TBPN - AI Is Coming for Your Memes, Axios NPM Package Compromised, Claude Code Source Code Leak | Alex Pruden, Qasar Younis, Sebastian Mallaby, Forrest Heath, Dino Mavrookas, Will Ahmed, Jannick Malling, Ryan Daniels, Chris Yu

Starting point is 00:00:00 You're watching TVPN. Today is Tuesday, March 31st, end of Q1, 2026. Boy, we're live for the TVPN Ultradome, the Temple of Technology, the Fortress of Finance, the Capital of Capital. Let me tell you about ramp.com. Time is money. Save both. Easy to use corporate cards. Bill pay, accounting, and a whole lot more. All in one place. Yay! I got a new sound cue. I know. You were pulling for me. Dangerous. I got three now. Dangerous. I got three now. Watch out. I'm not going to go too crazy. I'm not going to overdo it. We've been there. We learned. We changed.

Starting point is 00:00:30 We evolved. We became better as people. As did our linear lineup, we have a banger show. Let's pull it up. Linear, of course, is the system for modern software development. 70% of enterprise workspaces on linear using agents. Alex Pruden. Yes.

Starting point is 00:00:42 Coming in from Project 11, going to be talking about Google's quantum news. The crypto quantum crash. Say that three times fast. Crypto quantum crash. Then we have Kacer from Applied Intuition. Yes. Very excited to catch up with him, an absolute dog. Then we have Sebastian Malibi

Starting point is 00:01:01 releasing his new book, The Infinity Machine, an insider account of deep mind. Tyler's got it pulled up right there. Super Intelligence. I'm a huge fan of Sebastian Malibai. You might have read more money than God. You might have read the power law,

Starting point is 00:01:15 the history of Silicon Valley. It's the definitive count of how venture capital became what it is today. Highly recommend that book. This is a very interesting departure from that because it focuses on a single person, it's a biography,

Starting point is 00:01:27 not a history of an entire industry. but very excited to talk to Sebastian Alibi. And then we have four us from Somos, raising a $40 million round. Then Dino from Serronic, Will from Woop, Janick from Public, Ryan from Crosby, and Chris U. He's working on a spin-out from Rivian. Very exciting. Already has a billion-dollar valuation.

Starting point is 00:01:48 There we go. Well, friend of the show, our president here at TVPN, Dylan Aberscato, headed to the TBPN newsletter, which you can sign up for at TBPN.com. wrote a fantastic essay, summarizing a trend that we've been discussing with him around

Starting point is 00:02:05 how AI is changing meme making. And I found it very interesting. I'm glad that he wrote this piece. And so we'll read through this and then discuss it, debate it, and see where we can take it further. And then obviously...

Starting point is 00:02:17 And Dylan's from Long Island, New York. So John is going to be... I'm going to do it in a Dylan Aberskato impression of the voice. Memes are changing. That became abundantly clear during the Oscars a few weeks ago.

Starting point is 00:02:32 When Conan tried to create a new Leonardo de Caprio memes, I don't know what accent that was. That's just like UFC announcer to go alongside the classic Leo memes. In doing so, especially by using TFW, that feeling when, and the blocky white font

Starting point is 00:02:49 that defined early internet memes, he inadvertently demonstrated that the meme templates millennials grew up with have become increasingly stale, even cringe. It's a good point. Instead, AI-generated videos are the new meme template that every network and studio should be focusing their launches on. Look at what happened. Look at what's happening with the Harry Potter reboot.

Starting point is 00:03:10 When the trailer first dropped, the reaction to the new Snape played by Ghanian. Ghanian. Ghanian. He's from Ghana. Ganean. English actor, Papa Isidu, was predictably and unfortunately negative. According to the L.A. Times, he received death threats since being cast in the new role. But after a few incredibly viral and well-produced AI videos, one, an original Snape versus Black Snape MMA match and another AI-generated rap video and another Dripworts, the school of Drip, the narrative has started to shift. Have you seen any of these? I think I've seen drip warts, but can we pull up the original, the quote-unquote original Snape versus Black Snape M&MMA match? Because I have not seen this one. And I think it is illustrative of what to be.

Starting point is 00:03:58 Dylan is talking about here. Snape v. Snape in the UFC ring. While we pull that up, let me tell you about Plaid. Plaid powers the apps used to spend, say, borrow, and invest, securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. And let me also tell you about Restream, one live stream, 30 plus destinations. If you want to multi-stream, go to Restream.com. So let's take a look at Snape v. Snape in the UFC ring. Any luck? Here we go. I just dropped it in. Cool. And we have a few others here. The videos have amassed tens of millions of views, and on Dylan's timeline, at least, sentiment around both the character and the reboot has been a complete 180.

Starting point is 00:04:35 Here we go. Really photorealistic. Does this, are there any red flags here as a UFC enjoy or does this feel like a proper UFC? I'm in the actual video quality is insane. He's so bulky. The video quality is insane. Wait, but Old Snape won. In the fight?

Starting point is 00:05:01 Yeah. Okay. But I think it just, I, okay, wait, how, how do you know that? I think it just sort of like makes the characters more entertaining, more fun, shows you that this is just creativity at the end of the day. This is just, like, you should not be so up in arms about something that's a movie. Like, it's entertainment, and here's some more entertainment.

Starting point is 00:05:25 And so you're adding entertainment to the discussion, and people are enjoying that. There's another AI generated rap video about the new, Snape, which we can pull up a little bit of here. AI meme videos are inherently viral and driving real awareness in a way traditional memes no longer can, not just because they're novel and more entertaining, but because a single AI clip can travel further and compound harder than traditional meme formats and social feeds that now heavily favor video. This suggests, yeah, that's interesting. On X, it's still very easy for an image to go viral, but if you think about, you know, Instagram, YouTube,

Starting point is 00:06:00 like a standalone image just can no longer actually get that. escape velocity. I mean, what about dripped out Pope? Remember that? Yeah, a little bit, but people are just spending so much time in the short form feeds. And there can go in there, but there's certainly...

Starting point is 00:06:19 Yeah. Yeah, I mean, I guess even some of the dripped out Pope, or what was it? Was it Valenciaga Pope? I don't remember what the name was. Dylan says, this suggests a new playbook for marketers, especially in entertainment. If you're about to drop a trailer for a new movie or show, you need to be thinking about your rage bait character, the one people will latch onto, remix with AI and build around. Conan tried to force a Leo meme down our throats at the Oscars.

Starting point is 00:06:45 Didn't see that because I was sleeping. But this might have worked 12 years ago. That playbook is over. Today, in rage fans and communities will, if you're successful, take your characters or moments and turn them into something much bigger, entire cinematic universes. Yeah. I'm just very impressed by the overall quality of, you know, of those outputs.

Starting point is 00:07:05 The Oscar selfie, I remember this. I think became the most liked image on Twitter at the time in 2014, briefly. That image, this is the canonical clout bomb. If you're a fan of Bradley Cooper, you like it. If you're a fan of Merrill Streep, you like it. You're a fan of Brad Pitt, you like it.

Starting point is 00:07:23 And so you're amplifying all of it. The ultimate collab post. And this has become a format that's been used time and time again. It's effective. We did a little bit of it at the Super Bowl. That's fun. It works. But now the future is AI. Let's pull up the DripWartz School of Drip Video. I want to watch this one because I saw a clip of this. I didn't see the whole thing. Let's see if we can play this.

Starting point is 00:07:48 That's Harry Potter. Are you really Harry Potter, my G? Shh. Type shit, type shit, type shit. Type shit. None of that, none of that, broskey. We're all here on the Mayback Express for one reason and one reason only and that's to go to drip watch the school of drip. The Mayback pulling the train is pretty good. And they're going to get. And there's the new Snape character. So yes, very effective.

Starting point is 00:08:22 I was reflecting on this and thinking about how it's not just AI videos that are unlocked as the new meme format. Like 20 years ago, video editing was extremely difficult. you had to do it on a desktop, you had to have a piece of software that probably cost a lot of money. It was not widely accessible. And so these image makers, image memes, I was talking to Brandon about this, like, good guy Greg was one of these, or like the insanity wolf. And it would just be like a picture, one image of a duck. And the duck would be on sort of like a solid colored background. And that would be the template and then somebody would put white text with black like block text impact font on the top and the bottom and that was like the image meme and that was accessible in the sense that

Starting point is 00:09:10 it could be like generated on on the fly it was it was it was free to generate it basically then we got video editing you know cap cut instagram reels as an editor called edits and all of a sudden it became easy for someone to take a vibe reel and put different text over it I send you a bunch of these where I'll find some crazy vibriel and I'll just re-contextualize it with a new new caption basically. And so the classic one is like those four, those four jets and the new top gun. And it's like when you and the boys all drive somewhere in separate cars or something like that, you know, it's an example. But now you can generate, you know, full AI videos that can express the joke of the meme. And I think the next version of this is like software as a meme

Starting point is 00:09:59 S-A-A-M, something like that. And we've been experimenting that with the simulators. There's TBPN simulator, Jeremy Gaffan simulator. There are more simulators coming. And all of a sudden, the idea of building a video game, becoming a video game studio, was like an impossible challenge. It would be months and months of time,

Starting point is 00:10:19 maybe millions of dollars to get anything reasonable. So you had to be commercial about it. You could not do it as a comedy bit. But now you can, or it's getting closer. Certainly, our organization is set up to where we can turn Ben or Tyler loose for a few weeks and say, yeah, like, you know, work on this vibe coding project for a few days, a few weeks. Like, it's okay. You don't have a lot of other responsibilities that are going to creep in.

Starting point is 00:10:44 But increasingly, it's going to be more and more just like a few prompts on your phone to get the piece of software that is that meme. And you can think about the J-Mail suite from Riley Walls as another software as a meme moment. where he's making a commentary on the Jeffrey Epstein saga and all of that, but he's instantiating the humor, the commentary in a piece of software that actually works. Although, of course, the feature set is a little bit boiled down from the full Google suite, but the UI is familiar and the UI is part of the joke. And so I think that's a little bit of where this goes. Well, let me tell you about cognition.

Starting point is 00:11:26 They're the makers of Devin, the AI software engineer, Crusher backlog, with your personal AI engineering team. And let me tell you about label box. Oops, sorry. Label box. RL environments, voice, robotics, e-vals, and expert human data. Label box is the data factory behind the world's leading AI teams. So there is a whole bunch of hack news going on.

Starting point is 00:11:47 We're in a very weird week in terms of the news cycle because it's spring break. And so a lot of executives of big tag companies are like, don't launch while my kids are out of school and we're going on vacation. I actually think this is my real. real theory. So we're in a little bit of a slow news week and you can see that like the journal is covering announcements that happened last week. They're talking about SORA. They're talking about Disney. They're talking about, you know, things that, uh, that are more like reflective in Stratory. Ben Thompson has sort of a 50 year retrospective on Apple. It's not driven by a news item. Like, it's not like Apple launched a new product this week. Uh, so Ben Thompson is taking a step back and

Starting point is 00:12:24 reflecting. It's a great piece. But it's not exactly news driven because there isn't that much news coming from big tech companies, coming from the labs, etc. But there are a ton of crazy hacks, starting with Axios. There's an active supply chain attack on Axios, one of NPM's most dependent on packages. So if you have been vibe coding, Axios is a package that helps with HTTP requests, so it gets sucked into all sorts of different projects. And if you upgrade it to the latest version, you basically got a virus with that. And if that's running, in the cloud, it's building, and that's probably maybe bad because it could steal API keys or SSH keys. It could do a lot of things. It could wreak havoc on your system. Also, if you built this

Starting point is 00:13:11 piece of software and you included the contaminated Axios installer or package locally, it could potentially weasel its way out of your local environment and get onto your desktop. It's a virus. So be careful out there. And I'm sure people will be responding. The recommendation from Ferros, who sort of broke the news over at socket security, is that if you use Axios, pin your version immediately and audit your lock files do not upgrade. Socket analysis confirmed that this was malware. Plane CryptoJS is an obfuscated dropper loader that de-obfuscates embedded payloads

Starting point is 00:13:52 and operational strings at runtime dynamically loads, FSOS, and exec sync to evade static analysis, executes decoded shell shell commands, stages and copies, payload files into OS temp, and Windows program data directories, deletes, and renames artifacts post-execution to destroy

Starting point is 00:14:11 forensic evidence. So, very risky. I would say, like, if you have installed this, you should just, like, freak out, basically. And if you break your computer, that's, like, the first thing you should do, just, like, try to slam it.

Starting point is 00:14:24 Yeah, take the computer, throw it in the lake. Throw it in the ocean. That's how you should. start. I concur. I mean, practical, yeah. I mean, there is going to be some sort of like power law response here where of the people

Starting point is 00:14:39 that are victims of the attack, they will go after the most vulnerable with the highest like ransomware potential. And I think we're seeing that with one company. I believe McCore was targeted. But I don't know if that's being this. But I don't believe, was that. Yeah. My understanding is that, yeah, the crazy thing is you have, you have this like Claude Code leak.

Starting point is 00:14:58 That was completely separate. Even though I do believe they use Axios in Claude Co. I saw something on that. Sure, sure, sure. And you have the Mercor leak, which is... It's not a leak. It's a ransom. It's a ransomware.

Starting point is 00:15:11 Someone stole some data. Yeah, they stole a bunch of data and now they're trying to, you know, get bids on it. We'll get to that in a little bit. Okay. And then there's this Axios supply chain attack. A niche had a little bit more context. He said a tiny piece of code called Axios. runs inside almost every app on your phone and every website you visit. Developers download it

Starting point is 00:15:33 100 million times a week. A few hours ago, someone poisoned it with malware that hands an attacker full control of your computer. If you've never heard of Axios, that's normal. It does one boring but important job. It lets apps talk to the internet. When a website pulls up your feed or an online checkout processes your card, Axios is probably doing the work underneath. Over 173,000 other code packages plug into it. It's everywhere. The attacker stole a lead developer's login for NPM. Think it as an app store, but for code that programmers use. Once inside, they swapped the developer's email to an autonomous proton mail account and uploaded the poisoned version by hand. That jump past every security check the project normally runs before new code goes live. And this was not a rest job.

Starting point is 00:16:13 The stackers staged the malware at least 18 hours before pulling the trigger. They built separate versions for Windows, Mac, and Linux. They poisoned both the current version and an older one within 39 minutes of each other, casting the widest net possible once the malware ran on a machine. It deleted itself to cover its tracks. The trick was smart. They never touched a single line of code inside Axios itself. Instead, they tucked in a fake add-on called Plain Cryptojs, built to pass as a well-known trusted library. It copied the real library's description and author info, so nothing looked off at a glance. When a developer installed Axios, this fake package quietly ran the malware on its own, when a smaller package called UA Parcerjs got hijacked back in 2021 with about 8 million weekly downloads,

Starting point is 00:16:56 the security world treated it like a four-alarm fire. Axios has $100 million over 12 XI Expoosure with 173,000 packages depending on it. Socket, the security firm that flagged this, caught it in about six minutes. That's fast, but six minutes is still plenty of time for automated systems at companies everywhere to pull and install the bad version before anyone can react. If you or your team run Axios, freak TF out. Now, lock your version to 1.4.4. 14.0. Change every password API key and access token on any machine that installed the compromised update and check your network logs for connections to SFRCLAK.com or the IP address 14211-20673.

Starting point is 00:17:43 Carpathie had some context if you want to go through this, Sean. I will, but first I'll tell everyone a very important message from CrowdStrike, which is super relevant today. Your businesses in AI, their business is securing it. Crowdstrike secures AI and stops breaches. And I'll also tell everyone about Cisco. Critical infrastructure for the AI era. Unlocked seamless real-time experiences and new value with Cisco. So Andre Carpathie said, new supply chain attack this time for NPM Axios, the most popular HTTP client library with 300 million weekly downloads. That's a lot. Scanning my system, Andre Carpathie says he found a use imported from Google Workspace slash CLI from a few days ago when I was experimenting

Starting point is 00:18:27 with Gmail, G-Cal, CLI. The installed version luckily resolved to the previous version, the unaffected 1.13.5, but the project dependency is not pinned, meaning that if he did this earlier today, the code would have resolved, everything would have updated, and he would have been poned. It is possible to personally defend against these to some extent with local settings, e.g. release age constraints or containers or etc. But I think ultimately the defaults of package management projects, PIP, NPM, etc., have to change so that a single injection, usually luckily fairly temporary in nature due to security scanning, does not spread through users at random and at scale via unpinned dependencies. So very, very crazy,

Starting point is 00:19:17 crazy story. Scott Wu said that Devin Review caught the Axios supply chain attack for multiple cognition customers before the attack was publicly known. These attacks will be 10x more frequent in the age of AI. It is critical that repo maintainers start using AI

Starting point is 00:19:33 for defense as well showing one example below where Devin Review caught the attack within an hour of its release, text minorly edited for anonymization. So I was debating this with Tyler earlier. The question is like How does this update diffusion of coding agents, diffusion of vibe coding coding.

Starting point is 00:19:55 I was sort of saying, is this bullish for cursor, windsurf, code readers? Because you would see an organization that said, hey, we were having a great time vibe coding. But going forward, we have a standard in this organization that we're going to have more humans in the loop. Does this make people be more inclined to put humans deeper into the situation? Tyler's counterpoint, I'll let you explain how you were saying that maybe this is actually bullish for just more token generation, more code gen. Yeah, I mean, clearly like there just needs to be more code review, right? Okay.

Starting point is 00:20:32 The package was still seen within seven minutes by an automated system, right? That's true. So, like, yeah, I think people will just, like, there's going to be much more of an emphasis, this like, okay, use a coding agent to write the code. You also use a coding agent to review the code every time. Like right now, that's kind of a thing you do maybe later. If you're in a big team, you have code review, but if you're just doing it solo, maybe you don't do as much code review, right?

Starting point is 00:20:54 But it just becomes more embedded within the agents, right? You talk to codex, you talk to cloud code. Yeah. There's already like every single. I just think it's bullish overall for cybersecurity. Like, I think every cybersecurity company will probably do well. People are on edge already. Yep.

Starting point is 00:21:10 and even though this type of attack has happened for years long before like the popularity of vibe coding, it just feels like there's a bunch of new solutions that are needed. The kind of incumbent cybersecurity players will do well. They're going to release a lot of new products. I think the question that I have is like, why seven minutes, right? Yeah. Why not check it before it's merged in in the first place? Yeah, yeah.

Starting point is 00:21:36 Or just like, you know, these are machines. So theoretically, they can be constantly monitoring versus like... Yeah, I don't know. And the question is, we're going to be digging into this story more over the next few days. But I'm interested to know, like, it's found in seven minutes. When is it actually rolled back? If you look at 300 million weekly downloads, like clearly there are people that were downloading it at that moment in time. At all seven of those minutes, there's probably like thousands of downloads, if not, you know,

Starting point is 00:22:07 tens of thousands, just doing like a rough ballpark on what seven minutes means over a week of 300 million per week. But the question is, like, how quickly was it rolled back? So is it only if you're in that seven minutes, or was it discovered in seven minutes? And then it took them another 20 minutes to roll it back and stop serving the contaminated package. Understanding the scope of this, because it's very clear that, as Andre Carpathie explained, like he was actively using it every single day and yet was not caught in that seven minute window. And so he was cleaned. And understanding the scope and scale of the impact is very much determined by how many,

Starting point is 00:22:50 just how broad and how many installs happened during the contamination. Anyway, Will Brown has a good take. He says, I hope someone at Axios is reporting on this. And I completely agree. It's going to be, it's going to be confusing when they do. Anyway, let me tell you about Gusto, the unified platform for payroll benefits and HR built to evolve with modern, small and medium-sized businesses. And let me also tell you about 11 labs. Build intelligent real-time conversational agents, reimagine human technology interaction with 11 labs.

