently the horns are critical because there are cameras on the end of each horn and that allows to see the ground, which couldn't put those cameras anywhere else. I guess it'll be a lot of

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fun and then closing out with Ron over at Intology. But let's get into the show. What happened over the weekend? Did anything happen over the weekend, John?

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There were a couple things. The big debate that I was tracking sort of outside of tech but tech adjacent, was the cancellation of Hank Green, the YouTube creator. Not quite a cancellation, more just some backlash. Hard to always put a proper sizing on a mob when a mob comes after a creator. But Hank Green, the YouTuber and Really Media entrepreneur, he's grown a huge business which we can sort of go into is getting pilloried on social media over using chatgpt for research. Very controversial these days. Only a billion people do it, but yeah, it's the number one app in the App Store. But he's getting, he's getting a lot of backlash from certain members of his audience. I don't want to characterize the whole audience as being part of this, but it's a very silly.

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There's at least thousands of people, it seems like that.

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It's always hard to tell. I mean, thousands of people that are liking a post about it. There's like maybe dozens of posts. I don't really know how to put, how to put a scale on these things, but Hank Green is definitely going through it, having to sort of apologize or qualify or sort of state that he will adjust things in the future. And it's just sort of interesting to hear how he went through this process, what he says is going to change and where the backlash is coming from because there's a lot of misunderstandings about it. And what's interesting is that he is a science and education creator and science and education are potentially the most affected by AI right now. And so it's a real challenge to simultaneously say, I'm going to cover math, I'm going to cover science, but I'm not going to touch AI. That AI stuff's bad because as we also saw over the weekend, AI is making a bunch of advancements on math. We've been seeing this for a while. But the latest version of the story comes from Noam Brown Polynomial over at OpenAI says an internal version of Astra, OpenAI's next major frontier, next major model family solved 10 major open problems in mathematics, quantum complexity and theoretical computer science. The, the achievements are so, so extreme at this point that I don't even think it's worth us trying to break them down like we did that with

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the so instead problem Tyler is going to run a 5k here in the ultra dome to do a little victory lap for the research team.

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But not everyone is impressed with it because Gary Marcus says, wake me when Astra solves a significant open world problem that doesn't revolve around formal verification. And of course, Daniel Eth says the goalposts are on a completely separate planet. It is a good point. Obviously AI is doing better, informally verifiable tasks at the same time. Still impressive because there's a lot of things that are useful and verifiable, like did this drug cure your cancer or not? Or did this job get done or not? Like we've been using these recommender systems for Lots of things, they're very valuable all over. But it is funny, the debate over, is this AGI, is this asi? Those terms will always be vague then.

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Yeah. Going back to Hank.

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Yes.

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So all he did was admit that he used some sort of AI tool for research.

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Yes. So I will take you a little bit more through it. First, I'm going to tell you about Shopify. Shopify is the commerce platform that grows with your business, that lets you sell in seconds online, in store, on mobile, on social, on marketplaces. And now with AI agents, they got AI on Shopify. So if you're selling something, you're using AI. So Hank Green, he's an OG YouTuber. He joined YouTube in 2007, I think less than two years after the platform actually launched. And he grew, he got a lot of views, but he also built a huge audience and created a real media company around it. So he has vlogbrothers, like a vlog channel. Then he has Crash Course, which is a really, really huge educational channel. He runs VidCon, which is basically the premier conference around YouTube and the creator economy. I've been, I think, once or twice. It's a lot of fun. And over the last 20 years, he's become one of the most trusted educational creators on the platform. He's also just like, he gets the vibe of YouTube very well because he's been around it so long. Never really stepped back fully, but always been solid audience there. So last Wednesday, he published an episode of a show called Ask Hank Anything. And it's an interesting concept for a show. So he brings on a guest, but then instead of just doing the interview, tell me your life story. Ask the guest a whole bunch of things. The guest brings questions for him about science or whatever. They have a big, long conversation. And if there's something in the show that he can't answer on the fly or he's not prepped for, he will go do the research and then get the actual answer and then cut that into the final episode. So you'll be watching them hang out, they'll talk about some odd thing. He was talking about this. Have you heard this Kiki and Bouba thing? There's like two words. That one, basically, there's two shapes. One's like a fluffy cloud, the other's like spiky. Spiky, like star, essentially. And if you ask people generally, which one would you assign the word Kiki to and which one would you assign the word Bouba to? People always pick. Bouba is the cloud, and Kiki is the spiky one. And it's like the sound of the word has a shape to it. And this is just something in our language that shows up all over the place. So he's like, telling the story of this. Like just somebody ran a science experiment. They put a bunch of people here, they pulled a bunch of people, they put together this result, and this is what happened. And so he needs to compile all of that quickly because you get off the show, you have the rest of your job, but then you have to go answer these questions and have all the information. And of course, he uses all sorts of research tools, but he was accused specifically of using ChatGPT to write the script, which is interesting because after the episode went up, manager JoJo posted a clip of him from the episode and accused him of using ChatGPT to write the script. The key line is Hank saying, quote, I appreciate the pushback. And that's sort of an AI phrase. But that wasn't one of the really trigger AI phrases like, you're absolutely right or it's not this, it's that I appreciate the pushback is something that the AI models say occasionally, but you wouldn't think it would make it into a script. But that's why people jumped on it. They were like, wow, he was so careless that he left in a turn of phrase. That was the model talking to him about, I appreciate the pushback. That's not what happens. He's actually responding to the guest pushing back on him about this concept. And then he answers it. But he was just talking. But it feels out of place because he's talking to the camera at that point. Even though in the video he's talking to the guest after the fact, the way it's edited is him direct to camera. So him saying, I appreciate the pushback to the camera. What is this, Beans?

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I don't know.

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But him saying that I appreciate the pushback feels a little weird when you just watch it, but it makes sense in the context of the longer video. So the headlines proliferated over the weekend to the tune of Hank Green accidentally reads AI prompt feedback. Feedback left in his script. Hank has to not has to deny this, but he goes on to admit that he does use ChatGPT for research. Dun, dun, dun. This did not land well. People don't like the idea of him using ChatGPT research, and clearly it's just a small subset of his audience that actually takes the time to flame online about AI usage. But it is. There are still dozens of posts, maybe hundreds of posts about how AI cannot be used for research because it hallucinates or it removes some key human element of the process of learning, something like that. It's very odd for anyone who's used modern models because there's a lot that I can't do well yet. But pulling a bunch of links and quotes together from across the Internet is something good, pretty good at, and it's definitely reliable for that. And so Hank clarified, the script was not written by AI. He was just going on ChatGPT and saying like, hey, where did this original research come from? Pull up the paper, download the PDF, crunch it all together for me, pull some quotes from it, change this into a different format. I want it in this unit instead of that units, those types of questions. But he still said that he has not been happy with how he's been using AI and may wind up publishing less as a result. He feels he's on a little bit of a treadmill because he's more productive with AI, but then he posts more and then that's a feedback loop. And of course, at this point in time, he's built his career over 20 years. He has a very sustainable business. He probably doesn't need to be on as much of a treadmill as perhaps an early stage creator might be. So it doesn't feel like it's total audience capture, but there is this interesting opportunity here that I was sort of just identifying. AI is clearly this wedge issue. Billions of people use AI and get value from it, but at the same time, it's deeply unpopular. And there's lots of people who like to post angrily online about how AI is bad for a variety of reasons, but education and science in particular are going to be intertwined with AI for the foreseeable future. Like, every advancement in science is going to be AI enabled. And so if you're a science educator and you constantly have to be dancing around AI and be like, oh, yes, like they solved this math problem, but I don't like it because AI was used. Well, you're going to wind up just not being able to talk about math or science or whatever's happening because you're constantly doing this dance around AI. And so that's fine. There's that audience that will love that, but there's also an opportunity for a new audience that's maybe a little bit more nuanced about this and maybe just, yeah, it's fine that you use that for doing research. Maybe as long as the script sounds good, I'm fine. Or as long as you are clear about your policy, which is odd because that's what he. He was always clear. He's just still got attacked and had to go on this defensive. I believe he has, like, a published policy around how him and his employees at his media company can use AI or do use AI or don't in various scenarios. But this was the first time I've seen, like, real backlash to just pulling that up on ChatGPT. I totally understand there. I mean, there are people that could just use AI to generate the video and not be involved at all, or use it in the script or use an AI voiceover.

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Yeah.

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It's just funny because I have this. This reaction all the time.

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Yeah.

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When I realize a video on YouTube is just fully. It's a fully AI generated script. Somebody just reading over.

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Yeah.

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Or AI voice is reading it. Yeah, yeah, yeah. It sort of just depends. At the end of the day, it's just like, is the content quality? Is the insight valuable? And what I would go to Hank for would be he does a bunch of research across a whole bunch of tools. Google, ChatGPT, whatever he uses. Read a book, read papers, watch documentaries, listen to podcasts about a topic, and then tell me what Hank thinks is interesting about that. The filtering process and the taste is what.

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Back in your day growing up, did teachers ever say, I really don't want you using Google for the homework?

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No, there was never pushback because Google didn't exist. There was pushback against Wikipedia. It was. It was like, oh, Wikipedia, is that reliable?

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That's it.

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Anyone can edit Wikipedia. So don't use Wikipedia as a source.

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Which really just means, well, that was fair. Go to the. Go to the original.

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And it's kind of the same thing with ChatGPT. It's like, don't, like, go to the source that ChatGPT links you. And if that's a paper and it's academic and it's hosted on the right thing and it's has the right. The right provenance, then it's okay to use. I don't know. It'll be interesting to see how this all fares. There's a lot of backlash, but it was sort of like a lot of people in tech, I think, were getting, like, sort of whiplash from watching all of these arguments pile up. Someone put together a cool chart here of the good arguments and the bad arguments from the pro AI crowd and the anti AI crowd. So an example of a good argument around this from the pro AI crowd would be, AI is a powerful and capable tool. And then Like a bad argument from the anti AI crowd would be, AI is useless in research in general. But there were bad arguments that were put forth by pro AI people. Something like, you use data centers, like Hank uses data centers. And it's like, yes, YouTube is hosted on a data center, so are you

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to write this comment?

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Yes, but that's not. The actual data center that's required to host an online comment is wildly different than a massive gen AI system, like cooking tons of tokens and actually setting the GPUs on fire. Right. And then a good argument. The best argument from the anti AI crowd was said that AI usage in science communication reduces trust at least a little. Which is interesting. I mean, yeah, you do have to check these things. And we do see tons of examples of people actually leaking, you know, AI phrases and weird AI like hallucinations into scientific research. There was that example of. There was some PDF that was scanned and there was a word in one column and a word in another column that got bled together when the document was imported. And then a whole bunch of. A whole bunch of scientific research started referencing this phrase that doesn't exist and just came from basically a hallucination or like a quirk of the optical character recognition. So anyway, they canceled my goat for using LLMs to search papers that he would need to read to make his videos. They want him to use Google search like a Caveman in big 2026.

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That about the crazy thing is I don't. Can you even turn off AI mode in Google now? Maybe.

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I think you can. I think you can. You could use DuckDuckGo. I don't think that has AI yet. We'll see. Anyway, Jeremiah Johnson says, I'm fascinated by.

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Wait, is it really by duck AI?

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No, no, no. Wait, are you serious?

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Yeah, go to duck AI.com or no, just duck AI.

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Good name. Duck AI. There you go.

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GPT 5.4 nano.

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There we go. Okay.

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Unavoidable.

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Wow. Yeah. The market has spoken, I suppose.

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Yeah.

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What do people do? I imagine you can turn off AI mode somewhere in the settings. Or at least you could. Or at least you could get some sort of Chrome plugin that deletes that. Like an ad blocker, if you really, really cared. But it seems like a lot of work at this point.

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Anyway, this was interesting. Ryan Low on X is sharing a heartbreaking essay by a mathematician last week for this most recent news drop. So this was before Noam Brown.

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Yeah.

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Showed the recent breakthroughs by Astra, said, there is nothing I can do. There may be Nothing you can do. I have no prescriptions, policy recommendations or coherent call to action. I just want to be honest and open about my emotional in spiritual response. I want to feel seen. I want folks like me to feel seen. I need the architects of our new mathematical paradigm to look me in the eyes and acknowledge our shared humanity and soul before they deliver the coup de grace. I need most of all for us to understand what we are really doing.

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The Dark night of mathematics Kerwin, Hampshire. Mathematician, researcher from the University of Auckland who recently authored the viral essay studied mathematics. Interesting. It feels like I would be surprised if mathematical education goes away. It feels like a lot of these problems should be interesting to apply, but I understand that's a different. That's a completely different discipline. It will be interesting to see what happens next because there are more advanced problems. The Millennium Prize problems. P versus np. Navier Stokes. Right. There are a number of problems that are still unsolved. What happens when they're all solved? Do we create new problems? Where do we go from there? Do we start applying them in different ways? What do you think, Tyler? Yeah, I mean obviously like any advice for mathematicians?

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I think so. In the Scuttle article he says like mathematicians are paid to like solve.

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21 year old podcaster has advice.

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Math.

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Exactly.

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So he says math sessions are paid to solve theorems, which obviously I'm not in academia, but it seems like it's kind of their job. But also it's like you're in a university, right? It's like to teach it.

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Yeah.

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I mean there's plenty of math professors that sort of try and solve theorems, but also mostly teach and don't solve that many theorems.

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Yeah.

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And also presumably if you can solve all these conjectures, there's going to be new questions that open up. This is like the entire history of all science, right?

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Yeah.

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It will be interesting to see the application of this stuff because it's so abstract at this point and it feels like it's very. Everyone's saying like, okay, based on this, this is going to flood through material science and flood through chemistry and biology and that would be awesome. Everyone would love. Oh all of a sudden like the electric cars have twice as much range because we solve some fundamental thing. It'll be interesting to see where the new bottlenecks are. There of course will be always Math professors hate AI for one simple trick. Just scale, scale, scale, I suppose. Let me tell you about railway. Railway is the all in one intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases and more while Railway automatically takes care of scaling, monitoring and security.

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Boom.

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Boom.

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What else is going on?

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This I just like this Gary Marcus. He's really in the arena with this. There's this post.

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It's a really good bit. Which one? The Gary Marcus bit.

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It's not a bit. He really believes it.

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No. But I think at some point he flipped into bit mode.

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The pure LLM. Yeah. So he he will always take issue with the idea of something being a pure LLM. A pure LLM solving something. And who is it? Hassam says the LLM use a calculator burn the impure Bro Horses are very useful. This is likely not a pure horse. Pure horses still can't carry an entire family and they don't have wheels. The goalposts are on a completely separate planet now. First they came for the mathematicians and that sucked because I was a mathematician and really did not expect that. Not going to lie. It will be interesting to hear from Terrence Tao. He's been talking about how he uses AI in math and has been sort of a white pilled voice every time I've heard him talk. So we'll be interesting to see how he reacts to the latest round of advanced mathematics. John, what is left?

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It's time.

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What?

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It's time to talk about the rise of one person $1 companies. One person $1 in the Wall Street

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Journal Million dollar companies the rise of

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million dollar companies with just one employee.

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Let me tell everyone about Console. Console builds AI agents that automate 70% of it, HR and finance support, giving employees instant resolution for access requests and password resets.

