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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN. Today is Monday, 08/03/2026. We are live from the TBPN UltraDome, the temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com. Time is money.
Speaker 1:Say both. He's used corporate cards, bill pay, accounting, and a whole lot more all in one place. How's your weekend, Jordy?
Speaker 2:My weekend was good. Yeah. So my weekend was
Speaker 1:A little hot here in Southern California, but a little more reason to get to the beach, enjoy the nice weather.
Speaker 3:It's been
Speaker 1:a good summer.
Speaker 2:On a boat. That's nice. What more can you ask for?
Speaker 1:That's nice.
Speaker 2:We got a great show today.
Speaker 1:We
Speaker 2:do. Unfortunately, only one venture capitalist and I think that's because it's August. Oh, yeah. Gonna see us really struggling. It's gonna be be hard to to find
Speaker 1:get those VCs to
Speaker 2:Get those VCs every other month. It's hard. They're happy to jump on same day Yeah. Moments notice.
Speaker 1:You know it's important.
Speaker 2:We got one today.
Speaker 1:Yeah. Got one.
Speaker 2:Shaun Maguire coming out with Isaiah Taylor announcing a $1,000,000,000 series b
Speaker 1:Yeah.
Speaker 2:Led by Sequoia.
Speaker 1:Very excited.
Speaker 2:Very excited for that conversation. We got Justin, co founder of Base Power, another $1,000,000,000 round series d. And then we have the very the the founder of the demon robot Yes. That you may have seen It's last a centaur with horns.
Speaker 1:Bo Gaston.
Speaker 2:And we're very excited to talk with Bo and and get a sense for what went through his head when he made Can a robot like
Speaker 1:you stop? Can you not?
Speaker 2:Can we pull up a picture of the robot? I wanna I There it is. There it is. This is the friendly robot that Bo excited to get into disaster zones to help rescue people.
Speaker 1: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 couldn't put those cameras anywhere. So, yes. It'll be a lot of fun.
Speaker 2:And then closing out with Ron over at Ontology. But
Speaker 1:That'll be fun.
Speaker 2:Let's get into the show. What happened over the weekend? Did anything happen over the weekend, John?
Speaker 1:There were there were a couple things. The the big, 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, He's getting pilloried on social media over using chat GPT for research.
Speaker 1:Very controversial these days. Only a billion people do it. But yeah. And 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.
Speaker 1:I don't want characterize the whole audience as being part of this, but, it's a very silly silly situation.
Speaker 2:There's at least thousands of people It
Speaker 1:seems like that really mad about. 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. Don't I really know 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, you know, state that he will adjust things in the future.
Speaker 1: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. So 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.
Speaker 1: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.
Speaker 1:Like we did that with the So in said
Speaker 2:Tyler is gonna run a five k here in the UltraDome to do a little victory lap for the research team.
Speaker 1:But not everyone is impressed Get
Speaker 2:ready, Tyler.
Speaker 1: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 e f says the goalposts are on a completely separate planet. It is a good point. Obviously, AI is doing better in formally 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?
Speaker 1: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?
Speaker 1:Those terms will always be vague. Yeah. Dig in.
Speaker 2:Going back to Hank. Yes. So all he did was admit that he used some sort of AI tool for research?
Speaker 1:Yes. So I will take you a little bit more through it. First, I'm gonna tell you about Shopify. Shopify is the commerce platform that grows with your business. It lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
Speaker 1:They got AI on Shopify. So if you're selling something, you're you're you're using AI. 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.
Speaker 1:So he has Vlogbrothers, like a vlog channel. Then he has Crash Course, is a really, really huge educational channel. He runs VidCon, which is basically the the premier conference around YouTube and the creator economy. I've been, I think, once or twice. It's a lot of fun.
Speaker 1:And over the last twenty years, he's become one of the most trusted educational creators in the platform. He's also just like, he gets the vibe of YouTube very well because he's been been around it so long. Never really stepped back fully, but always been, you know, solid audience there. So last last Wednesday, he published an episode of a show called Ask Hank Anything. And it's an interesting concept for a show.
Speaker 1: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 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.
Speaker 1:He was talking about this have you heard this kiki and booba thing? There's like two words that 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.
Speaker 1:And it's like the sound of the word has a shape to it even and this is just something in our language that shows up all over the place. He's like Mhmm. Telling the story of this like just somebody ran a science experiment. They, you know, put a bunch of people here. They pulled a bunch of people.
Speaker 1: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, 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, 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.
Speaker 1: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 and about this concept and then he answers it.
Speaker 1:He was just talking to but it's but it feels out of 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 push pushback to the camera. What is this? Beans?
Speaker 1:I don't know. But him 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 left in his script. Hank has to not, has to deny this, but he goes on to admit that he does use chattypt for research. This did not land well.
Speaker 1:No. Don't like the idea of him using Chattypedia research. 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's 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 AI can't do well yet, but pulling a bunch of links and quotes together from across the Internet is
Speaker 4:something Pretty good.
Speaker 1: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 try GPT and saying like, hey, where did this original research come from? Pull up the paper.
Speaker 1: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 units instead of that Those types of questions.
Speaker 1: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 like 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. Of course, like at this point in time, he's like built his career over twenty 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.
Speaker 1: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. Like 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 science is going to be AI enabled.
Speaker 1: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.
Speaker 1: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 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 a like real backlash to just pulling that up on ChatGPT.
Speaker 1:I totally understand. There, I mean, there are people that could just use AI to generate the video. Yeah. And not be involved at all. Or use it in the script or use an AI voice over.
Speaker 2:Yeah. It's just funny because I have this this reaction all the time Yeah. When I realize a video on YouTube is just fully it's a fully AI generated script Totally. Somebody's just reading over.
Speaker 1:Yeah. Or or AI voice is reading it. Yeah. Yeah. Yeah.
Speaker 1:It sort of just depends. At the end of the day, it's just like is the 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. That the filtering process and the taste is what Back
Speaker 2:in your day growing up
Speaker 1:Yeah.
Speaker 2:Did teachers ever say, I really don't want you using Google for the homework?
Speaker 1:No. There was never pushback against
Speaker 2:Is it Google didn't exist?
Speaker 1:Was pushback against Wikipedia. It was it was like, oh, Wikipedia is unreliable. It. Anyone can edit Wikipedia. So don't use Yeah.
Speaker 1:Wikipedia as a source, which really just means
Speaker 2:go to the original
Speaker 1: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 how this all fares. There's a there's a lot of backlash, but it it was sort of like a a lot of people in tech, I think, were getting like sort of whiplash from from watching all of these arguments pile up.
Speaker 1: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 slash in general. But there were bad arguments that were put forth by pro AI people. Something like you use you use you use data centers.
Speaker 1:Like Hank uses data centers. And it's like, yes. YouTube is hosted on a data center
Speaker 2:in Yeah. Are you to write this comment?
Speaker 1:Yes. But that's not that the the actual like 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 which is interesting. I mean, yeah, you do have to check these things.
Speaker 1:And we do see tons of examples of people actually leaking, you know, AI phrases and and weird AI hallucinations into scientific research. There was that example of there was some PDF that was scanned and there was a word on 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 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 20 '26.
Speaker 2:That about The crazy thing is I don't, can you can you even turn off AI mode in Google now?
Speaker 1:Maybe. You can. I think you can. You can use DuckDuckGo. I don't think that has AI yet.
Speaker 1:We'll see. Anyway, Jeremiah Johnson says, I'm fascinated DuckDuckGo. By Wait. Is it really?
Speaker 2:By duck duck.
Speaker 1:No. No. Wait. Are you serious?
Speaker 2:Yeah. Go to duck.ai.com. Duck. Or no. Just duck.ai.likeduck.gov.
Speaker 2:Good name. Duck AI. There you go. Using GPT 5.4 nano.
Speaker 1:There we go. Okay. See.
Speaker 2:Unavoidable. Wow.
Speaker 1:Yeah. The market has spoken, I suppose. Yeah. What do people do? I I imagine you can turn off AI mode somewhere in the settings.
Speaker 1:Or at least you could or or at least you could, you know, get some sort of Chrome plug in that that that deletes that like an ad blocker if you really really cared. But it seems like a lot of work at this point. Anyway
Speaker 2:This was interesting. Ryan Love on X is sharing a heartbreaking essay by a mathematician last week Mhmm. Before this most recent news drop. So this was before Noam Brown Yeah. Showed the recent breakthroughs by Astra.
Speaker 2:Said there's nothing I can do. There may be nothing you can do. I have no prescriptions, policy recommendations, or a coherent call to action. I just wanna be honest and open about my emotional and spiritual response. I want to feel seen.
Speaker 2: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.
Speaker 1:The dark knight of mathematics, Kirwan Hampshire, mathematician researcher from the University of Auckland who recently authored the viral essay. Studied mathematics. Interesting. I I It feels like I would be surprised if 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 that's a completely different discipline.
Speaker 1: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 there are a number of problems that are still unsolved. What happens when they're all solved?
Speaker 1:Do we create new problems? Where do we go from there? Do we start applying them in different ways? What do you think, Tyler?
Speaker 5:Yeah. I mean, obviously, like
Speaker 1:Any advice for mathematicians?
Speaker 5:I I think so so in this article, he says like mathematicians are paid to like
Speaker 2:solve 21 year old podcaster has advice for Exactly.
Speaker 5:Like, so he he says like mathematicians are are paid to solve theorems which like like I I don't obviously, I'm not in academia but like it seems like that it's like kind of their job but also it's like you're in a university. Right? It's like teaching.
Speaker 1:Yeah. I mean, there's plenty of there's plenty of math professors that they'd sort of try and solve theorems but also mostly teach and, you know, don't solve that many theorems or
Speaker 5:Yeah. And also like presumably if you can solve all these conjectures like there's gonna be new questions that open up. This is like the entire history of all science. Right?
Speaker 1:Yeah. It will be interesting to see the application of this stuff because it's so abstract at this point and and and it's it's it feels like it's a very everyone's saying like, okay, based on this, like, this is gonna like flood through material science and flood through chemistry and biology and that would be awesome. Everyone would love, you know, 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.
Speaker 1: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 agent to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security.
Speaker 1:Boom. Boom.
Speaker 2:What else is going on?
Speaker 1:Lots of yeah. This I just like this Gary Marcus. He's really he's really in the arena with this. There's this post.
Speaker 2:Can't It's a really good bit. Which one? Like I Just The Gary Marcus bit.
Speaker 1:It's not a bit. He really believes it.
Speaker 2:No. But I think at at some point, he flipped into bit mode.
Speaker 1:The pure LLM. Yeah. So he he he will always take issue with the idea of something being a pure LLM, a pure LLM solving something. And who is it? Hasam says the LLM use a calculator.
Speaker 1: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 goal posts are on a completely separate planet now.
Speaker 1:First they came for the mathematicians and that sucked because I was a mathematician and really did not expect that, not gonna lie. It will be interesting to hear from Terence 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. It will be interesting to see how he reacts to the latest round of advanced mathematics. John.
Speaker 1:What is left?
Speaker 2:It's time. What? It's time to talk about the rise of one person, $1 companies. One person, $1 companies. No.
Speaker 2:In the Wall Street Journal.
Speaker 1:Million dollar companies
Speaker 2:of million dollar companies with just one employee.
Speaker 1: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.
Speaker 2: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 Broca launched a company last December that offers AI tools to entrepreneurs.