Starting point is 00:23:17 So, moving on. More hats. Last night. More leaks. What's going on? Last night, quad code, source code was leaked via map file in the NPM registry. There's just a link to. Wait.

Starting point is 00:23:31 Someone's just actually, do not click. a link. If somebody ever says, hey, I got some really great source code here, just click this link. Probably don't click it. Let other people screenshot it. There's plenty of meta analysis over here. Seems messy, seems unfortunate. A heart goes out to the folks who are dealing with the situation. At the same time, Codex is open source. It's not the end of the world. But it did reveal a bunch of things about the roadmap and also some of the internal April fools. That is the worst part. We love a secret surprise April Fool's joke. I love a good joke.

Starting point is 00:24:08 And nothing spoils a joke like hearing about it a day early. But much more importantly, there are lots of other critiques of the way Claude is implemented. What are the bad words? Yeah, I don't think this hurts their business at all. No. Because people are using Claude Code to make other products. Yeah.

Starting point is 00:24:26 And then also having to take basically a fork of Claude code, maintain that, try to be shipping. features against it, which is, again, I think it's, it's not, it seems to not be legal at all to just fork the code base just because it's out there. Oh yeah, you can't just like steal it as your business. People are converting it into other languages and maybe there's some argument there, but still, I don't think this hurts their business at all, but understand some of the secrets, what's special. But at the end of the day, all of these tools, especially something in Cloud Code that's so new, like, it's more of like the process. It's more bad for, for the overall brand of vibe coding.

Starting point is 00:25:06 Totally, totally. Yeah, yeah, it's rough. And the, you know, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the future related to cyber security, all the big cyber companies have been selling off, you know, tens of billions of dollars. Yeah, yeah, yeah, the question of like, yeah, does this build trust in, like, using vibe code? Yeah, so overall, overall, it, uh, it, it, uh, it, it, uh, it hurts some trust, but, but, but again, but again, you know, very obviously going to get through this. Yeah. So the how it started, how it's going is,

Starting point is 00:25:39 of course, landing like a ton of bricks. In the last 30 days, 100% of the contributions to Claude Code were written by Claude Code. And how it's going is that it leaked the source code, which is not what you want to have happen. Yes. Angel says Mythos is so good at security that Claude source code got leaked. Okay, let's, I don't know, should I, this is like, you know, you didn't get to watch the Super Bowl, you have it DVRed at home. Do you want spoilers? Should we review the April Fool's joke or should we leave it unspoiled so that we can enjoy it tomorrow? What do you think? I mean, it's not, it's not, it's cool. It's very cool. You've already read it? I read through it. But it's not, it's not to my, I don't think we're getting, I don't think we're getting a knee

Starting point is 00:26:26 slapper out of it. But it's very, it's very cool. Okay. I think it'll be cute. Okay. Well, well, then we can move on. What else did we learn? Tuki summed it up here. Do you understand what just happened to Anthropics? Someone on their team ran a production build of Claude Code. The compiler generated a dot map file, which is literally a blueprint that reverses the entire code base back to its original source, and then they published it straight to NPM for the whole world to download. And it really does show you how fast the NPM downloads, like there are people that are downloading it every single minute. And so even if it's only up there for a minute, someone's going to get it. And then all they need to do is send it to somebody, zip it and post a link on X and it goes viral.

Starting point is 00:27:07 It's like locking every door in your house, installing cameras, hiring armed guards, then accidentally uploading your floor plans to Google Maps. Does that matter? No, that's a bad analogy. I don't like that analogy. Because floor plans are not why I lock every door in my house. I install cameras. I hire armed guards. Aren't floor plans public on like Zillow? Oftentimes. They're not always, you can skip over this. John, if you scroll down this account, just kind of post like the same format every single time.

Starting point is 00:27:35 So we can skip that. If there's a red alert emoji, you got my attention. Let's go over to Lisan Alga. Yes, yes, yes. A few takeaways from the Claudecote Code leak, Anthropic is actively using mythos for development. Okay. They are already a Capi B8.

Starting point is 00:27:51 We learned last week that Capi Bars are huge, but can be deadly in the rest of. context. Capi Barre still has issues. The foreshadow is crazy. The foreshadow is crazy. We were talking about how the Faustian bargain that is getting up a Capybar as a pet. It seems so cute, but it can bite you.

Starting point is 00:28:10 And it seems like that might be what happened. Capy Barre has $1 million token. Context Window and Fast mode. Numbat is another interesting code name tagged with at Model Launch. Remove the section when we launched Numbat. Fenwick seems to be the Fennick Fox. Fennick Fox is very cute. also not a domesticated animal.

Starting point is 00:28:29 How about we get some golden retriever code names? How about big fluffy poodle? That's a good code name for your animal-themed AI model. Anyway, let me tell you about console. Console builds AI agents that automate 70% of IT,

Starting point is 00:28:46 HR, and finance support, giving employees instant resolution for access requests and password resets. And let me also tell you about Lambda. Lambda is the super intelligence cloud, building AI supercomputers for training and inference at scale from one GPU to hundreds of thousands. Arvid says hot take,

Starting point is 00:29:00 Anthropic leaked Claude Code intentionally to get a Nerdosphere code review. It would have never gotten if they had just open sourced it. Oh, that's actually true. Way more attention. You don't leak your entire feature roadmap and you don't do,

Starting point is 00:29:15 I mean, it's funny, and I'm sure they'll make the most of this. This is 4D chess right here. But I'm not seeing the 4D chess. I'm seeing the 40 trust now. I'm convinced. This is, I mean, we're in completely, completely uncharted territory for marketing stunts and pre-releases and sneaky footage that

Starting point is 00:29:33 goes viral and maybe was planted and you don't know and it's like some leaked account. Like, I don't know. I think everything's, I think the gloves are off. Everything's on the table. This could be an April Fool's joke. This could be a stunt to drive attention to an open source move. Although, Tyler, you said that Dario is not a fan of open source at all, right? He's like against unilaterally.

Starting point is 00:29:56 He doesn't want to do open source. I feel like, isn't there some steel man there where, where if you open source, like, I don't know, like, like opus two or something that's like really old, it's entirely commoditized in the research community. So all of those secrets that went into like making opus two good, those have been commoditized. They've been discussed at the house parties in SF. The researchers have moved from one place to another. So everyone knows these that have implemented. They're available as open source, but by open sourcing your model, you can share with more of like the up and coming academic community. Like if I'm a, if I'm a computer scientist, I'm interested in all the research is already commoditized.

Starting point is 00:30:40 Yeah, I guess you could just use the other ones. It doesn't really have a benefit. Maybe. Yeah, so has any, has anyone at Anthropic, has anyone at anthropic commented on this at all? I haven't seen anything. I haven't seen anyone. What is undercover mode? that is a way to contribute to projects without letting people know that you're using ClaudeCote. Oh, interesting. That's a hack.

Starting point is 00:31:07 Gergley over at Pragmatic Engineer says this, Gergi, sorry. This is either brilliant or scary. Anthropic accidentally leaked the source code of Claude Code, which is closed source. Repos sharing the source are taken down with DMCA, but this repo rewrote the code using Python and so it violates no copyright and cannot be taken down. Okay. And there's a warning. Do not store the code, even though it has leaked. Do not store it because you might get DMCA'd, according to the primeogen. The last time Anthropic, in their infinite PhD-level wisdom, leaked their own source code. February 25th, that happened? I missed that entirely.

Starting point is 00:31:47 They DMCA'd all repos that had their code. Careful storing the code because Anthropic will have no mercy. 40,000 users forked it, so maybe unfork it if you did that because it sounds like you might get a legal letter. Again, a DMCA is not like an actual lawsuit. It's more just on fork, on fork. And people are of course making a joke that the Codex source code has been leaked in full here and they're linking to the GitHub because Codex is open source, which is cool. I don't know. It's interesting. And more and more people are building their own harnesses. There some interesting data that Opus performs extremely well better than in clog code in cursor on some benchmarks. And so there is this new, this new paradigm of like, you know, how can you add

Starting point is 00:32:35 different value when you're building a harness? So what else? Yes, certainly there's other, plenty of other companies that are building harnesses and they're going to be able to dig through this and get some benefit, be able to improve their products. That's not, that's not great. But at the same time, Codex has already, the source code is already open source. Yeah. And so that's not, that hasn't been hurting codex's progress and growth. So, end of the day. Ultimately, I would say, I would, I'm assuming very, very embarrassing for the, for the individual that ultimately contributed to this, but they will get past it.

Starting point is 00:33:13 Well, we will put the blame squarely on the AI model so they can take it. Dax is getting line of code mogged, LOC-Mogged, because clog code open source is, uh, clod code source is 512 lines of code, whereas open code, his project is only 118 lines. And so he's got to get those numbers up. And GT mocks everyone with over 50 billion lines of code. He doesn't have 50 billion lines of code. GT, Gary Tan, will be coming on the show, hopefully this week.

Starting point is 00:33:43 And we will get the full scoop on how he's using G-Stack and other models. which should be fun. Before we move on, let me tell you about TurboPuffer, serverless vector and full-tech search, built from first principles and object storage, fast, 10x cheaper, and extremely scalable. And let me also tell you about vibe.co. Where DDC brands, B2B startups, and AI companies,

Starting point is 00:34:01 pick channels, advertise on streaming TV, pick channels, target audiences, and measure sales, just like on meta. Zach says, NDAs are a great way to keep your corporate secrets safe from one or two beers, but not three years. Why is there a community note on this? Oh, this joke was posted,

Starting point is 00:34:17 before on Instagram. It's a little joke theft. Interesting. Got him. Interesting. But it's a good joke. And I'm glad that he brought it over to X where we could enjoy it along with 36. The original post was an NDA is a lock and three beers is a key.

Starting point is 00:34:32 Okay. Well, yeah, he toned it down for the timeline. Anyway, there is news out of Google. A Google paper warns that warns crypto on quantum risk ahead of 20, 29 timeline. So we've heard about the risk of quantum computing affecting the cryptocurrency industry, crypto projects broadly. There is some new research out of Google that provides some more perspective. So Google researchers have warned that future quantum computers may be able to break some of the cryptography protecting Bitcoin and other digital assets with fewer

Starting point is 00:35:10 resources than previously thought, adding urgency to the debate over how the industry should prepare. The researchers did not indicate such a machine exists today, but said new work suggests the computing power needed to carry out that kind of attack, maybe lower than earlier estimates had suggested. In a Google research blog post, this is from Bloomberg, the researcher said that a future quantum computer could break elliptic curve cryptography, a form of public key encryption used across much of the market. Their latest estimate points to a 20-fold reduction in the quantum computing hardware, to break what's known as ECDLP-256, a mathematical problem that helps secure crypto wallets in transactions.

Starting point is 00:35:52 That does not mean Bitcoin and Ethereum are suddenly exposed, but the researchers in the white paper dated Monday said the clearest defense is a shift towards post-quant cryptography or PQC. I'm sure this would be a hot topic over the next few months. A newer form of security designed to withstand attacks from powerful machines. They also urge the crypto industry to cut avoidable risks in the meantime. We urge all vulnerable cryptocurrency communities to join the migration to PQC without delay. Google cast the paper as a warning meant to give the industry time to act, not as a prediction of imminent collapse. Last week, the tech giant introduced a timeline to fully migrate its own security systems to post quantum cryptography by 2029.

Starting point is 00:36:37 Fears around quantum computing is a realistic threat to crypto have swirled for years. In January, Coinbase established an independent advisory board to study. what quantum computing could mean for the blockchain. That's the month. Christopher Wood, global head of equity strategy at Jeffries, removed a 10% allocation to Bitcoin from his model portfolio, citing fears that the advent of quantum computing could undermine the token. On Tuesday, Bitcoin shrugged off the news of the Google paper,

Starting point is 00:37:03 making the rounds rising as much as 2.6% to $68,300. I'm not sure where it is today, but a majority I'm sure you can pull that up. Even so, the researchers said, the time left before such machines arrive still appears longer than the time needed to move public blockchains to post-quantum cryptography. However, BTC is currently at 67. 67. So slightly off of yesterday. A lot of this stuff has been discussed ad nauseum in the crypto community for years. I remember hearing about quantum potentially breaking Bitcoin as far back as 2016. So you're saying you were already in that kind

Starting point is 00:37:41 of like post-quantum? Yes, 100%. I was locked. did. No. Yeah. I was aware of it. One concern that people in the community have had that I've seen talked about is this idea that if you did have a computer powerful enough to crack these encryptions, you would, unless you were like Google and you already had, you know, billions and billions and billions of dollars of cash flow, you wouldn't exactly stand up and say, like, hey, I have cracked

Starting point is 00:38:13 Bitcoin. because the incentive for a certain team would just be to go around and find these wallets that were maybe didn't have any activity for a long time and just start cracking those individually because if you just stood up and said, hey, I have a quantum computer that destroys Bitcoin. The price would go down and then the hacker wouldn't get any benefit from it. Yeah. It's interesting. What are quantum stocks doing on this news? probably ripping they rip on everything

Starting point is 00:38:45 Cy quantum is that one of them Riggette is up 8% Okay there we go Oh Syquantum's probably privately held There's another one Dwave right

Starting point is 00:38:57 Dwave are they public Yeah they're up 10% today But they're down 12% over the past five days But and 25% of the last month and 42% of the last six months But they're up 88% over the past year, let's go. D-Wave is a $5 billion company.

Starting point is 00:39:15 There's apparently a bull market in Nick on our team's email inbox. Oh, yeah? Quantum companies that want to come on and talk about. Well, we do have someone coming on, right? We have Alex Prudent from Project 11 coming on to break it down for us at noon. So Nick Carter was talking about this. He said, many are wondering what Google saw that caused them to revise their post-quantum cryptography transition deadline to 2029 this week.

Starting point is 00:39:40 It was this, and it's from research, Google, research doc Google, which we will go through. Max the DC says Google's basically saying, we've cut the quantum resources needed to break Bitcoin's encryption by 20x. We can now break it. We can prove it. We're just not going to tell you how. We've slowed down research to give crypto a chance. You have until 2029 to figure out a solution.

Starting point is 00:40:03 Good luck. Elon chimed in and said, on the plus side, if you forgot your password, the password to your wallet, it will be accessible in the future. Also to everyone else. Yeah. Yeah, I don't know. I mean, how do property rights? If somebody does have a quantum computer

Starting point is 00:40:22 and they crack your Bitcoin wallet that you forgot the password to, but you can prove that you owned and then they get busted for stealing your Bitcoin, you could potentially get it back. Do you ever really own code? I don't know. Nick also said,

Starting point is 00:40:37 and the craziest thing is that the quantum AI, Google Quantum AI paper is maybe not even the most concerning quantum paper release today from Project 11, who's coming on. Shores algorithm is possible with as few as 10,000 reconfigurable atomic qubits. So this will be interesting to dig into further. Within minutes, with 500,000 physical qubits, Google is now more confident on a 2029 post-quantum transition. Well, speaking of Google, let me tell you about Gemini 3.1 Pro. With a more capable baseline, it's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view or bringing creative projects to life. And let me also tell you about graphite.

Starting point is 00:41:23 Code review for the age of AI, more important than ever. Graphite helps teams on GitHub ship higher quality software faster. So, there's a lot of news about this quantum story. Nick said, good morning. Now is not the time to panic. The time to panic is if Bitcoin devs read these two papers and double down on their chosen solution of hoping it goes away, then panic. That's ridiculous. Dan Shipper says, the first thing I've seen that could make Bitcoin go to zero or allow competitive coins to catch up.

Starting point is 00:41:52 So other coins clearly have at least like a very clear like marketing story to tell if they are like the quantum proof or the first to be quantum proof or the most seriously regarded. in the quantum proofing race will be interesting. Ariana Simpson chimed in and said, except all or most other coins have this problem too. But that is the opportunity that someone can maybe change something. So the chance that NASA lands on the moon, we were tracking this yesterday.

Starting point is 00:42:22 The missions are starting to happen. Before 2028 on Kalshi is now at 14%. Before 2027 is at 4.7%. So they are racing. Of course, this Artemis 2 mission is not boots on the ground. ground on the moon. It is rocketing around the moon.

Starting point is 00:42:42 We'll have more about this tomorrow. They're just going to check it out. They're going to be gone for 10 days. They're going to be in space for 10 days. And we'll be very interesting. Brenna Grell was doing some deep dives on the technology, the streaming technology, what we really care about here, that will be on board. Something like 20 cameras, 4K, live streams, laser beams to

Starting point is 00:43:05 make sure it's low latency. Super chat. be a lot of fun. Super chats would be good. We got to get a chat going. I'm sure there might actually be, because they usually stream on YouTube, and so I wouldn't be surprised if there is in Is it going to be a 24-7, like perpetual stream that's always on? Yeah. Even when the astronauts are taking a sleep? Yeah. Taking a little nap? Yeah, yeah. Okay. Yeah. Okay. Yeah, it's going to be funny. VFX artists are going to be sitting there watching it very closely and then pausing.

Starting point is 00:43:35 There was a glitch. Did you see that glitch? That was VFX. That was AI. No, this is my mark. I will believe that it's real if I see an astronaut put three fingers in front of their face. Yep. Because this is the one thing that the AI can't do right now.

Starting point is 00:43:49 If you're ever on a Zoom call with someone who suspect of being fake, a scammer who said, hey, let's get on Zoom. Let's talk about some financial investment opportunity. And it looks like someone you think is the person. but you suspect that it might not be, and they will be able to show you, look at the fingers. The fingers are perfect. It's fine.

Starting point is 00:44:13 It's fine. That's because this part is not AI. Just the face is AI. This is the deep fake stuff that's happening. So what you have to do is you have to ask them to hold up three fingers. They'll be like, yeah, three fingers. This is fine, right?

Starting point is 00:44:24 I satisfy the task. You've got to say, no. Put the three fingers in front of your face. Because if you put the three fingers in front of your face, the AI gets confused, and it breaks the deep fake that's happening underneath. So you got to go like this. Show us some depth of the field.

Starting point is 00:44:37 You have three fingers in front of the face. This is the trick. This is the only way you'll survive in the future. Be careful out there. Mercor had a breach. This is crazy. The design language for the hacker is very hacker-coded. The hackers that are putting out a bounty created like an image that looks very aesthetic to me.

Starting point is 00:45:03 They, the, the design of this, I didn't realize hackers, um, did stuff like this. This is very interesting. But, you know, it's like, you think about the hackers. They're kind of like, cosplaying as hackers. They are. But they have, they have, they've like adopted like the green, like the green text in the black terminal. It's like they're, they're, they're, they're, they're, it's, uh, it's like life imitates art that, that type of thing. Anyway, it seems like a very rough leak, very unclear what's actually happening. There's a whole bunch of, there's a whole bunch of of different questions in here. There's a database of candidate profiles,

Starting point is 00:45:37 source code, video, all sorts of stuff, tail-scale VPN data. Unclear how much of this is real. They could be faking it. I don't know where the comments are, but the risk is that if there is some sort of

Starting point is 00:45:51 Equifax-style payout, that could be extremely costly because if they have millions of people in their database and they've got to pay everyone 400 bucks like Equifax did, because they have sensitive information, that could be very, very expensive. Well, we have had the more core folks on the show many times and are hoping that

Starting point is 00:46:10 they get through this smoothly. And everyone's... Yeah, absolutely brutal. I mean, it's, it sucks, it sucks first and foremost for all the individuals who's PII is now potentially floating out there. Totally. It's probably quite bad for their customers. Yes. paid for paid for the, you know, some amount of this data and now it's just floating out there.