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Wall Street Journal is saying AI tools make it easier for founders to get started alone, and many stay that way as they grow. Ben Broka launched a company last December that offers AI tools to entrepreneurs.

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That name's familiar.

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We've had him on the show, already added 10,000 paying customers and is on track to bring in 10 million in revenue this year. One thing he hasn't added any other employees. The 40 year old is part of a class of entrepreneurs who are launching and often running new companies on their own artificial intelligence tools. Answer broke his emails help write and debug code field requests from customers, sign up new subscribers and grant refunds when when issues arise. Broca relishes his ability to make whatever decisions he wants on his own, often from his sun drenched Sausalito, California living room. I think compromises make lukewarm results, he said. Once upon a time, running a business of a certain size required a team. AI is turning that assumption upside down. And more aspiring entrepreneurs are going it alone. An analysis by the payments company Stripe. Tyler, look up Stripe shows there are thousands of solo operators on the company's platform that are generating over 1 million in revenue, with their ranks doubling between 2023 and 2025.

22:03

That's pretty crazy. So this is on Pulse, right?

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No, no, no, no, no.

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Oh, on Stripe.

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Definitely not.

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Okay.

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This is just Stripe.

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Okay.

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The number of solo. I'm sure I would be curious if Pulse has any companies that do more than, you know, a thousand dollars.

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I mean, you're, you're looking at the.

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Because, because, to be honest. Because, to be honest, like, I actually do think success for pulsea is like just making back even a dollar more than you're spending on Pulsea. Right?

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Because there's a YouTuber who's been demoing different AI systems. Fable and Soul and Kimmy. And saying like, go make me money is basically the only prompt. And he lets it cook for like a week. And he'll be on like a $200 a month subscription, see if it can make 6 cents, see if it, if it can make $10. And he's getting closer every time. And he of course, has to do something, set up API keys and do little things. But it's an interesting experiment. Ben Awad, you should go check it out.

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So the number of solo operators, according to Stripe, also crossing the $10 million threshold, nearly tripled in that same span. In the past, people without business contacts or particular savvy might not have known how to get their ideas off the ground, said Ernie Tedeschi, Stripe's chief economist. Now AI can be a built in business partner.

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Yeah. How does Stripe know if you're a solo operator? Like if you're. Because if you're a podcaster and you set up a Stripe account to accept money from advertisers, you could be having a million dollars move through there. But if you hire an editor or not, that doesn't necessarily show up in Stripe. So they must do some sort of polling and ask.

24:20

Yeah, I think in your account at some point you say, how many employees do you have?

24:41

Okay. And if you say, yeah, I just got one.

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But interesting. I guess one question, it's definitely grow. One question I have with the data is like, what if you just set up your Stripe account? It's like, how many employees do you have? And you.

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1. And then you wind up adding people and you don't go on update. Yeah, possible.

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Yeah. Because they don't have the payroll. I don't know how. I don't know how they would have visibility into, into payroll, especially like individual employees.

24:58

Yeah, yeah.

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They do have a sense for how many people obviously are like added to your account, but sometimes it's like, oh, true account. If you add your cpa.

25:11

Yeah. You know, and that's a contractor, not an employee.

25:17

Yeah.

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AI's ability to handle various administrative tasks makes it potentially useful for launching solo businesses in many fields. But the technology's ability to handle key tasks in tech like coding, make that field a particular hotspot. Analyzing Census Bureau data, Bank of America's Institute economist Taylor Bowley found that among all industries, new business applications in the information sector

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have seen the biggest percentage increase, nearly 45% over the past year.

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Yeah.

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At the same time, the rate of information sector applicants saying they plan to hire workers has experienced the sharpest decline of any measured industry. This census dataset doesn't track solo operated businesses, but the numbers broadly show in tech and beyond that applications are flat among businesses likely to hire workers, but generally rising elsewhere. Economists say that's a strong sign that solo operators are in the upswing. Wow. Yeah, that chart is really up and to the left. New business formation. This is in the information sector in particular. I want to know more about what these people are doing because at the same time we saw levels IO talk about like the indie hacker sort of seeing declining revenues or more headwinds there because the little SaaS product that they would that indie hacker might build. I'm thinking of like those one off websites like YouTube downloader4k.com, it's just like a piece of software that people land on through SEO or like something that is like an image background removal website and it just does one thing thing and it does it pretty well and it scales to six figures or seven figures. Those little sites are now getting sort of eaten by models and eaten by other people and you might be able to buy code your own, but at the same time like they might have a long, long term.

25:45

Tyler update.

27:03

Okay, so they basically calculate the number of solopreneurs based on how many people have like there's like special plugins or platforms that are directly for like the solopreneur. So they basically use that to like get a proxy of the general percentage of solo people on stripe.

27:05

On stripe. Oh, they have like a special flow for solopreneur.

27:22

Interesting.

27:26

Yes.

27:26

Cool.

27:28

So they say that they're almost certainly underestimating the number.

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Hey, Julian Weiser, I know him, says the bar for getting started has never been lower, said Julian Weiser, who runs a San Francisco based accelerator for solo founders working in tech. The accelerator, which offers founder seed money and mentorship in exchange for an equity stake, attracted 4,500 applicants for 10 slots made available its most recent cycle, nearly five times the number it drew when it launched last May. Now he's been growing this a lot, but that is staggering. A lot of people want to be solopreneurs. Going alone with AI can still be surprisingly expensive. Broca said he was losing money on many customers accounts while paying to access Anthropic's Claude to run his clients requests that AI company as well as others charged based on usage. He has since switched to free open source models from China. Broca says he has raised $30 million from investors and at the same time has saved millions in salary since he hasn't needed a team of software engineers. Another risk if it's easy for one entrepreneur to launch an AI assisted business, copying them can be easy too. This creates anxiety for founders like Troy Johnson Johnston, who runs an AI assisted business alone in Orlando, Florida. Everybody has the sword and we all have the ability to unsheathe Excalibur now. Johnston what a great quote for the Journal. I love it. He's 40. He used an AI. He used AI to code an app that helps people get the most out of credit card benefits. Huh. It's interesting. Pick, pick which card you want to use because you might have multiple cards. One that's good for dining and you build an app for that. There's been a few apps that do that. The points guy had a whole blog around it, media company around it still does, but interesting to sort of like yeah, go and actually vibe code that a lot of these things. It's like you could probably just use the models themselves for this. Just have a thread that says hey, these are the cards I have go pull all of the data. When I'm about to buy something, let me know. But at the same time, there might be some value for something new with a deeper integration somewhere. The company makes around $3,000 a month in profit with no employees and continuing to grow. What a run for Troy Johnson, who loves King Arthur related metaphors for business. What one person businesses will mean for the labor market remains to be seen. Polling has shown that Americans are worried that AI will replace jobs and ties. Top economists are wrestling with that possibility too. But AI is also creating lots of new jobs, and the go to loan entrepreneurs show the technology can both open doors and limit employment opportunities. If everyone's hiring less, but you get four four times more firms. What does that do to headcount? Said Rembrandt Koning, an associate professor at Harvard Business School who studies entrepreneurship. He co authored a recent study that found that among 50,000 startups the researchers examined, those focused on AI tech tended to operate with 25% fewer employees. It's interesting because haven't we seen the ramp data that said that AI adopting companies were hiring faster but maybe they still lower operational headcount but hiring faster because of hiring growth? There's like three different factors that are going on here, sort of mixing all together. Koning, the professor also believes in believes a soft hiring environment that has left some people mired in long job searches has encouraged more to try their hand at launching businesses. That makes sense. Some founders cite different motives. It's a perfect storm of post pandemic burnout and a reevaluation of one's priorities and also booming AI and a sense of what's possible, said Samir Ahmad, 39, who lives in Brennansville, Pennsylvania. Two years ago, Ahmad decided to leave the corporate job he had worked at at Verizon for almost two decades to start a solo co coaching and consulting business. He had been seeing social media posts touting the ease and virtues of AI, which he liked to chart, which he used to chart a business plan and help with marketing. It was like my chief of staff second in command. The business ultimately petered out within months though and Ahmad is back to full time corporate role with a utility company. For Claire Vaux, 41, AI helped turn her passing impulse into a business. She was working full time as a tech executive when she tapped AI in late 2023 to help code an app that would help manage documentation and design for new products with customers ranging from financial services to healthcare firms. I was copying and pasting from ChatGPT, said Vo, who lives in San Francisco. She put her app online for $1 a month. Wow, that is cheap. And within weeks we I thought we

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didn't know how to make apps that cheap anymore.

32:01

Yeah, I mean it is a subscription at least not one time. But she put it online for a dollar a month and within weeks people downloaded thousands of times. Nearly three years later, Vo's company, which she ran solo for nine months before hiring an engineer, now has 100,000 users and is on track to make seven figures in profit this year. Wow, that's remarkable. At a dollar a month. That's crazy. AI handles the company's marketing, sales and customer support. Well, AI is a shortcut Vo said her network and credibility in the industry were key. I think people over index on how easy AI is and under index on how much I did to get to this point. She said she's still.

32:03

Yeah, I just want to see, I want to see five companies that make more money from their business than they give pulsea every month.

32:40

Yes. Polsia has some public dashboards for how much people are spending or something like that.

32:51

Yeah, they have a public dashboard. Let's see if I can find that again.

32:57

While you're doing that, let me tell you about Cisco. Critical infrastructure for the AI era unlocks seamless real time experiences and new value with Cisco. And if Jordy's continuing to look, I'll also tell you about public investing for those who take it seriously. They got stocks, options, bonds, crypto treasuries and more with great customer service.

33:05

Trying to find the dashboard. I was looking at the dashboard that was showing. There's some, there's. Okay, I think Tyler found it. Thank you, Tyler.

33:26

Yeah.

33:37

So right now you can see all the different things that the companies on pulsea are doing or at least some of them right now. So far Today, companies on Pulsea have spent $373.

33:37

Is that today on ads today?

33:51

Yeah.

33:53

Well, it's still morning.

33:53

It's still morning.

33:54

So we're pacing only about. I don't know what time zone this is in, but yeah, the big question is, is any of this stuff actually working or is it more like kind of a video game effectively that people just enjoy watching the machine hum, but there's not really much happening.

33:55

I mean that was the thing for midjourney. And so Suno, I think in many ways, like midjourney, when it launched, people totally.

34:15

I mean,

34:23

no, okay, hear me out.

34:26

Okay, I'll hear you out.

34:29

Okay.

34:30

When midjourney launched at the Steel man,

34:30

when midjourney launched, people were like, this is going to take artists jobs. And it was like, okay, so if that plays out, then I'm going to go to the MoMA and there's going to be a show for someone that just prompted midjourney and the highest auction at Christie's is going to be some midjourney artist. And that's not really what happened. Like people aren't using midjourney to make fine art, but people love mid journey. Like they love the activity of going on midjourney and generating and prompting and getting an image back. And then maybe they send it to their friends, maybe they use it a little bit, but it's not exactly the same of, like, the process of becoming a fine artist. It's more like they're enjoying the process of just making. It's more like just having a guitar that you just like to practice and noodle on versus like actually being a touring artist. And so, like, that's certainly my experience with Suno is it's fun to try and make a song and then listen to it and then be like, wrestling with the thing. And it's possible that that could be the same activity for. Or like, okay, I'm gonna go build an online business, see if I can get something out. But it's not really like a job. It's more of like an entertainment product.

34:32

I don't know.

35:43

What do you think?

35:44

Yeah, I mean, you could easily see it turning into like an ender's game scenario where it's like a game and then it's like, oh, that was actually a real business you were starting.

35:44

And, you know, you offshored the last

35:50

job,

35:53

you sent all the labor overseas. You rolled up the entire H Vac into industry. That wasn't a simulation. No. Based on my steel, man. Do you agree or do you still disagree?

35:56

No, I just think that you could use Mid Journey to create a beautiful asset that you could get some enjoyment out of, or you could use it for your business or whatever you're doing or to just create AI art. And you could use. Suno is just, like, deeply entertaining. You go on there and in five seconds you make a real song that sounds like it was recorded in a real studio.

36:08

Yeah. And there might be something too, like, okay, it is fun to go and build a SaaS product. Like, it is fun to go the pro. Like, the game. It's a game, right? I don't know, Tyler.

36:31

Okay, just on your example earlier of, like, the MoMA artists, like, that's like the insane long tail of artists.

36:43

Yeah.

36:48

That's not like the average, you know, center of the. Of the curve artist that, like, okay, midjourney maybe is like, doing a similar thing to what people are producing.

36:48

Yeah, maybe. I don't know. I would just be surprised if the. I don't know. Maybe the way to put it is like, I'd be surprised if, like, the majority of midjourney users are using the product as an artist career path or an artist career path. Like, they're like, okay, I got my image. Now I need to get it printed. Now I need to go do a small gallery show. Now I need to go talk to an auction house. Now I need to go and pitch it to a Bunch of collectors and, like, go through the process of being an artist. I think a lot of people are just like, cool, I got an image. Like, this is nice. Like, job's done. Now back to whatever else I was doing. Oh, like, I have some free time. I could go play a video game. I could go listen to music. I could go generate some images. Images and have fun with that and see what those are like and then just enjoy them myself.

36:57

Right.

37:51

I don't know.

37:52

I think there's like a smaller, tighter loop with some of these services that might be overridden and I'm wondering if there might be one in the, like, design a business, like gamification of business world. I don't know.

37:52

It does seem Ben has done a really good job positioning pulsea and like, you know, using some different methods to get attention. I have something. I feel like I have a little bit against the whole thing because I just get spammed massive DMs from him. He doesn't follow me on X, but he spams me with messages asking for different things, which I just think is. I think is somewhat entertaining if you're trying to run the anti AI slob company. Right?

38:06

Yeah. Is it? I thought it was pro AI slob. I thought that was the whole game was.

38:34

No, no. He's very. He's saying, this is not slop.

38:38

This is because there is a world where you're like, it's slop, but it's good slop and it's fine. There's a lot of programmers that say, yeah, the answer for more slope for slop code is more slop and it'll be fine. It's not a problem. You might not like the way the code is written, but it doesn't matter as long as it works. You might not like those artifacts in the AI image, but it's fine because it illustrated the point. Just like. Like you wanted. Anyway. Tyler, do you have something else?

38:41

Yeah, I was going to say, like.

39:09

Yes. Slap is like a temporary term. At some point the running actually becomes good, the writing, whatever the output of the model.

39:10

Yeah, Writing does seem behind a little bit.

39:18

It's like verifiable.

39:22

No, it's not verifiable.

39:23

No. People say it's good or bad.

39:25

Not fast enough. The loop isn't tight enough and there's too many people that say it's good when it's bad.

39:27

You can make it.

39:31

Maybe. Maybe. It did get a lot better.

39:32

Still, once a week it got a lot better. Someone prominent posts fully AI generated content yeah.

39:36

What was happening when the cash.

39:43

No, it just happens. It happens once a week. It's just an iron law of once a week, someone really, really talented and smart posts something that is just entirely AI.

39:45

Maybe we gotta rip it. We gotta try it just to feel something. Cause maybe it's like a forbidden frame fruit. Like the full Just like, just like go to go and prompt. Like write me a blog post. Thought leadership about business. That's the prompt. Copy, paste, rip it.

39:56

Maybe it's also a strategy. You have something that's like, you really want to get out, but it's a little bit boring. And so you know that if you use AI, you're going to get ratio so much more ratios. Way more people see it. And as long as the first 42 sentences are kind of delivered the message.