Speaker 1:He That name's familiar. We've him on the show.
Speaker 2:Already added 10,000 paying customers and is on track to bring in 10,000,000 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 Broca's emails, help write and debug code, field requests from customers, sign up new subscribers, and grant refunds when issues arise. Broca relishes his ability to make whatever decisions he wants on his own, often from his sun drenched Sausalito, California California living room.
Speaker 2: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 1,000,000 in revenue with their ranks doubling between twenty twenty three twenty twenty five.
Speaker 1:That's pretty crazy. So this is on Polsia. Right?
Speaker 2:No. No. No. No.
Speaker 1:Oh, on Stripe?
Speaker 2:Definitely not. Okay. This is just Stripe. Okay. The number of solo, I'm sure I I would be curious if Polsia has any companies that do more than,
Speaker 6:you know 1,000.
Speaker 2:A thousand dollar because because to be honest Marketing. Because to be honest, I actually do think success for Pulsaic is like just making back a doll like even a dollar more than you're spending on on Pulsea. Yep. Right? Because
Speaker 1:There's a YouTuber who's been demoing different AI systems, Fable and Soul and Kimmy, and saying, like, go make me money is, like, basically the only prompt. And he lets it cook for, like, a week, and he'll be on, a two hundred months $200 a month subscription, see if it can make 6¢, see if it can make $10. And he's getting closer every time and he, of course, has to do some things, set up API keys and do little things. But it's an interesting experiment. Ben Awad, you should go check it out.
Speaker 2:So the number of solo operators according to Stripe also crossing the $10,000,000 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.
Speaker 1:Yeah. Wait. How does how does Stripe know if you're a solo operator? Like, 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.
Speaker 1:So they must do some sort of polling and ask. Yeah.
Speaker 2:I think I think in your account
Speaker 1:You say.
Speaker 2:Some point you say how employees Okay. Do you have?
Speaker 1:Okay. Then if you say, yeah, I just got one.
Speaker 2:But Interesting. I guess one question I have 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 just One.
Speaker 1:And then you wind up adding people and you don't go out and update.
Speaker 2:Yeah. Possible. Yeah. Because they don't have the the payroll. I I don't know how I don't know how they would have visibility into into payroll, especially like Yeah.
Speaker 2:Individual employees.
Speaker 1:Yeah.
Speaker 2:Yeah. They do have a sense for how many people obviously are like added to your account, but sometimes it's like Oh, account if you add your CPA. Yeah. You know?
Speaker 1:And and and that's a contractor, not an employee. Yeah.
Speaker 2:Yeah. 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 Bowie found that among all industries, new business applications in the information sector
Speaker 1:Mhmm. Have seen the biggest percentage increase, nearly 45% over the past year, yeah. 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 data set 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.
Speaker 1:Wow. Yeah. That chart is really up and to the left. New business formation. This is in the information sector in particular.
Speaker 1:I I wanna know more about what what these people are doing because at the same time we saw Levels. Talk about like the the Indie hacker sort of seeing declining revenues or or more headwinds there because the little SaaS product that they would that Indie hacker might build. I'm thinking of like those those one off websites like 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 and it does it pretty well and it scales to 6 figures or 7 figures, those little sites are now getting sort of eaten by models and eaten by other people and you might be able to vibe code your own. But at the same time, like, they might have a long long term.
Speaker 5:So Tyler, update. Okay. So so they basically calculate the number of, like, solopreneurs based on how many people have, like there's, special plugins or platforms that are directly for, the solopreneur.
Speaker 1:Mhmm.
Speaker 5:So they basically use that to, like, get a proxy of general, like, percentage of solo people on Stripe.
Speaker 1:On Stripe. Oh, they have like a special flow for solo printer. Interesting.
Speaker 3:Yes.
Speaker 1:Oh.
Speaker 5:Cool. So they say that they're almost certainly underestimating the number.
Speaker 1:Hey. Julian Weiser, I know him, says the bar is getting 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 founders seed money and mentorship in exchange for an equity stake attracted 4,500 applicants for 10 slots made available in 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 that is staggering. A lot of people wanted to be solopreneurs.
Speaker 1:Going it alone with AI can still be surprisingly expensive. Broca said he was losing money on many customers' accounts while paying to access Anthropics Cloud 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 $30,000,000 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.
Speaker 1: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.
Speaker 1:He used an AI. He used AI to code an app that helps people get the most out of credit card benefits. 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.
Speaker 1:There's been a few apps that do that. The points guy had a whole blog around it. A whole media company around it still does. But interesting to sort of like, yeah, go and go and actually vibe code that. Lot of these things it's like you could probably just use the models themselves for this.
Speaker 1:Yeah. 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.
Speaker 1:The company makes around $3,000 a month in profit with no employees and continuing to grow. What a run for John Troy Johnson. Story. Who loves who loves King Arthur related metaphors for business. What one per what one person businesses will mean for the labor market remains to be seen.
Speaker 1:Polling has shown that Americans are worried that AI will replace jobs and 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 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 this recent study that found that among 50,000 startups the researchers examined, those focused on AI tended to operate with 25% fewer employees.
Speaker 1:It's interesting because haven't we seen the the ramp data that said that AI AI adopting companies were hiring faster, but maybe they still operate lower operational headcount but hiring faster because of hiring growth. There's like three different factors that are going on here sort of mixing altogether. Koenig, the professor, also believes in a soft believes a soft hiring environment that has left some people mired in log job searches has encouraged more to try their hand at launching businesses. That makes sense. Some founders cite different motives.
Speaker 1: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 Brenningsville, PA. Two years ago, Ahmad decided to leave the corporate job he had worked at at Verizon for almost two decades to start a solo 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, a second in command. The business ultimately petered out within months though and Ahmad is back to full time corporate role with a utility company.
Speaker 1: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 twenty twenty three to help code an app that would help manage documentation and design for new products with customers ranging from financial services to health care firms. I was copying and pasting from ChatGPT said Voe, who lives in San Francisco. She put her app online for $1 a month. Wow.
Speaker 1:That is cheap. And within weeks,
Speaker 2:we I found thought we didn't know how to make apps that cheap anymore.
Speaker 1:Yeah. I mean, is a subscription, at least not one time. But she put it online for a dollar a month, and within weeks, people downloaded it thousands of times. Nearly three years later, Vow's company, which she ran solo for nine months before hiring an engineer, now has a 100,000 users and is on track to make 7 figures in profit this year. Wow.
Speaker 1: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.
Speaker 1:Vo said her network and credibility in the industry were key. I think people over index how on how easy AI is and under index on how much I did to get to this point. She's still
Speaker 2:Yeah. I I just wanna see I wanna see five companies Mhmm. That make more money from their business than they give Pulsia every month.
Speaker 1:Yes. So so Yes. Pulsia has has some public dashboards for how much people are spending or something like that?
Speaker 2:Yeah. They have a public dashboard. Let's see if I can find that again. Mhmm.
Speaker 1:While you're doing that, let me tell you about Cisco. Critical infrastructure for the AI era unlock seamless real time experiences and new value with Cisco. And if George is 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.
Speaker 2: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. Mhmm. Thank you, Tyler.
Speaker 2:Yeah. So right now you can see all the different things that the companies on Pulse C are doing, or at least some of them. Mhmm. Right now, so far today, companies on Pulse P Pulse C have spent $373
Speaker 1:Is that today?
Speaker 2:On ads. Today.
Speaker 1:Yeah. Oh, it's still morning.
Speaker 2:It's still morning, so we're we're pacing. Okay. I don't know what time zone this is in. But, yeah. The the the big question is like, is any of this stuff actually working?
Speaker 2:Or is it more like kind of a video game effectively
Speaker 1:Yeah.
Speaker 2:That people just enjoy like watching the machine Yeah. But there's not really much happening.
Speaker 1:I mean, was the thing for Midjourney and Suno, I think in in many ways. Like, Midjourney, when it launched, people
Speaker 2:Totally. I mean
Speaker 1:No? Okay. Hear me out.
Speaker 2:Okay. I'll hear you out.
Speaker 1:Okay. When Yeah. Mid journey launched Yeah.
Speaker 2:The steel man. When when mid journey
Speaker 1:people were like, this is going to take artists jobs. And it was like, okay. So if that plays out, then I'm gonna go to the MoMA. And there's going to be a show for someone that just prompted mid journey. And the highest auction at Christie's is going to be some mid journey artist.
Speaker 1:And that's not really what happened. Like, people aren't using mid journey to make fine art, but people love mid journey. Like, they love the activity of going on mid journey and generating and prompting and getting an image back. And then 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.
Speaker 1: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 and and Yeah. It's possible that that could be the same activity for, like, okay, I'm gonna go build an online business, see if I can get something out.
Speaker 1:But it's not really like a job. It's more of like an entertainment product. Yeah. I don't know. What do you think?
Speaker 5: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, ender, you know.
Speaker 1:You you offshored the last job. You sent out you sent out the labor overseas. You rolled up the entire HVAC industry. That wasn't a simulation. No.
Speaker 1:Based on my steel, man, do you agree or do you still disagree?
Speaker 2: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.
Speaker 1:Yeah.
Speaker 2:Or to just create AI art. Yeah. And you could use Suno. Suno is just like deeply entertaining. You go on there and in Exactly.
Speaker 2:Five seconds you make a real Yes. Song that sounds like it was recorded in a real studio.
Speaker 1: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 the pro like the game. It's a game. Right? I don't know.
Speaker 1:Tyler, really?
Speaker 5:Okay. Just just on your example earlier of the MoMA artists, like Yeah. That's like the insane long tail of artists. Yeah. That's not like the average, you know, center of the of the curve artist that like
Speaker 6:Okay.
Speaker 5:Midjourney like maybe is like doing a similar thing to
Speaker 1:what Yeah. Maybe. Producing. Yeah. Maybe.
Speaker 1:I don't know. Yeah. I I I would just be surprised if if if the I don't know. Maybe maybe the way to put it is like, I'd be surprised if like the like the majority of mid journey users are using the product as a as a, like, a an artist career path or an artist career path. Like, they're like, okay.
Speaker 1: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.
Speaker 1: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.
Speaker 1: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 and have fun with that and see what those are like and then just enjoy them myself. Right?
Speaker 1:Yeah. I don't know. I I I think there's like a smaller tighter loop with some of these services that might be you know, overridden. And I'm wondering if there might be one in the like design a business like gamification Yeah. Business world.
Speaker 1:I don't know. It does Ben seem
Speaker 2:Ben has done a really good job positioning policy and like Yeah. You know, using some different methods to get attention. I I have some something I feel like I have a little bit against the whole thing because I just get spammed to massive DMs from him. He doesn't follow me on X, but he spams me with messages asking asking for different things, which I just think is Yeah. I think is somewhat entertaining if you're trying to run the anti AI slop company.
Speaker 2:Mhmm. Right?
Speaker 1:Yeah. Is it? I thought it was pro AI slop. I thought that was the whole name
Speaker 2:was No. No. He's very he's saying this is not Slop. Oh. This is
Speaker 1:Because there is a world where you're like, it's Slop, but it's good Slop. And like, it's fine. Like, there there there's a lot of programs that say like, yeah, the answer for more Slop the answer for slop code is more slop. And then it's like it'll be fine. It's not it's not a problem.
Speaker 1: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 it illustrated the point just like you wanted. Anyway, Tyler, do have some of those?