Starting point is 00:46:36 Yeah, yeah. And then, obviously, you know, unfortunate for the company. But it's still unclear. I was looking up Lapsis, which is,

Starting point is 00:46:44 uh, the hacker group. Styled as LAPS US with a money sign. Mm. Classified as by Microsoft as strawberry tempest and more recently identified as or a part of shiny hunters is an international extortion focused hacker group known for its various cyber attacks against companies and government agencies. The group was active in several countries and has had its members arrested in Brazil and the

Starting point is 00:47:09 UK in 2022. According to City of London Police, at least two of the members were teenagers. Lapsis uses a variety of attack vectors, including social engineering, MFA, fatigue, sim swapping, and targeting suppliers. Once the group has gained the credentials to a privileged employee within the target organization, the group then attempts to obtain sensitive data through a variety of means, including using remote desktop tools. Attempts at extortion follow. Initially, the messaging app telegram has been used for communications to the public, including recruitment and posting sensitive data from their victims.

Starting point is 00:47:42 The first major cyber attack attributed to Lapsis was against the Brazilian Health Ministry's computer systems in 2021. Lapsis gained a variety for a series of cyberattacks against large tech companies, including Microsoft, Nvidia, and Samsung. following these attacks, City of London Police announced that it had made seven arrests in connection to a police investigation into Lapsis. Although the group had been considered inactive by April 2022, it is believed to have reemerged in September 2020 with a series of data breaches against various large companies through a similar attack vector, including Uber and Rockstar Games, with subsequent arrests again by City of London Police and Brazilian Police. the group appears to have become inactive after September 2022, with members perhaps dispersing to other groups and the conviction of two British members. It's also interesting because they don't enforce, like,

Starting point is 00:48:33 brand intellectual property around hacker collectives. And so anyone can pick up the brand and use that, whether or not they're in the organization. It seems very fluid. But good luck to everyone who's working on their response and hopefully a good resolution that is, resulting quickly. Let's move on to some good news. We will be having Sebastian Malibai join the show at 1230 today. But Colossus magazine published an exclusive chapter from the book, which Tyler has

Starting point is 00:49:05 there, the biography of Demis Havas from Google DeepMind. And he secretly built a hedge fund inside of DeepMind trying to beat Jim Simons. Google shut it down. So there's this interesting, there's this interesting screenshot that Colossus shared. Hasabas, for his part, assembled a secretive hedge fund operation within Deep Mine. He recruited a team of 20 researchers to train high-frequency trading algorithms and explored a collaboration with the Wall Street behemoth BlackRock. It was not a project of which Google approved. But Hasabas, a five-time World Games champion at the International Mind Sports Olympiad. Sick. Hopeed he'd found another game that he could win. One day, I asked about

Starting point is 00:49:49 the story of this trading project, I was told that Hasabas wanted to beat Jim Simons, the mathematician who founded the wildly successful algorithmic hedge fund Renaissance Technologies. Rentech operated in secret, which Demis loved, my acquaintance explained to me. Did the secret deep-mined trading team make money? I wondered, no, came the answer. Because of Google's wariness, it was quietly disbanded. I heard about something, maybe it wasn't this deep-mine team. Gabe says, but did they rip Siggs?

Starting point is 00:50:16 Oh, yeah. Could have been the missing ingredient. Jim Simons, he also never wear socks and always speeds and just pays the tickets because his, his like risk-adjusted value in terms of his opportunity cost is that he should never drive the speed limit, which is sort of a wild move. True, true wild man. I heard about the potential of a Google hedge fund years ago. I don't know if it was related to deep mine, though, but just the amount of cash they have on the balance sheet, like they need a trading desk, basically, to move that money around, even if they're just buying treasuries, they need strategy, Forex. There's so many different

Starting point is 00:50:52 operations. And there was a pitch I heard about years ago that they were thinking about, like, should we be more active? We have a lot of information. We have a bunch of great engineers. We could build a hedge fund here. But they decided that it was not compatible with like the don't be evil philosophy. It was not core to the mission. And that they, you know, at some point, there is risk associated with active trading. And so you could potentially blow up. There are certainly plenty of examples of hedge funds that had fantastic teams, but could not stick the landing and wound up, wound up zeroed. Sophie says Google shutting down a deep mind hedge fund quit right before they were about to get it big. It really is this meme. They probably would have printed.

Starting point is 00:51:36 Although it's not like the high-free-insured training firms are not using AI or not using, I mean, Jane Street invested in a custom server company or custom silicon company, something along those lines specifically for high frequency trading. So they have a lot of AI researchers there. And you see this with a lot of the labs saying, hey, does anyone from the high frequency trading industry or quant finance want to come work over here? We can maybe start matching your salary, maybe give you a more interesting project that you can actually talk about, and people will be potentially.

Starting point is 00:52:13 excited about. I don't know. Anyway. Bone GPT, the rapper Eater shared. I don't want this part of my brain to grow, which is a quote from this. So in the weeks after the presentation, the two sides finally converged on a fleshed out version of the Pichai plan. Sullyman would lead deep minds applied side from within Google, while Hasebis would run research as an independent global interest company. For Suleiman, this was a triumph. Google had finally signed a complex term sheet, granting most of what he wanted. Hasebus was equally pleased. The plan guaranteed him an astronomical $15 billion in Google funding to sustain AGI research over the next decade. And it would put an end to the meetings on corporate structure, which he found screamingly boring.

Starting point is 00:52:57 After two years of negotiations, he had hit his limits. I don't want this part of my brain to grow, he often said, when asked to get his mind around another legal document. That's hilarious. That's a great saying. I don't want this part of my brain to grow. So it's so funny that, you know, you're going through two years in negotiation. And they're like, okay, you're going to be, you're going to be have so much funding to build AGI. $15 billion.

Starting point is 00:53:26 You're like, oh, so like a seed round for like a Neo Lab? Like, great. Like, oh, so like one data center from a NeoCloud or something. It's like the numbers have gotten so, so big that 15 billion does not feel like anywhere near enough. at this point. Colossus, hit it, hit me, John. Let me tell you about Railway. Railway is the all-in-one

Starting point is 00:53:49 intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases, and more, while Railway automatically takes care of scaling, monitoring, and security. Tell me what the list. Elon, Colossus shares. Elon has spent a decade trying to control an AI lab.

Starting point is 00:54:02 He tried to absorb deep mind into Tesla in 2014 than Open AI in 2018. When that failed, an intern spoke up. It did not end well. Let's read through this. He also tried to control XAI to some degree. Well, doesn't he control XAI? Well, he controls it, but at what cost?

Starting point is 00:54:20 Right? All seven co-founders gone. Oh, true, true, true. That's what you're referring to. Got it. Anyways, from the book, pushing back against Musk's obsession with the race against Google and DeepMind Brockman added,

Starting point is 00:54:31 it doesn't matter who wins if everyone dies. Musk responded the next morning at 3.52 a.m. He confronted Brockman with a proposal that recalled Pichai's pitch. Open AIs should spin into Tesla. Initially, Open AIs team could accelerate Tesla's development of autonomous vehicles. Next, it could use the profits from self-driving cars to fund its AGI moonshot. Tesla is the only path that could even hope to hold a candle to Google. Musk declared even then the probability of being a counterweight to Google is small.

Starting point is 00:55:00 It just isn't zero. Back in 2014, Musk had Skyped Hasebis from a closet in L.A. What a funny. Proposing that Tesla or SpaceX should absorb deep mine. Almost exactly four years later, the new version of this proposal played into Altman's hands. It proved Musk's power hunger. With little difficulty, Altman now persuaded Brockman and Sutskiver to take his side. Together, the three told Musk that OpenAI would not attach itself to Tesla. At an all-hands meeting on the top floor of a converted truck factory that housed Open AI,

Starting point is 00:55:31 Musk announced to the employees that he was quitting the lab, scornfully, adding that... I need raptors. I need a new Ford Raptor, potentially every day. we got to put this lab inside of a truck factory. This is amazing. Scornfully adding that open AI would have to sprint faster to stay relevant.

Starting point is 00:55:48 I guess they did. I guess they did. Hoping to lure away some researchers, he declared there was a much better chance of building AGI at a strong business like Tesla. Yeah. Showing courage or perhaps just youthful innocence and intern asked Musk

Starting point is 00:56:01 if speed might be reckless from a safety perspective. Besides, wasn't developing AI at a for-profit company like Tesla the same as creating it at a for-profit company like Google. Isn't this going back to what you said you didn't want to do? The intern demanded.

Starting point is 00:56:16 You're a jackass, must retorted. Then he stormed out of the meeting. That intern? Tyler Cosgrove. No. That intern was Steve Jobs. I'm just kidding. That intern was Taylor Swack.

Starting point is 00:56:30 It is, it is, my interesting read on this is like, it's crazy that Elon was interested in, in basically buying all. of deep mind, absorbing all of deep mind. And then four years go by. And he's like, I'm still, I still want a lab. I want to absorb all of open AI. Instead of just incrementally adding to an internal lab at Tesla, just one researcher at a time. Like he was able to assemble eight.

Starting point is 00:56:56 They were already working on self-driving. Yeah. And he was able to assemble eight co-founders at XAI. Of course, like, they wound up leaving. But if you just think about it as like, okay, there's going to be some churn. Maybe the churn will be higher even. But if you start the process in 2014 and you're hiring researchers continuously and using cash flow from Tesla to fund that. And then, yes, researchers might leave, but then you get new ones and you're just building that capability.

Starting point is 00:57:23 It's like the supercharger network or, you know, Starlink. Like you have to build a team and you have to continually add. But instead, Elon's been in this world where it's always like all or nothing, which is a very odd strategy to me. instead of just like home growing it. I don't know. It is just like an interesting, it's an interesting strategy, I suppose. Let me tell you about the New York Stock Exchange.

Starting point is 00:57:46 Want to change the world, raise capital at the New York Stock Exchange. And let me also tell you about Figma. Agents, meet the canvas. Your AI agents now create and modify your Figma files with design system context in beta starting to go. And without further ado, we have our next guest in the Restream Waiting Room.

Starting point is 00:58:03 Let's bring in Alex, then Project 11 to the TV Mideltram. Alex, how are you doing? I'm going to be here, guys. Is it over or are we back? What's going on? How bad is it? Tell it to me.

Starting point is 00:58:14 Do you give it to me straight? How long do I have? Well, according to Google, you have until 2029. Okay. That's like forever. That's forever in my mind. Yeah. Although maybe not forever.

Starting point is 00:58:27 If you think about blockchains that take a long time to change, Bitcoin's last upgrade took four years. And that's 2029's listed four years away. Yeah, that seems really risky. Take us through, like, what actually changed? Because I feel like that. A little context. We'd love some background on you and Project 11, and then we'll get into all the papers.

Starting point is 00:58:48 Yeah, all good. Yeah. So me, I'm a former Army Green Beret. Got out, or I got really interested in Bitcoin working in the Middle East. Got out, went to 10. Thanks. Nice, nice sound effect. Got out, went to Stanford, and then he got a job working in venture first.

Starting point is 00:59:01 Then entered the blockchain space at a company called Aalio, whereas after five years before getting really excited about solving this quantum problem that blockchain is faced. So that's what that led me to found. Project 11. So in Project 11, I kind of gave it away. It's all about securing digital assets on blockchains into the post quantum future. Right. So the way I like to frame it is what quantum computers threaten is the underlying foundation of cryptography that all blockchains are built on. Right. So it's that level that we have to fix. And then ultimately, everything on top of that, as you guys know from tech, like there's all kinds of dependencies at each layer of the stack. And we have to rebuild the whole stack. And that's what

Starting point is 00:59:36 Project 11's all about. Just to put it into perspective, when did you found Projects 11? You said it was five years. You spent five years at the last company. When did you actually get started on this? October 2024. So just over, I guess, almost a year and a half ago. And what was the general dialogue around quantum and the risk to crypto at that time?

Starting point is 00:59:59 That it wasn't real. That quantum computers were always going to be 20 years away. That, you know, that no one had to pay attention. bigger things to worry about. Honestly, I feel like that's slowly changed. And I think today's, not just so there's a paper from Google, there's another paper out of Caltech, both dropped on the same day, both effectively lowered the bar massively that a quantum computer had to clear to be considered cryptographically relevant to threaten Bitcoin. So that was the breakthrough. And I think this is a watershed moment where really at this point, when Google, the head of the Ethereum

Starting point is 01:00:32 Foundation and a Stanford cryptography professor all pound the table and say, we cannot wait to migrate anymore, that people are going to start paying attention. Okay. What actually changed? Because it doesn't seem like the number of logical qubits or physical qubits, like that seems to be growing exponentially. But even when you trace out the curve, you're five, 10 years away from what we thought we needed.

Starting point is 01:00:57 So is this a new algorithm, a new stack of code, or is it new math? Like what change that we got this 20x increase in efficiency in terms of cryptography breaking via quantum computers? Yeah, a couple things. So first off, these two papers are not necessarily about a quantum computer that's bigger or more capable. So they're about what it takes to break cryptography, right? And so what changed? So one of the things that changed was that interestingly, physicists and kind of quantum cryptographers that looked at this problem for a long time studied an algorithm called RR. RSA. It's not worth defining, but it's kind of an older cryptographic algorithm. But that's not what really any blockchains use, right? Because, you know, RSA keys are very large, right? So it turns out, and this was kind of the key, one of the key upshots of the Google paper. It turns out that if you actually focus on the cryptography used by Bitcoin, Ethereum and other networks, it's actually way easier to break than they thought it was compared to RNSA. So that is one of the major things. The other big breakthrough, and this is from the other paper from Caltech, is that, you know, quantum computers,

Starting point is 01:02:03 as you guys may or may not be aware, as your audience may not be a mirror, are kind of, you know, they're very fragile generally. So to be useful, they need to have what's called error correction applied. And that error correction can kind of result in a lot of overhead. You need to have tons of physical qubits to get to,

Starting point is 01:02:19 you mentioned logical cubit, to get one logical cubit. Well, this Caltech paper basically showed, hey, we have some new ideas to do error correction. And it turns out if we apply those, we don't need hundreds or thousands of physical cubits. Maybe we just need a handful to make one logical cubit.

Starting point is 01:02:33 So the title of their paper, actually, the headline is, you may only need 10,000 physical qubits to break short, to run Shores algorithm. And by the way, they demonstrated last year 6,000 qubits. Okay. So we're close. Yeah. That's, you know, no one can put a timeline on it, but how fast do you think can close that gap is the question. Okay. Is it possible?

Starting point is 01:02:56 Jordy was thrown out the idea of someone having a secret quantum computer going around the blockchain, siphoning Bitcoin. from, you know, cold wallets that haven't moved. I wasn't implying that it exists yet, just implying the incentive of if somebody were to create one of these. But, but, but, yeah. The way you're reacting, I'm imagining, it's like if somebody does it, it'll be Google first, which is maybe a good thing. I don't know.

Starting point is 01:03:22 It's like, it's really hard to know how it's going to play out. I read a whole blog post on our blog on our blog on Projecteleven.com. People can check out called Quantum War Games. And it was really fun because it's exactly, it's like the what if scenarios, right? You know, because why do people want quantum computers generally? Well, they're great for science. Two, like you can imagine governments that want to do espionage might want the ability to break cryptography too.

Starting point is 01:03:42 They probably don't want to reveal what they have. Certainly not if it's China or Russia. Yeah. Right. And, you know, but in private companies, maybe not Google, maybe some of these pure play quantum companies, like how are they going to make money? Well, one way would be to recover Satoshi's Bitcoin as if it were buried treasure, right? You're like, oh, it's a buried treasure.

Starting point is 01:04:01 Like Satoshi's not here. It's mine now. Right? So, I mean, that could be another scenario. So look, I think that there is just a whole bunch of uncertainty about how this is going to play out, about who's going to execute the attack, about how long a quantum computer will take. And again, because blockchains like Bitcoin fundamentally rely on this cryptography, like it's existential for them. That's one of the reasons like I founded Project 11 and we pursue this, you know, solving this problem very vigorously is because everything's on the line here. And we have to solve it for these chains like Bitcoin out of a future. Yeah.

Starting point is 01:04:29 Is there generally low optimism right now that Bitcoin developers will be able to react quickly? Enough? What's the statement about, like, I think Churchill said about democracies or the Americans, maybe where it's like they'll do the right thing when every option is exhausted. I think this is, look, I think this is true of decentralized networks like Bitcoin. I mean, their greatest strength is the fact that there's no single party that says how it works or how it should work. right? And this is encoded into how it was built by Satoshi as a as a reaction to the great financial crisis, right? So that's a great philosophical strength in the face of a crisis like this that demands a massive technical effort to overhaul. It's a daunting challenge because unlike, say, Google, which, you know, Google has said they're going to upgrade all their systems by 2029.

Starting point is 01:05:21 That's just, you know, someone at Google can make that decision snap, right? In Bitcoin, because it's a distributed community, everyone's kind of first has to agree there's even a problem. then everyone has to agree on the solution. But I think there's examples of places where blockchains, like, you know, I'll take Ethereum, have done amazing things, right? So one is they transition from an old system of consensus called proof of work to a new system called proof of state. It took four years, to be sure, but it involved thousands of people out of the world. And they did it.

Starting point is 01:05:46 They did it. The blockchain's been running. Ethereum is second large blockchain by market cap. So I don't think it's impossible, right? But I do think, especially in light of these two papers, these two breakthroughs, you just can't stop or you just can't wait. anymore before starting that process. What about the rest of the digital world? Because if Bitcoin is having problems,

Starting point is 01:06:08 then so many other kind of core institutions and companies, organizations, I imagine, would have issues as well. Maybe because they are centralized, there's easier to react, easier to kind of lock things down, but still need to upgrade overall. encryption.

Starting point is 01:06:29 Yeah, there's no doubt that other institutions need to upgrade, but in my mind, there's also no doubt that, you know, blockchains and digital assets are just the most vulnerable. I mean, one reason is obvious. I mean, Satoshi, uh, Satoshi is Bitcoin, so the founder of Bitcoin, who we think has gone away or died or something, you know, they have a bunch of their early Bitcoin that hasn't moved. There's a bunch of lost coins.

Starting point is 01:06:49 You know, all in all, you know, it's about to maybe 15% of all of Bitcoin supply is estimated to be lost. I mean, that's hundreds of billions of dollars. potentially in, right, in, you know, in market terms. So that's just a huge incentive that, like, let's take, let's take the counter example of, you know, if someone wanted to hack into a bank or something. And as you pointed out, banks are centralized. They can kind of react.