40:11

Yeah, this is good. This is really good. Yeah, I think we gotta do it. We'll test it on Tyler's account first, though.

40:27

Joe Wiesenthal.

40:36

Yeah, let's do it.

40:38

I love all the AI people who are like, nobody's prepared for what's coming. It's like, maybe just speak for yourself.

40:39

Joe's ready. Joe's ready. No, it is very funny that there's this whole meme of like, no one knows what's coming. It's not priced in. It's like all anyone talks to about ever. It's on the front page of the Wall Street Journal every day.

40:46

Lots of people are talking about this.

41:00

And most people that say nobody's prepared for what's coming will not give you a really concrete.

41:02

Yeah, like what?

41:07

He's exactly. Like the last time we had this, like, nobody's prepared for what's coming moment was. What was the guy who was comparing AI to Covid back in March?

41:08

Is that Schumer? Matt Schumer?

41:19

Yeah.

41:22

So something big is coming.

41:22

Yeah, something big is happening.

41:24

And it's like, yeah, something big is happening. Like, the models are getting better. Like, the math is. Is getting solved. But like, you can still go outside. Like, yeah, like, at this point in 2020, unemployment had spiked to 10%. And like, it was very much like, you're a bold patriot if you're going outside. Like, it was a crazy, crazy time. And now it's like, yeah, there might be some softness in the. In the job market. Like a hedge fund blew up. There's like, there's things that are happening, some big things, but.

41:25

But the hedge funds, mostly the hedge fund blew up from being a little too bullish. Like, things maybe like, they got the. You Know the basically directionally correct but got the timing wrong, right? Mike Isaac says, yeah, these MF's don't know how much I got stockpiled in my basement. And Joe says these MF's don't know that if a man has a why, he'll find his how. Well said.

41:59

Well said.

42:28

Yeah, Buco Capital was having fun with Kevin Roos over at formerly New York Times, now Hard Fork independent. I don't know. Did they take the A, did they take the ip? Are they still using Hard Fork outside of nyt?

42:28

I don't know but.

42:42

But Buko just says weird comment for a guy writing a book on AGI. He is exactly and literally wrong. Everyone is pricing it in. Why do you think OpenAI and Anthropic are priced at $1 trillion? What nobody is pricing in is that besides coding and math, very few domains have embedded verification. But Tyler over there thinks that you can formally verify whether or not the Odyssey is a good book and in Lean or something.

42:43

Well, I think we can. I think we can formally verify that. Tyler's goated, right? A lot of people would say like it's kind of like gray area, right? You can't totally define what it means to be the greatest of all time,

43:11

but you've been working on that quantifying aura. As long as it's fully quantifiable, you'll be able to verify it. Yes. Andrew Curran says, shorten your timelines, friends. I've started this account to say this and in many ways have posted for the past four years has been saying the same thing. Some of you increasingly feel it. We passed the threshold in November. We are already inside the singularity. Lots of people are picking up the we're no longer in the foothills of the singularity. We're in the singularity now. Demis on stage at Google I o just a couple weeks ago, a couple months ago saying we're in the foothills. Well, now we're on the mountain. If you followed this account for a long time, Andrew Curran says, I apologize for losing my mind a few times using GPT 3.5 and then Bing forced me to update all of this at once in one shot and that was the correct time to update. Like talking to 3.5 and the first ChatGPT moment, Bing Sydney, if you updated on that, you did very, very well across everything, both with the growth in the labs and the growth in the data center build out and everything like that was the key moment.

43:24

Also there was a moment in 2020 this was coming up over the weekend that somebody used GPT3 to generate like a fully functional REACT app. You remember this?

44:34

Yes.

44:43

I forget what it was called. It was called like the something. But anyways that in hindsight was like such a big moment.

44:43

Yeah.

44:53

And um, but at the time it got like 2000 likes and people were like, wow, this is really cool.

44:53

Yeah. But no one, no one took it from there to be like, businesses will be spending hundreds of billions of dollars on this in just a few years. Yeah, like. Or I mean a lot of people did. Honestly. Yeah, like tons of, tons of people across venture and private market, public markets.

44:57

A lot of people did. But way more people didn't update any of their behavior.

45:13

Yeah, yeah. I guess it's mind blowing to me how few people realize that their lives and everything they know will change drastically in the near future. At this point it should be pretty clear, says Jerry Turek. Yeah, Wild times. Elon Musk says 100%. He's completely agreeing. Let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents. Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to finish. We gotta look at this simulator. You're into racing simulators? I gotta up you, I gotta one up you with a train simulator. Look at this guy. This guy on Z80ME has built a full scale train simulator controller. For the three years I've been building a physical train simulator in my apartment modeled on the UK class ADX passenger train. I've been trying to replicate the instruments and controls in the real cab as closely as possible. Look at this.

45:18

This is amazing.

46:18

In many cases, managing to acquire real components and in others building my own replicas. I've gone down rabbit holes for design. From custom can bus, transceiver board and a variety of daughter boards to tie the simulator together to the actual panels, all of which on the consoles and instruments are mounted. I usually wait until I complete a component or step before I write a blog post. But over the last half year I've instead made forward progress on several disparate aspects of the project. Therefore, this blog post will update as a status update on many of those aspects.

46:19

I'm feeling the acceleration.

46:51

John.

46:52

This is such a cool DIY project. Imagine just sitting there driving train in the train simulator.

46:53

So one thing I'm not seeing is any type of visuals. So is he

47:00

like.

47:06

You mean the software that's driving the.

47:07

Yeah. To me he only cares about the tactile experience. Of pushing the buttons. Right. Like he's optimizing for actually feeling like he's in the, in the, in the train.

47:10

But no, there is a screen and that screen is running a game that simulates a train. The name of that game, Train Simulator, you can get it@train- Simulator.com. it's also on Steam. Yes, Train Simulator Classic is I believe the one that he's playing. But yeah, he's playing the full train simulator. Aws, Sunflower, I don't know. Anyway, funny, funny story. Balogy is moving to Kazakhstan. This is huge for the Bora community. Absolutely huge for the Borat community.

47:22

He posted a video. This is Kazakhstan. Let's see.

47:58

This is a beautiful video. I have no doubt it's a beautiful place. It's a little bit crazy because Network School I thought of as sort of like a startup incubator, a Y Combinator adjacent entity. He was in Singapore for a while, then Malaysia and now maybe Kazakhstan. Did he actually move to Kazakhstan or is he just like touring and vacationing there? Because what is the actual support?

48:00

Here's the news. It says, I'm pleased to announce that a memorandum of understanding has been signed between the Republic of Kazakhstan and Network School. Our new campus will become a haven for global techno optimism with expedited visas, streamlined redomicilation and active recruitment of talent. Excited for Biology. Excited for Kazakhstan. Excited for Network School Biology. Very smart and very entertaining and I've enjoyed having him on the show. I do think it is very funny to be trying to recreate the incredible techno optimism that many different sub communities already have in the United States where he, you know, where he effectively had all of his success at Coinbase and Andreessen Horowitz and sure, many other businesses. And I think it is. This whole chapter is deeply entertaining to me. The Kazakhstan chapter, it's just, it's such a funny place.

48:28

King in the castle. I love it. So quick tip for anyone who's planning to do sort of like the, the bicoastal things, San Francisco, Kazakhstan, you're in for like a 30 hour trip because there are no nonstop flights. I think you have to connect in Istanbul, Frankfurt, Seoul, Doha or Dubai. You're looking at 25 to 35 hours, depending on the layover that is really, really far. The Miami thing was a tough pitch because so much activity is happening in New York, so much activities happening in San Francisco and it was still hard to get people to relocate. Like great engineers, they come out the.

49:38

No, I mean this is just truly full send the toughest possible Sell. I think he's trying to. I think he's weed out the week. I think. Well, I think in some ways he's been so successful that he wants a challenge that to him feels almost impossible, which is to convince the best and brightest from all over the world to move to Kazakhstan. I know so many. I mean, some major selection bias here, but I know a bunch of bright people that are not U.S. residents. And they would do anything to be able to be in Kazakhstan. Not quite. Maybe now. Maybe now, but they would do anything to be able to have free access to America, to be able to set up shop here, to build their business here, to be able to.

50:23

To be the king of the castle,

51:20

to be not even the king, but a pauper, just someone. Just someone in the castle, in the castle. At all. And so. Yeah, and I haven't. Yeah, just.

51:21

We gotta go. It's very clear.

51:34

Very clear.

51:36

We gotta go. Or at least we gotta send Tyler.

51:38

I would go.

51:41

It looks fun.

51:41

Pack your bags, buddy. See you in 30 hours when you land. Absolutely wild. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Mark Zuckerberg was answering questions about his AI strategy on the latest META earnings call. And Ben Thompson wrote about about what meta's position is in AI, how they're grappling with a few things. There was a bunch of interesting points in this stratechary update. One I wanted to call out was what Ben Thompson thought the best moment on the call was when an analyst asked him why the company can't just use other models. Like, why can't you just do the Apple thing, do nothing, win. Like partner with one of the labs, do some license agreement. If you need an image model, you get an image model. You need a text model, you get a text model. If you need to speed up, your programmers or your engineers, hire the best coding agent and negotiate with them. Right. And here's how Mark Zuckerberg answered it. He said, I can take the open source question. Let's see. So basically the question is, do we think that because there are some open weight models that we can just rely on those? I mean, right now, the open. Open source models are not as strong as the frontier models. Good point. So no is the basic answer. META needs to be on the frontier with their intelligence that they use. So they have to be there, according to him. He says, and then there's also just the. There's also just always the perpetual, both policy debate and question around other companies actions and whether that's a thing a company like Meta can rely on. So if you're using Chinese open source and there's some regulatory risk, it seems like that's sort of what he's getting at is these things might not rely, they might not be available all the time. And then also some of these companies, they might be open source for a few years and then go close source and then start charging you an arm and a leg. So you don't want to be in a place where you become super dependent and then all of a sudden get hurt once you're super dependent on a particular product. So he says, and I think that's very tricky. So on both fronts we believe we're going to be able to do better work and we think that there's some risk in that reliance. I don't believe that's the right thing to do. So that felt like not a great answer to me in the sense that the Apple approach seems to be working so well. We'll talk to Jon Gruber about that in a few minutes. But then he goes on to explain some of the history of Meta. And it's very, very interesting. He says, I think that we're a company that if you look at Meta from take a step back on this. A lot of people view the service layer of we build some social media apps and we have an ad business. We are really a full stack technology company. We build our own data centers, our own infrastructure, our own chips, our own low level software when we got started. He says, my background in engineering, I wrote a lot of the systems code. A lot of the reason why Facebook worked was because it actually it just worked. Which is a crazy thing to say based on the history. But he makes a really good point. He said like it literally worked when other social networks did not work fast and efficiently. And I think we just have the ability to build things that can be more personalized, more optimized, more efficient. Some qualitative experiences are just not even possible for others to build build because we go all the way down the stack. And it just seems to me pretty clear that having kind of sovereignty over building your own models is going to be an important part of that stack going forward, which is why it's important for Meta. And so that was very interesting that that was a differentiator in the early days that certain other competitor sites would just be slower, they wouldn't be able to launch new features quickly. And by vertically integrating all up and down the tech stack, they were Able to do things, things very aggressively. This is the REELS thing. They built like two extra data centers to be able to do the REELS algorithm because if they didn't have that compute capacity, they could not have launched a competitor to TikTok on any normal time frame because it was actually a compute intensive project, not just a design. People see, oh, they just put a new button there and there's some video. But it's like behind those videos is a massive recommender system that is very computationally intensive and stores a lot of data. And you can't just spin that up for 3 billion users or however many billions of users they have on a dime if you don't have the infrastructure, if you're not actually vertically integrated. So there's a whole bunch of other things where in terms of personalization, understanding the user, like delivering a really first class experience. They sort of do need to bring it in house. But investors are very upset about this. They're not very happy because Ben Thompson calls it the financial tail wagging the dog and says that they have to sort of double spend right now. He makes a good point about this. They're double paying. The company right now is basically double paying for infrastructure without a clear path to monetization. And to make matters worse, it's improving. Monetization story lost a bit of its luster. So they're both renting AI compute, paying a bunch of money for new researchers and then also spending all the capex for the next data center. So all of that needs to come together in this moment to actually deliver. And the investors are starting to ask all these questions about what the strategy is. But Zuck's sticking with it. He's not, he's not backing down, but we'll see.

51:42

Yeah, tough position to be in when capital markets don't have a ton of faith and you just see that in the stock price, the company broadly. Right. There's a lot of infighting, frustration around just how MSL is treated versus the rest of the company just paying for msl. So Zuck is, is at war. Fighting a war with multiple fronts.

57:20

It is. It's a big war.

57:47

Well, he'll get through it though.

57:49

We'll dig into it more. I still think this, this Pierre Richelson tweet is so funny. Shower thought. Why is no one doing outbound for pizza? Hey, this is Gigi from Gigi's Pizza calling. You ordered last week. We have a pepperoni pizza ready and could deliver it in 10 minutes. You hungry? Hilarious concept would be extremely Invisible annoying to have every possible low tier business that you've bought anything from with spamming you. I mean, they basically do this with email awareness. Like, hey, there's a Super bowl coming. Do you want to place an order?

57:50

What if we made a law that said that restaurants could only call between 5:30 and 6pm when you're hungry? So you knew you'd be getting calls coming in and you could kind of play them off each other. You get a pizza offer, you're like, look, I'm kind of interested in pizza, but I have an open conversation with the taqueria.

58:23

Yeah.

58:42

And I need to wait to understand like what they can offer tonight. I'll let you know.

58:43

Yeah.

58:46

Taqueria calls, they go, four steak tacos, side of rice. You win.

58:47

Yeah.

58:53

And then you get a price, you get a bid, you go back to the pizza, you kind of play them off of each other a little bit and then you go with, you know, with what you're really feeling at the end of the day.

58:54

Do you know what it's called, called on Wall street when you have multiple parties negotiating to sell a block of stock or debt or something like that, and you want to bring them all in really quickly. Let's say you're negotiating with Tyler and I have extra information. I might have a buyer and I want to jump in. Do you know what that's called? Barging your line. So like, oh, yeah, I'm going to barge his line, jump in there. And then will be on like a three way call, basically. And you can do that when your phone system's set up with multiple lines. So you could potentially have, okay, you got Domino's on line one and then you got Pizza Hut on line two. And you could be like, okay, I'm just gonna put you as all in conference call time. Let's debate. Let's get to the bottom price. Because that's basically what you're doing. You're saying we're just gonna hold an auction right here?

59:02

Yeah.

59:51

This might be the solution. I like this post. Explaining to my wife, explaining to my ape. Why wife? That I have to spend nights and weekends learning the bone so we don't end up in the permanent underclass. Is this from 2001 Space Odyssey? Yeah, it's a good movie. Jordy, have you seen 2001 A Space Odyssey?

59:51

Yes.

1:00:13

You have?

1:00:13

Yeah.

1:00:14

No way.

1:00:14

Yeah, I remember that scene.

1:00:15

What? How did that happen? That's wild.

1:00:16

I think I was forced to watch it.