Speaker 5:Yeah. Was just gonna say like, yeah, SLAP is like a temporary term. Yeah. At some point, the running actually becomes good.
Speaker 1:Yeah. The writing?
Speaker 5:That whatever. The output of the model.
Speaker 1:Yeah. Writing does seem behind a little bit.
Speaker 5:You can it's like verifiable verifiable. No. People say it's good or bad.
Speaker 1:Yeah. Not not fast enough. The loop isn't tight enough. And there's too many people that say it's good when
Speaker 5:You it's can make it.
Speaker 1:Maybe. Yeah. Maybe. It's it did get a lot better.
Speaker 2:Still, once a week
Speaker 1:It got a lot
Speaker 3:better.
Speaker 2:Someone prominent posts fully AI generated content.
Speaker 1:Yeah. What was happening with the cash? No.
Speaker 2:It just happens it happens once a week. It's just an iron law of once a week. Someone really really talented and smart Yeah. Posts something that is just entirely AI.
Speaker 1:Maybe we maybe we gotta rip it. We gotta try it just to feel something. Because maybe maybe it's like a forbidden 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.
Speaker 1:Copy, paste, rip it.
Speaker 2: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 get ratio. Much more ratio. Way more people see it, and as long
Speaker 1:as the first few
Speaker 2:shots. Sentences are kind of delivered the message Yeah.
Speaker 1:On. This is good. This is really good. Yeah. I I think we gotta do it.
Speaker 1:We'll we'll test it on Tyler's account first, though.
Speaker 2:Joe Weisenthal.
Speaker 1:Yeah. Let's do the Joe Weisenthal.
Speaker 2:AI people who are like, nobody's prepared for what's coming. It's like, maybe just speak for yourself.
Speaker 1:Joe's ready. Joe's ready. No. It is it is very funny that there's this whole there's this whole meme of like, no one knows what's coming. It's not priced in.
Speaker 1:It's like all anyone talks about ever. It's on the front page of the Wall Street Journal every day. Lots of people are talking about this.
Speaker 2:And most people that say nobody's prepared for what's coming will not give you a really concrete
Speaker 1:Yeah. Like what exactly?
Speaker 2:Like the last time we had this nobody's prepared for what's coming moment was what was the guy who was comparing AI to COVID back in March?
Speaker 1:Was that Schumer? Matt Schumer? Yeah. So something big is coming?
Speaker 2:Yeah. Something big is happening.
Speaker 1: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
Speaker 2:Yeah.
Speaker 1:Like, we at this point in 2020, unemployment had spiked to 10%, and, like, it it was very much like, you're a bold patriot if you're going outside. Like it was a crazy crazy time. Yeah. And now it's like, yeah, there might be some softness in the in the job market. Like a hedge fund blew up.
Speaker 1:There's like there's things that are happening. Some big things. But
Speaker 2:blew up from being a little too bullish. Like things maybe like they got the you know, the the basically directionally correct but got the timing wrong. Right? Mike Isaac says, yeah, these MFs don't know how much I got stockpiled in my basement.
Speaker 1:Yeah.
Speaker 2:And Joe says, these MFs don't know that if a man has a why, he'll find his how. Yeah.
Speaker 1:Buco Capital was having fun with Kevin Russe over at formerly New York Times, now Hard Fork Independent. I don't know. Did they take the IP? Are they still using Hardfork outside of MIT? Don't know.
Speaker 1:But Bukka, just this 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 $1,000,000,000,000? What nobody is pricing in is that besides coding and math, very few domains have embedded verification.
Speaker 1:And so but Tyler over there thinks that you can formally verify whether or not The Odyssey is a good book in in lean or something.
Speaker 2:Well, think we can Yeah. No. I think we can formally verify that Tyler's got it. Right? A lot of people would say like Yeah.
Speaker 2:It's kind of like gray area. Right? Totally define what it means to be the greatest of all time. Yeah. But You've
Speaker 1:been working on that quantifying aura. As long as it's fully quantifiable, you'll be able to
Speaker 2:Auto out.
Speaker 1:It. Yes. Andrew Curran says, shorten your timelines, friends. I've started this account to say this, and in many ways, I've posted for the past four years has been saying the same thing. Some of you increasingly feel it.
Speaker 1: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 singularity. We're in the singularity now. Demis on stage at Google IO just a couple weeks ago, a couple months ago saying we're in the foothills.
Speaker 1: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 my all of this at once in one shot. And that was the correct time to up to update, Like talking to 3.5 and and the first ChatGPT moment, bang Sydney, that it was if you if you updated on that, you did very very well across everything. Both with the growth in the labs and the growth in the the data center build out and everything. Like, that was the key moment.
Speaker 2:Also, was a moment in 2020 this was coming up over the weekend Yeah. That somebody used GPT three to generate, like, a fully functional React app.
Speaker 1:Do you
Speaker 2:remember this? Yes. I forgot what it was called. It was called like the something. Mhmm.
Speaker 2:The Yeah. But anyways, that in in hindsight was like such a big moment. Yeah. But at the time, it got like 2,000 likes and people were like, wow, this is really cool.
Speaker 1: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.
Speaker 4:Yeah.
Speaker 1:Like, or I mean, a lot of people did, honestly. Yeah. Like, tons of tons of people across venture and private market and public markets.
Speaker 2:A lot of people did, but way more people didn't update any of their behavior.
Speaker 1:Yeah. Yeah. Guess. It's mind blowing to me how few people realize their lives and everything they know will change drastically in the near future. At this point, it should be pretty clear, says Jerry Turek.
Speaker 1:Yeah. Wild wild times. Elon Musk says 100%. He's completely agreeing. Let me tell you about Codex.
Speaker 1: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 got to look at this simulator. You're into racing simulators. I got to up you.
Speaker 1:I got to one up you with a train simulator. Look at this guy. This guy on z80.me has set has built a full scale train simulator controller. For the last three years, I've been building a physical train simulator in my apartment modeled on The UK class 80 x passenger train. I've I've been trying to replicate the instruments and controls in the real cab as closely as possible.
Speaker 1:Look at this.
Speaker 2:This is amazing.
Speaker 1: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.
Speaker 1:There's a status update on many of those aspects.
Speaker 2:I'm feeling the acceleration, John.
Speaker 1:This is such a cool DIY project. Imagine just sitting there driving train in the train simulator.
Speaker 2:So one thing I'm not seeing is any type of visuals. So is he
Speaker 1:Like, you you mean you mean the the software that's driving the
Speaker 2:To 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
Speaker 4:in the
Speaker 1:In the train. But no. There is a screen and that screen is running a game that simulates a train. Okay. The name of that game, Train Simulator.
Speaker 1:You can get it at train-simulator.com. It's also on Steam. Yes. Train Simulator Classic is I believe the one that he's playing. But yeah.
Speaker 1:He's playing the full full Train Simulator. AWS Sunflower? I don't know. Anyway, funny funny story. Balaji is moving to Kazakhstan.
Speaker 1:This is huge for the Borah community. Not the absolutely huge for the Borah community.
Speaker 2:He says This is Kazakhstan. Let's see.
Speaker 1:This is a beautiful video. I I I have no doubt it's a beautiful place. It's a little bit crazy because network school I thought of as sort of a like a startup incubator, a a y combinator adjacent entity. He was in Singapore for a while, then Malaysia, and now maybe Kazakhstan. Is he did he actually move to Kazakhstan or is he just like touring and vacationing there?
Speaker 1:Because what is the actual
Speaker 2:Here's the news. Okay. He 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 Balaji, excited for Kazakhstan, excited for Network School.
Speaker 2:Balaji is very smart and very entertaining, and I've enjoyed having him on the show. I do think 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. Yeah. Where he, you know, where he effectively had all of his success at Coinbase Yeah. And Andreessen Horowitz, and I'm sure many other businesses.
Speaker 2:And I think it is this whole chapter is deeply entertaining to me. The Kazakhstan chapter.
Speaker 1:It's just it's such a funny place. King of the Castle. I love it. So quick tip for anyone who's planning to do sort of like the the bi coastal thing, San Francisco, Kazakhstan. You're in for like a thirty hour trip because there are no nonstop flights, I think.
Speaker 1:You have to connect in Istanbul, Frankfurt, Seoul, Doha, or Dubai. You're looking at twenty five to thirty five hours depending on the layover. That is really really far. The Miami thing was a was a tough pitch because, you know, so much activity is happening in New York, so much activity is happening in San Francisco. And it was still hard to get people to relocate like great engineers.
Speaker 1:They come out of the
Speaker 4:beat No.
Speaker 2:Mean, this is just truly Full send. The toughest possible sell. I think he's trying to I think he's Weed out the weak. I think well, I think in 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 to move to Kazakhstan. It's it's I know so many I mean, some major selection bias here, but I know I know a bunch of bright people
Speaker 1:Mhmm.
Speaker 2:That are not US residents. And they would do anything to be able to
Speaker 1:be In Kazakhstan?
Speaker 2:Not quite. Maybe now. Maybe now. But they would do anything to be to be able to have free access to America. Oh.
Speaker 3:To be
Speaker 2:able to set up shop here to Yeah. Help their business here. To be able to
Speaker 1:To be the king of the castle.
Speaker 2:To be to be not even the king,
Speaker 1:but a pauper. Just someone just someone in the castle.
Speaker 2:In the castle at all. Mhmm. And so Yeah. And I haven't Yeah. Just
Speaker 1:We gotta go. It's very
Speaker 2:clear. Very clear.
Speaker 1:It's very clear that
Speaker 2:gotta go
Speaker 1:or at least Tyler. I
Speaker 5:would go. It looks fun.
Speaker 1:Pack your bags, buddy. See you in thirty hours when you land. Absolutely wild. Me tell you about CrowdStrike. Your business is AI.
Speaker 1: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 were a bunch of interesting points in this Strathecari update.
Speaker 1: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.
Speaker 1:You need a text model, you get a text model. If you need to speed up your programmers or your your your engineers, hire the best coding agent and negotiate with them. Right? And here's how Mark Zuckerberg answered He said, I can take the open source question. Let's see.
Speaker 1: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 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.
Speaker 1:He says, and then there's also just the there's always there's there's also just always the perpetual both policy debate and 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 closed 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, you know, super dependent on a particular product. So he says, and I think that's very tricky.
Speaker 1: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 John 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.
Speaker 1: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 surface 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 got started, he says, my background in engineering, I wrote a lot of the systems code.
Speaker 1: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 but he makes a really good point. He's 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 because we go all the way down the stack.
Speaker 1: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 very aggressively. This is the reals thing.
Speaker 1:They built they built, like, two extra data centers to be able to do the reals 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 videos. 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 3,000,000,000 users or however many billions of users they have on a on a dime if you don't have the infrastructure, you're not actually vertically integrated. So there's a whole bunch of other things where in terms of personalization, understanding the user, like, a really first class experience.
Speaker 1:They sort of do need to bring it in house, but investors are very upset about this. They're not very happy because they they Ben Thompson calls it 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.
Speaker 1:So they're both renting AI compute, paying a bunch of money for new researchers, 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 backing down.
Speaker 1:But we'll see.
Speaker 2:Yeah. Tough position to be in when capital markets don't have a ton of faith, and you just see that in in the stock price. The the company broadly, right? There's a lot of infighting, frustration around just how MSL is treated versus the rest of the company, which is paying for MSL. So Zuck is is at war Mhmm.