Starting point is 01:07:10 Also, the cryptography, the way that banks implement this cryptography is just kind of one of many layers of security, right? So it's kind of, this freaks, like theoretically someone tried to wire all the money out of my account, my bank would call me. Yeah, no, they literally have tape drives where, you know, they have cold storage, they print things out and they have a ledger and they can potentially, roll back, which is crazy to think about, but like they could if there was like a catastrophic hack, they could be like, look, everyone's just going back to yesterday's accounts and, you know,

Starting point is 01:07:37 that's better than the chaos that we were in. That's it. And that's not true for Bitcoin. All I need is one signature and all of Satoshi's or Coinbases or Binances. Bitcoin is mine. There's no fallback. There's no anything. That's how it was designed. That's the point. That was the point. Permissionless finance. That was so that's the challenge. So what is the state of the more faster moving coins, faster moving chains? Are you consulting or do you think you'll plan on launching something yourself that is quantum secure, quantum proof? How do you think this plays out? Because it does feel like, you know, I'm optimistic that I'm rooting for Bitcoin. I hope the devs figure it out quickly. You know, hopefully that happens. But it does just feel in terms of like the marketing of that. new project, there is a bit of a white space to say, we're the ones that are taking this particular feature most seriously. Yeah.

Starting point is 01:08:40 Look, I mean, it's kind of hard to know how things are going to play out, but the white space that we're occupying is we want to be the bridge for digital assets to the post quantum future. Right. Now, that doesn't necessarily rule out potentially having a platform to issue on top of at some point. But I think for now, our priority is more or less, you know, people have already decided. that things like Bitcoin and Ethereum and Solana and stable coins have value.

Starting point is 01:09:01 And I think overwhelmingly they would like to keep the things that they already value and just make them secure. So that's what we focus on. And there's no shortage of things for us to do because the protocols all have to get fixed. All the smart contracts have to get fixed. All the apps have to get fixed. And then all of the user wallets have to get fixed. And so again, going back to the fact that this is a stack and you're breaking the bottom

Starting point is 01:09:21 part of it. So I mean, we really focus all the way across. So we've done work with Solana, the Salana Foundation. We did the first post-quantum test net for them. We've worked with a few other protocols as well. We designed actually a new novel post-bunum algorithm designed for blockchains with the founder of Zcash. We've done that too. We collaborated with the EF.

Starting point is 01:09:36 And we're getting ready to launch our own post-quantam wallet as well. Yeah. Talk about the information flow. How much of the work that you do, the work that will be done by the Bitcoin Foundation, Ethereum Foundation, all the different developers, how much of that is open source by default or license? or just can be understood by other parties and implemented very quickly? Like how should we expect diffusion once this problem is solved to actually roll out? Will it just be like, oh, yeah, like we're just following the Solana standard.

Starting point is 01:10:10 And so we're just going to mirror that over onto, you know, whatever chain we're working on. Yeah, I think there will be diffusion. I think there will be, you know, consensus, if you will, around a certain subset of post-quantum algorithms, but I don't think it's just, you know, one and done because Solana is a very different system than Bitcoin, right? Bitcoin's digital gold. It's sort of meant to be slow. You know, and there's no apps on it. Salinas meant to be fast, right? Yep. And so the cryptography that works for Bitcoin might not be this cryptography that works for Solana. And this is actually, it was kind of the results of some of the experiments we ran with Solana. And look, this is one of

Starting point is 01:10:47 the challenges, right? And this is, again, by why we keep saying, this is like time to start as now, because we don't know how long it's going to take the migrate. Because, you know, these new algorithms, there's tradeoffs that come with them. And by the way, even if you choose to implement one, you need to test it and you make sure it secure, all this stuff. So have you tried to quantify or guess estimate what the quantum discount rate is on Bitcoin right now? Because it's an interesting thing where like if you own a lot of Bitcoin, there's a bunch

Starting point is 01:11:12 of people on the timeline today talking about this, they don't have an incentive to like really freak out and spread the narrative, but they have some incentive to say like, hey, we need to have a conversation. we need to make progress on this. But do you think that's factoring into price at all? Totally. I mean, the way I would put it is I think if this risk didn't exist, Bitcoin would be priced significantly higher.

Starting point is 01:11:34 So I think exactly what you said is right. You're like, oh, I'm not going to sell my Bitcoin because, you know, I mean, it's maybe not right around the corner. And I'm hoping people fix it. But I also think there's people that would maybe enter. And they're like, you know, Chimov has said this exact thing. He's like, hey, is this really digital gold? with this quantum threat hanging over everyone's head.

Starting point is 01:11:53 So I think if that threat was removed, then you know, you remove this cloud over that ecosystem and potentially, you know, you'd have a lot more people coming in and therefore price would be up. Yeah. And it's easy to imagine as you approach that 2029 mark, more selling pressure, more concerns if meaningful progress isn't made in the next two years. What countries have the most kind of advanced quantum projects outside of the U.S.? I can guess China's investing heavily here? Do they have their own retail quantum companies that are trading like crazy? What's going on over there?

Starting point is 01:12:35 Yeah, first off, I think definitively the leaders, both companies and research, is American. So I think we should be proud to be an American here. But look, I think one interesting thing about the way China has chosen to attack this is they've made quantum computing a priority. And what that means in China is, you know, it's like there used to be a lab at Tencent and if I do and a few other places and at some point, a Chinese Communist Party official came in and said, guess what? You guys all work for us now. And guess what? You're all working together now. And guess what you're not allowed to talk about it anymore.

Starting point is 01:13:05 And that's the state of things. It's kind of a, I don't want to say Manhattan project, but it's like that level of secrecy in China. and there's a legitimate question around how far back they are. So the best estimates that we have from quantum, like we have a quantum physicist who's an advisor to Project 11 that tracks generally resource estimates across the world. And their view is that China may be six to 12 months behind at most. And so this is, yeah, exactly.

Starting point is 01:13:29 That's not that far. Yeah, that's really true. You know, and so can we expect, you know, quantum computer in the hands of the Chinese Communist Party that maybe is more willing to crush dissent in places like Hong Kong to carry. much about the philosophical principles of Bitcoin and decentralization. If it serves their purposes to do otherwise, I don't think we can.

Starting point is 01:13:47 And so I think, again, back to the fundamental problem, uncertainty, right? And it's better to be safe than sorry. So we need to basically prepare today to prevent the crisis tomorrow to keep the trust in these systems. Well, thank you for everything that you're doing. Thank you for your service, both here and before. Project 11.com is the website, correct? Yep.

Starting point is 01:14:07 Yeah, you got it. All spelled out. Yep. Fantastic. Thank you so much for taking the time to come chat with us. We'll talk to you soon. Appreciate the breakdown. Have a good one. Great to be here, guys. Thanks. Cheers. Goodbye. Let me tell you about Vanta. Automate Compliance and Security. Vanta is the leading AI trust management platform. And without further ado, we have Kaser Yunis in the Restream waiting room from Applied Intuition.

Starting point is 01:14:30 He's the founder and CEO of the company. And we'll bring him in in just a second. We need a little bit of time. a little bit ahead of schedule. A little bit ahead of schedule. We need a little bit of time. And it's hard because there's not all that much short-term news. There is one news item that we can go through quickly. All birds just sold for $39 million.

Starting point is 01:14:54 The company was once worth over $4 billion with D to C Darling. Followed this company closely because I was building a D to C company at the same time. I was like, wow, they are really getting big. But it seemed like it did not particularly scale. It was more of a niche product potentially. And, of course, you know, margins and cost of sales creep in. And then everything collapses to private equity multiples. Did you ever wear a pair of allbirds?

Starting point is 01:15:23 Were they ever ever pull you away from Butega, get you in some allbirds? You know, it's Australian wool. You know? It's kind of like Italian leather. Australian wool. Yeah. There's something like that. No, I never, I never own a pair of birds.

Starting point is 01:15:38 Not even if you're visiting San Francisco. It's a great sign of respect. Did you ever have a pair? I probably did. I think I had one pair at some point. They were okay. They didn't, I don't know. They sort of like look okay and are comfortable on day one,

Starting point is 01:15:54 but then they sort of deteriorate a little quickly. This would be probably two to three trillion dollar company if the shoes had aura. Yeah. But they had not. They should have released a line of aura. It seems like they potentially had neck. negative war. Yeah.

Starting point is 01:16:11 And they got, and I mean, the stock suffered. They had to pay the ore tax. The aura discount. Massive aura loss. Yeah. I mean,

Starting point is 01:16:18 still a very interesting launch, very interesting, go-to-market, telling the story of where the materials are from. That was certainly a playbook that was adopted by a lot of companies. Showing,

Starting point is 01:16:30 putting the supply chain on display, basically. It was the right, very fit at the time. But people are not, not into it. The chat is not, is not happy about

Starting point is 01:16:41 Let's ask our dear friend Kayser, Ginesh, from Applied Intuition because he's here. He's in the TBPN Ultrodome now. Cacer, how you doing? I'm doing great. How about you guys? We're doing great.

Starting point is 01:16:52 We have to ask, do you own a pair of allbirds? What's your preferred shoe when you're walking around a factory like that? I don't own any allbirds when you're in a factory. You're going to have to wear. Yeah, exactly.

Starting point is 01:17:08 You have to have steel. There's no allbirds. Maybe they should. Maybe that's the comeback story for them. So they just, they were worth $4 billion. Now they're worth 40. Maybe the steel toe allbirds are what gets it done. A steel toe all bird would look fantastic.

Starting point is 01:17:20 We seem to be having a video delay. I think the team will work it out, but we can hear you. Can you hear us? Okay, great. Yeah, I can hear you and I can see you okay. Okay, fantastic. Exactly what's going on. Well, great to have you back on the show.

Starting point is 01:17:31 I'd love for you to just reset with us for the shape of the business, where the company is today. How big are you? Give us, you know, the broad strokes, and then we'll go into the partnership today. Yeah, thank you. Thanks again for having me. The company applied in tuition, we're a $15 billion company still doing what we were doing before, which is taking intelligence and putting into physical machines. Today, we have our first ever physical AI day where we're bringing lots of investors

Starting point is 01:18:00 together, bringing industry analysts, you know, bringing everybody who's kind of relevant in the field to talk about all the things. that are happening in physical AI. We're pretty strong believers that the future, you know, the next kind of big thing is AI going out of screens and going into the real world. Yeah, I couldn't agree more. Talk about the most recent partnership, LG.

Starting point is 01:18:23 Yeah, LG Intertech. We just announced this a couple of days ago. I don't know how many of your viewers know, but LG provides a lot of things. You're putting AI in TVs. That's what you're doing. Yeah. The AI is going on the TV.

Starting point is 01:18:37 No, we're not. And I'm going to be able to ask questions. The smartest, the biggest. No, that is not what we're doing. Much more serious. I mean, what's happening in the self-driving space is there is, now the models are basically working and they're figuring out. So really there's an aggressive downward pricing pressure of how to make self-driving cheaper.

Starting point is 01:18:58 The research kind of question is done, and now it's just an engineering question. And that's just another way is saying it's a cost question. So companies like LG who are doing, you know, sensors at really, really large scales and really, really cheaply, you know, they're entering the space as well. We're working together with them on self-driving. Yeah. So, yeah, take me through, when people think self-driving, they always think Waymo, Tesla, but the, the market map of, like, products that need autonomy and that would be defined as vehicles. Give me some examples. I mean, you're standing in front of something. I know that it's very broad.

Starting point is 01:19:37 what's in this partnership and then what else are you focused on? What's adjacent and what's on the roadmap? Yeah. So I think what's different about us versus, let's say, vertical players like a Waymo or a Tesla is we provide this, you know, AI across all types of machines. So you see ag machines behind me. If you guys were here for physical AI day, we take the same models and we put them in defense. We put them in commercial trucks. We're running driverless trucks in Japan right now

Starting point is 01:20:09 that are going into commercial operations in the next quarter. We are running in mines. So both all the way from Arizona to Australia. So our hypothesis basically is these technologies, what is self-driving or the underlying operating system, they're so expensive and they're so complex to build and maintain. The only way that you really make this a viable business is that you actually spread this across lots of manufacturers

Starting point is 01:20:35 and lots of industries and lots of use cases. I mean, our kind of crazy claim to fame is, you know, our company's almost 10 years old, and we've preserved basically all the capital we've ever raised. That's amazing. Which is kind of, you know, it almost sounds like BS, right? Yeah, it's crazy. The whole mantra is, you know, raise a lot of capital.

Starting point is 01:20:54 And we're a real AI company. We have real AI bills, and we've figured a commercial model, which is a lot of scale. We have over 1,000 engineers, and so we're one of the, if not the, biggest physical AI companies on the planet. That's obviously also commercially viable. But it all goes back to that simple thing is like you want to distribute all this cost

Starting point is 01:21:15 across lots and lots of companies, lots of lots of verticals. What about shared learnings? Like is a team that's working on mining? Are they able to find a breakthrough or discover something you can apply to trucking in Japan? Like is there a lot of... Bingo. Absolutely. That is the heart of the company. And so there's all the, what you described is like shared learning kind of broadly, but there's also technical advantage. What we've seen is taking data,

Starting point is 01:21:39 which is just obviously also not obvious, but taking really, really diverse data from a mine actually makes our self-driving car system better. And taking data that we have from our self-driving car in Germany, you know, makes our defense work better. And so it really is, it really is a core to our strategy. Yeah, I've heard so many stories about that where like there will be like exactly

Starting point is 01:22:03 one instance of a chicken being chased by a woman on a tricycle in the training set. And so it's very hard for the machine learning system to actually understand that if you see that exact scenario, you got to slow down. But that's the nature of big data and machine learning and these scaled systems. And it's not, it sounds crazy, but it's not that crazy to imagine some weird scenario that you see in a mine actually teaching you something that you could use just on a normal street. Yeah, maybe getting a level lower just so, because me being an engineer always bothers me to talk in pure generality, because you tend to mix them, this thing.

Starting point is 01:22:42 Just getting to a level lower, what you're really talking about is anomaly detection. And it's not necessarily like, you know, you need to see the chicken running across the road in Thailand, and that's going to make the mind better. But what's really happening is models are getting a better understanding of the physical world around them. And the kind of parameters around them. If you look at, you know, kind of the last kind of generation, I'm crazy to say last generation, but really large language models, large language models really improve with diversity of data. That is really like, you know, kind of a big breakthrough.

Starting point is 01:23:13 And, of course, scaling laws. All of that stuff is being brought in to the physical world. Yeah. And we're powering that. Yeah, I mean, truly no one would have predicted or, I mean, of course, some people did predict, but I would have never predicted that, like, including poetry would help a model get to, like, solving math. Like, I would just see those as different things. I'd say, put the poetry team over there, put the math team over there, but actually bringing all these things together worked really well.

Starting point is 01:23:37 Play out the counterfactual for me. You haven't, you haven't been a high burn company. You haven't been super capital intensive. If you'd done vertical integration and built the tractor behind you, that would have been extremely capital intensive, correct? Is that, like, impossible? Well, nothing is impossible. There we go. You know, my undergrad was at this obscure school called the General Motors Institute.

Starting point is 01:24:02 And as the name implies, it's really about automotive. It's like the West Point for automotive. And when you spend a lot of years in factories, as I have, there are some deep lessons that get imparted into you. And one of those lessons is, holy crap, these factories are extremely cost-intent, the capital-intentness, and they're extremely complex. and the strengths of Silicon Valley are actually don't quite overlap with the strengths of building a large factory. Now, in terms of the core question, we had Mark and Dresen here today, and we talked about this. Mark was one of our first investors and has kind of been along with us with the entire ride. I mean, all the way to the presentation today.

Starting point is 01:24:44 And we asked them this question about vertical, horizontal, what do you see happening in AI? What do you see happening physical AI? And the punchline is, you know, all of our values that applied intuition can be reduced down to to two words, radical pragmatism. And if there are verticals that we think that we should be a bit more vertical in, we'll do that. And I think it's kind of a false tradeoff to say what we do in, you know, trucking is what we're going to do in construction, what we do in agriculture is what we're going to do in mining. What we're really trying to do is bring intelligence out into the real world. And each of these verticals are facing really, really different problems. You take, you know,

Starting point is 01:25:20 with a tractor behind me, the average American farmer is 58 years old. There's a, you know, nobody coming to replace that person. And so what is going to happen? Because, you know, if you take that person, their kids have left and they're often not coming and taking over the farm, like maybe in previous generations. So that farmer needs, you know, we don't need to teach them how to use Claude Code. That's not what's going to change the farmer's trajectory. What's going to change the farmer's trajectory is the machines are intelligent and they're working harder and smarter on on their behalf, and so he can run an entire farm

Starting point is 01:25:53 with a swarm of machines. And that's not, you know, that's not too far into sci-fi. One of the key components here that we're doing, and we believe, is you need to abstract that hardware and software away. We, as technologists, you look at like your laptop and your phone, and you kind of

Starting point is 01:26:10 take for granted the miracle that exists. Android runs on thousands of hardware devices flawlessly. So that's also something that applied does. We're just abstracting the hardware and software. Once you do that, you can make every machine, you know, intelligent. Have you tried to estimate the economic impact, assuming you guys, you know, stay at the, you know, at the current kind of improvement rate or accelerate as the technology kind of starts to diffuse

Starting point is 01:26:35 in some of these industries like trucking and mining and agriculture? Like, what are the downstream impacts? I mean, there's such a debate right now around what impact will AI have on the economy? so much of the economy is like moving physical things around, producing things, shipping them. Exactly. Let's separate a little, because economy is such a generalization. So when you're talking about, like, you know, code complete and white collar work is very different than, you know, trucking, where there is a huge labor shortage.

Starting point is 01:27:07 It's very different than in mining where, you know, people don't want to go live in kind of remote areas doing 12-hour shifts. I mean, literally labor shortages are preventing construction companies. from, you know, collecting billions and billions in revenue. So these are industries where AI can't get there fast enough. Yeah. It's a very different calculus than a kind of, you know, I think what the normal narrative is. And then we're super obviously excited about that.

Starting point is 01:27:31 Let's take defense as a particular example. It's a very salient example. We don't need more warfighters in harm's way. We need less warfighters in harm's way. And no warfighter wants to go out into that ecosystem where autonomy is really becoming the dominant thing. And so I think the way to think about this impact in the physical world is it's a lot less resistance. There's a lot more pull.

Starting point is 01:27:55 Now, the first question you asked is the size of impact. I don't want to, you know, sound like I'm pitching my own book here with, you know. I'm asking you to, I'm asking you. I want the biggest number. I want the biggest number. The numbers are absurd and ridiculous. But I can tell you this much. If you think about, you know, the way I think about, you know, I used to be a Y Combinator before I was the CEO and, you know, ran the firm.

Starting point is 01:28:18 funded lots of interesting companies. And one of the analogies I used to use to help founders understand market potential, market sizes. Yeah, I grew up in Detroit. You're sitting in the Detroit Metro Airport and you're sitting in a gate. You look around. How many of those people are like really deeply using Claudeco? I mean, frankly speaking, not many.

Starting point is 01:28:37 Not we'll probably be using something like ChatGPT, some variants of that, maybe Gemini. But how many of those people drive? How many of those people work at construction sites? how many of those people ride in buses, how many of those people serve in our armed forces, the point is a much, much larger group. And I feel a little, again, the engineer in me feels a little awkward saying these kind of pitching these things,

Starting point is 01:29:01 but I think the market for physical AI is way, way bigger, purely because the surface area is much bigger, and it's compounded by the way that, the way technology diffuses with phones and laptops creates this like, rabid, you know, competition that you see in, you know, that you're seeing in all these kind of subspaces, right? Yeah. In physical AI, you've got to kind of know what's going on in the car business.

Starting point is 01:29:27 And I'm not saying, you know, I'm not gatekeeping and saying, yeah, you've got to go to the General Motors Institute to build technology for the car business, but you bet your bottom dollar, it helps. And we're doing that across a bunch of industry. I think it's, you know, I'm as confident about the companies ever before. You know, the question, we always get asked this question. And why the hell did you raise all this money, you know, almost a billion dollars? He's going to keep plowing away in the bank account.