1:00:19

Oh, yes. This old Leopold lore is coming back up the Author of this New York Times article definitely doesn't realize Leopold was being literal about the stars and galaxies. Asked in a 2004 podcast interview with Dwarkesh Patel what his goals were, he answered, eventually, you are going to go to the stars. You are going to go to the galaxies. He added, done, right? There's a lot of money to be made. That was true for a while, at least. Well, the fund was the center of the hottest trade on the planet. The fund made a return of more than 2,200% after fees as anything tied to AI shot higher. One investor said, yes, there was a funny line where Leopold's talking about buying galaxies. And some investors, like, oh, like the particular brand of private jet that's referred to as a galaxy, like the Galaxy 750 is the one that you want. And Leopold was like, no, no, no, I'm going to.

1:00:24

By an actual gal, Tae Kim says, who will play Leo and Ken in the movie. We know it's coming. Story is too juicy.

1:01:14

Okay, we gotta play. We gotta play this clip of Ken Griffin, because this came up on my for you page. And it's a wild story of when Ken Griffin had his darkest moment, basically, and lost a whopping 4% of the fund. Something like that. Play this.

1:01:20

You know, 1994, I was in Switzerland. We'd had a rough year in 94. We lost about 4% of our capital in 94. It was one of our only losing years in the history of the firm. And I'm in Switzerland. I mean, it was a rough day. My lunch, my lunch. I sat down at lunch. This person sits down, oh, you're not John Griffin. No, I'm. I'm Ken Griffin. He goes, oh, I thought you were John Griffin from Fenchurch, another firm. He goes, I. I gotta go.

1:01:40

Like, great.

1:02:07

I flew all the way to Switzerland for my lunch date to get up and leave the table. And then around three or four in the afternoon, I was with another Swiss banker. And we're in his office. His office was like almost the square

1:02:08

footage of the stage.

1:02:20

Beautiful furniture.

1:02:22

Goes, do you mind if I smoke? Takes out a big cigar. He's smoking this cigar, and we're talking for about 45 minutes. Such a pity that such a bright young man so picked the wrong career. Like, well, that's the most graceful no I've gotten today. But you just have to tolerate. You're going to hear no a lot. But you need to become accustomed to Leopold's dad. Again, whether it's to people that you

1:02:24

want to have work for.

1:02:57

You trying to give you capital or customers? You need to get comfortable with the art of selling.

1:02:58

Great clip. It's so funny that someone was like, Ken Griffin, like, you're just in the wrong job. You should be.

1:03:04

Yeah, I don't know.

1:03:11

This is. This is not for you.

1:03:12

I wonder what that banker would have preferred Ken Griffin do. Like, did he have a prescription? Was he, like, you should be core seller, a hustler, I don't know, skier or something. Anyway, fun little trip down memory lane. We have Jon Gruber from Daring Fireball in the waiting room. Let's bring him into the TVP and Ultra Dome for the second time. Welcome back to the show, John. How are you doing?

1:03:13

Good.

1:03:38

How are you guys?

1:03:38

We are great to see you.

1:03:39

How's your summer been?

1:03:41

Yeah, hot.

1:03:42

Hot.

1:03:44

As the. As the tech news been overwhelming or underwhelming this summer compared to previous summers?

1:03:46

Oh, I'd say much busier. I wouldn't say overwhelming, but definitely busier.

1:03:56

It feels like the. I don't know. I mean, at least there's like the traditional news, which is like a company does a thing. There's a process, something launches. That has felt very light recently. But then there is like, the meta drama of, like, situational awareness blowing up. And that start stuff has been really, really crazy. Like the, the hugging face hack and like, mythos and all these different stories that are sort of like, not planned in the same way of like, there's a release cycle. We all got to talk about the thing that's like, goes through the PR turn.

1:04:01

Yes. I don't think that there was a marketing schedule for when we're. When they're going to have a. Hey, our AI broke out of a sandbox and attacked a major partner of ours during a testing run.

1:04:34

Well, it just depends if you believe in, like, the Truman show thesis. So the simulation theory was like, now have the hedge fund explode. That will be the entertaining.

1:04:53

Well, the funny thing is there was. There actually was people that were making the allegation that the hack was just. Mark was just marketing.

1:05:01

Yeah, I think they. They don't mind. Right. Like, I don't think it's so. I don't think there's a conspiracy in that it was fake or deliberate, but I do think there's a strong sense of. Oh, no. You mean that the news cycle for the next 24 hours is going to be about how scarily effective and intelligent our model is? You know, I do think that there is a laughing all the way to the bank aspect of it, even Though it wasn't delivered.

1:05:11

Sure.

1:05:42

Yeah. Or like a parent watching their kid and like the, you know, play sports and like the kid runs up like, you know, a bunch of points on the other team and the, and the coach has to talk to the parent and say like, hey, look like your son is very good but like he's got to pass the ball a bit more and like it's not really that sportsmanlike to, you know, run up the score. That crazy. He should focus on, you know, teamwork.

1:05:43

Yeah.

1:06:06

I heard. While we're on conspiracy theories, I heard a funny one that the person that's the most happy about situational awareness blowing up is potentially Apple because they've been under all this pressure from memory. Situational awareness was of course very long memory. There's a flywheel there where the stock goes up, the memory gets more expensive. Now I feel like the real take here is that in fact pumping up memory stocks is the best way to lower the price of memory because they will all fund capex and that will ultimately make Apple devices cheaper. But how do you think about the, the pressure that Apple's been under around component pricing, supply chain pricing, getting caught flat footed versus just recently reacting to what's happening in the world.

1:06:08

It is extraordinary and I really do think that to go the other way, I think Tim Cook's public remarks on it as being a once in a hundred year flood situation and that he's been looking at this market his entire career and there is no comparison point. Ram in particular has always gone through these boom and bust cycles. This is just a boom with a capex expenditure fueling it. That is just such an extraordinary amount of money that it's like nothing else. I don't know that even though that Apple was caught flat footed, it's like the sort of situation you just can't prepare for. Right. If you live on a floodplain, you take precautions and you build levees and you take out, you pay insurance that's based on that. If you don't live anywhere where there's ever been a flood before, you don't pay exorbitant amounts of money for flood insurance, you don't build levees. And if something happens where you still experience a flood, well then it a catastrophe. And I wouldn't even. Catastrophe is a strong word. But Apple having to go, you know, I guess it was just a month ago but it feels like just speaking to how the summer is going, it feels like a while ago. But for them to come out and say we're Going to have to raise prices and then a week later raise prices mid cycle. Just Apple just does not do that. And for Apple that's like a minor catastrophe. But I don't know what else they could do. I don't think there's any point where you could look back 18 months ago and say, oh well, Apple should have really foreseen this and somehow done something different. What could they have done?

1:07:00

How much. Do you see the leasing program as a direct response to higher prices? Do you think the leasing program is something that was rolled out because the prices were raised so abruptly, or is this something that they've always been sort of moving towards? This program was probably in the works three years ago and Apple works on a long time cycle. And so this is just the natural arc of things because they've had a, they've had a refresh program where you could effectively subscribe for pre memory price spike, right?

1:08:53

Yeah, yeah. They had the old iPhone upgrade grade program which was just for iPhones and I think they've seen it as a success. And so I think this was sort of a natural 2.0 way of. And it's no, I mean they're the ones who discontinued the old iPhone upgrade program. The day that the new Apple upgrade program for all of their major products, products come out. I mean you can even get like, I think you can even get like AirPods on Apple upgrade. It's not just for, I don't know, I think so, but certainly like all the Macs, all the iPads. So I think this was in the works and I do think that they've been, I mean the whole consumer market is moving towards. There's a lot of competition in, in paying over time. And for a while I think that it was sort of at the consumer level just locked into credit cards. You get a credit card, you buy something and you pay the credit card company over time. And I think a lot of people just looked at that and thought we're leaving money on the table because they're buying our products. It's not just Apple, but everybody is looking at that and thinking, well, this is crazy. They're charging these consumers, consumers 13 or 14% APR. How do we get involved in that? Apple specifically now they have the Apple card which is, I don't know, seven, eight, nine years old. It's been a while. And they've had a program through that where if you buy an iPhone, you get 24 months of zero interest. I think the big change though, it's all clearly about the fact that for so many people, I don't even want to pass judgment on them. But I think for some of them, they are mathematically disinclined to be able to extrapolate a monthly payment by the terms they're agreeing to and realize this is what you're going to pay over time.

1:09:26

Sure, sure.

1:11:34

They just look at the monthly payment and they say, I can pay that. And they look at the lump sum payment of $1,200 for the iPhone they want. They say, I can't pay that, but if I agree to this, I can get a new iPhone. I can walk out of the store with an iPhone 15 minutes from now. And so I think Apple just looked at that and thought, well, how can we offer something that's attractive? And the lease. I think the big difference with the lease is clearly that the monthly payment is even lower, you know, than the buy over time of the old iPhone. Apple. Great program, but in either case it is good for the consumer. And I know some really smart people who are like, I'm doing this, you know, because it is, there's, there's no interest on it. And if you do get a new iPhone every year, it is just an easy way to, you don't really lose anything. You're not paying any interest penalty and you just have like an easy system and they mail you the box to send the old one back in every year. So I, I think it's just a way for Apple to sort of kneecap the number of people who were buying their iPhones with credit cards and paying interest penalties over time. So I think it's better for everybody.

1:11:36

It feels like I could bundle the leasing program, the MacBook Neo, into a Apple is going down market strategy. Do you think there are other plays that they will make to sort of calcify that strategy or really deliver on it or, or is this sort of like, you think it's a pretty mature strategy that they have?

1:12:43

I think it is incremental. Let's say these are not major moves. Even the MacBook Neo. I mean, I think the MacBook Neo is one of the, certainly the most interesting Mac product since the Apple silicon in 2020. And it is that, that there were a couple of times where MacBook Airs dropped to like 8, 899 or something like that. But that 999 starting point had been the starting point for a base MacBook Air for, I don't know, at least 15 years. And so when you consider inflation, the price has been coming down, but not down in the way that what's the entry model for an HP laptop or something like that, which is like $400. So to drop the entry price not just by like $100 or $200 but all the way down to $599. I guess it's up to $699 now with the price increases but still that is significantly lower. And I think they've been doing the same thing. I think on the iPhone side, the switch from selling SE models, iPhone, SE that only get updated every three or four years to an annual schedule of having whatever the current number is, they stick an E at the end, 16E. 17E. There will be an 18E next year. Those are really low prices for a brand new iPhone that has the latest silicon. I mean it doesn't have the greatest camera but so many people do not care about the camera. And that camera on the E phones it is fine, it's one camera on the back, it's a 1x camera that you can get 2x optical with the, the fancy sensor system that they have, it takes great photos. But it's the same sort of thinking where they're not going to sell years old products as their. Okay, fine, here's our affordable stuff. Here's brand new stuff. It's just less technically advanced silicon wise, but it is brand new. Right. The Neo is months old and it's at a record price. So, so they're incrementally moving down market but I think only insofar as they think that there's people with money to spend.

1:13:07

Yeah.

1:15:20

Jordan, what percentage of the employees, the team over at Apple do you think are excited, truly excited about AI and think that it can make the Apple ecosystem significantly better over time? It feels like to me there's, it feels like to me that the whole company is like ah, like why is this happening to us? Instead of like, instead of saying like hey this is this like you know, useful set of tools that can make our software better, that can make our devices more magical to use.

1:15:21

That's a good question.

1:16:00

And the last thing I would say is like there's, I don't know anyone who's excited about AI that's saying like I gotta go work at Apple because they have the best devices in the world. They have billions of users.

1:16:02

Biggest opportunity.

1:16:13

This is such an amazing opportunity. Like if I want to work on consumer AI, I have to go work there like that. Just I don't know anyone like that.

1:16:14

Yeah, I think that's true. I don't either But I don't know that it's a problem. And I do think clearly AI is where Apple was caught flat footed. I don't see how else you could describe that. Right. And I think as time goes on, looking back at the WWDC from two years ago, 2024, when they first announced Apple intelligence and then announced the stuff that eight months later was supposed to be rolling out, and they were like, you know what, we're going to have to postpone this by a year. And really, when they postponed it and said it'll be coming in the coming year, this is the coming year. Right. And it still isn't really out. It's in the public betas this summer, it's coming out this fall. So they were, they announced something that they were saying was going to come out to consumers, be in people's hands in the first half of 2025 and it's coming out at the end of 2026. And in, in this market, in the AM AI market, that is a big, big miss time wise. Now, 10 years from now, will people look back at this and say, wow, that was a huge gap of time? Probably not. And when people look at the new Siri AI that's in the OS 27 betas right now, is anybody who really is juiced into the whole AI system saying, wow, they've really taken the lead here in any way? No, absolutely not. Right. This is very basic stuff, but it all does work. And it's going to be the intro to LLM based generative AI for hundreds of millions of Apple customers. Hundreds of millions of them have never used any of the stuff. However popular ChatGpt and Claude remain in the App Store, there are hundreds of millions of Apple users who've never used this. And you know, I've been using ChatGPT in particular for, you know, years. I'm definitely not amongst my peers in the tech media. I use it less than most, but I'm pretty familiar with it. But I have to say, testing it this summer, ever since wwdc for all of the basic bitch questions, the Siri AI is great and just being able to squeeze the side of the phone is, is a great way to do it. And I honestly think it's like what triggered OpenAI to have the fiasco of a launch of the new desktop app for ChatGPT. Clearly the biggest driver of that is their fear of missing out with Claude and Anthropic taking the lead. As if you just pull everybody who watches tvpn, who's who's in the lead right now. I think it's very clear. I mean, you'd be. I think you'd be kind of nuts, not to say Anthropic.

1:16:22

Yeah.

1:19:15

It's verifiable based on revenue run rate.

1:19:16

Yeah.

1:19:19

So, yeah, just the state of things, right. You just put. Lick your finger, put it in the air and who's got the momentum? Right. I think. And that's put open AI. They, they seem to have and still I think are panicking over that. They really seem to have formed a sense of self which was that they had already won. I think somewhere around 18 months ago or so, that whole company had the. We've won this already. We're just mopping up the chessboard at this point. And now they found out that they're in a long term race and they're not. So that's clearly the biggest driver is that they looked at the way Anthropic has bundled up Claude and Claude code and said we need to do something more like that. But I do think, I absolutely think part of it is that the Siri AI app that Apple is rolling out, which visually, just look at it, it looks like ChatGPT, right. It's black and gray. And at a glance, if I showed it to you in May before WWDC and I just quick showed you a screenshot of it, you'd say, oh yeah, that's ChatGPT. No, it's Siri AI. And I think that there, you know, in the Apple world, we call it Sherlocking because there was the Sherlock thing 20 years ago where there was a. Apple had an app called Sherlock and some third party developers made a much better version called Watson and then the new version of Sherlock came out. Sherlock was Apple's first. Then there was a third party thing.

1:19:19

I've heard the story the other way.

1:20:51

I always get it flipped. Yeah, thank you. The.