Speaker 2:With fighting a war with multiple fronts.
Speaker 1:It is. It's a big war. Well
Speaker 2:He'll get through it though.
Speaker 1:We'll dig into it more. I still think this this Pierre Richelsen 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.
Speaker 1:We have a pepperoni pizza ready and could deliver it in ten minutes. You hungry? Hilarious concept. Would be extremely annoying to have every possible low tier, you know, business that you do that that you bought anything from with spamming you. I mean, they basically do this with, you know, email awareness, like, hey, there's a Super Bowl coming.
Speaker 1:Like, do you wanna place an order?
Speaker 2:What if we made a law that said that restaurants could only call between 05:30 and 6PM.
Speaker 1:When you're hungry?
Speaker 2:And so you knew you'd be getting calls coming in, and you could kinda play them off each other. You get a pizza offer. You're like, look, I'm kinda interested in pizza, but I'm I have an open conversation with the taqueria Yeah. And I need to wait to understand, like, what they can offer tonight. Yeah.
Speaker 2:I'll let you know. Yeah. Taqueria calls, you
Speaker 1:go Yeah.
Speaker 2:They go four steak tacos Yeah. Side of rice. You win. Yeah. And and then you you you get a price, you get a bid, you go back to the pizza, you Yeah.
Speaker 2:Kinda play them off of each other a little bit, and then you go with, you know Yeah. With what you're really feeling at the end of the day.
Speaker 1:Do you know what it's called on Wall Street when you have multiple parties negotiating to sell a block of stock or debt or something like that, and you wanna bring them all in really quickly? Like, let let 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.
Speaker 1:Mhmm. So like, oh, yeah. I'm going to barge his line. Jump in there, and then we'll be on like a three way call basically. And and you can do that when your phone system's set up with multiple lines.
Speaker 1:So you could potentially have, okay, you got Domino's on 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, you know, all in
Speaker 2:Conference all time.
Speaker 1: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. Yep.
Speaker 1:This might be the solution. I like this post. Explaining to my wife explaining to my ape 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 thousand one Space Odyssey? Yep.
Speaker 1:It's a good movie. Jordy, have you seen 2,001 Space Odyssey? Yes. You have? Yeah.
Speaker 1:No way.
Speaker 2:Yeah. Remember that scene. What? How how did that happen?
Speaker 1:That's wild.
Speaker 2:I think I was forced to watch it.
Speaker 1:Oh, yes. This this old 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 Dwarkish Patel what his goals were, he answered, eventually, you are going to go to the stars. You are going to go to the galaxies.
Speaker 1: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 2,000 200% after fees as anything tied to AI shot higher.
Speaker 1:One investor said, yes. There was a funny line where 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 seven fifty is the one that you'd want. And and Leopold was like, no, no, no. I'm gonna buy an actual galaxy.
Speaker 2:Tay Kim says, who will play Leo and Ken in the movie? We know it's coming. Mhmm. The story is too juicy.
Speaker 1:Okay.
Speaker 2:We gotta
Speaker 1:play we gotta play this clip of of Ken Griffin because this came up on my my For You page. And it's a 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 clip.
Speaker 7:Know, in 1994, I was in Switzerland. We'd had a rough year in '94. We lost about 4% of our capital in '94. Was one of our only losing years in the history of the firm. And I'm in Switzerland.
Speaker 7:I mean, was a rough day. My lunch my lunch I sat down at lunch. This person sits down. Oh, you're not John Griffin? No.
Speaker 7:I'm I'm Ken Griffin. He goes, I thought you were John Griffin from, Fenchurch or the firm. He goes, I I gotta go. I'm like, great. I flew all the way to Switzerland from my lunch date to get up and leave the table.
Speaker 7: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 footage of this stage. Beautiful furniture. He goes, do you mind if I smoke? He takes out a big cigar.
Speaker 7:He's smoking this cigar. And we're talking for about forty five 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 but you just have to tolerate.
Speaker 7:You're gonna hear no a lot. But you need to become accustomed
Speaker 2:to We uphold staff. Yeah.
Speaker 7:What you stand for. Again, whether it's the people that you wanna have work for you,
Speaker 1:people that
Speaker 7:are trying to give you capital or customers, you need to get comfortable with the art of selling.
Speaker 1:Great clip. It's so funny that someone was like, Ken Griffin, like, you're just in the wrong job. You should be
Speaker 3:Yeah.
Speaker 1:I don't know.
Speaker 2:This is this is not for you.
Speaker 1:I wonder what that banker would have preferred Ken Griffin do. Like, did he have a prescription? Was he like, you should be?
Speaker 2:Course seller.
Speaker 1:A hustler. I don't know. Skier or something. Anyway, fun little trip down memory lane. We have John Gruber from Daring Fireball in the waiting room.
Speaker 1:Let's bring him in to the TBPN Ultra Dome for the second time. Welcome back to the show, John. How are doing?
Speaker 8:Good. How are you guys?
Speaker 2:We're Great to see good. How's your summer been? Yeah.
Speaker 8:Hot.
Speaker 1:Hot? Has the has the tech news been overwhelming or underwhelming this summer compared to previous summers?
Speaker 8:Oh, I'd say much busier. Much busier. But but definitely busier.
Speaker 1:It feels like the I don't know. I mean, at least the the the there's like the traditional news which is like a company does a thing, there's a process, something launches. That felt that has felt very light recently but then there is like the meta drama of like situational awareness blowing up and that 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 term, you know?
Speaker 8:Yes. I don't think that there was a marketing schedule for 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.
Speaker 1:Well, it just depends if you believe in like the Truman Show thesis or the simulation theory. Was like, now have the hedge fund explode. That will be the entertaining Yes.
Speaker 2:Well, the funny thing is there what there there actually was people that were making allegation that the hack was marketing.
Speaker 8:Yeah. I think they don't mind, right? Like, don't think it's So I don't think there's a conspiracy and 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 twenty four 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 deliberate.
Speaker 2:Yeah, sure. 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 coach has
Speaker 8:to and talk to the
Speaker 2:say like, hey, look, your son is very good, but like, he's got to pass the ball a bit more, and like, it's not really that sportsman like to run up the score that crazy. He should focus on, you know. Teamwork?
Speaker 8:Yeah.
Speaker 1: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.
Speaker 1:But how do you think about the pressure that Apple has been under around component pricing, supply chain pricing getting caught flat footed versus just reacting to what's happening in the world?
Speaker 8:It is extraordinary. And I really do think that to go the other way, think, you know, Tim Cook's public remarks on it as being a once in a 100 year flood situation and that he's been looking at this market his entire career and there is no comparison point. Yeah. You know, that the and RAM in particular has always gone through these boom and bust cycles and 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 the sort of situation you just can't prepare for.
Speaker 8:If you live on a flood plain, you take precautions and you build levies and 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 levies and if something happens where you still experience a flood, well then it's a catastrophe. I wouldn't even I mean, 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, Apple just does not do that.
Speaker 8: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 eighteen months ago and say, oh, well Apple should have really foreseen this and somehow done something different. What could they have done?
Speaker 1:How how much do you see the the leasing program as a direct response to higher prices? Is this do 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 refresh they've had program where you could effectively subscribe for pre memory price spike, right?
Speaker 8:Yeah. Yeah. They had the old iPhone upgrade program Yeah. Which was just for iPhones.
Speaker 1:Mhmm.
Speaker 8:I think they've seen it as a success, and so I think this was sort of a natural two point o way of of you know, and it's no 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 come out. I mean, you can even get like I
Speaker 3:think you
Speaker 8:can even get like AirPods on Apple upgrade. Not just for, I don't know. I think so. Interesting. But certainly like all the Macs, all the iPads.
Speaker 8: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 paying over time.
Speaker 9:Mhmm.
Speaker 8:It's, you know, 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. Sure.
Speaker 8:But everybody is looking at that and thinking, well, this is crazy. They're charging these consumers 13 or 14% APR. Well, how do we get involved in that? And Apple specifically, now they have the Apple Card which is, I don't know, seven, eight, nine years old. I mean, it's been a while and they've had a program through that where if you buy an iPhone, you get twenty four months of zero interest.
Speaker 8:I think the big change though, it's clearly about the fact that for so many people, you know, 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.
Speaker 1:Sure, sure.
Speaker 8: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. Yeah. But if I agree to this, I can get a new iPhone. I can walk out of the store with an iPhone fifteen minutes from now. And so I think Apple just looked at that and thought, well, how can we offer something that's attractive?
Speaker 8:The lease, I think the big difference with the lease is clearly that the monthly payment is even lower than the buy over time of the old iPhone upgrade program. In either case, it is good for the consumer and I know some really smart people who are like, I'm doing this because 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 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.
Speaker 8:So I think it's better for everybody.
Speaker 1: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 is this sort of like you think it's a pretty mature strategy that they have?
Speaker 8:I think it is incremental, let's say. Like, there's it's 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 there were a couple of times where MacBook Airs dropped to like eight ninety nine or something like that, but that nine ninety nine starting point had been the starting point for a base MacBook Air for, I don't know, at least fifteen years.
Speaker 8:And so, you know, when you consider inflation, the price has been coming down, but not down in a way that like 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 a $100 or $200, but all the way down to $5.99. I guess it's up to $6.99 now with the price increases. But still that is significantly lower. And I think they've been doing the same thing.
Speaker 8: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, 16 e, 17 e, there will be an 18 e 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.
Speaker 8:It's a 1x camera that you can get 2x optical with 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. It's here's brand new stuff. It's just less technically advanced silicon wise, but it is brand new.
Speaker 8:Right? The Neo is months old and it's at a record price. So they're incrementally moving down market, but I think only insofar as they think that there's people with money to spend.
Speaker 2:Yeah. Jordy? What percentage of the employees and 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 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.
Speaker 8:I'd It's a good And I think last thing
Speaker 2: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.
Speaker 1:Biggest opportunity?
Speaker 2:This is such an amazing opportunity. Like, if I want to work on consumer AI, I have to go work there. Like, that's just don't know anyone like that.
Speaker 8:Yeah. I think that's true. I don't either. But I don't know that it's a problem. Mhmm.
Speaker 8: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, 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 will be coming in the coming year, this is the coming year, right?
Speaker 8:And it still isn't really out. It's in the public betas this summer. It's coming out this fall. So they announced something that they were saying was going to come out to consumers be in people's hands in the first half of twenty twenty five and it's coming out at the end of twenty twenty six.
Speaker 1:In
Speaker 8:this market, in the AI market, that is a big miss time wise. Now, ten years from now, will people look back at this and say, Wow, that was a huge gap of time? Probably not. 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.
Speaker 8:Right? This is very basic stuff, but it all does work. It is 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.
Speaker 8:You know, I've been using ChatGPT in particular for 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 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?
Speaker 8:Clearly the biggest driver of that is their fear of missing out with Claude and Anthropic taking the lead as if you just polled everybody who watches TBPN, 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.
Speaker 2:Yeah. Verifiable based on Payroll. Revenue run rate. Yeah. So Yeah.
Speaker 8:It should And just the state of things. Right? You just put lick your finger, put it in the air, and who's got the momentum. Yeah. Right?
Speaker 8:I think and that's put OpenAI 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. Think, you know, like somewhere around eighteen months ago or so. That whole company had the we've won this already. It's we're just mopping up the chessboard at this point.
Speaker 8:And now they've 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, you 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.