Starting point is 01:29:49 We're doing over a simple, a simple reason. Because if we need to, we can invest very aggressively to take opportunities that we think we can accelerate, you know, beyond just traditional organic growth. And so far, that's work. It's not to, you know, promise the future that we won't. But those are kind of debates we have every single day. Yeah, that makes sense. Well, thank you so much. I just want to say I can see the path to $100 and then a trillion dollars in run rate.

Starting point is 01:30:14 I agree. Well, I mean, Waymo, you know, a company that, we love them. They're a local, you know, we're also in Mountain View now, Sunnyvale. That company, you know, is a great company, but is burning a lot of capital and is a smaller revenue base than us and just raised at $126 billion. I mean, I love those guys. I mean, we have so many friends there. I'm not, I'm not trying to talk poorly about this. No, we love Waymo, too. It's very impressive what they're doing. You know, 15 that we're at and 100 and 22,000, I think I think you got room to run. Massive, massive. Yeah, we have room to grow. Tell Mark, tell Mark, you're ready. You're ready for the big one.

Starting point is 01:30:54 Believe, believe me, everybody wants to show, you know, it's somewhere. I feel like it's foie gras where they want to keep putting money, you know, money into the company. We don't need any of my work. That is the best analogy for Avenger Capitalists. Yeah, yeah. We are the farmer stuffing the goose. We have our own, we have our own farm, you know, and we're making. our own money, so that that's really great. And frankly

Starting point is 01:31:16 speaking, I mean, like I said, Waymo is great, but it's just Robotaxies. Yeah, yeah. And that's a small... So much broader. Go to, go to Warren, Michigan. Yeah. And you just go to the party shop in the corner and say, hey, are you excited about Waymo? I don't think, you know, it's not hit the masses yet, which just shows obviously Waymo's growth potential, but also shows, I think, how big physical AI is going to be.

Starting point is 01:31:40 Yeah. Well, thank you so much for taking the time to come chat with us. Thank you for having me again. I hope. Fantastic. I'll talk to you soon. Thanks. Goodbye. See you.

Starting point is 01:31:47 Let me tell you all about public.com investing for those to take it seriously. We've got stocks, options, bombs, crypto, treasuries, and more with great customer service. And we're talking to them later today. But first, we have Sebastian Malibi. He is the author of The Infinity Machine. Sebastian, how are you doing? I'm doing great. Thank you.

Starting point is 01:32:05 Thank you so much for time. This has been, you've been on John's dream guest list for a lot. Dream guest list for a long time. We met maybe four years ago at a talk you gave around the power law. And it was very fascinating. I love that book. This book goes in a different direction. And after that conversation, I asked you, probably the worst question you could ask to an author,

Starting point is 01:32:33 I asked you, what's your next book going to be about? Because you had selected venture capital. Venture Capital had done very well. And I presume that whatever you would pick would be a great investment category because you seem to be a good picker. You told me that you were thinking about biotechnology, biotech investing. You went a different direction with AI. Is there anything I should read into that? Well, I always kick the tires on a few ideas before I settle on one.

Starting point is 01:33:03 And I think it took me from the parallel coming out in February of 2022 to summer. to somewhere around the summer, maybe August, when I really settled on AI. And then it took me another, I don't know, three months to get the courage up to go and pitch Demis Asabis on the idea of giving me a ton of access so I could write this book. And then I got lucky because I pitched him. And one week later, guess what, ChachyPT came out? So what I thought was maybe a fringe subject went mainstream super fast. Super fast.

Starting point is 01:33:35 What was the response with the team? What was the process? Obviously, he's extremely busy. He also sleeps at very random times. We can get into that. But what was your actual interaction? How much time did you spend? What was the research process like?

Starting point is 01:33:50 So once he agreed to be in, he was really in. It took about six meetings, two with him, four with his team, to get them to agree. And, you know, my pitch was, hey, if you say in every speech you give that artificial intelligence is the greatest invention in history. That means you're way too important not to have a book about you, and it's going to happen. So you better get used to it. And also, if you're going to upend our lives, you know, change the way we think about ourselves as humans because it's a rival form of machine intelligence.

Starting point is 01:34:25 You know, you better explain your motives to people, otherwise they're not going to accept it. So that was the pitch. He agreed. And then once he agreed, we would meet, like, for two hours at a time. We would go to a pub near his home in North London, and there was a kind of secret staircase at the back, go upstairs, kind of dusty little room with nobody else there,

Starting point is 01:34:46 and we would sit there for two hours, usually. And he would just riff, you know, talk about philosophy, movies, computer science, neuroscience. I mean, he's such a range of a person, and by far the most fascinating person I've ever written about. Wow, that's high praise. How do you think about balancing the biographical timeline, the history, the financial impacts, which you've covered in the past? When I think about the stories that you've told in the power law about venture capitalists, there's a little bit of their philosophy, but it's a lot of how the deals came together, fly on the wall.

Starting point is 01:35:29 I love that type of storytelling, but this goes a little bit of a different direction. So how did you think about balancing all the different perspectives that you could bring to his story? Yeah, I mean, I always want to do the personality, the figure, but then the landscape behind as well. So it's always a mixture of, you know, you need a character who drives the story, but the story's boring if it doesn't mean anything. So you have to link it to larger stuff that's going on in capitalism and how society is going to change and all that. And, I mean, in this case, because Demis is, who he is, and he would just riff in these extraordinary paragraphs of like storytelling and theoretical stuff.

Starting point is 01:36:14 And, you know, it's just so fascinating that I did give him the microphone more than I have in any other book. I mean, I basically quote him at some length, you know, and it's broken up with me asking him questions. And so I'm kind of the reader's lens through which to see Dem is talking. And I'd never use the first person. really before in my other books, but in this case, those 30-plus hours I had talking in a pub with this extraordinary man, that was the gold dust I had. So to really make the most of it,

Starting point is 01:36:46 I did have these passages of us talking together, which kind of interspers the more analytical or narrative bits of the book. How, after the transformer model dropped, what was Eli that gave us a reaction and why did open AI get ahead? You know, I cover all that stuff as well. But I do have these passages where you see events through Demis's eyes because I think it's worth doing because he's so unusual. What was your understanding of AI or view on AI in 2022 before you meet Demis for the first time?

Starting point is 01:37:24 Are you aware of the doom arguments? Were you a believer in the technology? Did you think it was 20 years away, 100 years away, two years away? Like, where were you before this book? Because I feel like it probably changed you. Yeah. You know, I had met Demis before at tech conferences because of the power law and writing about venture capital.

Starting point is 01:37:47 I would go to tech conferences in Europe and he would sometimes be there. And I actually cheekily, you know, raised the issue of hedge funds and especially, you know, the one Renaissance-Tenolns. The main CEO, Peter Brown, had done a PhD with Jeff Hinton about AI back in the day. And of course, I knew that Dennis would know that. And so I said, you know these guys who used deep learning and applied it to markets? And that got his attention. So I talked to him a bit.

Starting point is 01:38:21 So I knew that he was amazing. I knew that the technology was ripe in the sense that he'd produced this string of breakthroughs, Alpha Go, defeating the human Go champion, then Alpha Zero, which was even stronger. Then there was Alpha Fold, which won him the Nobel Prize for predicting all the shapes of protein in nature. So there was a series of good models. And what they all had in common was,

Starting point is 01:38:45 they dealt with insane amounts of data, crazy combinatorial spaces. Like in Go, there's 361 first moves you can make. Okay, that's way more than chess. and so unscrambling Go and the strategies in Go was much harder than chess and I knew that these breakthroughs were not just cool in themselves but they represented the coming of a time when machines could make sense of an almost infinite amount of data and extract meaning and hence the term the infinity machine

Starting point is 01:39:18 the title of the book and hence my enthusiasm for writing about it and you know so I knew it was breaking out I knew Demis was amazing what I didn't know is was going to break out literally the week after I met him and pitched him on the idea. What has surprised you about how the industry overall has evolved since you started meeting with Demis? Because in some ways, I have to imagine you kind of maybe it hasn't been that surprising at all, even though a lot of the growth is impressive. But do you feel like you had a view into the future from those first conversations in the pub? Yeah, I mean, I think, you know, I was lucky that the meetings were bookended by, you know, going to see Demas sort of maybe the third meeting or something, chatheed by this point had gone viral, and him saying to me, okay, this is war. You know, you could see his competitive side come out, right? This is war. These guys, he said, have parked the tanks in my front yard. You know, I'm fighting back. So you could see that. And then after that comes the merger between Google Google.

Starting point is 01:40:24 brain and Mountain View and the deep mind team in London, so the two kind of halves of Google's AI talent base are united. And then I think you get what, you know, a business school professor is in the future going to write about is kind of like a textbook case in how you make a merger successful. Because everyone knows the mergers are hard. And when you do it with eight time zones between the two teams, one in London, one in California, and you're doing it, in the middle of this knock-down, drag-out, you know, capitalist fight over building LLMs, this is going to be, you know, most people would say this is going to fail. And I would come to Silicon Valley while I was doing the book,

Starting point is 01:41:05 checking with my friends at, you know, different venture capital shops. And they'd always say, I game over, open AIs won. And, you know, the surprise is that within two and a half years, de Misty Service's, you know, Google Deep Mine model, Gemini, was doing better on the rankings than the open AI model. So that was an incredibly fast to come back. Yeah. How do you think about the importance of being like a business person or a deal guy in AI?

Starting point is 01:41:35 It feels like Demis has this quote, he doesn't want to grow that part of his brain, referring to some legal negotiations that took a number of years. Solomon. Oh, oh, is that Mustafa? No, actually, that was Demis saying. I don't want part of this, this brought my brain to grow. And so, and so.

Starting point is 01:41:54 Take away these legal briefs. I completely get that. And it seems incredible for him to stay in the research mode, build the research organization. And yet, because of scaling laws, we're in this weird regime, in this paradigm where sometimes doing a deal to Marshall an extra 10 billion of compute actually does unlock a new capability. And it is almost in the research track. And I'm wondering how you perceive the relative importance or, or demonstrate. perception of the relative importance of these sort of like business dealings that might be more critical path to AGI than the Demis of 2021 might think.

Starting point is 01:42:41 You know, I would say that the single most important business relationship in the world today is between Sundar P. Chai, you know, CEO of Google and Demisiziz, who's running the AI brain trust. Because Sundar has Demis' back. He deals with providing the resources, supporting the notion that you're going to spend all these tens and maybe hundreds of billions on compute. That's Sundar's, that's what he delivers.

Starting point is 01:43:11 And he gives Demis the oxygen to then just go do the science. And sure, he has to build products. But I think, you know, he said to me several times, Temis, we've got to a point where building a product like Gemini, is in fact advancing the progress towards AGI. There's no tension between the two. If you had stopped your AGI research 10 years ago and taken a sidetrack to build some widget,

Starting point is 01:43:36 yeah, that would have been a waste of time. But now that it's so mature and you're actually, to build the next LLM, you've got to kind of figure out, you know, a reasoning model, then it's going to be a genetic, and then you're going to be scaling it even more and all this stuff that we've seen. And this is genuine scientific progress as well as product advance.

Starting point is 01:43:57 Yeah. Do the products also help sort of shift the culture in Google? I'm interested in understanding this concept of like AGI pilling, becoming a believer in the Demis worldview of the impact of AGI, what artificial intelligence will do. that mindset has to diffuse through Google. The chat GPT viral moment clearly had an impact. I'm sure agentic coding has had a similar impact. But what has Demis's role been in being the culture carrier of that belief in AI progress internally? Well, I think he's used all his sort of visionary communication skills to unite the Mountain View team and the London

Starting point is 01:44:46 team. And I think the one sort of organizational contribution he's made, which is sort of super powerful, is that from a long time ago, Deep Mind had always two different cultures going on at once. There was a kind of blue sky research for scientists. You get a lot of freedom. You could publish papers and all that. You know, go go find what you want to find. And then there were moments when Demis decided that if you pushed really hard on a particular product or a particular project, you could get a, you know, breakthrough achievement that would really shock the world.

Starting point is 01:45:23 And so he did this repeatedly with, you know, AlphaGo and AlphaFold. And this was sort of like his judgment, scientific taste being applied to knowing when, you know, the moment was ripe to really go for it. And once he decided that, there was, you know, the blue sky research

Starting point is 01:45:39 kind of bottoms up stuff. You know, that went out the window and it became a top-down strike team, they called it. and in a strike team there was a lot of top-down direction and kind of everybody had to work on the same code base you couldn't just like go off and code your own experiment on the side you had to be contributing to the main one

Starting point is 01:45:56 and that drives towards a team is driving in a united way towards an outcome and I don't think Google Brain had that Google Brain had much more of the bottom-up stuff and there was no strike team component and so Demas brought this strike team team idea. And it came from

Starting point is 01:46:17 video game design. Earlier in his life, he'd been a builder of video games and he, in fact, started a company doing that. And so this was like how you ship product and that's been a key insight for Gemini. Yeah. Google and Gemini have every

Starting point is 01:46:33 advantage just due to the massive cash flows that they have from their other businesses. How do you think that has impacted the culture of deep mind given that they have something very real to lose, right? It's not just about the, you know, maybe Demis's personal desire to be at, you know, be at the forefront of this research. But if you're not successful, then you lose one of

Starting point is 01:46:58 the greatest business, you have the potential to lose or have your kind of core business. Google search. Yeah, Google search in such a big way. Yeah. Yeah. And I think, you know, Google search stands for a more general point that, you know, Google's whole reputation stands on. providing reliable information. And so the penalty for screwing up is very high. You've got this very valuable company. You don't want to spoil its reputation. And so I think they were more worried about, you know,

Starting point is 01:47:27 releasing a chatbot fast. And so they had prototypes of a chatbot in the fall of 2022, and they didn't want to release, and then Open AI went ahead and did it. And so that kind of forced their hand. But their first instinct was, this is going to hallucinate this is going to do bad stuff

Starting point is 01:47:47 we can't afford that hit to our reputation and you know Demis was quite honest with me in saying well you know the surprise was actually the public's quite happy to play with the tool that hallucinates you know they still it still went viral you know so we should be less inhibited

Starting point is 01:48:03 but that was an example of how being at Google could be a kind of inhibition in moving ahead how do you how does Demis and he's always told a very optimistic story about AI. I love him as a science communicator as a, as an optimist. How is he interfaced with the effective altruist community, more of the AI doom crowd?

Starting point is 01:48:29 Does he, because he doesn't talk about it that often, but does he think about it often? He does think about it. In fact, you know, he met his co-founder Shane Legg at an AI safety lecture, right? They bonded in a safety lecture. Yeah. And so right from the beginning, safety has been a big part of the agenda. And when Demis sold his company to Google in early 2014, part of the deal was you're not going to use this technology for weapons ever.

Starting point is 01:48:55 And you're going to have a special independent oversight kind of committee, which will decide on AGI deployment because we don't want that to be just up to the corporate board of Google. Now, you know, he's slipped on some of these things, particularly the military staff. But he has been thinking about safety, and, you know, the question is, what has he got to show for it? It's all very well to think about something, but what can you deliver? And I think, you know, this is why towards the end of my book, he's talking to me quite honestly about how it's a sort of paradoxical moment. He's doing great as an AI inventor. He's doing terribly badly as a sort of AI steward, as making it safe.

Starting point is 01:49:37 It's just, it turns out that there's a race dynamic, the race dynamic includes. it's China, you know, how do you control this technology when everybody is racing to jam it out the door? Yeah, it was interesting. Last week, we were talking about how, you know, Bernie Sanders has come out with a push to pause data center development. And he quotes Demis and some other lab leads talking about how they would agree to a pause if other countries were kind of in agreement on it.

Starting point is 01:50:08 And Bernie obviously left out the fact that. I don't think any lab lead could see China pausing on development. So how is your personal definition of AGI evolved over the last few years? Because everyone has their own definition. Half the people that come on the show says it was six weeks ago. Exactly. And then yet we're still in so many of these kind of more high-level conversations, lab leads, talk about race, you know, where AGI is six months away, you know.

Starting point is 01:50:39 You're completely right. Everybody has their own definition. And so my solution is not to have that discussion. I mean, who cares? You could say right now, Gemini is artificial, it's general, it's intelligent, game over. But just a definition thing. I think the other one which is sort of usually fruitless is,

Starting point is 01:50:58 is AI conscious? Could it become conscious? What is consciousness? Nobody has a good idea. So that's just sidestep those things. I heard one good idea, which was something around training a model specifically that would hold back all data and all and all training data related to consciousness and the idea of consciousness. And so it cannot just pull from the archive and reference or simulate consciousness.

Starting point is 01:51:25 And if it develops consciousness from that and can talk cogently about consciousness without having any training data ever seen the idea of consciousness, then maybe that's conscious. I don't know. It was just an interesting thought experiment. I don't know that anyone's actually run the test, and I don't know that I would even accept it if they did, but it is something to think about. Did you feel an acceleration in your personal writing process due to AI? I felt an acceleration in my learning process,

Starting point is 01:51:53 which is sort of what I do before I go interview people. So because all of the computer science papers are basically on archive, and recently there's been less publication, but it's certainly up to about 2022, you could go see a scientist either at Deep Mind or one of the rival labs and just have a conversation with a model about, okay, this person has done four papers, what was the connecting thread, why is this person different to the one I interviewed last week?

Starting point is 01:52:20 That was a super efficient way of getting up to speed, and I didn't worry that it might be wrong because I was going to speak to the human and cross-check it. But that was helpful. Do you think Demos is having a home base in the UK, in what ways do you think it would have helped or hurt the company so far? Like, has it been beneficial from the talent war standpoint? I'm sure, I'm sure lab U.S., some of the other lab leads have taken a trip out to the UK.

Starting point is 01:52:52 Mark Zuckerberg's hosting nightly dinners for AI leads at his house, which is just a couple blocks from all the other labs. Can't do that if you're in, if the researchers are in the UK. Right, yeah. I mean, there is movement across the Atlantic, but I think the deal is, if you're in London, is a little harder to recruit people, but once you've got them, they're probably stickier than they would be if you're in Mountain View or somewhere. You know, I think Demis has stayed in London because actually he is weirdly patriotic.

Starting point is 01:53:21 You know, he comes from this mixed up sort of, you know, a Greek heritage father, a Singaporean Chinese mother. In a way, that makes him a typical Londoner. Yeah. Because London is really a melting pot. But, you know, he stays there because he feels he wants, he believes in sort of British social democratic values. It's made me ironic to an American audience. But, you know, actually, he thinks it's more egalitarian in Britain than it is in the US. You know, the US, if you go to the Deep Mind Office in London, you know, you go past the sort of public spaces like this kind of fountain with toddlers playing in it.

Starting point is 01:53:57 And there's kind of free movies in the summer by the canal. And then you get to this green space where the kids from. the local housing project to playing soccer. And then you get to the Deep Bine Office. And it's hard to imagine you'd find that on the way to the, you know, the Apple headquarters or something. You know, it's just a different vibe.

Starting point is 01:54:18 Could you ever see Demis as CEO of Google or what do you have to do too much paperwork? You know, this gets to the heart of the digotomy about Demis. It's so difficult because he's so many different things at once. I mean, you know, he is this Nobel Prize winning scientist. who would love to just do pure research and he often would sort of fantasize to me about, hey, I want to retire

Starting point is 01:54:40 to the Princeton Advanced Institute of Advanced Studies and do what Einstein and Oppenheimer did before me and go there. And I think he really means it when he says that. At the same time, he also wants to be in command of an AI lab and he likes the capitalist competition. So if he had the opportunity to be chief executive of the whole of Google.