1:20:53

No, and the third party one was called Watson and it was way cooler. And then the next version of Sherlock was like Watson and it was sort of. It's like tough luck to the outsider. But it's like everybody looked at Watson and was like, oh, this is the way Sherlock should be. This should. You know. And Apple looked at it and thought, this is the way Sherlock should be. And you know, Apple had this stance that was quite outspoken about it, like Craig Federighi, I think it was with Joanna Stern last year, said that Apple did not see chatbots as a good interface to AI. Yeah. And they're just like, you know what? It is a great interface to AI. So why don't we make one too? And I sort of think like ChatGPT sees that for non advanced usage, nobody's going to go to these third party ones when C Siri can answer that. So no. Is it exciting and is it where the people who want to work at the frontier want to work? Do they want to work at Apple? No. I mean, why would you? They don't really have a product that's even aiming for that. But Siri AI isn't aiming for that. It's just aiming for the type of trivia questions that people just ask as a one off, two off chat session. And it does a fantastic job and it has these integrations with stuff like if you use Apple Mail, if you use imessage, it finds stuff in your imessages just like they promised. It really does work. All of the stuff that's in my Apple notes, I ask questions about it and it just finds the answer to it. It's really, really useful. Is this impressive to people who've been following AI for the last three, four years? Not at all. But this is the Apple way is take something that is super exciting, super cutting edge and boil it down to its basic bitch core and put it in a way, a usable interface that people will be normal people will be able to understand and give it to everybody.

1:20:56

Okay, let's play it out a bit further because I'm curious where you imagine Siri AI goes. I've always felt similar to you in that there's so many questions that you don't need, you know, incredible advanced intelligence, you just need a simple answer to something. And I can see a lot of that flowing through Siri. But where does this product go over time? Is this something because if you play it out far enough and the product gets enough traction, then at what point is Apple competing not just with other LLM providers, but competing with Google itself? And then they say like, oh, we're the private, you know, we're for privacy and all these things. But then at what point do they say hey we're, this is costing us a lot of money to run, we got to start running ads. And then at that point like do we do targeted ads or non targeted ads or do they try to take the moral high ground and say we're better than ads, even though they run ads and in maps and they run ads in the app Store and all these things. So play it out for me. How does this go? Let's assume that, let's assume that it's a success. To the degree that they keep investing in it for many, many years to come.

1:22:57

The ad question is interesting because obviously Apple never had to or never decided to make, make a search engine for Safari. And they just sat on, you know what, we'll just have Google as the default and Google will pay us for the traffic acquisition. And we all know from various court cases that however much they'd like to keep it under the radar, it's like 25 billion a year now. And it had been in that range. It's been a lot of money for a lot of time. And for a while in the early era of Tim Cook's services narrative, even though it was a lower number 10 years ago, it was a huge percentage of Apple's services. Tim Cook said to Wall street, our growth area is services. And their services number kept going up, but it was really for a long while just the Google traffic stuff. Why would Google keep paying this much money? Because when people would search, you would see the Google results. And what does Google show them? Ads. Right? And there's very simple, oh, this is kind of. You see how this works for everybody. There's a sort of flywheel. Google gets all this traffic from the terrific audience, the demographically attractive Apple user audience, and is obviously very profitable at showing ads and search results. They pay a significant portion of that to Apple to have it as the default in Safari. And everybody just keeps searching in Google and everybody can kind of bitch about the ads that have gone into the search results, but people still use Google. What happens with Siri where there are no ads? Why? How does that financial relationship work with Apple and Google for the back end? Who's paying for it? That's a real mystery. They've. And it's one of those questions where when Apple just reported results at the end of last week, every time, I never listen because I find those calls, they're like 45 minutes long and they feel like 45 hours to me. So I skim the transcript and I'm like, I would love if somebody could ask and I don't think that they would answer, but if they clue about how that.

1:24:18

It's so interesting to me because Google is like, we're going to help Apple because we want to try to commoditize the LLM space because we're behind and we're in our business is threatened for the first time because a billion people are using effectively another search engine, an answer engine, right? They're using ChatGPT, they're using some Gemini, they're using some Claude. But like obviously by and large that usage is going, going somewhere else besides Google. And so Google makes the call to support Apple and Apple's effort to try to commoditize the sort of assistant category. But then through that they, if you assume that partnership is going to be successful, then what happens to their existing Apple partnership and then what happens to search over time and then even with a demographic, even with a group of like customers, like iPhone customers, if you, there's a lot of people that are not going to sign up and say oh I'll spend another 20 bucks a month on AI with Apple.

1:26:32

Right.

1:27:37

People already complain about the like you know, twice a month you see a charge from Apple and it's like what's that charge? You know. And so the big question to me is like Apple right now to me is like positioning the entire company around being against ads and you know, really pushing privacy. I see random out of home ads for like Safari and it's like finally private browsing that is like already counter positioned against Google who is now their partner. And then eventually I just think if you want to serve this product to the entire Apple user base, they're probably going to, it will probably make sense to do ads that at that point do they dance with Google again and use like the Google Ads network. But it's so hard to see where this actually goes.

1:27:38

They are, but Apple is dipping its toes into ads, right? That the App Store is ground zero for this. Where when you search in the App Store they have a big ad in the top spot. Now and sometimes if you're searching for, for let's say signal and Signal is the example I always go to because they don't pay. They don't seem to pay. But if Signal, the Signal group or whatever the organization is bound Signal pays for an ad on the keyword signal, you can buy your own name as the top result and then you get an ad and then you get the second spot too because that's where you naturally show up. But there's or you search for Roblox or something that kids play and sometimes there's gambling apps that show up. It's crazy. Now they've added a second spot in the third spot. So for most things you search for in the App Store, the top spot is a paid ad, often paid for by the app you're searching for. But they're still paying. Now they're double dipping because Apple's taking the commission from the App Store transactions and making you pay to get that top spot. The second spot is the top natural search result. And the third spot is another paid ad now. And I think that's off brand for Apple. I really do. I think it is. You know, like I always go back to hbo, which it just was when I was a kid. It just seemed too good to be true that you could watch movies and there were no commercials. And it's like the only. What's the catch? Well, you're parents to spend whatever 10 bucks at the time in the 80s, like 10 bucks a month extra on the cable bill. But it seemed like such an amazingly good bill, good deal. And that's always been sort of the Apple thing. It's like, oh well, MacBooks cost more than other laptops and iPhones cost more than other iPhones. What do you get? Well, part of the experience is you don't get inundated with ads. And I go back to the Safari thing with Google search. It has been such a good deal for Apple. It is 20 to 25 billion dollars in cash that just comes in. It is almost no margin. You can say that you could subtract

1:28:31

almost 100% margin

1:30:42

almost right at this. I mean what's the salaries of the team that makes Salary Safari and WebKit compared to $25 billion a year. Right. Close to 100% margin as anybody could reasonably get. It is year after year. And it doesn't look like Apple is serving you the ads. So you're just Joe Schmo, Apple customer. You use Safari on your iPhone because it's the default browser. You search, you see ads. It looks like Google's Google is showing you the ads. But it's like Apple gets all this money and their hands are free. That really can't happen with safety Siri. Right. They could partner with Google to have Google sell the ads, but it's coming through the Siri. It would be in theory in the future it would be coming through the Siri interface. I don't think they'll ever do it. I don't think they'll ever put ads in Siri. And I think if anything, don't put like a cap on the number of queries you can do that need the server.

1:30:46

But then the question is like Apple, the question is you just play it out, play it out, play it out. And how much of a 3 like is Google creating an even bigger monster than the one they were trying to, you know, keep down in ChatGPT. Right? Like if you make, you help make Siri a massive success and there's no ads and I have gone A year ago I didn't use ChatGPT for really any like product based searches. Like I just still thought that Google was just like objectively better if I want to, if I was like looking up a car or a piece of clothing or anything like that. And more and more and more of that, of those kind of searches, I've just ended up in chat because they have better images now and I can be like, hey, I'm looking at this exact type of product. Just go find it for me. Find me the cheapest version of it. And so you would expect that Apple, Apple's like maybe like two years ish behind or maybe 18 months behind in terms of AI capabilities. But I could imagine 18 months from now Apple becomes pretty good at finding you a product that you want and you have Apple pay built in. It's like they have your address. And so you potentially just fully cut Google out in a way that doesn't even necessarily, that becomes a cost center for Apple and sort of cannibalizes like Google search revenue, but doesn't even necessarily get Apple that much out of it itself. And then like you were saying with like on the App Store like it does, you're right in that like searching for an app and then being flooded with a bunch of like what feels like spam on an Apple surface area. The Apple, the company that's meant to be dedicated to just giving you the most magical product experiences, it doesn't feel Apple at all searching on the App Store anymore. Because Apple knows exactly the app I'm looking for and yet they're serving me junk, right?

1:31:44

And it's usually like, and the Apple monetization for the App Store Store should just be the commission they charge on all the transactions through the App Store, right? And that's controversial enough and has been the source of antitrust and all sorts of complaints. But at least in terms of, well, how do you fund, how do you profit from the App Store? The story was very simple. They take 30 to 15% of every transaction. And that should be good enough, right? Because you're paying. And if you know at some level as a consumer you have to assume that you're paying at least, least a little bit more for everything you buy through the App Store because Apple is taking that commission. And to double dip and show it would be like hbo. You pay extra money and in the middle of the movie they have one commercial interruption, right? And it's like with the World cup where oh, they still don't have commercial breaks, but they have hydration breaks

1:33:35

and

1:34:28

it's like, that's sort of what it feels like with the App Store showing you these ads when you search. And it's like, I'm just trying to find a freaking thing. How about you just fix search? And their search still kind of sucks. So, Jordy, I think your big question is what's in it for Google, right? Why is Google helping Apple here? And I think it is from Google's perspective and I don't think anybody knows, I really don't think anybody knows where any of this is going to be four years from now. Right. It's so fast moving. But I think Google would rather dance with Apple who they know and they know what Apple culturally wants to do. And I don't think there's any kind of, I mean Apple is doing AI research, they have AI teams and I think Apple would obviously love to handle as much of this on their own as they could. But is Google seriously, is anybody seriously afraid that four years from now Apple is going to be the producer of the leading edge models, the frontier models? Nobody. And I don't think anybody really thinks there's even like that they've got a path to that or that they're even trying for it. So I think Google is comfortable working with them where, well, in a way that they would just prefer to kneecap OpenAI and anthropic. And if there is, if Apple was fishing around for a partner like we, we need somebody who knows their shit to give us an LLM back end so that Siri is actually useful. I think Google was willing to cut them a sweetheart deal to say let's do this. If it entrenches Siri for a decade to come as something that a billion iPhone users around the world are relying on, we can handle that.

1:34:28

Right?

1:36:15

We know Apple. We're not worried that's not going to. We'll still figure out a way that we'll make money. We'll still have everybody who's not using Apple products. But a world where like that two year ago deal with OpenAI which now makes you laugh, with the deterioration, to say the least, between Apple and OpenAI at a corporate level. But if that had cap continued and it was OpenAI who was partnering with Apple to do this in a way and, and again, the original deal two years ago had ChatGPT branding in the answers and it was like, you know,

1:36:15

yeah, the whole thing is so funny because you have Google being like, okay, we need to help Apple because like we need to help Apple attack Chat GPT because chatgpt is threatening us. But if we, if we are, if Apple's really successful, then they'll end up threatening our core business. And Apple's like, well, we also want to take, we also want to try to kneecap chatgpt because they're now building devices. But then it, Google and Apple's relationship is just like headed on a pretty interesting path. And I, and I can't imagine, I think both companies will look back and be like, man, you remember those days where I could just give you tens of thousands, billions of dollars and we can just be friends and then you play it all out and it doesn't seem as friendly.

1:36:56

Yeah.

1:37:42

And I think basically it comes down to Google is very comfortable playing in a world where the technology is commodity level and that they can, because of their scale, they can not just succeed, but thrive in a commodity world. Right. Like, is the actual computer science behind Google search significantly better than what Microsoft has with Bing? No, not really. It's just that the scale is there on Google's side and so it's perpetuating. And I think that if AI works out that way. There was somebody at Google years ago who Google invented all of this technology that we now consider AI, all the LLMs stuff. But there was a paper that came out of Google where one of the scientists argued that there is no moat around this technology. No one company is really going to own this. And I think it's an open question whether that's true or not. Right. The superintelligence hypothesis is that if somebody gets to the breakthrough of superintelligence first, then that superintelligence will accelerate their AI at a pace that nobody else can keep up with and no one will ever be able to catch. I don't think that's where it's going and I don't really. It just goes back to what we were talking about half an hour ago with the hugging face thing and chatgpt and it's like, oh, coincident. And this is what makes people roll their eyes and think it's a marketing stunt is then three or four days later, anthropic came out with. But we went back and looked at our logs and we found Claude broke into somebody four months ago. We didn't even know it, you know, and it's, you know, they're even Steven. And I think, I just think ultimately Google looks at this of, let's just shut those guys up. Let's let this bubble burst. We'll still be here. They won't. And Apple will Certainly still be here. You know, Apple's the one big company with no exposure is in this bubble. And I think Apple's bet is back to there is no moat here and if they don't own this technology that it does, it's fine. And I kind of think it's shaking out that way, at least for Apple's business.

1:37:42

Yeah.

1:39:59

Well, last question and you can answer in 30 seconds. Do you think.

1:40:00

All right.

1:40:05

Do you think Apple will make an acquisition of an AI company? Could be an acqui hire or product, but I'm thinking more acqui hire north of $10 billion.

1:40:06

I think you're going to 100 million.

1:40:18

Yeah.

1:40:20

1.

1:40:20

Okay, then let's bring it down 1 billion because there's just not that many. There's not that many great teams to be honest, that you could get for less than.

1:40:22

I mean they bought Siri, that was a hundred.

1:40:30

And I was kind of expecting them to try to pick up Poke, which Cognition just bought. Poke was like a really nicely designed assistant that worked in imessage and that felt like a no brainer for them to just bring in some talent that is excited about AI that's already working in the Apple ecosystem.

1:40:32

I would look at it on the silicon side because I think that as this gets commodified I think that something like the picture PA semi acquisition that led to Apple Silicon, that that's who Apple I suspect is hunting for is somebody who has like a breakthrough spitball idea. And again at this point $1 billion probably isn't that much. So something in that range but I would think hardware something that Apple can do for silicon.

1:40:51

Yeah.

1:41:21

If you have really optimized silicon serving lagging models that are yellow year or two old inference cost can actually be pretty low. And then that changes all the calculations about ads that you were talking about. So thank you so much.

1:41:21

And ultimately I think it's why Apple's ultimately I think it's why Apple staying out of the capex race, building out these data centers. The idea of why are we going to spend all this incredible sums of money, all of our free cash flow to build data centers that are going to be completely technically outdated five years from now.

1:41:34

Yeah. Well, I want to have you back to have a great debate about electron versus native apps. We got to go through all this, get to the bottom of what's going on with these AI labs. They have such powerful coding agents and yet they can't ship native code apparently. We'll get to the bottom of that next time you're on the show. But thank you so much for taking the time to come chat with us. Have a great rest of your summer.

1:41:52

And yeah, you stay cool out there.

1:42:11

Thanks so much. Talk to you soon. Goodbye.

1:42:13

Cheers.

1:42:15

Let me tell you about FIGMA agents. Meet the canvas. Your AI agents can now create and modify your FIGMA files with design system context. And up next we have Sean McGuire and Isaiah Taylor. Isaiah, dynamic duo, two guests. Third, fourth time on the show. How's it going? What's up guys?

1:42:16

Look at you. Nuclear reactor.

1:42:36

We got to get the eagle scream every time. This is like. This is our intro. This po. Exactly.

1:42:38

There we go.

1:42:44

What happened guys? What happened?