Speaker 8:And I think that there you know, in the Apple world we call it Sherlocking because there was the Sherlock thing twenty 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.
Speaker 2:Oh. Then there was a third party the other way.
Speaker 1:I always get it flipped. Yeah. Thank you. This is helpful. Right.
Speaker 8: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, you know, 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.
Speaker 8:And, you know, Apple had this stance that was They they quite outspoken about it. Like Craig Federighi, I think it was with Joanna Stern last year, you know, said that Apple did not see chatbots as a good interface to AI. That's right. You know? Yeah.
Speaker 8:Yeah. 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 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?
Speaker 8:No. I mean, why would you? This you know, 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, you know, the type of trivia questions that people just ask as like a one off, two off chat session.
Speaker 8: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
Speaker 2:to it.
Speaker 8: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.
Speaker 2:Let's Derek. Let's play it out a bit further because I'm curious where you where you imagine Siri AI goes. I've always felt similar
Speaker 1:to
Speaker 2: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 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?
Speaker 2:And then they say, oh, we're for privacy and all these things. But then at what point do they say, hey, is costing us a lot of money to run. We gotta start running ads. And then at that point, 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 in maps and they run ads in the app store and all these things?
Speaker 2: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 The
Speaker 8:ad question is interesting because obviously Apple never had to or never decided to 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 how, you know, however much they'd like to keep it under the radar, it's like 25,000,000,000 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 ten years ago, it was a huge percentage of Apple's quote unquote services. So Apple's 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?
Speaker 8:Because when people would search, you see the Google results and what does Google show them? Ads. Right? And then you you know, there's a very simple, oh, this is kind of you see how this works for everybody. There's a sort of flywheel.
Speaker 8: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 you know, how does that financial relationship work with Apple and Google for the back end? Like, who's paying for it?
Speaker 8:That's a real mystery. And they've they've very and I I every it's one of those questions where when the like, Apple just reported results at the end of last week. Every time I've I I never listen because I find those calls in they're like forty five minutes long and they feel like forty five hours. So I skimmed the the transcript and I'm like, I would love if somebody could ask and I don't think that they would answer but if we
Speaker 2:It's
Speaker 8:have
Speaker 2:any kind clue about how that so it's so interesting to me because Google is help is like, we're gonna help Apple because we wanna try to commoditize the LLM space because we're behind Yep. And we're and 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.
Speaker 2:But then through that, they if you assume that partnership is gonna 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 gonna sign up and say, oh, I'll spend another $20 a month on on AI Yeah. With Apple. Right?
Speaker 2: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 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 gonna it will probably make sense to do ads.
Speaker 2:Then at that point, do they dance with Google again and and use like the Google Ads network? But it's so hard to see where this actually They
Speaker 8:are, but Apple is dipping its toes into ads, right? 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, let's say, Signal, Signal is a good is the example I always go to because they don't pay. They don't seem to pay. But if the signal group or whatever the organization is, Balance Signal, pays for an ad on the keyword signal, you can buy your own name as the top result.
Speaker 8: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 there's like Sometimes there's like gambling apps that show up
Speaker 1:in
Speaker 8:number It's crazy. And now they've added a second spot in the third spot. 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 like double dipping because Apple's taking the commission from the app store transactions and making you pay to get the top spot. Yep. The second spot is the top natural search result and the third spot is another paid ad now.
Speaker 8:Mhmm. And I think that's off brand for Apple. I really do. I think it is 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?
Speaker 8:Where you're got parents to spend, you know, whatever $10 at the time in the eighties, like $10 a month extra on the cable bill. But it seemed like such an amazingly good bill. Good deal. And that's, you know, 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.
Speaker 8:What do you get? Well, part of the experience is you don't get inundated with ads. I go back to the Safari thing with Google search. It has been such a good deal for Apple. It is 20 to $25,000,000,000 in cash that just comes in.
Speaker 8:It is almost no margin. You can say that you could subtract
Speaker 2:I mean almost a 100% margin.
Speaker 8:Almost, right? At this I mean, what's the salaries of the team that makes Safari and WebKit compared to $25,000,000,000 a year, right? It is as close to a 100% margin as anybody could reasonably get. It is year after year and it doesn't look like Apple is serving you the ads. You're just Joe Schmo Apple customer.
Speaker 8: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 that really can't happen with Siri. Right?
Speaker 8:They could partner with Google Yeah.
Speaker 2:That's perfect.
Speaker 8: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
Speaker 2:But then
Speaker 8:put like a cap on the number of queries you can do that need the server.
Speaker 2:And I But think then the question is like Yeah. Question is you just play it out, play it out, play it out. And how much of a threat 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 And I'm
Speaker 8:so make
Speaker 2:Siri a massive success and there's no ads, and I have gone a year ago, I didn't use ChadGBT for really any product based searches. I just still thought that Google was just objectively better if was 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.
Speaker 2:And so you would expect that Apple Apple's like maybe like two years ish behind or maybe eighteen months behind in terms of AI capabilities. But I could imagine eighteen 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. That is crazy. 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 and sort of cannibalizes like Google search revenue but doesn't even necessarily get Apple that much out of it itself.
Speaker 2:And then 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? And it's usually like
Speaker 8:And and and the Apple monetization for the App 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 Mhmm. You know, 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.
Speaker 8:They take thirty to 15% of every transaction and that should be good enough because you're paying At some level as a consumer you have to assume that you're paying at least a little bit more for everything you buy through the App Store because Apple is taking that commission. 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. Yeah.
Speaker 1:Right? That's
Speaker 8:funny. That's That's so sort of what it feels like with the App Store showing you these ads when you search. It's like, I'm just trying to find a freaking thing. How about you just fix search? Their search still kind of sucks.
Speaker 8:Jordy, I think your big question is what's in it for Google? Why is Google helping Apple here? I think it is from Google's 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. 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.
Speaker 8:And I don't think there's any kind of I mean, is doing AI research. They have AI teams and they're, 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.
Speaker 8:So I think Google is comfortable working with them where well, in a way that they would just prefer to kneecap OpenAI Anthropic. And if there is if Apple was fishing around for a partner, like, we need somebody who knows their shit to give us an LLM back end so that Siri is actually useful. Yeah. And I think Google was willing to cut them a sweetheart deal to say, let's do this, and 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. Right?
Speaker 8:Know Apple. We're not worried. That's that's not going to we'll figure out 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 deterioration to say the least between Apple and OpenAI at a corporate level. But if that had 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 Yes.
Speaker 8:In the answers and it was like a, you
Speaker 2:know Yeah. The whole thing Google being like, okay, we need to help Apple because like, we need to help Apple attack ChatGPT 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 is like, well, we also wanna take we also wanna try to kneecap ChatGPT because they're now building devices, but then it Google and Apple's relationship is just like headed interesting path, and I and I can't I imagine I think they both companies will look back and be like, man, you remember those days where I could just give you tens of billions of dollars and we could just be friends, and then, you know, you play it all out and and it doesn't it doesn't seem as as friendly.
Speaker 8:Yeah, 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? 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. 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 LLM stuff, but there was a paper that came out of Google where they were one of the scientists argued that there is no moat around this technology.
Speaker 8:Right? No one company is really going to own this. And I think it's an open question whether that's true or not. Right? Like the super intelligence hypothesis is that if somebody gets to the breakthrough of super intelligence first, they will That super intelligence will accelerate their AI at a pace that nobody else can keep up with and no one will ever be able to catch.
Speaker 8:I don't think that's where it's going and I don't really You know, it just goes back to what we were talking about half an hour ago with the hugging face thing and chat GPT. And it's like, oh, coincident, you know, and this is what makes people roll their eyes and think it's a marketing stunt. Is then, you know, three or four days later, Anthropic came out with, well, 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 they're even Steven.
Speaker 8:And I think, I I 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.
Speaker 8:Mhmm. You know, Apple's the one big company with no exposure in this bubble. Yeah.
Speaker 1:That's true.
Speaker 8:And I think Apple's bet is back to there is no moat here. If they don't own this technology, that it does it's fine. Yeah. This and I I kind of think it's shaking out that way at least for Apple's business. Yeah.
Speaker 2:Well Last question. And you can answer in thirty seconds. Do you think
Speaker 1:Alright.
Speaker 2:Do you think Apple will make an acquisition of an AI company, could be an acquihire or product, but I'm thinking more acquihire, north of $10,000,000,000. No.
Speaker 1:I think you're just gonna have a 100,000,000.
Speaker 2:Yeah. One Okay. Then let's bring it down. 1,000,000,000. Because there's just not that many there's not that many great teams, to be honest, that you could get for less than
Speaker 1:mean, I bought Siri, that was 100%.
Speaker 2: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.
Speaker 8:Yeah. I I would look at it on the silicon side, and I think because I think that as this gets commodified, I think that, something like the PA Semi acquisition that led to Apple Silicon, that's who Apple, I suspect, is hunting for is somebody who has a breakthrough spitball idea. And again, at this point, $1,000,000,000 probably isn't that much. So something in that range. I I would think hardware.
Speaker 8:Something Yeah.
Speaker 1:If you
Speaker 8:have Apple can do for silicon.
Speaker 1:Yeah. If you have really optimized silicon serving, you know, lagging models that are a year or two old like, the 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 for
Speaker 8:And your ultimately, I think it's why Apple's I ultimately, I think it's why Apple's staying out of the CapEx race Yeah. And building out these data centers.
Speaker 4:It'll just wait.
Speaker 8:The idea of why are we going to spend all this incredible sums of money, all of our free cash flow
Speaker 1:Yeah.
Speaker 8:To build data centers that are going to be completely technically outdated five years from now.
Speaker 1:Yeah. Well, I want to have you back to have a great debate about electron versus native apps. We got to go through
Speaker 8:all this.
Speaker 1: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 and too.
Speaker 2:Out
Speaker 1:there. Thanks so much. Yeah. Talk to you soon. Goodbye.
Speaker 1:Cheers. 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 Shaun McGuire and Isaiah Taylor.
Speaker 1:Dynamic duo. Two guests, third, fourth time on the show. How's it going? What's up, guys? Tell us the new
Speaker 10:Look at you. Nuclear reactor.
Speaker 4:Two We gotta get the eagle scream every time. This is like this is our intro this morning. Exactly. What happened? There we go.
Speaker 2:What happened, guys? What happened?
Speaker 4:$1,000,000,000 series b. Deepest back, baby, with the wind up.
Speaker 2:Crazy crazy moment. Where should we start? Isaiah, you wanna kick it off?
Speaker 4: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 Shaun's partnership in in getting to know this company is he just wanted to know about the hardware.
Speaker 1:Mhmm.
Speaker 4:That's really my favorite type of investor. They're like, show me the stuff. Like, are you actually building things? 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 to meet the Sequoia team and and get to know everybody.
Speaker 1:And this facility, the the you're no longer purely in the Gundo. You've expanded. Where is this facility now?
Speaker 4:So this is our Orangeville, Utah site. Utah. It's our first first nuclear site. Yep.
Speaker 1: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 gonna be generating power? When when do you start building the factory that build the machine that builds the machine?
Speaker 4: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. And but it's still a test unit. And what we're building toward is something that we call a data site.
Speaker 4: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, and eventually all of the industrial stack that has been falling behind in The United States. It depends on energy.
Speaker 4:Aluminum electrolysis, steel, you know, all of the the different input metals to to making everything in the physical world starts on our our giga sites. That's what's coming next and that's really what this raise is is gonna help support.