Starting point is 01:55:06 I suspect he's too competitive to say no. But who knows? I mean, there is that science side. So it's genuinely unpredictable. He probably doesn't know himself. Were you left personally optimistic after this process? About just our AI future broadly net positive impact from AI? I mean, clearly there's a lot of upside,

Starting point is 01:55:29 especially in medicine and pharmaceutical discovery. I think you have to be honest and say there's also downside, significant downside. And as I continue to do the research for this project, you know, I became more worried about the downside because, you know, people like Jeffrey Hinton, I went up and spent two hours in his kitchen in Toronto and sat there debating. Not necessarily whether machines would be more intelligent humans. Obviously that they will be. but whether the machines have a motivation to harm humans and he's very persuasive

Starting point is 01:56:04 in arguing that they will I mean my point was humans evolved over centuries to survive to pass on their DNA we're hardwired to survive that's why we fight each other machines aren't like that

Starting point is 01:56:19 so why would they attack us why are you so worried Jeff and Jeff is like well imagine you've got the super powerful AI and it's going to be attacked by the enemy AI and you have to defend it So you tell the AI, if you see a cyber attack coming, you've got to fight back, you've got to defend yourself. And now all of a sudden you've given your AI a survival instinct.

Starting point is 01:56:38 And so don't tell me that evolution has to happen as it happened to humans. The evolution can happen in a machine way. But these systems are going to want to survive. And they're going to be more intelligent than us. So we're in trouble. And I think you can't dismiss that. So I'm kind of both worried and excited at the same time. I think that's how humans generally respond to all technology.

Starting point is 01:57:02 And if we didn't take that trade and move forward with both the excitement and the scariness of technology, if we didn't take that, we'd be still living in caves. So in some sense, the story of Demis is like, you know, the story of all of us, but magnified 10x. There's a documentary that was just released or might be releasing right now that features an interview with Demis, the AI doc. and it spends more time talking to all the different lab leads and voices in the industry, more focused on the doom question.

Starting point is 01:57:36 Can we be apocalyptic? Should we be optimistic? But what I found most interesting was that the creator of the documentary, you know, summed up his full takeaway and said that AI is a Ponzi scheme. And I'm wondering if you got any, any vibes that everything will collapse, that this is, just not financially viable. No, my view is that there's no AI bubble,

Starting point is 01:58:02 but there's only just an open AI bubble. You know, in the sense that the technology clearly is getting better and better pretty fast, right? You know, we had the first chat bot in 2022, and it hallucinated, then they killed the hallucination, then they had longer context windows, then they had, you know, multimodal systems that could handle all video and pictures,

Starting point is 01:58:24 and then they went to reasoning models, and now we're getting agentric models and now next there's going to be world models that will be built into these things. This is a lot of progress in just three and hour of years. So I think it's accelerating in progress and therefore it's not a bubble. But what is true is that it's super expensive to develop.

Starting point is 01:58:47 And if you're not attached to a really deep pocket, like Demis is attached to Sundar, you're in trouble. because I don't think Open AI can raise enough money to bridge from today when they have a very popular chatbot but almost none of those customers pay for it to some future where the product is stickier somehow and they can charge money.

Starting point is 01:59:11 And so I think Open AI has been running two simultaneous experiments. One is with a new frontier technology and the second is how deep our global capital markets and they already raised, you know, 41 billion last year which was a record for any private fundraising, bigger than any IPO, by the way, as well. And so, you know, kudos to Sam Altman for raising that much money. But can you pull that trick, like, on a bigger scale every year

Starting point is 01:59:40 until 2030 when they hope to break even? No. And that's why they're cutting products like SORO. Except for right now. Because they just raised the $100. $1.20. But if you look at the $100, it's kind of smoke and mirrors. A lot of that is contingent on, you get this money if you go public, you get this money in the future, you get this money in kind in terms of computer or something.

Starting point is 02:00:04 The 100 wasn't really 100. Isn't there a little bit of a dynamic where you could wind up with like an anti-Google alliance? Maybe there's, you know, there's like tension between the industry and Google. This is like the foundational myth of the AI industry and the AI labs broadly, although they of course have fractured. many, many times at this point. Yeah, I mean, you know, of course there's always rivalries. You know, one might say people gang up on Nvidia. You know, that's the occupational hazard of being the leader, right?

Starting point is 02:00:37 Yeah. I think they'll deal with it. I mean, I don't think it's a winner-takes-all-market, by the way. I think that, you know, there'll be space for others. Yeah, that makes sense. Last question from my side, then we'll let you go. did you have any takeaways or kind of ideas

Starting point is 02:00:54 around the diffusion of physical AI and robotics? Did anything stand out? Do you have a strong opinion there? Right now it feels like we've entered the sort of software singularity. But we just had KER from applied intuition on

Starting point is 02:01:11 and we're talking with him about how autonomy and AI is diffusing through the physical world. But I'm curious if you had any takeaways. I mean, look, I think that, you know, one thing sometimes people don't quite understand is that large language models and the transformer architecture that underpins them is super consequential for lots of applications, not just chat pots. And so robotics is being improved by this technology. And, you know, I fully expect to see a huge breakthrough, you know, over the next two or three years with the capability of robotics. And so I think that's going to be the big story. I kind of agree with the guy from KSar you had before,

Starting point is 02:01:56 that the movement of atoms is going to be affected as much as anything else. So that's part of why I don't think this is a bubble. I think, you know, the potential in, you know, this super powerful AI is enormous. Yeah. Well, thank you so much for coming and joining the show. It was a pleasure talking to you. The book is The Infinity Machine. It's available everywhere.

Starting point is 02:02:18 books are sold. Thank you so much. Fantastic cover too. Yeah, beautiful cover. Thank you for having me. We'll talk to you soon. Have a great rest of your week. All right. Goodbye. Thank you guys.

Starting point is 02:02:28 Let me tell you about fin.a.I. The number one AI agent for customer service, if you want AI to handle your customer support, go to fin.a.i. And we will kick off the Lambda Lightning round. Let's see. Oh, look at this. We got everything.

Starting point is 02:02:43 This is amazing. Let's bring in Forrest. Forrest from Somos. Welcome to the stream. How are you doing? Hello, guys. How are you doing? We're doing great. First time in the show. Please introduce yourself. What a setup here.

Starting point is 02:02:56 This is a great setup. This looks fantastic. I come well-armed with a bunch of nerdy stuff from the team, all the things we're building. No, I guess. Amazing. Yeah, break it down. Yeah, kick it off. Let's see, where do I start?

Starting point is 02:03:12 I'm Forrest. I'm a fancy plumber building infrastructure from scratch down here in Columbia to make internet way better and make compute and everything kind of work well in Latin American beyond. So very weird journey, but making the fastest internet in the world at the lowest cost is kind of a summary in a very short nutshell. Amazing. You have a lot of fans. I got a bunch of texts from investors that were excited for you to come on.

Starting point is 02:03:38 What were you doing? Before we get into Somos, what were you doing before this? Dude, I came to Medellín when I was like 18 years old, basically just dropped. out of high school, it started building stuff, and ostensibly came to visit a friend for a couple weeks, and that was eight years ago, and here I am. So I made websites. I kind of took a very non-traditional path, and it's led me to doing a bunch of weird stuff here. That's actually a non-traditional path. Normally, when somebody comes on and says they had a non-traditional path, it's like, you know, Stanford to a meta-internship, a Google internship, a VC internship. But very, very cool. What,

Starting point is 02:04:15 But yeah, breakdown, like, you know, Somos, you're raising a series B today. Like, how long have you been at it? What initially, I can kind of guess what the initial inspiration might have been. You're building digital products, it sounds like, and we're probably frustrated with internet speeds, but what's the backstory? No, I came to Columbia in 2018. I got roped into helping people build this, like, blockchain incentivized, blah, blah, back when everything was going to be blockchain in like urban slums here in Medellin.

Starting point is 02:04:47 And as those blockchain projects happened, everyone got bored really quickly. So they just left me with all the equipment. And I just kind of became fascinated by how do you build connectivity in slums and didn't speak any Spanish and know anything about telecom and just started tinkering. And the first couple of years were me like literally living in a slum here in Medellene, building internet, stringing stuff up in the middle of the street. And kind of bit by bit, I just became fascinated by the concept of like internet. is the most basic thing for the modern world,

Starting point is 02:05:15 and we just sort of assume that it's been solved, and really we haven't done an engineering in the last 30 years. It's the same underlying architecture that John Malone was building in cable cowboy days. Yeah. Every time I go travel to another country, I always look up who the biggest industrialists are

Starting point is 02:05:31 and who the richest people in the world are. It's always the people that built the railroads, the mines, the telecom infrastructure, the Wi-Fi, the internet, the power lines. It's always like the stuff that once you install it, It provides value. Yeah, it sounds like you're doing a lot. What is what is in your strike zone of things that you want Somos to take on

Starting point is 02:05:51 versus where do you work with external partners? Like what is what is the kind of core path? This is kind of the insanity of Somos. So we literally do everything from like we interface with the submarine cables. We built like a nationwide backbone crisscrossing the country. We like make the Wi-Fi route. So like the things that go inside of the thing here is all PCBs. Oh, that's a Wi-Fi route.

Starting point is 02:06:10 I thought that was just a pretty lamp. That's crazy. So this is literally the router that goes in customers home. So instead of being some like ugly, blinky box, it's like a beautiful lamp. That's super cool. You're like, wait, does it have to be an ugly box? No one thought of this? It's incredible.

Starting point is 02:06:25 Like the internet is like literally the most incredible machine humanity's ever built. And we're just relegated it to being this like ugly piece of infrastructure and kind of our ideas like, what if it was dope? That's amazing. So yeah, like how do you like how does the coverage map like spread out? Everyone's familiar with those like AT&T and Verizon coverage charts of like the map of America. Do you have to go city by city, block by block? Are there ways that you can, like, how do you actually scale out to reach an entire coverage area? So I literally have like a thousand plus employees cabling the streets.

Starting point is 02:07:00 We have like linemen and installers and they're all at work directly for Somos. And this is kind of the insanity of what we're doing. And it's been a bit of a like slow flywheel to get ramping. But then at the end of the day, you're building this actual moat because it turns out it's really hard to build new infrastructure from scratch. So we literally are cabling the entire city from scratch with a new type of fiber to connect people to faster, cheaper internet. Yeah. In what ways do you think it's easier to do in a place like Colombia than the United States and vice versa? Yeah, I think this is one of the interesting things is like the U.S.

Starting point is 02:07:34 kind of looks archaic in comparison to some of the stuff we're building here. So like my base plan for a customer is like $12. a month and is a gig and we're giving people 10 gig connections and soon 100 gig connections in their home. So the kind of weird thing that has happened in the U.S. is we sort of believe Comcast is sacred so we don't let people go build new infrastructure and we're almost, there's a world where it's like 10 years from now we're like shit, the U.S. has like third world internet infrastructure and what we thought of as the third world has infrastructure. Let's us do all these crazy things that AI is enabling that you couldn't do before.

Starting point is 02:08:07 So I think this was inversion happening kind of the same way as there were no landlines in Africa. We're kind of leapfrogging all the crappy old cable and just building internet as it was intended back in the ARPA days. That's amazing. How do you get people to move to Columbia to work on this? What's your pitch? Not saying anything wrong with Columbia. It's just it's a long way away. It's a long flight. The time zone's not too bad, but it's 75 degree other year around. We have awesome engineering. It's like San Francisco without the fog and we get to just build it whatever the hell you want. It's kind of like cowboy Western technology, galtz, galtz, in the middle of the jungle. That's amazing. Last question for me. I'm sure you got to ask this

Starting point is 02:08:50 in all the VC pitches. How is Starlink rolling out? How is satellite internet fit into this? Is that a competitor? Is that a compliment? A lot of people in America sort of have both. But how does that fit into the picture? I think the big takeaway here is I would sell your Comcast or telephonic or telemix stock because I think what's happening is Starlink is attacking lower density areas moving stuff mobile. Somos is basically building think of Starlink for city so we're building a pure play just the best internet for dense urban environments and I think there's like a density threshold where below that Starlink will win above that a thing like Somos will win but the realistically like if I'm on level if I'm on the third floor of a 15 story building in the heart of

Starting point is 02:09:38 the city, like, you're going to win on reliability, connectivity, speed, cost, all of that, right? Just base physics will be cheaper and way better and more reliable. Like, even Elon will say this. He's like, Starlink isn't really for cities. It's for everywhere outside of that, right? Okay. Yeah. So, like, basically unaffected by everything there because of physics.

Starting point is 02:09:56 Always good news. Mutual friend, Zach asked me to, told me I should ask about how kind of AI is impacting bandwidth needs and how that factors into the opportunity for you guys. Yeah, I think we're going to look back and say, like, damn, the infrastructure we have currently is far underbuilt for the future of applications with AI. And one of the things that we are thinking a lot about in Somos is, what if you extend the data center to everyone's end home, all the crazy application that you can build on top of that, not only just speed, but reliability, redundancy, low latency. I think there's a world where compute lives in data centers and we're streaming your OS. Think of, like, super chromebooks to everybody, and that that's a world where you make compute way cheaper and way better. in a way that historically wouldn't really be doable

Starting point is 02:10:41 in traditional telecoms. And I think this is back to like, there's a world where Latam has orders of magnitude better compute than parts of the US just simply because we rebuilt the telecom infrastructure from scratch. Wow. What other markets are on the roadmap? Yeah, well, we're heading to Mexico in the very near future.

Starting point is 02:10:59 And I don't know, there's some interesting neighbors of Columbia that are becoming open again, that it would be a new place to expand to from Colombia. So I think Somos Caracas might be a thing in the future. Before we hit the gong, another mutual friend, Aaron asked me to ask you about the high frontier. What's up with that? Yeah, I mean, I'm obsessed with this vision of the future as it used to be.

Starting point is 02:11:25 And I think one of the things is stoked for me right now is like it feels like we're building awesome things like new ship factories and new infrastructure in the world that are like building a future as it used to be. Like we used to think the future was going to be awesome. And we kind of got okay with a very boring, muddling kind of version of it. And it feels like we're now turning this wave of like, let's go build orbital space stations and the Lagrange points. Let's build fleets of autonomous vehicles.

Starting point is 02:11:51 Let's build all these amazing things from scratch. So it's like build infrastructure, rebuild the world, make awesome things happen again. It's fantastic. How much did you raise? We just raised 40 million in this round. There we go. Who came in? So Ribit led this.

Starting point is 02:12:11 We had Bracket Capital and then USB, Kazik, and Y Combinator all kind of doubled down from the past. I love it. A great way-gray-C story, too. Yeah, fascinating company, fascinating industry. Just, yeah, I love it. Did you pop up to the West Coast for the race, or did you make everybody visit you? It's a little bit of both. We get people to come down to Medellin.

Starting point is 02:12:36 They're definitely not regretting when they come visit. We have some fun adventures driving the countryside. I love it. Well, thank you so much for taking the time. Great to me, Forrest. I'm sure we'll be back on soon. Have a great day. Cheers, guys.

Starting point is 02:12:47 Goodbye. Let me tell you about Phantom Cash. Fund your wallet without exchanges or middlemen and spend with the Phantom card. Our next guest is Dino from Serronic. He's in the restroom. Let's bring them in to the TB in Ultram. Dino, how you doing? Good, guys.

Starting point is 02:13:02 How you doing? Thanks for having me on. Thanks so much for joining. Great to finally have you on. Yeah, give us the State of the Union. What's going on with Seronik? Yeah, likewise. You may have seen today we announced a $1.75 billion financing round. There we go. Thank you. So do we need to build some ships? What's going on?

Starting point is 02:13:24 We've got to build some ships. We're super excited for this. I mean, it is a true byproduct of the execution that the team has delivered on over the last, not just 12 months, but the last really 36 months since we started the company. I mean, our team is truly A plus. If you look at where we were just a year ago, we came off a $600 million financing round. What that let us go do is we opened our first

Starting point is 02:13:51 shipyard. We launched Marauder which is 180 foot autonomous and unmanned ship. We then announced a multi-hundred million dollar project into that shipyard to scale production of Marauder. And then Coursera, which you see behind me right

Starting point is 02:14:07 here, our small USB platforms. We've already taken production of those. well into the thousands. So now as we look forward, what we're going to do over the next 12, 24, 36 months with this capital raise is we're going to accelerate that. We're going to accelerate the production,

Starting point is 02:14:23 accelerate the deliveries of our vessels to the U.S. and our allies around the world. We're going to launch new products. We're going to build new ships. And then we're going to go and build new shipyards. We're going to invest in the shipbuilding industrial base in this country to the tune of billions of dollars. We're going to create thousands of.

Starting point is 02:14:41 of jobs and ultimately we're gonna we're gonna unlock production rates that we haven't seen in this country since World War II and we're doing it in a very technology first software first approach. You mentioned USV is that unmanned surface vehicle? Unmanned surface vessel. Vessel, got it. And then so walking through the the use of boats used to transport people, now we put equipment on them, how versatile are these vehicles, what are the different use? use cases are some weapons platforms or some just ISR capabilities? What is the range of utilities that the armed forces will get out of these USBs? Extremely virtual. The whole point of the platforms we're building is actually for them to be modular by nature.

Starting point is 02:15:31 And actually we actually try to change the acronym around a little bit. USVs like unmanned surface vessel. You know, when you look in the past, it's really like a remote control platform. Yeah. Very similar to a predator drone. We use ASV, autonomous surface vessel, because what we're building at Serronic is not just one-to-one control, but it's true maritime autonomy to then go and deliver these platforms at scale and be able to control them at scale, meaning fleets of hundreds or thousands of vessels

Starting point is 02:16:01 through the most advanced software on the planet for the maritime domain. And then when you're looking at the missions, the use cases that you mentioned, it really all just boils down to scale, persistence, and risk reduction. Right? How do you operate large numbers of vessels? How do you do that continuously in what's becoming an increasingly dangerous maritime environment? And then how do you offer like real capability to commanders while keeping sailors out of

Starting point is 02:16:32 harm's way? Keeping people safe is very, very critical and a key point to what we're building here. I don't want to diminish the work, but I'm curious about how. How much of a challenge is it actually to create an autonomous surface vessel because it feels like when you're driving on the road, there's so many random conditions and the car can flip over. But boats, it's a little bit safer, I would feel like. But am I missing something there? The other issue is you have people, other boats that are trying to kill you. Okay, okay.

Starting point is 02:17:03 Maybe that's it. But I'm just thinking like a plane, you know, if it doesn't land perfectly, it'll crash. Like boats, you know, they just kind of rock through the water, but there's obviously more to it. So what went into making it fully autonomous? There's a lot of, yeah. So the ocean is just a completely different environment altogether. So we deal with a lot of different challenges. Sure.

Starting point is 02:17:22 One of the challenges that's really different from self-driving cars is, yes, there's a lot of complexities on the road. Yeah. But that singular car really only cares about how it gets to its end destination. It doesn't care about how the other hundred cars get to. its end destination as well. Sure. And how they're all working together collaboratively on a mission. Oh, and then you start throwing in six, eight, ten foot seas, high winds,

Starting point is 02:17:49 enemy environment, some of the things that we're seeing now. And like, whether it's the Black Sea, the Middle East, and we're anticipating in the Indo-Pacific, like, those are very, very complex challenges that we're solving at Serronic. Yeah. What goes into setting up a new shipyard? Do you have to kind of co-locate around existing shipyards? Can you kind of stand something up, you know, totally independently?