1:42:44

$1 billion series, baby, with the wind up.

1:42:47

Crazy, crazy, crazy moment. Where should we start? Isaiah, you want to kick it off?

1:42:57

Yeah, I mean I'm right here in the reactor hall right now with the hardware. This is where I like to spend my time. And one thing that was just amazing about Sean's partnership in getting to know his company is he just wanted to open the hardware. That's really my favorite type of investor. They're like, show me the stuff. Like, are you actually building things? And I think that's what's special about this company is that we just build and we build fast. And yeah, it's been really great to meet the Sequoia team and get to know everybody.

1:43:03

And this facility, you're no longer purely in the Gundo, you've expanded. Where is this facility now?

1:43:29

This is our Orangeville, Utah site. It's our first nuclear site. Yep.

1:43:36

Okay, and what are the short, medium, long term goals with this site and beyond? Is this still an R and D site or is this going to be generating power? When do you start building the factory that build the machine? That builds the machine.

1:43:41

Yeah. So we've already made a tiny bit of nuclear power here. We became the first startup in history to make nuclear power about a month ago, but it's still a test unit. And what we're building toward is something that we call a gigasite. These are massive campuses of reactors and we think they'll make the cheapest energy on earth. And so that's what we're working toward here. And it starts right here in Utah for sure. This is a great place to serve data centers, AI factories, then eventually all of the industrial stack that has been falling behind in the United States, that depends on energy. Aluminum, electrolysis, steel, all of the different input metals to making everything in the physical world starts on our giga sites. So that's what's coming next. And that's really what this raise is going to help support Massive.

1:43:56

Sean, I have to assume you've met every nuclear startup. There's a lot of them but you've got enough time in the day to meet them all. I don't know, I doubt. There's so many different applications of the technology. There's a lot of good ones.

1:44:37

It's not only valor, but there's only one Isaiah. That's for the for sure.

1:44:53

Yeah. So talk about what drew you to the company. And this is like this is not a series A check. This is a billion dollars.

1:44:57

No, it's a big check. This is a big boy check here. This is an ultra high conviction investment. Look, I'm a former physicist, I have a PhD in physics. I've loved nuclear since I was a little kid. I was hoping that I read Richard Rhodes Manhattan Project book when I was 17 and I've kind of been waiting for there to be an opportunity in nuclear. I didn't think it was going to happen. I thought we were just going to go like solar battery or solar plus some other storage mechanism future. Just given how regulated nuclear was, it just didn't seem like it'd be possible to get to scale. And then two things happened. One, power became important in the west again, which is pretty amazing. Second, this administration. But I got to say this, I think a very bipartisan thing. Both the Democrats and Republicans this power became a bottleneck have been pushing for more favorable nuclear regulation and it's starting to happen. So even three years ago the regulatory side was too scary for me. So we've had kind of regulatory breakthroughs with this next generation of founders that are really trying to bring in this nuclear future. But for me, with Isaiah, there are a few things. One, just like when you get to know this guy, the level of intensity is psychopathic. And I mean this in the best of sense. But like the day he went critical in this reactor he's in, first of all he thought he was going to go critical the day before. It ended up being the next day. So he was up kind of all night, two nights in a row. Then that night that he went critical, they didn't go critical on like 9pm or something. There was a candidate he wanted to close whose partner was in San Francisco. So the day he went critical, after not sleeping for two days, he got on an airplane that night to fly to San Francisco to have drinks with a candidate and the guy's wife. I don't know what time he went to sleep. And then the next Day he's back in, I think it was Utah, maybe Los Angeles. But getting to know Isaiah, the level of intensity is just absolutely incredible. And the only person, I don't know many people that have this level of intensity. And then just one more thing, something that I learned, a mistake I made in the space industry was Elon started off trying to build the Falcon one, which was a pretty simple rocket relative to what NASA could do in the, you know, 80s, 90s. It was like a 1960s rocket or maybe even earlier. And there were all these other companies that were telling these like advanced science stories. We're going to use carbon fiber, you know, frames to have, you know, less mass, or we're going to 3D print the rocket. So other people were like trying to do this very advanced technology to have better mass ratios, etc. And Elon was like, I'm going to do the simplest thing possible, put up one satellite, get that revenue, and then go from there to something that's Falcon 9 pretty damn hard, but still not state of the art compared to what NASA had done in say the 90s. And then from there go to what's truly state of the art reusability, and then from there go to Starship, which is just completely pushing the limit. And Isaiah understands this. He's one of the only founders I've ever met, ever, in any industry that really understands the power of starting with the simplest unit where you can actually scale and win, and then climbing from there. So anyways, Isaiah should do the rest of the talking.

1:45:06

That was great.

1:48:40

Yeah. I think that's one thing that Sean and I just connected on very early is like lots of investors trying to understand the nuclear space want to know what's special about this technology, what's really unique about this technology. They want to find this sort of like IP technical edge where you're doing some special sauce that nobody else is doing. And my approach is like, no, like we want this reactor to be as simple as we possibly can. Like if we could just staple this thing together from Ikea, then this would be a trillion dollar company much faster. And so there's like two, two philosophies that we use in building the reactor is we try to buy things that are completely off the shelf, like 100% commodity, or we make it ourselves. And there's very few things in between. Right. There's very few places where we have a supply chain that's dependent upon the existing nuclear industry. Because if you think about it, we're trying to go 100 times faster than the nuclear industry has ever gone before. And so if we're plugging too deeply into the existing network, it's not going to work that well. So we want to use standard off the shelf things and, and make things ourselves where we can't buy something off, off the shelf. And by necessity, that means the design. The design is extremely, extremely simple. The more complexity you add to it, the harder it is to be one of those two options and the harder it is to scale. So, you know, I think especially in nuclear, this is a difficult thing because it's full of very smart people. It's full of physics people and PhDs and people who have spent their life doing complex analysis and they actually want something that is a little bit complicated. It's like, it's an ego thing to design something that is like, complicated and looks very sophisticated. And we have just really rooted that out of our minds at Valor. Like, we work extremely hard to reach that mentality out. Like, it's, it's our preference that this thing is so simple that somebody with nuclear PhD looks at it like that's like a toy. And it's like, great, because people make toys in like the millions, right? They just like, stamp them out. And that's exactly what we want to do. And then the other aspect that's super unique here is just the safety of the overall architecture lends itself to this approach. If you build a really, really safe reactor, you're also by necessity building a really safe reactor, because most of the engineering complexity in nuclear comes from safety engineering. If you look at a modern pressurized water reactor plant, they're very complicated, and 90% of the complexity comes from trying to make it safe. So the approach that we've taken instead is design it to be safe from the physics. And you can actually just delete a huge amount of the bill of materials, just like completely remove it. It doesn't even exist in our bomb. So those are the philosophies we've taken here. And yeah, listen, I can't give enough credit to Sean in particular, and also

1:48:41

the

1:51:19

guy's building nuclear reactors. I'm wiring money. Like, get out of here. I got to give a couple shout outs, though. I got a shout out Palmer Lucky, who gave me the hat tip that this is a special company. Thank you, Palmer. Hat tip to Liam Corrigan, you know, newest investor at Sequoia, who was my wingman here. Physics guy, Rhodes scholar, Olympic gold medalist, rower. Six, five.

1:51:22

Chad

1:51:44

total. Chad. And Max Yukoprina, who's on the team at Valor who is someone I've known since I was a kid who for years was trying to get me to come meet this company. I was like, oh, dude, nuclear is too hard. Regulatory is not favorable. And anyways, Max, I look stupid.

1:51:47

Good job, Isaiah. How have the. Have there been talent wars in nuclear? You know, you're flying on such an important day to go to go meet someone which many founders will have done, but that's felt like maybe urgent. How intense has the competition for talent been? This round, I imagine will give you a lot of advantages. Just having yet more firepower to continue compounding a great team. But walk us through the last maybe two years in the category.

1:52:03

Yeah, look, I view my job essentially as trying to get most talented people in the world to come and build this mission with me. There are no blockers in front of us. We have a regulatory environment that's ready to move. We have an enormous demand signal. We have customers that want to buy. We have an architecture that's very simple and very scalable. And now we have a lot of capital in the bank and the blocker on us becoming the 1050, $100 trillion company that makes most of the world's energy. Is the smartest people in the world coming and joining us in this mission. So I spend an enormous amount of time, of my time doing that. I actually would say that our. Our primary talent competition is in other places where you can move the needle on a global scale that need incredibly talented engineers. I don't, I don't see it as sort of like, okay, other nuclear companies. It's more like, you know, what are the other companies that are genuinely going to change the course of humanity in the next 50 years? And like, those are the people that. That I'm fighting for.

1:52:33

Mm.

1:53:31

Yeah, that makes a lot of sense.

1:53:31

Lessons from. Oh, sorry.

1:53:32

Well, if I can say one thing on that, something I've seen from Isaiah that is very rare. He is looking for just ultra talented generalists. And he tests people like crazy. And it's. And like real world tests, you know, like, hey, I'm going to be in. Someone says, like, hey, I want to interview. And he says, okay, I'm in Texas. Like, meet me here tomorrow. And if they get to Texas, then they have a shot. And if they don't make it to Texas, then they're weeded out. It's just not having that level of commitment. And anyways, there are not many people that understand you have to kind of design the hiring process to find the people that select into a crazy mission.

1:53:34

High agency.

1:54:10

Yeah, yeah, you're revealing, you're revealing the secrets here, Sean. Now the next three are going to show up to the meeting and I have to figure out some, some other way to weed them out. But yeah, that was. It's very true.

1:54:11

If they show up, it's still a good, it's true.

1:54:24

It's still a great set.

1:54:26

Lessons from SpaceX. One of the interesting.

1:54:28

Yeah, I can imagine. Yeah, sorry. I got a dentist appointment in Utah, of all places. I got to get out there. It's like this, you know, people being like, yeah, I got a dentist appointment.

1:54:30

I have to take three commercial flights, you know, and drive three hours to get to my dentist appointment.

1:54:40

Yeah.

1:54:45

One of the interesting SpaceX stories is residual capability. They build all this launch capacity. They have maybe too much launch capacity. You get Starlink, amazing business. Becomes a telecom company. Not probably not in the first pitch deck, Sean, you'd know. But is there a world where there's a residual capability from what you're building here, where you're using the electrons that you're generating yourself? Or do you see there's just like so much demand that just that, that's something that is very, very unlikely to happen?

1:54:48

Yeah, I mean, look, you, you know, and you and I have talked about this before, like I think valor actually started. I, look, I grew up watching Elon, right? I, I watched, I read everything that I could about the Falcon 1 and the Falcon 9 and saw this very simple path that you just. They call it flight rate. I think it's SpaceX, we call it tick rate. Tick rate is basically how quickly can you go from cores turning on. You know, each one, it's, it's like a look back average metric of the time between new course turning on and it is predictive of who's going to win and who's going to have the lowest cost and the highest capacity and all these different things. And we actually started with the idea of that excess capacity and being able to make the world's commodities. Right. And I think that the AI thing happening as quickly as it did and power prices changing so dramatically, where people will sign a $200 is like, okay, obvious that we should sell electrons.

1:55:18

Yeah.

1:56:08

But no question. Is our long term vision to actually have the cheapest energy on earth and to use it for our own things. I mean, we see a vision of the world where steel is just way cheaper than it is today. Aluminum is way cheaper than it is today. The manipulation of matter is a lot cheaper because you have robotics hooked up to AI that's doing matter manipulation and vision and all these things just take energy. And so it'll be interesting to see like where we decide to play in the stack. I think like we want to be in the business of turning on thousands of reactors primarily, but there will be a couple of like massive, massive markets that we attach to that that we can just make at a competitive price that no one else will take.

1:56:08

And also like the nature of the AI boom is that you need a lot of energy in a single place which is perfectly suited for you. As opposed to if we were in some boom where we need everyone in their pocket needs twice as much energy. You would have to maybe transform into another source of energy or do something else in the supply chain. Sean, did you have something?

1:56:45

I. No, I agree.

1:57:06

I concur.

1:57:08

Violent agreement.

1:57:08

Fantastic. Well, thank you so much.

1:57:10

Honestly, I was just going to say

1:57:12

that the AI thing perfectly matches gigasites. The idea is nuclear is a thing that benefits from extreme scale. If you could build 1,000 nuclear reactors right next to each other, you should like you will get the cheapest energy anywhere in the universe if you do that. And so AI is like the, the perfect thing to do with that first. But we will do many, many interesting things with it over the next century.

1:57:13

Well, congratulations. Thanks for having us.

1:57:37

Excited for you guys to partner up. Dynamic duo tags.

1:57:40

Teams are fun.

1:57:42

Peace.

1:57:43

Goodbye.

1:57:43

Cheers.

1:57:44

Let me tell you about MongoDB. What's the only thing faster than the AI market your business on MongoDB don't just build AI own the data platform that powers it. We're going backto back energy rounds with another backtack billion dollar round. We have Justin Lopez from Bas Power company. Justin, how you doing?

1:57:45

Good, how you doing? Good to see you.

1:58:04

Give us news.

1:58:06

What happened today?

1:58:07

Raised. Raised a bunch of money. And.

1:58:10

Not just the capital raise though. Break it down. But, but first for anyone that's been living under a factory reintroduce base power, what you're working on, why it's important. And then I want to talk about the news under the headline from today.

1:58:16

Yeah. So welcome to Factory One. Good to see you guys. Thanks for having me on. Today we're announcing three different things. Number one, launch of the factory that I'm sitting in right now, it's behind me that builds batteries. Number two is $1 billion raise, a $13 billion post money valuation. And the third thing is base core is our custom, fully custom designed, engineered, installed, manufactured here in Texas. What we do is we design batteries, we manufacture them here we're on homes, and then we own and operate them as a distributed fleet. Distributed power plant. That's the business today.

1:58:33

Incredible. Talk about the decision to not announce the factory or talk about the factory very much until it was actually producing products.

1:59:08

Yeah, you know, it's like I put this on X, but, you know, a lot of factories get announced with a bunch of people in suits and hard hats shoveling, like an ounce of dirt. And that's cool. It's groundbreaking. That's exciting and all that. But, like, factories are meant to make stuff, and we wanted to make stuff beforehand, so we're doing that today. We're just getting the line ramped up. The station behind me is starting to build some modules. You'll see some come through as we talk here. But, yeah, look, you want to have. You want to have the real deal ready before you talk about it.

1:59:19

That's right. And when did you. When did you guys actually break ground on this site? Because I imagine so the site.

1:59:48

Yeah, the site was already here. So this is actually the old printing press of the Austin American Statesman building. We started building the equipment behind me about five months ago, so it hasn't been a super long time. And we started warehousing here about eight months ago. Previously, we had a smaller facility just north of here in Austin. But, yeah, we're, We're. We're live and running now.

1:59:55

Very, very cool. Talk about, talk about the state of the business overall. You know, how the, how the market in Texas is evolving, what people can expect from base over, over, you know, the next couple of years in terms of new markets and things like that.