Speaker 2:Massive. Shaun, 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 and
Speaker 10:different You know, it's not only Valor but there's only one Isaiah, that's for sure.
Speaker 2:Yeah. Yeah. So talk about, yeah, talk about, yeah, what drew and you to the this is like, you know, this is not a series a check. This is a billion dollar check.
Speaker 10: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.
Speaker 10:I have a PhD in physics. I've loved nuclear since I was a little kid. I was hoping that you know, I read Richard Rhodes' Manhattan Project book when I was, like, 17, and I've kind of been waiting for there to be an opportunity in nuclear. Candidly, didn't think it was gonna happen. I thought we were just gonna go like solar battery or solar plus some other storage mechanism future, just given how regulated nuclear was.
Speaker 10:It just didn't seem like it'd be possible to get to scale. And then two things happened. One, like, power became important in the West again, which is, like, pretty amazing. Second, this administration but I gotta say it's, I think, a very bipartisan thing. Both the Democrats and Republicans as power became a bottleneck have been pushing for more favorable, you know, nuclear regulation, and it's starting to happen.
Speaker 10:So even three years ago, I just the the regulatory side was too scary for me. So we've had kind of regulatory breakthroughs with this next generation of founders that are, you know, really trying to bring in this nuclear future. But for me, with Isaiah, there were 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 the day he went critical in this reactor he's in first of all, like, he thought he was gonna go critical the day before.
Speaker 10: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 in an airplane that night to fly to San Francisco to have drinks with, you know, a candidate and the guy's wife. I don't know what time he went to sleep.
Speaker 10:And then the next day he's back in, you know, I think it was Utah, maybe Los Angeles. But, like, getting to know Isaiah, the level of intensity is just absolutely incredible, and candidly, the only person I just I don't know many people that have this level of intensity. And then just one more thing. Something that I learned, like, lesson a mistake I made in the space industry was, you know, Elon started off trying to build the Falcon one, which was a pretty simple rocket relative to, you know, what NASA could do in the, you know, eighties, nineties. It was like a nineteen sixties rocket or maybe even earlier.
Speaker 10:And there were all these other companies that were telling these, like, advanced science stories. We're gonna use carbon fiber, you know, big frames to have, you know, less mass, or we're gonna three d print the rocket.
Speaker 1:Yep.
Speaker 10:So other people were, like, trying to do this very advanced technology to have better mass ratios, etcetera. And Elon was like, I'm going do the simplest thing possible, put up one satellite, you know, get that revenue, and then go from there to something that's, you know, Falcon nine, pretty damn hard, but still not state of the art compared to what NASA had done in, say, the nineties. 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.
Speaker 10:He's the only he's one of the only founders I've ever met ever in any industry that, like, really understands the power of starting with the simplest unit where you can actually scale and and, like, win, and then climbing from there. So, anyways, Isaiah should do the rest of the talking.
Speaker 2:That was great.
Speaker 4:Yeah. I I think that's one thing that Shaun 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 they want to find this sort of, like, IP technical edge where you're doing some special sauce that that nobody else is doing. And my approach is like, no. Like, we want this reactor to be as simple as we possibly can.
Speaker 4:Like, if we could just staple this thing together from IKEA, then this would be a trillion dollar company much faster.
Speaker 1:Mhmm.
Speaker 4:And so there's like two two philosophies that we use in in building the reactors. We try to buy things that are completely off the shelf, like a 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.
Speaker 4:Because if you think about it, we're trying to go a 100 times faster than the nuclear industry's ever gone before. And so if we're plugging too deeply into the existing network, it's not gonna work that well. So we wanna use standard off the shelf things and and make things ourselves where we can't buy something off the off the shelf. And by necessity, means the design the design is extremely, extremely simple. The more complexity you add to it, the harder it is to do one of those two options and the harder it is to scale.
Speaker 4:So, you know, I think especially in nuclear, this is a difficult thing because it's 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 to design something that is, like, complicated and looks very sophisticated. And we have just really rooted that out of our our minds at Valor.
Speaker 4:Like, we work extremely hard to root that mentality out. Like, it's it's our preference that this thing is so simple that somebody with nuclear PhD looks at is, 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.
Speaker 4:And that's exactly what we wanna 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.
Speaker 4:Just like completely remove it. It doesn't even exist in our in our bomb. So those are the the philosophies we've we've taken here. And, yeah, like, listen. I can't give enough credit to Shaun in particular and also the
Speaker 10:No. No. This all Isaiah. This is this guy's building nuclear reactors. I'm wiring money.
Speaker 10:Like, get out of here. I gotta give a couple shout outs, though. I gotta shout out Palmer Lucky Yeah. Who gave me the hat tip that this is a special company. Thank you, Palmer.
Speaker 1:Yeah.
Speaker 10:Hat tip to Liam Corrigan, know, newest investor at Sequoia, who was my wingman here, physics guy Yeah. Road scholar, Olympic gold medalist rower, six five Chad.
Speaker 4:Total Chad. Total Chad.
Speaker 10:Chad. And Max Eucoprina, 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. Was like, oh, dude. Nuclear is too hard. Regulatory is not favorable.
Speaker 10:And anyways, Max, I look stupid. Good job.
Speaker 2:How Isaiah, how have the have there been talent wars in in nuclear? You know, you're flying on 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? Imagine will give you a lot of advantages just having, get more firepower to to continue compounding a great team. But walk us through the last maybe two years in the category.
Speaker 4:Yeah. Look, I I view my job essentially as trying to get the most talented people in the world to come and build this mission with me. There there are no blockers in in front of us. Like, we we have a regulatory environment that's ready to move. We have an enormous demand signal.
Speaker 4:We have customers that wanna 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, you know, $10.50, $100,000,000,000,000 company that makes most of the world's energy is the smartest people in the world coming and and joining us in this mission. So I spend an enormous amount of time and of my time doing that.
Speaker 4: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 I don't don't see it as sort of like, okay, other nuclear companies. It's it's more like, you know, what are the other companies that are genuinely going to change the force of humanity in the next fifty years? And like, those are the people that that I'm fighting for.
Speaker 2:Mhmm. Yeah. That makes a lot of sense.
Speaker 1:Lessons from I'll just say Yo. Sorry.
Speaker 10:Hey. 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 gonna be in someone says, like, hey.
Speaker 10:I wanna 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.
Speaker 10:And if they don't make it to Texas, then they're weeded out. It's just not having that level of, like, 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.
Speaker 1:High agency.
Speaker 4:Yeah. Yeah. Revealing the secrets here, Shaun.
Speaker 10:I know.
Speaker 4:Now the next now the now the next three are gonna show up to the meeting and I'll have to figure out some some other way to weed them out. But yeah, that's that's very true.
Speaker 10:If they show up, it's still a good
Speaker 4:it's true. It's just still a great sign.
Speaker 1:Lessons from SpaceX. One of the interesting
Speaker 2:Yeah. I I can imagine. Yeah. Sorry. I got a dentist appointment in Utah of all places.
Speaker 2:I gotta get out there. It's like this about, you know, people being like, yeah. Got a dentist appointment.
Speaker 10:I have to take three commercial flights, know, and drive three hours to get my to my dentist appointment. Yeah.
Speaker 1: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, Shaun, you'd know.
Speaker 1: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's, like, is very, very unlikely to happen?
Speaker 4: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.
Speaker 4:Right? I I watched I read everything that I could about the Falcon one and the Falcon nine and saw this very simple path that you just call it flight rate. I think it's SpaceX. We call
Speaker 3:it tick rate. Tick rate
Speaker 4: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 cores turning on. And it is predictive of who's gonna win, who's gonna have the lowest cost and the highest capacity, 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?
Speaker 1:Yep.
Speaker 2:And I
Speaker 4:think that the AI thing happening as quickly as it did and power prices changing so dramatically where people will sign a $200 PPA is like, obvious that we should sell electrons.
Speaker 1:Yep.
Speaker 4: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.
Speaker 4:I think, like, we want to be in the 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 in the world thinks that.
Speaker 1: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 Exactly. If we were in some boom where we need everyone in their pocket needs twice as much energy, you would have to Yeah. Maybe transform into another source of energy or do something else in the supply chain. Shaun? Did you have something?
Speaker 10:I no. I agree. I concur. Byline
Speaker 1:agreement. Fantastic. Yeah. Well, thank
Speaker 2:you so much.
Speaker 1:Yeah. Well Honestly,
Speaker 2:I was
Speaker 1:just gonna
Speaker 4:say that's the the AI the AI thing, like, perfectly matches gigasites. Yeah. Right? Like, the the the idea is nuclear is a thing that benefits from extreme scale. Yeah.
Speaker 4:Like, you could build a thousand nuclear reactors right next to each other, you should. Like, you will get the cheapest energy anywhere in the universe if you do that. Mhmm. And so AI is, like, the the perfect thing to do with that first. But we will do many, many things with it over the next century.
Speaker 1:Well, congratulations. Thanks for having us.
Speaker 2:Excited for you guys to partner up. We'll talk to
Speaker 10:Thanks your fun. Peace.
Speaker 2:Goodbye. Alright. Cheers. Bye.
Speaker 1:Let me tell you about MongoDB. What's the only faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it.
Speaker 1:We're going back to back energy rounds Back to back. With another back to back billion dollar round. We have Justin Lopez from Base Power Company. Justin, how are you doing?
Speaker 3:Good. How are doing? Good to see you.
Speaker 1:Good to What see happened today?
Speaker 3:Raised raised a bunch of money and
Speaker 2:Not just a 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 wanna talk about the news under the headline from today.
Speaker 3:Yeah. So welcome to Factory One. Good to see you guys. Thanks for having me on. Today, we're announcing three different things.
Speaker 3:Number one, launch of the factory that I'm sitting in right now. It's behind me that builds batteries. Number two is $1,000,000,000 raise, a $13,000,000,000 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.
Speaker 3:We manufacture them here. We haul them on homes, and then we own and operate them as a distributed fleet, distributed power plant. That's the business today.
Speaker 2:Incredible. Talk about the decision to not announce the factory or talk about the factory very much until it was actually producing products.
Speaker 3:Yeah. You know, it's like I I 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.
Speaker 3:But, like, factories are meant to make stuff, and Yeah. We wanna make stuff beforehand. We're we're doing that today. We're just getting the line ramped up. The the station behind me is starting to build some modules.
Speaker 3:You'll see some come through as we talk here. But yeah. Look. You wanna have you wanna have the real deal ready before you talk about it.
Speaker 2:That's right. And when did you when did you guys actually break ground on this site? Because I imagine
Speaker 3:So the site 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.
Speaker 3:Previously, we had a smaller facility just north of here in Austin, but, yeah, we're we're we're live and running now.
Speaker 2: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 what people can expect from base over over, you know, the next couple years in terms of new markets and things like that.
Speaker 3:Yeah. So as I mentioned, look, 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 new utility partners, hopefully, by the end of this year as things get signed and and under contract.
Speaker 3:And it 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, they require deals with utilities. So we have two go to market motions, regulated and deregulated. Both work in various different states in the country.
Speaker 3: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.
Speaker 2:Alright. As a if somebody's a homeowner in Chicago or Austin or Texas broadly, give us the the elevator pitch for why they should install
Speaker 3:Yeah. Look. So we we make your power more affordable and more reliable. So if you're in a place like Houston or Dallas where you can choose your power providers, you sign up with us. We sell you electricity every month at a very affordable rate.