Starting point is 02:18:15 How does that work? Yeah, I mean, when you look at shipyards in the shipbuilding industrial base in this country, it's really how do you bring on net new capacity? You're not really co-locating next to anything because a lot of that capacity has really atrophied over the last 30, 40, 50 years. So what we're focused on is building new shipyards and then building the ecosystem. and the infrastructure to support that as well through partnerships and vendor relationships.

Starting point is 02:18:43 But one of our main projects and one of the things of a large part of this capital is going to go towards is Port Alpha. Right, we have a shipyard in Franklin, Louisiana, mentioned that we're investing hundreds of millions of dollars in that yard, but we're looking at a brand new shipyard, building this from the ground up, completely greenfield, investing billions of dollars

Starting point is 02:19:03 to 10x the size of our existing yard. right, to bring on new scale, new capacity, and rebuild the shipbuilding industrial base from the ground up. That's what's needed because if you go around the country right now, you go to places which used to be shipyards, and you'll see apartments and condominiums that are called naval yards. That's not just the name they came up with. It actually used to be a shipyard. So what we're doing now is we're investing in the shipyards of the future, again, to produce out a scale that we haven't seen since World War II. What's the best way to get a job at Seronic?

Starting point is 02:19:40 You can apply on our website. I mean, we are hiring. We are growing. I mentioned how amazing our team is. What we're doing is absolutely critical for the country. The team comes in every single day. The work they're doing is changing the world. And so if you're a top engineer or looking to get into the defense tech space,

Starting point is 02:19:59 please, please apply. Everything we're doing is absolutely critical. We grew the team from 200 to 13. hundred people over the last 12 months. And that's, that's only the beginning, guys. That's amazing. Well, thank you so much for coming and breaking it down.

Starting point is 02:20:15 Have a great rest of your day. Yeah, incredible progress. The chat says just put the S-1 in the SEC mailbox, DEN. We'll talk to you soon. Good to see you. Thanks, guys. Look forward to following up.

Starting point is 02:20:27 Let me tell you about Octa. Octa helps you assign every AI agent a trusted identity so you get the power of AI without the risk. Secure every agent, secure any agent with OCT. and our next guest is already in the restrib waiting room. We got Will Ahmed from Whoop. Whoop is back. How you doing?

Starting point is 02:20:44 Good to see you again. Welcome back. Hey, guys. Thanks for having me. Give us the update. What happened? How are you doing? Things are good, thank you.

Starting point is 02:20:52 We announced a round of financing today, our Series G, $575 million round. So, oh, okay. Is this, is this the capital that you finally need to make a bust down whoop? diamonds from the factory. That's what I'm looking for. Can you do anything for me? You know, we do. We do have some premium offerings in the mix that are going to be just right for you, actually.

Starting point is 02:21:19 Perfect. Very happy with product development. Jorny wants a bust out. No, no, seriously, give me the updates. What's changed? Where do you want the product to go? And yeah, I am interested to know. Are more collaborations in the works?

Starting point is 02:21:36 Do you see that as an important point? or are you just focused on more and more channel partners, more and more distribution, more growing because the product's pretty dialed at this point? Well, look, it's been an extraordinary 12 months for the business. You know, we ended 2025 with over 100% year-over-year growth, you know, $1.1 billion in bookings run rate to end the year. Our membership is growing around the world. We're operating in 60 markets. We've got WOOP members in over 200 countries.

Starting point is 02:22:07 We've launched medical grade technology now coming out with blood tests around the world. And so whoops really become this broad-based health platform. And you can see that in the financing announcement today. You know, we've got the history of whoop with the world-class athletes. We've added now, LeBron James is a new whoop investor. We've got Cristiano Ronaldo on the cap table, Virgil Van Dyke, Matthew Vanderpull, some of the world's very best athletes, really from every sport, are now on the whoop cap table. And then in addition to that, we've got a bunch of great existing investors continuing to support the company,

Starting point is 02:22:51 collaborative fund, IVP, Foundry Group, and more. And then we've brought in some sovereign wealth funds from the GCC, proud to have Mubadala and QIA and 2.0. So really some of the biggest funds in the world that are, I think, phenomenal long-term partners. And then lastly, to the point about health, you know, we've added the Mayo Clinic is an investor in Woop, one of the premier health institutions. There we go. That's a niche. That's a rare Pokemon, a venture world. I haven't seen, haven't heard of them on a capital. I'm not ripping a lot of seed checks while I see Demo Day. Yeah, they haven't, they haven't done a lot of investing, but we see a ton of synergies from research and medical capabilities.

Starting point is 02:23:35 ability standpoint. And we also have added Abbott as an investor and, you know, really one of the best medical device makers also in the world. So it's a phenomenal mix of investors. And I think we've been able to achieve this because of the remarkable growth that we're seeing as a company. And I think also just the tailwinds around health and longevity. How do you think your marketing mix will change over the next few years? Because I'm seeing $575 million, LeBron James, Christiana Gianna Rinaldo, that has like crazy Super Bowl ad written all over it. At the same time, your tech native, I could imagine going way further into AI generated, personalized ads, pushing the performance marketing further.

Starting point is 02:24:20 Like, what appeals to you? How do you think you'll change? What will stay the same? What will change over the next few years from a marketing perspective? Well, we never want to lose sight of the fact that we started in sports and we've built this aspirational performance. lifestyle brand. And so that'll really be at the core still of a lot of what we do for WOOP. But we also now have a product that, you know, can detect whether you have AFIB and tell you your blood

Starting point is 02:24:45 pressure every morning and help you do blood tests. So it's just a much broader health platform than it's ever been before. And our marketing needs to reflect that. You know, one of the areas, I would say, of maybe not weakness, but opportunity for Woop is brand awareness. You know, we don't have massive brand awareness around the world. And so this capital is going to give us the gunpowder to really grow broadly, internationally. And so you're going to be seeing a lot of whoop wherever you consume content. Super Bowl ad incoming. Yeah.

Starting point is 02:25:18 I mean, if you want to reach me specifically, maybe a partnership with an athlete like Johnny Knoxville might work. It just might make sense. We'll do a whoop live heart rate on some of the stunts. Stunts. I think that would do the trick. I'm curious, like, how, who, like, how do you guys think about improving accuracy at this point? Like, I'm assuming, like, so much progress has been made over the last however many years, but there's still always incremental progress.

Starting point is 02:25:54 Like, you can always be more accurate. How do you think about that? Is that still, like, a top priority? is it accurate enough at this point that there's better things you can focus, you know, the core energy of the team on? I mean, I think big picture, we want the product to be getting constantly smaller and smarter. You know, we want it to be an aspirational product in the sense that it's something cool that you wear on your wrist, or we want it to be something that disappears throughout your body and can essentially be invisible. And so, however, you can gather this data super accurately, have the,

Starting point is 02:26:33 the data sets grow in nature, more sensing, more capabilities, more medical approvals, the better. And I think that's going to continue to expand our TAM. I think it's going to continue to deliver deeper insights for our members. So we're going to be leaning in pretty heavily on research and development. You're going to see a lot of very powerful sensing coming from WOOP in the years to come. How is the peptide boom affecting Woop? Well, I think the underlying reason for the peptide boom is that people want to take more control of their own health. And they're sort of generally frustrated with the tools that they've had to improve their health. And so that leads in different directions. Peptides being part of it, supplements being

Starting point is 02:27:20 part of it, concierge, doctors being part of it, AI health coaching being part of it. But broadly speaking, it's, I think, good for whoop that people want to take more control of their health. And 10 years ago, I would talk about health monitoring and people would say, well, that sounds like something niche for athletes. And now, you know, everywhere I go, people want to talk about how they can improve their sleep or improve their VO2 max or what is heart rate variability. So there's just clearly been a cultural shift to care a lot about your health. And, you know, longevity has become one of the most common reasons that people use the product. Our health span score, the whoop age score, has become the most screenshoted page. in the WOOP app.

Starting point is 02:28:05 Yeah. So clearly you've got people who want to show off how old they are, or, you know, who want some counseling for how old they might be. Yeah. Yeah, that makes a lot of sense. Yeah, there's an interesting dynamic with the various health platforms where there's like kind of an incentive, there's like a weird incentive to like, you know, measure, like say somebody's, you know, their chronological age versus their biological age

Starting point is 02:28:30 make it like lowers and people are more likely to share. Like, I've seen, I've seen some people have, you know, come in and say, like, well, my biological age is 19. I did one test that said I had the mind of a five-year-old. It said, it was testing my brain health and it said that I had the. Is that good or bad? It's not. It's extremely young. I'm way over five.

Starting point is 02:28:52 So I assume it's good. I think we've built the most credible biological age metric because we did, first of all, we did it in partnership with the leading longevity. Institute out of California and then the Buck Institute. And then we show you in great granularity each of your biometrics and what's improving it and what's not and by how much. So here's a trivia question for you. What percentage of people on whoop do you think have a younger whoop age? Oh, interesting. I mean, if it was perfect, it would be 50-50, I would think. 70% because people that use whoop are much more likely to be healthy. Oh, true. Okay. So let's go with 70. What is it? it's 55%

Starting point is 02:29:36 but what that means is 45% are older on whoops you know they're early in their loop journey you guys have done a lot but this whole show is really dialed in no so 45%

Starting point is 02:29:50 are yeah so you know but that shows that like it's not just telling you what you want to hear it's gonna push you yeah Yeah, yeah, and I only brought that up originally because I've seen some of these come out and I'm like, okay, there's zero shot.

Starting point is 02:30:10 This person's biological age is lower than their chronological age. Based on the life we live. Not every platform, you know, platforms are just kind of every platform is going to run their own kind of algorithm to determine that and not necessarily working with the Buck Institute. Yeah, exactly. Well, very cool. Fantastic progress. Great to get the update. Congratulations.

Starting point is 02:30:29 Congratulations. Congratulations. the whole team. I feel like just in the last year, like the world has woken up to this kind of category and your guys' progress is a testament. And I still think it's, I still think it's very early. It must be fun to walk down the street for you. And, you know, someplace like L.A. Oh, yeah, you probably see them everywhere. And, you know, I'm sure it's like every 10th person has a whoop band on, but that means there's nine, nine or so. Yeah, it is, it is a trip seeing seeing whoop in the world. And, you know, for people who decide to take the hard path of building

Starting point is 02:31:03 hardware, it's an amazingly rewarding feeling when you see a physical product that your team's built in the world. So I will say that's a very gratifying thing. But you guys, you guys owe me a question here. You haven't asked me. What is it? What's the question? Aren't you going to ask me if the job's done? Oh, yeah. Is the job finished? Jobs not done, guys. We've got to keep going. Thank you. Thank you for that. Great stuff. Thanks. I appreciate you guys.

Starting point is 02:31:34 Keep it up. We'll see you at NICS soon, I'm sure. Yeah, get ready. The chat's gonna be your strongest supporters. Thank you so much for taking the time to come chat with us. We'll talk to you, say, well. Have a great one. Goodbye.

Starting point is 02:31:46 Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI, own the data platform that's power. It's continuing our lightning round. You know who we got? The CEO of Public.com. Yanik, how are you doing?

Starting point is 02:32:05 Hey, guys. I'm doing well, how are you? We're doing fantastic. Look at that stuff in the background there. I know. Do you recognize any of this stuff? Oh, yeah, yeah. You got the whole head to toe.

Starting point is 02:32:13 Head to toe. I don't recognize what Jordy is wearing. I don't think... This is new. This is the new polo. New. You're right there. Top left.

Starting point is 02:32:22 You got lead left. There's still more. There's a room on the wall. There's plenty of mail. room on the walls. Anyway, enough about our merch. Let's talk about your business. Walk us through the launch today.

Starting point is 02:32:33 Yeah, so today we launched AI agents for investing. Yes. The easiest, safest way to put AI agents to work directly inside your portfolio. Yeah. And the way it works is pretty simple. There's now an agents tab directly within the public app. You chat with an AI to set up agents that monitor markets, move money around, and even execute trades for you all within the app, right?

Starting point is 02:32:55 So there's nothing to install from a security standpoint. Obviously, everything stays in a safe, controlled environment because it's within the bridge. Can I install Axios? No, do not do that. That is such a niche joke. Everyone's going to think you're talking about the publication. Yeah. No, but I mean, it's been really fun.

Starting point is 02:33:15 I have a bunch of agents running now on my account. It's been really awesome to see how it's changed my behavior as an investor, right? John, relax. I like the sound of that. I knew you were going to do that. We got a little John in the studio. No, so, so, so, uh, make, makes total sense. What, like, if people are, like, uh, already signed up, which they should be, how,

Starting point is 02:33:37 what, what should they, what, what, what's the first thing that, that they should try to, like, set up or experiment with? Like, what, what was your first few agents that you've set up and, and, like, continue to keep running? Because I'm assuming you can effectively, like, run them, you can retire them at different points. Exactly. Exactly. The first one I set up was, um,

Starting point is 02:33:55 One that checks the oil prices before the market open and buys protective put options every day as a hedge. Sure. If there's a spike in those, I call it the, I'm tired of seeing red due to war agent. And so today that didn't fire. Thank God. You know, I have another one that just looks at my bank accounts and automatically sweeps any cash in excess of a certain amount into my bond portfolio. So I'm always yield maxing. You want to be yield maxing always, especially while rates are still high.

Starting point is 02:34:24 Yeah, that makes sense. And then I got some more advanced stuff. Like I got one that scans the markets for opportunities to write cover calls. Okay. Across my top position. So if there's a low risk opportunity to make like 20 grand a month, selling options premiums, I instructed it to just go ahead and place those orders. So that just rolls every time, all the time.

Starting point is 02:34:46 And I don't have to think about it. That exact strategy was the first thing a private wealth manager ever pitched me in my career, like a decade ago. They were like, and they had like a guy that did it. And you had to have a lot of money to, like, access that. And there were minimums and stuff. You should probably check on that guy after today's launch. No, no, no. But, so, so I, there are obviously, like, incredibly advanced things that you can do with these agents in, in the market.

Starting point is 02:35:09 I'm also interested in just driving behavior change because a lot of folks that I know are earlier in their career. They don't want to necessarily take a ton of risk. The biggest lever on their financial future will just be seamlessly funneling money from their paychecks into something as simple as VTI, and then they can do something more advanced down the road. But what does it look like in terms of the best practices or best functionality for just creating a set it and forget it? I want to make sure that every time I get paid,

Starting point is 02:35:42 money's flowing into the market. How easy is that these days? Well, I think with agents, that becomes really, really simple, right? I think this is sort of the whole point. You know, the stock market has always been about manually entering orders, right? Like, you do all this work and eventually you end up manually being like buy 200 shares of Apple at this price. Yeah. I think that user interface is now shifting to something like, um, increase my position if valuations compress 15% from here. Yeah. You know, and it stays within my

Starting point is 02:36:11 defined risk tolerances and so forth. And so I think it changes how people think about and manage their portfolios in a pretty profound way. And we do see it as a user interface shift like, you know, So the interesting thing about this industry is every technology kind of had their model of brokerage, right? Like we started on the horn and then the dawn of the internet gave us the discount broker with mobile came the Neo broker. And I think now with AI, it's the era of the agenic brokerage. But what's uniquely interesting about this shift is every previous shift was about streamlining

Starting point is 02:36:43 the process and reducing the responsibility set of the broker, you know, to basically just trade execution ultimately. But it actually used to be much more full service. To Jordi's point, there used to be a guy. I used to call you, used to pitch all these kind of ideas, risk, you know, trade ideas, et cetera. I think with the identical brokerage model, you're reversing back to that. And it's much more full service than obviously any human service could ever be because this thing can like write an algorithmic trading script for you in 10 seconds.

Starting point is 02:37:11 They can do taxiles harvest. They can instantly analyze risk. Sure. And so it's a shift back to a world where the brokerage plays a much larger role than just trade execution, it sort of goes into the realm of maybe a quant and a financial advisor. And that's what we're excited about the brokerage playing a much bigger role through essentially a genetic AI. George?

Starting point is 02:37:34 Can it pull in external data sources yet? I'm thinking like fear and greed index. Like should I, could I set something? Or even like unemployment rate or CPU. If you have like max fear that you want to buy on days when the fear. But that might not be an actual. like instrument in that you can buy and sell directly. Yep, 100%.

Starting point is 02:37:56 Unemployment data, CPI, FedCuts. Like one that people have been kicking around today is, you know, whenever there's a Fed cut, move money, obviously, out of my high-yield cash account in public, put it to work into high-growth tech. Yep. We like the sound of that. All right.

Starting point is 02:38:10 That makes sense. There we go. And so there's a lot of those. Yeah. CPI, like the Fear and Greed one was requested today. I think that's coming in. in the next couple of days. And so really, it's about getting all that into this natural language interface and just

Starting point is 02:38:27 letting people kind of instruct AI to do this on their behalf. Last question for me about AI on the platform. What have you, what are the capabilities? What have you learned about users educating themselves about various financial instruments within the public ecosystem? You know, okay, I see a company. You're going to surface price-dearnings ratio, market cap. the usual stuff.

Starting point is 02:38:52 But there's so much more that you can ask in LLM these days about what does a company actually do? What is their strategy? How, what's the history of this company? Do I, what's the founder? Like, these things are perfect for LLMs and you can vend those in. But what are users actually using what's the adoption been like? What have the learnings been?

Starting point is 02:39:12 Yeah, I mean, I think one of the tall task and application layer is to sort of figure out, obviously, what are users want to achieve? Yeah. And then which model and kind of harness. is best suited to achieve that purpose. But then also focus on like, what are we uniquely able to deliver, right? So we know what you own.

Starting point is 02:39:30 We know what you used to own. Yeah. We know what your risk tolerance is. By the way, we also know the difference between what that actually is and what you said it was when you signed up. Yeah. And we have real time data feeds of everything, right? And so I think as a product builder,

Starting point is 02:39:45 those are like some of the situations where you can really create a magic moment that general purpose LLM's can't. And I think a lot of that comes because we just have a lot of that kind of history about how people like to invest, what questions they've asked to your point in the past about the PE ratio or what the founders like, et cetera, because we've been basically running a research assistant since 2023.

Starting point is 02:40:08 And we're only a six-year-old company, so it's already for sort of like half the time that we've been live. And so we've been able to gather a lot of data for the last three years that we can now kind of repurpose. listen to this. What's your theory right now? It's obviously day, day one, but do you think in the future will get, you know, more volatility because you have, like, financial institutions that are effectively using, like, agents or algorithms to do trading? And then you also have retail. So when you get, like, a new CPI print, you know, you have, you know, even, you know, additional trading activity

Starting point is 02:40:44 off of these single events. Like, do you think this is something in the future that, that everyone will effectively have like a handful of agents running just naturally in the product and then some people you know be like you know maybe prosumers people that are more into it will have you know many or or at some point is everyone you know at what point do is it like you know old fashion to be just like you know buying a stock yourself even with a button totally i actually think we will look back at like tables and buy buttons and feel that's a little antique maybe already uh 12 months from now but i think the effect is things will get priced in faster, for sure. On the institutional side, they've used some version of AI for the longest time, right?