2:00:15

Yeah. So as I mentioned, look, we install batteries on homes. Turns out there's a lot of homes, not just in Texas. So we recently launched our Chicago market, and we've also launched, I think it's six or seven utility partnerships now here throughout the state of Texas. You'll see us announce a few new states and a few new utility partners, hopefully by the end of this year as things get signed and under contract. And that allows us to go into more states here in Texas, Texas has got a partially deregulated market, which means that we can go to market without having a direct relationship with the utility in other states, like California, where I'm originally from, in Michigan, those are regulated states, so they require deals with utilities. So we have to go to market motions. Regulated and deregulated. Both work in various different states in the country. And look, the goal is to have a battery on. On. On every home in the US and eventually, internationally. We've started here in Texas. We're in all the major markets now, also in Chicago, but we'll be launching new ones here pretty soon.

2:00:31

All right, as a. If somebody is a homeowner in Chicago or Austin or Texas, broadly, give us the elevator pitch for why they should install.

2:01:29

Yeah, look, so we make your power more affordable, more reliable. So if you're in a place like Houston or Dallas, where you can choose your power provider, you sign up with us, we sell you electricity every month at a very affordable rate. We also put a battery on your home that is only typically a few hundred dollars, depending on exactly where you live. That provides you backup protection if the grid goes out and also supports the grid when the grid is up and running. That's how we monetize and how we make money, is that grid support function. And so it's affordable, reliable power. That's the simple pitch.

2:01:41

Is there an element of price savings from drawing power from the grid at low rates, storing it, and then reusing it in the house when rates would be higher, and just sort of load balancing at the house level?

2:02:10

That's exactly right. That's basically how it works. So we charge the battery when energy is abundant and available, when there's not a lot of stress on the grid, and then we discharge it into the home. And sometimes, if we decide to spin the meter backwards, push back onto the grid. There's. When there's some stress on the grid or when there's peak demand times. That typically happens, you know, in the dead of winter and in the height of summers.

2:02:28

Okay, what about throughout the day, throughout the week? Like, when are typical peak load times? Because during the day it's hot, people are running air conditioning. But at the same time, that might be when solar panels are collecting energy. So, like, what. What is the actual reality of, like, a typical grid, the Austin grid? Does this vary grid to grid? Like, what. What is the. The differences and the nuances of load balancing?

2:02:51

Yeah, so you're. You're exactly right. Basically, what you care about is the difference between available capacity or supply and the amount of.

2:03:18

Yeah.

2:03:25

And so here in Texas and in many places, especially in the south, where it's quite hot in the summer, you typically have these peak times in the summer, at least in the. In the early evening. So kind of like, you know, 4 to 6pm, 5pm, 7pm where the sun is setting, so supply is coming offline, but people. People are coming home, plugging in their EVs, turning on their air conditioners, etc.

2:03:26

Got it.

2:03:47

And so that's really the, where the, where the supply and demand meets. Then in the winter here in Texas and in many places in the north, you have these early morning peaks. Basically, people are waking up using more electricity. Your heaters, your electric heaters are coming on. They're on throughout the night, but the sun hasn't risen yet. And so batteries help fill those gaps. That's at the macro level. And then at the more micro level, they're also able to shave peaks off of the lines on the grid. So you might have enough capacity in aggregate, in bulk, but one part of Houston or Dallas or Chicago may need support. And so because we've got tens of thousands of these systems out there, we can say, look, in this neighborhood, we need some support, we're going to discharge just in that neighborhood. And that's the beauty of having a high volume of systems.

2:03:48

I see a lot of robots of different types moving around in the background. Where are you guys getting the most leverage from robotics I can imagine as you started the facility, it can make sense to, to figure out the sort of process using a lot of your human talent. But where are you guys getting the most leverage and how automated can this become over time? Can it become fairly lights out factory? Is that even something to aim for? But what's your view on all that?

2:04:32

Yeah, robotics is a great place, but it doesn't have a place for everything. There are certain tasks that do not make sense to automate, or at least not as a starting point. And then there are other tasks that do so. Like what you see exactly behind me. You've got the robots that are driving through the tunnel, and that tunnel is placing these stacks of battery cells that are created also by robots outside of the frame here. That is a great thing to automate because it's relatively heavy, relatively repetitive, and requires a lot of fine precision. Then there are other tasks, loading in certain components, testing certain things that require a little bit more finesse, a little bit more dexterity that are pretty hard to, not impossible, but harder. And so we've said, look, we're not going to automate those as a starting point. We're going to focus on the things that are, you know, either either dangerous or hard to do repeatably or are quality concerns. And then we'll automate more and more over time. So it's just, it's a, I'd say it's a, it's a, it's a phase in approach. We're starting with what makes sense to automate and we'll likely trend towards more automation. But the fundamental thing is trying to, you know, not do tasks that you don't need to do in the first place. You delete the task, then you optimize

2:05:06

and then you automate it.

2:06:09

What's the state of blackouts, brownouts, blackout prevention? That feels like a huge selling point. You're selling a sense of security, a sense of comfort during a winter blackout or summer. But at the same time, how often are they actually happening? It seems like a known problem. Problem. Grids and energy providers have been working on this at a, at a, you know, higher level than you. So is the problem still broad? How big is the problem of just losing power outright? And how big of a factor is that for you in the sales process?

2:06:10

So it's huge in the sales process.

2:06:50

Right.

2:06:51

People want to have more affordable and more reliable power.

2:06:51

Yeah.

2:06:54

The reliability is different from, from place to place. So typically coastal regions, so we think of the Texas coast, Florida, the east coast, etc, where you have a lot of hurricanes, you typically have more power outages.

2:06:54

Okay.

2:07:05

Also in more rural areas. So if you're at the end of a line, basically any break in that line all the way up to the substation is, is going to cause you to have an outage. And so if you have more line in front of you, basically you have typically lower reliability. Yeah, it totally varies though. So very, very, very rarely is there an outage because there's not enough power. Most outages occur because of the weather events because, you know, a tree falls onto a, onto a power line, etc. Because of a storm. But, but outages are rising generally across the country. There are places where they are getting better.

2:07:06

Okay.

2:07:38

It's a factor in the sales process. But if I'm honest with you, the way we think about this is more about portability first, reliability as a, as a benefit of having this system on the grid. And it relies, it adds reliability to the whole system. Right. It's not just your home, obviously it'll back up your home if and when the grid goes out. But it's more about adding reliability and capacity to the whole system so you can have more load and, you know, more EVs, more homes, more data centers, etc. On the grid.

2:07:38

Got it, got it.

2:08:05

Absolutely crushing.

2:08:07

My last question is, what does it actually take to expand to a new market? I mean, I want one of these in California, but it seems like you're, I mean, you're growing the business in the factory. And like there's, there's, there's immense scale. Billion dollars raised, $2.5 billion raised. And yet geographically it feels like a little small. It feels tight. Sometimes you have companies that are. Yeah, we're available in every market, all over the globe. We'll ship our thing everywhere. And we're a tiny company. You're sort of the opposite, very focused. What does it take to bring a new state, new city online? Why the measured approach to actual go to market?

2:08:08

Yeah. So I'll start with the latter point, which is the sort of measured approach. I'll remind you that Texas is larger than most.

2:08:44

Yeah.

2:08:50

That's got more, more homes and more electricity load than many large company countries

2:08:50

that you've heard of.

2:08:56

Yeah.

2:08:57

Okay.

2:08:57

So Texas is a big place, but regardless, I'd say the, the geographical tightness is a feature, not a bug.

2:08:59

Okay.

2:09:05

Of course, the reason for that is like not only do we have a factory behind me that produces these things.

2:09:06

Yeah.

2:09:10

But more importantly, we have a factory in the field. We've got hundreds of people out in the field and so installing these things.

2:09:11

Okay.

2:09:15

And we've got trucks and crews and tooling and all this other stuff. And so having geographic density is very helpful from an efficiency. Now to answer your question though, on how do you expand to new markets, There are oversimplifying here, but there's basically two types of markets. There's ones like Texas, where you can choose your power provider.

2:09:16

Yep.

2:09:33

Places in Texas, not all of Texas.

2:09:34

And then there are.

2:09:36

There are markets like you have in California where for the most part, especially in residences, you cannot choose power provider. We live in Northern California. EG&E is the only game in town. If you live In Southern California, SoCal Edison or LADWP or other utilities. And so in the deregulated markets, we can essentially go there and start the business and there's nothing really stopping us except for a bunch of regulatory hoop jumping to do and setting up of a warehouse and hiring people and all that, which is its own challenge. In the regulated market, it's basically getting a deal with the utility and a B2B sales motion where we go to utility and say, hey, we offer megawatts as a service. We'll go install these batteries that we've, that we've built behind me. We'll put them on homes in your service territory. You can control them, operate them, and use them to add flexible capacity to the grid. And so that's a matter of, you know, B2B sales long sales cycles and, and working with both the regulators and the utilities in that State to go into those states. So I'll say we'll, we'll launch a few new regulated utility opportunities over the next next few months here, and then in the deregulated part will also launch a few new states. But as I said, like, it wouldn't be surprising to me if we're only in, you know, 10, 15, 20 states over the next few years just because again, the geographical density is so helpful for us.

2:09:36

Yeah, yeah. And of course, like you, you only have so much manufacturing capacity. You have to load balance your own business across your sales, all your installers, your manufacturing capacity, your supply chain, all of this stuff. That makes a ton of sense. Well, congratulations on the progress and thank you so much for coming on and sharing it with us.

2:10:47

Love seeing you guys cook. Yeah, amazing work and thanks for the. Thanks for the factory demo.

2:11:04

Yeah, of course.

2:11:10

I know. We'll come by next time we're in town.

2:11:11

Yeah, that'd be awesome. We'll talk to you soon.

2:11:13

Cheers.

2:11:15

Goodbye. Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange.

2:11:17

Just do it.

2:11:26

Folks, I think we have to issue sort of like a warning to the viewer. The next guest is building something truly horrific. So avert your eyes if you are a scaredy cat, because our next guest has built something terrifying. Beau Gaston, welcome to the show. How are you doing?

2:11:26

Great. How about you guys?

2:11:48

We're doing well. Talk to us about what you're building. Tell us about the journey, the goal, the mission. I want to get into the aesthetics, everything, but also the applications.

2:11:49

Yeah, sure. So the full timeline, a very high level. We'll start about six years ago. A paper comes out of MIT where a guy, Ben Pats, made this quasi direct drive actuator quite cheap. I think it's about 700 bucks. These are kind of like the building block of these humanoid robots. And a large reason that you're starting to see a lot of these pop up, that he open sourced the design as well. So I'd seen back then it kind of looked like it was going to become possible to build humanoids a few years in the future that are not only affordable to a huge lab. Right. So around 2022, I start to take on this design that you see in the background. What I wanted to do with it was really make a robot first for myself. And what I would like to do with the robot is, you know, not do the dishes or fold my laundry.

2:12:00

You want this thing to do the dishes?

2:13:01

No, no, no. He's Saying he doesn't care about a robot that will do the.

2:13:03

Oh, okay.

2:13:06

Software update. I wouldn't try that quite yet. My kind of thesis is it's going to be more useful to have something that's stronger than you at first and maybe you could sacrifice some precision and intelligence. Right, sure, sure. And yeah, running a chainsaw, I get that people have thought like, wow, this is crazy. To give a robot a chainsaw is a bit scary. But I mean, what's really scary is operating a chainsaw as a human. So I kind of looked at that, you know, which is something I'm well familiar with living out here in the woods. So my kind of thought is this is a good tool to start with. I mean, running a saw is the most dangerous job in the US it's 130 per 100,000 workers per year. It's 30 times more dangerous than the next most dangerous job. And yeah, I mean, you could imagine not only is a chainsaw dangerous as a tool, but what trees are you cutting down? Ones that are damaged near power lines, ones that are next to a firebreak and a wildfire. So it's just a preposterous kind of situation. So looking at what robotics.

2:13:09

Yeah, the form, the use case, makes total sense. I'm curious to get into a couple questions we should start with. I think what everyone's wondering is why make it look like, you know, a demon from Hades?

2:14:20

Yeah, yeah.

2:14:37

Especially some of these, like disaster use cases. You know, I was thinking I've been in situations where I've never been like really, really, really close to a wildfire, but I've been close enough where the sun gets a little bit, you know, blocked and it's dark and a little hazy. And if I saw one of these things kind of walking out of the smoke, I'd be a little freaked out. And I think a lot of people might feel that way. But yeah, so talk through the decision making on making it look demonic and then I really want to understand the actual functionality of the form which we can get to.

2:14:38

Yeah, sure. So I will say, yeah, the rescue stuff also was kind of propagated by the virality a little bit. That's definitely. I was not aiming to pick you up out of a burning building like a hero in a movie. Though I would point out if that did happen, if someone's saving you, I'm not going to probably be too picky.

2:15:23

And don't look at gift centaur in the mouth.

2:15:44

Yeah, exactly.

2:15:47

You just don't do it.

2:15:48

Yeah, but you know it's interesting with the anthropomorphic stuff on humanoid robots. I think it's actually really disarming, and people kind of aren't understanding what's really going on under the skin, which you can see a little bit here. Have you guys ever used a drill press?

2:15:50

Yeah.

2:16:06

Okay. So you kind of know they're dangerous, and, you know, the work piece could fly out of it, and they got a lot of torque. So imagine if someone hooked 20 drill presses up series parallel all together, and then used basically some arcane knowledge of machine learning to make it balance and walk. This is pretty much what a humanoid robot actually is. Right. That's around the same power that you're seeing on leg actuators on most humanoid.

2:16:07

Where you're going is basically like a humanoid itself looks tame, but in reality, it's potentially incredibly dangerous to be around.

2:16:38

So it's better to let people know you're putting, like, caution tape on it, effectively telling the user, hey, this thing is a chainsaw. It's gonna be doing work in a dangerous environment. You should be triggered, hey, I gotta step back because this is serious business.

2:16:46

Exactly. Like, yeah, I don't know if you guys have ever been on a big work site or in a factory, and first time you go in there, maybe you're kind of putting your back to the wall and, like, you're a little overwhelmed. And that's kind of the right attitude to take when you're around something that can knock your head off. So from my perspective, I made one in gray as well. And you could kind of imagine. It actually kind of looks like, you know, a little bit like a great goat. You know, you might want to go pet it.

2:17:02

Yeah.

2:17:28

This is.

2:17:28

So do you. Do you think that you think you'll end up reading redesigning it? Because if you want to just show that at least, like, the head. Because if you want to just show that it's dangerous, you could just have it, you know, maybe a speaker or a light that says, like, stay precaution

2:17:29

tape or, you know, there's a lot

2:17:44

of way to do it besides the horns. Even though clearly. Clearly it sounds. You just wanted to make this sounds like you live in the woods. Sounds like you want a few of these patrolling around your house.

2:17:46

Yeah. I mean, I think the other thing about humanoid robots, like. Like, we all kind of know that they're not purely like a perfect productivity maximizer device. Right? Like, they have. They have to be emotive and cool, and we've wanted them for 80 years or something, and Been dreaming of this stuff. And I'd say kind of like a car. Like no one buys a car because it's the perfect, like, mobility blob with no personality that is exactly as safe as you want. Maybe a few people do, but humanoid robots like cars. The ones that people really like have to have their own personality a little bit. So I think trying to redesign it to be like, okay, maybe the optimal safety would be to have a giant yellow siren on the top. But it's just not as exciting. So we got to keep it interesting. Right?

2:17:57

Yeah, I get it. And I'm sure there's people. People out there that want to cut down some trees that genuinely would prefer this form factor than something more tame. Talk about for the types of environments that you're imagining the robot in. Why four legs is better than one. I can imagine. Just wait.