Speaker 3:We also put a battery on your home that is only typically a few $100 depending on exactly where you live. That provides you backup protection if the grid goes out and also supports the grid when the grid's 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.
Speaker 1: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?
Speaker 3:That's exactly right. That's basically how it works.
Speaker 1:K.
Speaker 3: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. Typically happens, you know, in the dead of winter and in the height of summers.
Speaker 1:Okay. What 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.
Speaker 1: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?
Speaker 3:Yeah. So you're you're exactly right. Basically, what you care about is the difference between available capacity or supply
Speaker 1:Yeah.
Speaker 3:And the amount of demand. Yeah. 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 kinda like, you know, four to 6PM, 5PM, 7PM where the sun is setting. So supply is coming offline, but people's people are coming home, plugging in their EVs, turning on their air conditioners, etcetera.
Speaker 1:Got it.
Speaker 3: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 Yeah. And they're on throughout the night, but the sun hasn't risen yet.
Speaker 3:And so batteries help fill those gaps. That's at the macro level. And then at the 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.
Speaker 3:In this neighborhood, we need some support. We're gonna discharge just in that neighborhood. And that's the beauty of having a high volume of systems.
Speaker 2:Mhmm. 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 do to figure out the sort of process using a lot of, yeah, your your, human talent. But, where are you guys getting the most leverage and and how how automated can this become over time?
Speaker 2:Can it become, you know, lights out factory? Is that even something to aim for? But what's your view on all that?
Speaker 3:Yeah. You know, robotics is a great 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.
Speaker 3: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 gonna automate those as a starting point. We're gonna 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 just it's a I'd say it's a it's a it's a phase in approach.
Speaker 3: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 it, and then you automate it.
Speaker 2:What's the
Speaker 1: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.
Speaker 1:Grids and energy providers have been working on this 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?
Speaker 3:So it's huge in the sales process. Right? People wanna have more affordable and more reliable power. Yeah. The reliability is different from from place to place.
Speaker 3:So typically, coastal regions, so we think of the Texas coast, Florida, the East Coast, etcetera, where you have a of hurricanes, you typically have more power outages.
Speaker 1:Okay.
Speaker 3: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 Oh. Is is gonna cause you to have an outage. And so if you have more line in front of you, basically, you have typically a lower reliability. Yeah.
Speaker 3: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 a tree falls onto a onto a power line, etcetera, because of a storm. But but outages are rising generally across the country. There are places where they're getting better.
Speaker 1:Okay.
Speaker 3: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 rely 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, etcetera, on the grid.
Speaker 2:Got it. Got it. Absolutely crushing.
Speaker 1:My my last question is, what 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 yeah. I mean, you're growing the business and the factory and like there's there's immense scale, billion dollars raised, $2,500,000,000 raised. And yet geographically, it feels like a little small. It feels tight.
Speaker 1:Sometimes you have companies that are, yeah, we're available in every market and all over the globe. We'll ship our thing everywhere 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?
Speaker 3: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
Speaker 1:most. Yeah. That's true. Good point.
Speaker 3:Got more more homes and more electricity load than than than many large company countries that you've heard of in Yep.
Speaker 1:Okay. Fair. Fair.
Speaker 3:So so Texas is a big place regardless. I'd say the the geographical tightness is a feature, not a bug.
Speaker 1:Okay. Yeah. Yeah. Course. Of course.
Speaker 3:The reason for that is, like, not only do we have a factory behind me that produces these things
Speaker 4:Yeah.
Speaker 3:But more importantly, we have a factory in the field. We've got hundreds of people out in the field installing these things.
Speaker 1:Okay.
Speaker 3:And we've got trucks and crews and tooling and all this other stuff. And so having geographic density is very helpful from an efficiencies. 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. Yep.
Speaker 3:Places in Texas, not all of Texas.
Speaker 8:Mhmm.
Speaker 3:And then there are there are markets like you have in California where Yeah. For the most part, especially in residences, you cannot choose
Speaker 2:your power provider.
Speaker 3:If you live in Northern California, PG and E is the only game in town. If you live in Southern California, it's self gallivistic or LADWP or or other utilities. And so in the deregulated markets, we can essentially go there and start the business. And 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.
Speaker 3:It's a b to b sales motion where we go to utility and say, hey. We offer megawatts as a service. Yeah. 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.
Speaker 3: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, b to b sales, long sales cycles and and working with both the regulators and the utilities in that state
Speaker 1:Got it.
Speaker 3: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. Yeah. And then the and 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, ten, fifteen, 20 states over the next few years just because, again, the geographical density is so helpful for us.
Speaker 1:Yeah. Yeah. And, of course, like, you you only have so much manufacturing capacity. You have to load balance your own business across your salespeople, your installers, your manufacturing capacity, your supply chain, all of this stuff. That makes a ton of sense.
Speaker 1:Well, congratulations on the progress and thank you so much for coming on
Speaker 2:and Massive.
Speaker 1:Sharing it with us.
Speaker 2:Love seeing you guys cook.
Speaker 1:Yeah. Amazing work.
Speaker 2:Awesome. And thanks for the thanks for effective the factory Yeah. That is remarkable. Know. We'll we'll come by next time we're in town.
Speaker 1:Yeah. That'd be awesome. We'll talk to you soon. Cheers.
Speaker 2:See you.
Speaker 1:Goodbye. Let me tell you about the New York Stock Exchange. Wanna change the world? Raise capital at the New York Stock Exchange.
Speaker 2:Just do it folks.
Speaker 1:I think we have to issue sort of like 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. Bo, Gaston. On.
Speaker 1:Welcome to the show. How are you doing?
Speaker 6:Great. How about you guys?
Speaker 1:We're doing well. Talk 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.
Speaker 6:Yeah. Sure. So the full timeline, a very high level. Started about six years ago. A paper comes out of MIT where a guy and Pat made this quasi direct drive actuator.
Speaker 6:Quite cheap. Think it's about $700. 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 he open sourced the design as well. So I'd seen back then, it kinda looked like it was gonna become possible to build humanoids a few years in the future that are not, like, only affordable to to a huge lab. Right?
Speaker 6:So around 2022, I start to take on this design that you see in in the background. What I wanted to do with it was really make a robot first for myself. And what what what I would like to do with the robot is, you know, not do the dishes or fold my laundry as
Speaker 1:a You want this thing to do the dishes?
Speaker 2:Can we just No.
Speaker 10:No. He's saying
Speaker 2:he doesn't care about a robot that will do the
Speaker 1:Oh, okay.
Speaker 6:Yeah. Seems like he wants software update. Sure. Sure. I wouldn't try that quite yet.
Speaker 6:Okay. My kind of thesis is it's gonna be more useful to have something that's stronger than you at first, and maybe you could sacrifice some precision and intelligence. Right?
Speaker 1:Sure. Sure.
Speaker 6:Yeah, running a chainsaw, I get that people have thought like, wow, this is crazy to give a robot a chainsaw. It's, you know, a bit scary. But I mean, what's really scary is operating a chainsaw as a human. Yeah. I kinda looked at that, you you know, which is something I'm well familiar with living out here in the woods.
Speaker 6: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 it's a 130 per 100,000 workers per year. It's 30 times more dangerous than the next most dangerous job. Wow.
Speaker 6:And, yeah, I I mean, you could imagine, not only is the chainsaw dangerous as a tool, but what trees are you cutting down? The ones that are damaged, their power lines, ones that are next to a fire break in wildfire. So it's just a preposterous kind of situation. Looking at what robotics is needed do.
Speaker 2:Form the use case makes total sense.
Speaker 1:Yeah.
Speaker 2:Mhmm. I'm curious to get into a couple questions. We should start with Sure. I think what everyone's wondering is why make it look like, you know, a demon from from Hades. Yeah.
Speaker 2:Yeah. Especially some of these disaster use cases, you know, was thinking I've been in situations where I've never been like really really really close to a to a But I've been close enough where the sun is gets a little bit, you know, blocked and it's dark and a little hazy. And and if I saw one of these things, you know, kinda walking out of the smoke, I'd be I'd be a little freaked out. And I think a lot of people might feel that way. But but yeah, so so talk through the decision making on making it look demonic and then and then I really want to understand like the actual functionality of the form, which we can get to.
Speaker 6:Yeah. Sure. So I will say yeah. The the rescue stuff also was kind of propagated by the the virality a little bit. That's definitely I was not aiming to pick you up out of a burning building, you know, like a hero in a movie.
Speaker 6:Though I would point out if that did happen, like, you know, if someone's saving you, I'm not going to probably be too picky and Yeah. Don't look like
Speaker 1:a gift. Think the mouth. Yeah. Yeah. Exactly.
Speaker 1:You you just don't
Speaker 2:do it. Yeah.
Speaker 6:But, you know, it's interesting with the anthropomorphic stuff on humanoid robots. I think it's actually really disarming, and people kinda aren't understanding what's really going on under the skin, which you can see a little bit here. Yeah. I don't know. Like, have you guys ever used a drill press?
Speaker 1:Yeah.
Speaker 6:Okay. So you kinda know they're dangerous and, you know, the workpiece could fly out of it, and they got a lot of torque. So imagine if someone hooked 20 drill presses up series parallel altogether 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 that's around the same power that you're seeing on on leg actuators on That's most humanoids
Speaker 2:crazy. Yeah. Where you're going is basically like a humanoid itself looks tame but in reality it's potentially incredibly dangerous to be around.
Speaker 1:So it's better to let people know. You're putting like caution tape on it effectively
Speaker 6:100%.
Speaker 1:Telling the user, hey, this thing has a chainsaw. It's going be doing work in a dangerous environment. You should be triggered to say, hey, I got to step back because this is serious business.
Speaker 6:Exactly. Like, yeah. 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 Yeah. That's kind of the right attitude to take when you're Interesting. Around something that can knock your head off.
Speaker 5:So Interesting.
Speaker 6: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 vet it. Yeah.
Speaker 2:This is So do you do you think that
Speaker 1:That's the mission.
Speaker 2:Do you think you'll end up redesigning it? Because if you wanna just show that at least at least like the head, because if you wanna just show that it's dangerous, you could just have it, you know, maybe a speaker or a light that says like, you know, stay
Speaker 1:Caution tape or You
Speaker 2:know, hazard besides besides the horns. Even though clearly clearly it sounds like They weren't. You just wanted to make this. Sounds like you live in the woods. Sounds like you want a few of patrolling around your house.
Speaker 6:Yeah. I I mean, I think the other thing about humanoid robots, like, we all kind of know that they're not purely like a perfect productivity maximizer device. Right? Like 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 kinda like a car.
Speaker 6:Like, no one buys a car because it's the perfect, like, mobility blob with no personality that, you know, is exactly as safe as you want. Yeah. Maybe a few people do, but, you know, humanoid robots, 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, yeah, it's just not as exciting.
Speaker 6:We gotta keep it interesting. Right?
Speaker 2:Yeah. I get it. And I'm sure there's I'm sure there's people out there that wanna 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 weight.
Speaker 1:One leg?
Speaker 2:Sorry. Two. Two.
Speaker 6:Two. One leg is really tough.
Speaker 1:One leg. One leg. Pirate robot is the next.
Speaker 2:No. Four legs versus two legs. I imagine if you wanna be able to actually manipulate like something like a saw, you wanna be able Unstable. Having the stability Yeah. But also the terrain.