2:18:48

One leg.

2:19:09

Sorry, two. Two, two.

2:19:09

One leg is really tough.

2:19:11

One leg.

2:19:12

But imagine a human one leg.

2:19:13

Peg leg, the pirate robot.

2:19:15

No, four legs versus two legs. I imagine if you want to be able to actually manipulate like something like a saw, you want to be able to stable, having the stability, but also the terrain.

2:19:19

Yeah, you don't want to be on wheels.

2:19:29

I think there's been enough videos now of the robot dogs kind of running around crazier terrain that show that, yeah, four legs is superior than two to. To two.

2:19:31

I'm all in on centaurs. Let's hear it though.

2:19:41

All right.

2:19:43

Yeah. I mean, bipeds are tough. You have to move the center of gravity up for the whole bot. Right. Cause you're putting the pack up in the human chest, or I have it in the horse body. Um, you're getting actuators closer to the ground because their ankles are actuated. So if you think about walking around in the forest, you're putting electronics really close to the ground. And, you know, if you have a linear actuator, then a moving shaft, like right on the ground. Whereas this thing, you know, the closest actuator is nearly three, three feet off the ground. The way I'm driving, the knee, it's easier. You know, I'm not a. This is not a huge project. I think another kind of misconception from the viral explosions. Like we're some huge stealth startup that's popping up and these things are going to go knocking door to door. But now this, this is more of a passion project. So doing a biped to today is really tough. You're not going to see all but the best people doing. And even then, I'll Point out there's of course, a lot of curation for what you see with pipes from anyone. And I think everyone kind of knows that they're pretty tough to get stable. I think another question is why not do tracks or wheels? That's pretty tough in robotics too, because if you're trying to keep all four wheels on the ground, like, not like these, the ones you see out of China that are wheels and a dog, but just wheels, you know, then you're going to have to have some suspension, which is kind of the enemy of robotics is having these unknown spring forces and stuff like that. And tracks are just really heavy and really. Actually not all that stable for the size that they are. If you think about a little tracked square driving around the forest, if you're on hard pack gravity, it actually could still be a little tippy. So, yeah, four legs works pretty well. Yeah.

2:19:44

Have you gotten any death threats since the viral moment?

2:21:30

Seems like a long person to threaten.

2:21:35

He's got a robot army at his disposal.

2:21:37

I imagine some people might think now is the right moment before you have 100 of these on your property.

2:21:39

The real crazy ones, I guess, though the few people that were offended by the design are Christian, so that these useful people. So, you know, fortunately I've had, you know, people say I should stop or, you know, that it's. Someone sent me email today that said my company is now owned by God who will save me and stuff like that. But no, nothing too crazy. The more surprising reach outs have been police departments. That is what I wouldn't have thought would have happened.

2:21:47

But reaching out to partner with you or arrest.

2:22:21

Yeah. To ask if it could be used for. For public safety.

2:22:25

Okay.

2:22:29

Yeah, yeah, no, I do that. If you've ever been in at an event where a bunch of police calvary

2:22:29

horses and then there's just like people just dissipate.

2:22:37

Yeah, yeah.

2:22:40

Because there's something about being around a large horse where like it just doesn't.

2:22:40

No, I was going to say the human races. Oh, that gets.

2:22:44

I hadn't even thought about that.

2:22:48

Yeah.

2:22:50

I just think for riot control, the horse is just like. It won't quite. It's not like you're gonna get hit by a car, but there's a natural human reaction to sort of just moving out of the way.

2:22:50

The chat wants to know about the pogo humanoid. There is one pogo stick.

2:22:59

There is one.

2:23:04

There is, yeah. There's at least one. Look.

2:23:05

Yeah.

2:23:09

If you search.

2:23:09

That is even a scarier form where the Robot can jump 30ft in the air.

2:23:10

And it's just pogo stick. It's a psycho clown on it. Talk to me about controlling this thing. I imagine you're not doing full autonomous control, heavy tele operation, but what am I. Because you have multiple cameras. So are you looking at a screen with multiple camera feeds and then controlling with, like, an Xbox controller? What is the process? And then I imagine that as you go forward towards controlling a chainsaw, that's a little bit harder to control with a Xbox controller. So will you have gloves? VR? How are you thinking about that?

2:23:15

I got a solution for that.

2:23:52

Okay, let's see it.

2:23:53

Let's see if we could see. No one's seen this chainsaw, so I guess you guys could.

2:23:54

There we go.

2:23:58

Yeah, do it on your show. But there we go. Okay, so this chainsaw is, to a degree of freedom, kind of like. Let's see if I can line it

2:23:59

up a little better.

2:24:10

You can kind of see what's going on. Yeah, I got to go this way. My thing's mirrored. Yeah. But, yeah, it's something I thought about. So, yeah, think about like this. Like, you have. You can split robotics into moving around and doing something with the end effector. And the good thing about a quadruped is, you know, you could kind of park, and then the hips have enough mobility where you can kind of control it almost like it's an excavator, if you've ever been in one of those. So it's a little bit more intuitive to do than trying to do something like, dynamically. Like, you see people with VR goggles and gloves to control a humanoid that has hands or a biped and all that. That's, again, way outside what I'm able to accomplish. So you can think about it more like you're driving a big car that keeps his hips square to the ground. And then the top half kind of acts more like it's an excavator.

2:24:10

Yeah.

2:25:08

Where you're kind of on to plane.

2:25:09

Do you think there's more of a consumer market for robotic horses? Because there's a lot of. A lot of people out there that love horses, but horses are quite, quite expensive to maintain. And I imagine if you made a robotic horse that you could control with an Xbox controller and sit on it, there would be some consumer market for

2:25:11

it, like a riding one. There was a demo that came out of Japan. I think maybe we shouldn't be surprised that they're on the cutting edge of making that sort of thing. But, yeah, I don't know. Would you buy one?

2:25:34

I think I would. I think I would potentially get one for. For my daughter. Yeah.

2:25:48

Oh, not to commute in the.

2:25:53

The robo horse commuter galloping to work, if you could get it up to like 40 miles an hour would be. Would be quite appealing to me. But maybe, maybe more just for fun use case early on. So something to consider. You need to make the head a lot, a lot prettier though I think to really catch up.

2:25:55

Like an angler fish head, you're thinking?

2:26:13

I'm thinking more like a normal horse.

2:26:16

Oh, okay.

2:26:18

Well, thank you so much for coming on the show and breaking it down for us. Good luck with wherever this project goes. We'd love to stay.

2:26:22

Yeah. Keep us updated, Keep us updated.

2:26:28

Keep going.

2:26:30

I will say when John showed me the website, I said this is clearly somebody just messing around. That vibe coded a site.

2:26:32

I love that it's a real thing.

2:26:39

It's amazing to see.

2:26:41

Yeah, yeah. It's going to be amazing to see where this goes. Congratulations and thank you so much. We'll talk to you soon.

2:26:43

Have a good one.

2:26:48

Have a good one.

2:26:49

Cheers, pal.

2:26:50

Up next we have Ron Urell from Intology. He's the co founder and we're talking about rsi. Recursive self improvement. Is it here? It might be. We'll get his take.

2:26:50

Ron, how are you doing?

2:27:03

Very well.

2:27:05

Thanks for having me on guys.

2:27:06

Thanks for hopping on. First time on the show. Why don't you introduce yourself and the company a little bit?

2:27:07

Yeah, of course.

2:27:11

So my name is Ron. I'm the co founder of Intology. At Intology, our mission is to automate scientific discovery and we're starting with AI, R and D. So today we have some pretty exciting results to talk about regarding automated post training of other language models and lots more to discuss. So glad to be on.

2:27:12

Yeah. How would you characterize the progress, the announcement? Because people can get sort of lost in benchmarks. Are you 20% on this thing? 99% on that thing? Qualitatively. Where do you see the technology today?

2:27:27

Yeah, absolutely. So fundamentally we believe that automating discovery is a domain agnostic problem. What that means is that the structure of discovery problems is pretty similar across domains in the sense of no matter what problem you're looking at, like drug discovery or materials discovery, even like improving language models, there's always going to be some sort of process of proposing an experiment, getting feedback from that experiment, learning from that experiment and then using that information to propose the next set and continuing until you make the discovery. So it's a great question because we think about the problem on that access of how do we build and scale systems to these problems in which the evaluations and experiments become more expensive, more difficult, harder to access. And post training, for example, represents a problem space where experiments are pretty expensive. They can be quite noisy and they take a long time. Right. So if you're trying to build an automated research system that develops the next state of the art 70 trillion parameter model or whatever, you can't really imagine a system training 15,000 models until it discovers the best one, because training is expensive. So you have to think about how do you run efficient experiments, how do you gain information from those experiments better? And I think that today we're showing kind of a closer step in that direction because in the past we were doing things like kernel optimization, like MLE bench style problems, and now post training where obviously it's more expensive and takes

2:27:42

longer on the cost side. This does sound expensive. If you want to hammer a bunch of different experiments. What has been your approach? Just sort of suck it up and use venture capital dollars or partner with companies and labs that have big compute allocations, they have the resources, have them sort of front the cost, or is there another way to solve it? Because scale seems very important here and yet your whole job feels like burning compute.

2:29:11

Yeah, so definitely a little bit of both. I would say beginning it was a lot of burning venture capital money. And now we have partners and systems in place to run experiments that, you know, don't just burn money for no reason. You know, we have our own cluster, we have our own infrastructure that efficiently utilizes those resources. So we're at a place where we're not just like throwing money at the wall for no reason. So we're. Well, I mean, obviously it's an unsolved problem. We will always continue to work on making our system better at this, but I would say it's a mixture of having some great compute partners, you know, spending a lot of time on our infrastructure even before we start running experiments. And now we're at a place where I feel comfortable throwing hundreds of thousands of dollars at the wall if we feel like the system can actually make progress.

2:29:41

Gary Marcus, he says that doesn't count if it's not a pure LLM, that AI is only making progress in verifiable domains. You need a lean output that's fully verifiable. How optimistic are you? And I'm somewhat sympathetic to it because. Because it does actually seem like we are moving much faster in verifiable Domains like math than unverifiable domains like, I don't know, coming up with a script for the next great movie or joke writing or comedy writing or even some of the bio stuff that's maybe verifiable. But over a multi year process of going through FDA applications and test testing, in vitro testing in mice and in monkeys and humans, there's just things that the verification loop isn't just run some lean really quickly and see if it checks out. Right. So what do you see the future of transferring all the amazing learnings and ability for AI to make discoveries in ML in computer science and math to anything that's a little bit, bit less verifiable.

2:30:18

Yeah, for sure. So I think that it really just comes down to, I mean, so we focus on verifiable domains, but I think it really just comes down to, you know, how much you can actually query the evaluator. Right. So back to that example of, you know, post training the next large state of the art model. You could argue that, you know, that system could in theory train the whole model, get the ground truth feedback, see how it did. But that's not fully realistic for every run. Right. So it would have to do some sort of experimentation with either its own rewards or you know, not full ground truth rewards before making that progress. I think it's my, my take is I really think it's just about building systems that almost like wean off the requirement of the evaluator. So for example, you know, if you, if you're building these kinds of system for training small models, no problem. You train an infinite amount of models and you find the best one. But yeah, event like it's almost like as you scale on this access of data difficulty, it's almost like as a forcing function of compute availability or cost, you start having to think like, okay, well now I can't actually have my system train the whole model every time or I can't run an entire clinical trial every time I want to test a drug. It's almost like a nature of the research direction. And so I guess that I don't really think it's that different of a problem. I think it's more that if we continue on this path, like for example, with our system, if we continue on this path where it doesn't need to, you know, query the full evaluate every time, eventually it'll get to the point where it might not even need the evaluator or it'll only need it at the end when sending a drug to clinical trial or, or you know, a material and the fabricator. So I think it's really just. I think, I guess we, and collectively the AI for science community, I think we're heading in the right direction. I don't think. I view it as like black and white as we are only doing verifiable and then we're going to go to unfair, viable domains and like figure it out.

2:31:29

Interesting. I have one more question. Jordy, do you have anything?

2:33:12

Yeah, I was just going to ask, what do you. What do you think your business looks like two years from now? I won't say five or 10, but like, where, where, where is this work going?

2:33:14

Yeah, for sure. So, you know, we, I guess we really believe in not building copilots. You know, what we are really trying to do here is build fully autonomous systems that are deployed in R and D environments and just run the entire loop. Loop autonomously, perpetually. Obviously we're quite far away from that right now. We have to deploy the system, we have to monitor it, we have to see it work, make sure it's succeeding. But I think at the end of the day, definitely two years from now, we want to be at the point where our system can basically be deployed as infrastructure in any computational R and D problem. And then it gets access to the data on the problem, it gets access to the ability to run experiments on the problem. And then it gets deployed in an environment in which, which it's like, you know, hard to hack and you're getting good signal out of the experiments and then boom, you know, it runs autonomously.

2:33:25

It's.

2:34:08

It's cranking out discoveries, it's shipping them, and you know, humans can be there to take a look and make sure it's not messing up. But eventually we want it to, you know, be running end to end.

2:34:09

Last question. Tell us a little bit about the company. Where are you based? How big is the team? Who are you hiring?

2:34:17

What you were doing before this?

2:34:22

Yeah. What you shape of the company?

2:34:23

Yeah, for sure. So we're based in San Francisco. We just moved into our new office. That's why my background's pretty boring right now. We're growing pretty quickly and been really proud of the team we've been putting together. I mean, we have researchers coming from DeepMind, Anthropic Factory, AI, both in, I guess, industry and in academia. I think this is like a really fundamental problem that needs to be worked on. And it's not just a research problem, it's not just an infrastructure problem, it's the whole stack. And we've been putting a pretty incredible team together to do so. And I guess before this, my co founder and I ran a pretty large nonprofit research group. We were primarily funded by the National Science Foundation. Obviously very different from running a company nowadays, but we did a lot of fundamental research in coding language capabilities, published some of the first work in test time scaling with language models. And it kind of felt like a natural progression because we were really curious about how do we model agentic behavior in this kind of search process. And it kind of just made sense that this is the time, this is the place, let's make it happen. And that's what we're doing at Intellij.

2:34:25

Yeah.

2:35:25

Well, thank you so much for coming on the show.

2:35:25

I'm sure you'll be back on soon. Have a great rest of the very cool update. Great to meet you.

2:35:27

Goodbye.

2:35:31

Thanks Ron.

2:35:32

Let's go to this Paul Graham post. He had such a wild experience as he bought a book. It was awful. Didn't want it on my shelves but I couldn't throw it away so it sat on a table near the I

2:35:33

know someone that will rip it apart, feed it to a machine and burn it. I know someone. I don't know them personally, but I know they, they would love. They would love to take this off your hands.

2:35:47

Rushing to an appointment this morning, I grabbed it to read it first mistake. Then went to breakfast and had nothing else. So I spent the morning reading, reading the worst book I have found. It's such a funny, such a funny like, just like, I don't know, it feels like a curb your enthusiasm episode or something like that. Anyway, thank you so much for tuning into TVPN today. We'll see you tomorrow at 11am Pacific. Leave us on Apple Podcasts and Spotify.

2:36:05

It's been an honor.

2:36:31

Sign up for our newsletter tppn.com goodbye.

2:36:31