Speaker 2:Yeah.
Speaker 1:You wanna be on wheels?
Speaker 2:Seen and stuck. 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 and
Speaker 1:I'm I'm all in on centaurs. Let's hear it though.
Speaker 6:Alright. Yeah. I mean, bipeds are tough. You have to move the center of gravity up for the whole bot, right, because you're putting the pack up in the human chest or I have it in the horse body. Mhmm.
Speaker 6: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 Mhmm. You know, if you have a linear actuator than a moving shaft, like, right on the ground Mhmm. Whereas this thing, you know, the closest actuator is is nearly three three feet off the ground
Speaker 1:Mhmm.
Speaker 6:The way I'm driving the knee. It's easier, you know. I I'm not a this is not a huge project. I think another kind of misconception from the viral explosions, like, for some huge stealth startup that's popping up and these things are gonna go knocking door to door. But now this is more of a passion project, so doing a biped today is is really tough.
Speaker 6:You're not gonna see all but, you know, the best people doing and even then I'll point out, there's of course a lot of curation for what you see with pipettes from from anyone. I think everyone kinda knows that. They're pretty tough to to get stable. And and 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 gonna have to have some suspension, which is kind of the enemy of robotics is having these unknown spring forces and stuff like that.
Speaker 6: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 packed grounds, it's actually could still be a little tippy. So, yeah, four legs works pretty well.
Speaker 2:Yeah. Have you gotten any death threats since the viral moment?
Speaker 1:He's got a robot army at his disposal.
Speaker 2:I imagine some people might might think now is the right moment before you have, you know, a 100 of these on your property. The crazy ones.
Speaker 6:I guess, though, the few people that were offended by the design are are Christians, so that, you know
Speaker 1:Oh, sure.
Speaker 6:Peaceful people. So, you know, fortunately, I've had, you know, people say I should stop or Mhmm. You know, that it's someone sent me an email today that said my company is now owned by God Mhmm. Who will save me and stuff like that. But no, nothing too crazy.
Speaker 6:The more surprising reach outs have been police departments. Oh. That is what I wouldn't have thought would have happened, but
Speaker 1:reaching out to partner with you or arrest you?
Speaker 6:Yeah. To ask if it could be used for public safety.
Speaker 1:Okay. Yeah.
Speaker 2:Yeah. No. I do That that if you've ever been in an at an event where a bunch of police cavalry horses. Yeah. And then there's just like
Speaker 1:People just dissipate. Yeah. Yeah. Because there's something about being around a large horse where it just doesn't
Speaker 2:No. Was gonna say the species. Oh, okay. That that gets
Speaker 1:I hadn't even thought about that. Yeah. I I just think for for riot control, the the 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.
Speaker 2:The chat wants to know about the pogo humanoid. There is one. Pogo stick.
Speaker 1:There is one.
Speaker 4:There is one.
Speaker 6:Yeah. There's at least one. Yeah. Look, yeah. If you search
Speaker 2:scarier format where the can jump 30 feet in the air and it's just
Speaker 1: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 teleoperation. 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?
Speaker 1: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?
Speaker 6:I got a solution for that.
Speaker 1:Okay.
Speaker 6:Let's see it. Let's see if we could see. No one's seen this chainsaw, so I
Speaker 1:guess you guys could ask. There we go.
Speaker 6:Yeah. Do it on your show, but Thank you. There we go. Okay. So this chainsaw is two degree of freedom, you know, kinda like a let's see if I can wind it up a little better.
Speaker 6:You can kinda see what's going on. Yeah. Yeah. Yeah. I gotta go this way.
Speaker 6:My thing's mirrored. Yeah. But, yeah, it's something I thought about. So, yes, it's think about like this. Like, you have you could split robotics into moving around and doing something with the end effector.
Speaker 6:Yep. And the the good thing about a quadruped is, you you could kinda park it and then the hips have enough mobility where you could kinda control it almost like it's an excavator if if you ever been in one of those. So Okay. It's a little bit more intuitive to do than trying to do something like dynamically like you see, you know, people with VR goggles and
Speaker 1:Yep.
Speaker 6:Gloves to control a humanoid that has hands or a biped and all that. That's again, like, way way outside what I'm able to accomplish. So you can think about it more like you're driving a big car that keeps its hips square to the ground and then the top half kinda acts more like it's an excavator.
Speaker 1:Yeah. Where you're
Speaker 6:kind
Speaker 2:of Do controlling it on two you think there's more of a consumer market for robotic horses? A of people out there that love horses, but horses are 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 some consumer market for it.
Speaker 6: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.
Speaker 6:Would you buy one?
Speaker 2:I think I would I think I would potentially get one for Oh, yeah. For my daughter. Yeah.
Speaker 6:Oh, not to, like, commute in?
Speaker 2:The the robo horse commuter galloping to work, if you could get it up to, 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.
Speaker 6:Catch that. Like an angler fish head, you're thinking?
Speaker 2:I'm thinking more like a normal horse.
Speaker 6:Oh, okay. I haven't thought about that.
Speaker 1:Well, thank you so much for coming on the show and breaking it down for us. Sure. Good luck with wherever this project goes. We'd love to stay
Speaker 2:keep us updated. Keep us updated. I will say when when John showed me the website, I said this is clearly somebody just messing around that vibe coded a site.
Speaker 1:I love that it's a real thing.
Speaker 2:It's amazing to see.
Speaker 1:Yeah. Yeah. It's it's gonna be amazing to see where this goes. Congratulations and thank you so much. We'll talk to you soon.
Speaker 6:Have a good one.
Speaker 2:Have a good Cheers, bro.
Speaker 1:Next, have Ron Yarrell from Intology. He's the co founder. And we're talking about RSI, Recursive Self Improvement. Is it here? It might be.
Speaker 1:We'll get his take. Ron, how are doing?
Speaker 9:I'm doing well. Thanks for having me
Speaker 2:on, guys.
Speaker 1:Thanks for hopping on. First time on the show, why don't you introduce yourself and the company a little
Speaker 9:Yeah. Of course. 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.
Speaker 9:Mhmm. So, today we have some pretty exciting results to talk about regarding automated post training of other language models. Yeah. And lots more to discuss, so glad to be on.
Speaker 1:Yeah. Awesome. How would you characterize the the progress, the announcement? Because people can get sort of lost in benchmarks. Are you 20% on this thing, 99% on that thing?
Speaker 1:Like qualitatively, where do you see the technology today?
Speaker 9: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 you know, no matter what problem you're looking at, like, you know, drug discovery or materials discovery, even, like, improving language models, there's always gonna be some sort of process of proposing an experiment, getting feedback from that experiment Yep. Learning from that experiment, then using that information to propose the next set and continuing until you, you know, make the discovery.
Speaker 9:Yep. So it's a, you know, great question because, you know, 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?
Speaker 9:So it like, if you're trying to build an automated research system that, you know, develops the next state of the art, you know, 70,000,000,000,000 parameter model or whatever, you know, you can't really imagine a system training 15,000 models until it discovers the the the best one because training is expensive. So, you know, you have to think about how do you run efficient experiments, how do you gain knowledge, gain information from those experiments better. And I think that's, you know, today we're showing kind of a closer step in that direction because, know, in the past, we were doing things like kernel optimization, you know, like MLE bench style problems, now post training where, you know, obviously, it's more expensive and takes longer.
Speaker 1: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, you know, front the cost or is there another way to solve it?
Speaker 1:Because scale seems very important here, and yet your whole job feels like burning compute.
Speaker 9:Yeah. So definitely a little bit of both. Okay. I would say at the beginning, it was a lot of burning venture capital money.
Speaker 1:Sure.
Speaker 9: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.
Speaker 9: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, you know, I feel comfortable throwing, you know, hundreds of thousands of dollars at the wall if we feel like the system can actually make progress.
Speaker 1:Gary Marcus. He says that it 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 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 testing in vitro testing in mice and in monkeys and humans.
Speaker 1:There's just things that the verification loop isn't just run some lean really quickly and see if it checks out, right? So how what do you see the future of transferring all the amazing learnings and the ability for AI to make discoveries in ML, in computer science, in math to anything that's a little bit less verifiable?
Speaker 9:Yeah. For sure. So I think that it really just comes down to I mean, so we focus on verifiable domains, but Okay. I think it really just comes down to, you know, how much you can actually query the evaluator. Right?
Speaker 9: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 Mhmm. 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.
Speaker 9: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 difficulty, it's almost like as a forcing function of compute availability or cost Mhmm. You start having to think like, okay.
Speaker 9: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 wanna test a drug. It's almost like a nature of the research direction. And so I guess that I 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 and a 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.
Speaker 9:I I don't think I view it as, like, black and white as we are only doing verifiable and then we're gonna go to unfair viable domains and, like, Interesting. Figure it
Speaker 1:I have one more question. Jordan, do you have anything?
Speaker 2:Yeah. I was just gonna ask, what do you what do you think your business looks like two years from now? I won't say five or ten, but, like, where where where is this work going?
Speaker 9: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, you know, autonomously perpetually. Obviously, we're, you know, we're we're quite far away from that.
Speaker 9:Right now, you know, 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 wanna be at the point where, you know, our system can basically be deployed as infrastructure in any computational r and d problem, and then it, you know, it gets access to the data on the problem. It gets access to the ability to run experiments on that problem, and then it gets deployed in an environment in which it's, like, you know, hard to hack and you're getting good signal out of the experiments.
Speaker 9:And then boom, you know, runs autonomously. It's 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.
Speaker 1:Last question. Very cool. Tell us a little bit about the company, where you're based, how big is the team, who are you hiring?
Speaker 2:What you were doing before this?
Speaker 1:Yeah. You're I like this. Shape of the company.
Speaker 9: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.
Speaker 9:We're, you know, we're we're growing pretty quickly. I've been really proud of the team we've been putting together. I mean, we have researchers, you know, coming from DeepMind, Anthropic, Factory AI
Speaker 2:Wow.
Speaker 9:Both in, I guess, industry and in academia. I think this is, like, a really, you know, 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, you know, it's the whole stack, and we've been putting a pretty incredible team together to do so. And I guess before this, my cofounder and I ran a a pretty large nonprofit research group.
Speaker 9:We were primarily funded by the National Science Foundation. Obviously, very different from running a, you know, a company nowadays. But we did a lot of fundamental research in, like, 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, you know, 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, you know, this is the time, this is the place, let's make it happen, that's what we're doing in Ontology.
Speaker 1:Yeah. Thank you so much for coming on the show.
Speaker 2:I'm sure you'll be back on soon.
Speaker 1:Have a great rest of
Speaker 2:your Very cool update. Well, nice you. Goodbye. Cheers, Ron.
Speaker 1:Let's go to this Paul Graham post. He had such a wild experience as he bought 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 door.
Speaker 2:I know someone that will rip it apart, feed it to a machine, and burn it. Know someone I don't know them personally, but I know they they would They love. They would love to to take this off your hands.
Speaker 1: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 the worst book I have found. It's such a funny such a funny, like, just like, I don't know. If it say, it feels like a Curb Your Enthusiasm episode or something like that.
Speaker 1:Anyway, thank you so much for tuning in to TBPN today. We'll see you tomorrow at 11AM Pacific. Leave a spot for us on Apple Podcast at Spotify.
Speaker 2:It's been an honor.
Speaker 1:Sign up for our newsletter. Tbpn.com. Goodbye.