Starting point is 02:41:29 But then at the same time, retail have gone from being like 5 to 25% of the market. And on the retail side, folks haven't been as fast to react always, right? They haven't been a discipline. They're not necessarily glued to the screen 24-7. And so, you know, they can't always react as quickly as they want to. And agents obviously change that, right? And so I do think that there might be, I mean, it's a little bit like whether it's crypto prediction markets, there's always a little bit more of sort of an alpha opportunity or an ARP opportunity in the early, early days. And then over time, it becomes more mainstream and that kind of fades away.

Starting point is 02:42:05 And I would suspect that this follows something like a similar pattern at least. Yeah, I've just been thinking about it because the content on X is primarily user generated, at least the big accounts. It means that an event happens in the real world. It gets reported on or it pops up on a website or you get a newswire and then a human takes that and puts it on X. And then this trade, even the majority of retail volume is like flowing off of like that human seeing the news posting it. And then you get this sort of trading activity. But in a perfect world, you see news and then you go to your broker and the right trade has already been made on your behalf. Exactly.

Starting point is 02:42:44 And anybody that's not adopting this will just be like, well, I miss kind of, I miss opportunity unless you want to get out entirely. Totally. Speaking of X, a fun one is, that was from there was if DJT says bye, just buy. That's actually really smart. I think that's probably backtests very well. The backtests extremely well. What a crazy timeline we are in. Well, thank you so much for coming on and breaking it down for us.

Starting point is 02:43:14 Great to see you. I miss you. Let's, let's be sure to hang out. Let's hang soon. We will. Yeah. All right.

Starting point is 02:43:20 Bye. Bye. See you. See ya. Yeah. Let me tell you about Century. Century shows developers what's broken and helps them fix it fast.

Starting point is 02:43:27 That's why 150,000 organizations use it to keep their apps working. And without further ado, we have Ryan from Crosby. How you doing, Ryan? Welcome back. Hey, guys. Good to see you again. Dude, you're on here like every week. It's getting ridiculous.

Starting point is 02:43:42 Yeah, it's getting a bit much. Let me guess. Let's schedule the next one. You should just bundle all the fundraisers together into like series alphabet. Then you just do it all the ones. But I never get to see you guys. It is more strategic to break them up. But tell us what happened.

Starting point is 02:43:57 How much did you raise? What's going on? We have two announcements. The first announcement is we've raised $60 million led by Lux. The announcement, thank you. The second announcement is we did some math last month and we have now closed contract worth over a billion dollars for our clients. It's a big milestone for us. million dollars for the client.

Starting point is 02:44:19 Very cool. Is there a power law on there? Was there like one sneaky $950 million deal? Did you get one percent of this new Open AI round in there? Somebody was like, I'm going to review one clause.

Starting point is 02:44:31 And you know, I'm getting, no. It sounds like there's a lot of lawyers using it. That's right. I mean, these are small deals,

Starting point is 02:44:36 so it's a lot of velocity. I think definitely my corporate law friends are like, that's like one deal for me. That's not interesting. But for us, it's a really good milestone. Yeah.

Starting point is 02:44:45 So, yeah, take us through, I mean, it sounds like the shape of the work that is being augmented by Crosby these days. Yeah, so, you know, we're about a year and a half into it. We announced our seed around 230 days ago. We do commercial agreements. These are the sales agreements, MSAs, NDAs, VPAs for like fast-growing AI companies.

Starting point is 02:45:09 Now we're branching out. But since the beginning, we've been a law firm. So we have about 30 lawyers here who I'll give a shout out to are just the last the quarter, they're working so hard for our clients getting the deals closed, and we close deals fast, like in a couple hours. And so this idea has just taken off with a lot of tech companies now and now even bigger clients who just want to close faster. How have you been processing? You're kind of, I would say, very tapped into how well the models work in different roles. I'm curious your view on how application layer legal AI companies will

Starting point is 02:45:46 do compared to just the labs themselves, right? I feel like every other day on X, somebody says, wait, this LLM seems to be doing just as much as, you know, this application layer company, you guys are using all the models internally for your own internal tools. But like, how are you processing kind of what feels like, well, in the same way we saw with CodeGen, where you have application layer companies and foundation model companies, and then you have foundation models with their own applications. I'm assuming we'll see that in legal,

Starting point is 02:46:22 but how have you been kind of processing it? So, I mean, that is the question we have to ask ourselves every day. We think that code generation, more or less, is kind of like a year and a half ahead of the sort of non-self-verifiable domains, so I think it's not like math or code, and law is one of those, but it's a huge service area. And our sort of like insight a couple years ago was, let's not think about these sort of like AI co-pilots that are kind of like

Starting point is 02:46:50 you need equivalent of what cursor was a year and a half ago when you kind of hit tab to auto-complete but these long-form agents with bigger context that could do a full job end to end. And if you have agents that can do entire swathes of legal work, then the best thing you should do is start a law firm because you're selling work to clients, not, you know, fractions of work or kind of helping them along. And in truth, we were ahead of the models. And so we were selling something that like we weren't able to fully automate. And as the models are progressing, we're seeing more and more. of a compounding advantage as, you know, we have more and more contracts that we're processing.

Starting point is 02:47:21 We have more and more lawyers that we're able to help us, you know, tune judges and, you know, like, create better agents. And so we're able to just do end-to-end work in a way that, like, if you're just selling a legal, you know, co-pilot, I think you're going to face a lot of competition just from the models with no customization. Yep. Sorry. Wild. John's back.

Starting point is 02:47:41 Yeah, wild moment. I'm assuming you'll also face competition from clients that are just like, hey, we can, should we, should we have an in-house lawyer that we can, you know, speed up? But, but everybody's competing with everyone. But, yeah. How are you, how are you tracking the legal education market? I've seen, it, it seems very hard to predict for me. Like, there was this weird spike. I want to say, like, it was maybe post-chatchapT where there were, like, more people signing

Starting point is 02:48:13 it for a law school. And that was like sort of contrarian based on the model capabilities like the AISF discourse, but maybe it makes more sense. Like are you tracking that data? And then are you tracking like how legal education is changing? I imagine that using AI tools already happening in middle school for a lot of people, high school, definitely college, definitely law school. How will that all trace through and how closely are you following it? I mean, I think every industry is asking themselves, like, how do people get the entry-level jobs to learn those skills and become really good and senior and get leveraged by agents? I went to a law school of Stanford. I'm talking to a lot of professors there who are struggling with this question.

Starting point is 02:48:55 I think our insight for now, like the stat we found recently, is that the top 100 law firms last year made a little under $70 billion and just profit just in 2025. That's just paid out to their partners. That's just salary. And that's bigger than that's good. It says there's not enough. Good year. It's so good to hear. And that was more money than Google spent on all their R&D.

Starting point is 02:49:17 And so like our answer was, which is great. So like if we could just put some fraction of the profits law firms are making into building better tools and experiences for lawyers and for their clients, I actually think the legal industry gets a lot bigger. And so it's like for a person in law school today, it's a good time to be thinking, like, how can I just build better stuff? And that's just a new way of lawyers thinking. Okay, that's one way to put the profits to work.

Starting point is 02:49:40 let me pitch you another way. If I'm a partner at a law firm, and I see that, yes, agents can do the work of the associates that I would be hiring. Maybe I, you know, a contrarian in me wants to still hire associates just for the mentorship and building like the pipeline of partners that will do more human work, more deals work, more interpersonal relationship work, but I know that if I don't start buying and paying for that service right now, even if I'm getting less margin on it loosely because I'm paying an associate a bunch of money and it's work that an AI agent, like, sort of could do, and maybe they're a little bit more free, I'm actually incentivized to figure out how to accelerate them faster in their career,

Starting point is 02:50:27 have them start working on larger, stickier deals that AI can't necessarily navigate just yet. Yeah, I mean, I buy the argument. I think that there's two jobs for lawyers really to focus on right now. One is just doing client-facing work and being really good at being like talking to people and understanding what their points of view are and not being buried in the sort of paperwork like their typical associate. And the other is being able to explain reasonably well to an engineer or a researcher what it is you're doing and what you're thinking about and all the subtleties of context. And those two things I think are both things that if you're not hiring enough lawyers, you can't do well and you can't build better legal technology and experiences. And so I think we're feeling this and every law firm is feeling like you just need people to be really thoughtful about doing both those jobs.

Starting point is 02:51:08 Yeah. Are you guys fine-tuning any models based on fine-tuning like open source models or is that not even, you know, I've seen like Finn and Notion have had some success with this. Is that even a good use of time right now because I'm assuming your guys's like actual like inference costs or not that high relative to what you can charge clients, even if you're used. using the frontier models, but how are you thinking about that? I think, again, if we just look at cogeneration as like the blueprint for the future, you see like a lot of the co-gen companies got a lot of lift from just like, you know, the main, you know, three big models. And over time, you have to start fine-tuning our models as you get scale, as you get data,

Starting point is 02:51:52 and as you need a more competitive edge. So we're not there yet. We have a lot of lift from just getting the right context of models, building the right agent flows, like just doing some reinforcement learning on like basically, you know, we work with really, you know, Open AI Anthropic in Google's models. But yeah, in a year and a half, as you get really specialized in use cases of law, I'm sure, like, we're going that direction.

Starting point is 02:52:11 And part of the reason for this funding and doing it so quickly is to start investing in a research team that can kind of push the boundaries there. That's very exciting. Well, congratulations in the funding round. I'm sure we'll see you. We'll just book it now. You just tell us.

Starting point is 02:52:25 Same time next month. Thanks, gentlemen. We'll talk to you soon. Have a great day. Thanks, guys. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds, online, in store, on mobile, on social, on marketplaces, and now with AI agents.

Starting point is 02:52:41 And without further ado, we have Chris Yu. And also, how are you doing, Chris? I'm doing great. Thank you for taking the time. Yeah, thanks for having me. Welcome to the show. Since this is your first time, please introduce yourself. Yeah, my name is Chris Yu, and I'm the co-founder and president of also.

Starting point is 02:52:59 Okay, break it down for us. What is also? Give us some of the corporate lineage. the strategy, the product. It's just sort of everything. Yeah. So actually before 2020, RGA and I bet, and we immediately hit it off on this one topic. And so that turned into me joining Ribbonne at the time with the explicit mission to create a startup with and a startup.

Starting point is 02:53:19 The entire thesis that we had, and this is turned into also with a spin out last year, is that, you know, if you look at the vast majority of trips that happen for the movement of people and goods around the world, they happen in smaller than car things. Yeah. But nearly none of them have been electrified yet. And so it's really taken the Riviener Tesla playbook and applying it to these smaller form factors. Okay. Smaller form factors, that means everything from hoverboard to a horse and carriage. What are you thinking? We're focusing on wheels first.

Starting point is 02:53:48 But yeah. Okay. But yeah, yeah, narrow down the product for me, the go-to-market, the quad and the pedal-assisted electric bike. are there timelines, shapes, sizes, ranges? How do you think about narrowing down the product set? Because it is a really wide and diverse category. Totally. Yeah, so we think of it as, in a way, two phases of the business.

Starting point is 02:54:15 Phase one of the business is how do we create a vertically integrated software-defined EV platform, but optimized for small form factors. And we've applied that to our first products. We call them EVs that you can pedal. And we announced those back in October. So one is a consumer e-bike, and the other is a pedal quad, which we partnered with Amazon to deploy soon. That's really exciting. But if you look globally, again, today, things move around in things like two-wheelerers, like scooters, bo-a-bodas, tucktucks, microcars, K-trucks.

Starting point is 02:54:46 There's just these rich diverse set of form factors. And again, none of them have been electrified, and all of them are ripe for a really kind of tech-for platform, which is what we're building. But importantly today, we announced a partnership with DoorDash, and that kind of underpins phase two of the business, which is... Very good. Thank you. So if you look at the world becoming more and more autonomous, and even as that happens, some fundamental constraints don't change, meaning these trips are all happening in dense urban, suburban environments. Congestion is always going to be an issue. Cost per mile is always going to be a factor.

Starting point is 02:55:21 And so we believe really strongly that even in a fully autonomous, autonomous world, small form, factors make sense for a lot of these trips. And that's really what this partnership is about. Talk to me about, I mean, I love RJ. Arrivian's an incredible company. Obviously, a younger company in many ways than other EV makers that might be more vertically integrated. So I'm wondering, like, how much is it that you're taking the supply chain knowledge, the expertise, the best practices, the connections, and setting up sort of an entirely new supply chain that's distinct? versus you're just going to be able to buy stuff from Rivian or license it or there's going to be more of a business relationship other than just funding. It's all of the above. We, RJ and I talk about us as kind of like sibling companies, if you will.

Starting point is 02:56:10 So I think, I mean, there's a few aspects. One is we share the latest and greatest from a technical architecture standpoint. So if you look at how also vehicles are built, they're very, very similar in terms of how O'Rivian is built. there are some commodities that are shared. So battery cells, our first products actually use the same cell that are in Rivian R1s, and that helps a lot from a scale standpoint. But there are other areas where we are taking a decidedly different path because our products are different from a car truck or SUV.

Starting point is 02:56:41 So supply chain that you mentioned, that's actually one of them. We are fully engineered in-house, but we partner with contract manufacturers across the world to be able to do assembly. And that's right for smaller-scale products. Yeah, and with cars, you almost always want to manufacture them where they're going. Like, that's why, even like the Japanese car makers have facilities in America or Mexico, because you just would drive the car as opposed to put it out. That's exactly right.

Starting point is 02:57:04 If you look at a car, I mean, the size of tools necessarily, how custom they are, tariffs, like they all have to, like, you have to have your own factory in region. Yep. But if you look at any product south of a car, almost all of them are built with this contract manufacturing model. Okay, talk about the name and the brand. Rivian has those delightful headlights, a lot of different interesting brand decisions around Rivian. What are you taking?

Starting point is 02:57:29 What are you thinking? And where does the name come from? That's so great. I love it. We naming something is so hard. And so RJ and I battled quite a bit with this. But when we landed on this one, we knew it was the one because if you look at transportation, it's always been so singular narrative.

Starting point is 02:57:46 It's like it's just cars or it's just not cars. And for us, the approach. which is like whether it's a commercial enterprise or a consumer, it's all of above, most likely, meaning that I want to use my R1 to go on a long weekend trip, but my school drop off with my kid, it's a pain in the butt to sit in the car line and something smaller probably makes more sense.

Starting point is 02:58:08 And so the transformation and electrification of transportation is also. It requires all of the above in a way. And on kind of like how we present ourselves from a brand, And, you know, one analogy that RJ and I really love and use often is it's kind of like we're two characters in the Marvel universe, if you will. So it's like we have the same mission, but we can have very different personalities. And so also has an opportunity to be maybe in a way really expressive and take a little bit more liberties, which you're starting to see in some of our products than a more grown-up vehicle brand may need to be. Okay.

Starting point is 02:58:43 How do you think about competition with Chinese manufacturers, you know, Rivians had the benefit of not having to compete? with all the Chinese manufacturers in the U.S. I imagine micro mobility, you know, is not going to be having the same kind of export restrictions. You know, how do you think about that threat? You know, assuming that, you know, there's Chinese companies out there that for one reason or another will be able to like sell out a loss for some amount of time. Yeah, the DJI story, basically. Yep.

Starting point is 02:59:18 That's a great question. I think there's a couple of ways to. think about it increasingly as you get to the larger form factors in our portfolio when certainly as we get into autonomy, I think a lot of the similar factors that we're seeing in the automotive world in terms of the natural firewalls that are happening will exist in our space to some extent as well. But just to back up, I think one of the things that gets lost is there are a tremendous number of products in this kind of like small mobility or micromobility space that are coming out of China for sure. But I think it's without debate that the vast majority of these products

Starting point is 02:59:53 are commodity, like relatively low quality, white label type products. That being said, there are a small handful that are really, really great products and using the latest and greatest tech. And if you look at take apart one of those products and you take apart one of our products, architecturally and from a technology capability standpoint, they're actually more of the same than not. And I would say also is probably one of the only brands outside of China that you could say that of within this space. And so just purely from a product, feature quality and technical capabilities standpoint. We feel like we're very, very competitive. Okay, product pitch. The Rivian R1T has a gear tunnel. It fits a snowboard.

Starting point is 03:00:30 Electric longboard with a handle that flips up like a giant razor scooter that fits perfectly in the gear tunnel. Am I on to something? I love it. That's not the first time we've heard that one. Oh, really? Okay. The gear tunnel, it just does feel like such a unique feature. And it just, It just demands some bespoke thing that fits in there. You know, you want like a big speaker, Bluetooth speaker that fits in there, like barbecue or something. I want an ecosystem around the gear tunnel, even if it's, you know, who knows how viable that is. Anyway, very fun. Jordy, anything else?

Starting point is 03:01:03 Very cool. Thank you so much. I'm on the website right now. I'm interested. You're shopping. I'm shopping. I'm shopping. Oh, we'll hook you up.

Starting point is 03:01:09 Just let us know. We'll be very excited to ride these around. We've been doing some office chair racing in the studio. That's what I want. I want an electric office chair. Oh, there you go. We have, well, we have in-house, vertically integrated motors and rivers. We can power, we can soup those up.

Starting point is 03:01:27 There you go. So I can just sit here and go. Adjust me to the left, one inch. Yeah, just a little joystick. Thanks for bringing out, Chris. You know, if you're not in the right shot, you're a little bit to the left production. You can just move you. That's actually, you'll love that.

Starting point is 03:01:42 You will have one or two customers for this. If you've done it. Autonomous office chair. Hey, you have to leave the meeting. Go back to your desk. Drive you around it. I think we're on to something. Well, thank you so much for taking the time to get to chat. Yeah, thanks for having me. I'm on the show. Thank you. Thank you. We'll talk to you soon. Goodbye. Let me tell you about app loving. Profitable advertising made easy with axon.a.com. Get access to over one billion, billion daily active users and grow your business today. What's up? Brett Adcock. Yes. On the show yesterday. Yes. He had some interesting. comments about the state of AI. Okay. I disagreed strongly with many of them. Okay. But we have to cover

Starting point is 03:02:23 this video from the Sean Ryan podcast. Yes. It's a new gate. Okay. It's, uh, they're calling it telegate. Ad gate. Ad gate. Well, maybe that too. Who knows? So, so he is hanging out with a figure robot. Okay. Uh, on the Sean Ryan podcast. Oh, okay. He went outside for it. Yeah, I was wondering because Sean Ryan normally shoots not like very cinematic whiskey bar but he's outside and there's like a two minute video where they're hanging out with the robot

Starting point is 03:02:52 and let's pull this up and I want to get your take. All right turn around so this is the first time he tells it to turn around but at the end of the video it starts turning around and then he says turn around and Nima here says the video is the smoking gun that figures robots

Starting point is 03:03:12 are teleopt. Again, I love teleop. Not a problem. But Brett has He always says he's not doing teleop. You never do teleop. I don't know. This is not autonomous. Notice how the robot starts turning around before Brett says all right turn around. Yeah, you can skip forward a little bit. And there's pull up, pull up this other video that I'm actually on. There's another, yeah, there's another video quoting this that shows it on repeat. Let's see. Now, I think too is like we basically, uh, we basically, uh, the robots almost all they fully It's by Vic.

Starting point is 03:03:43 Vic, quote, read it and said, yeah. Okay, yeah, it's definitely not waiting for the command. This one. All right, it's very subtle. But you can see it's turning around and then he says, all right, turn around. Yes, but the steel man here? Premonition. Right, turn around.

Starting point is 03:03:59 The robot knew what was going to happen because personalized super intelligence understands that a turnaround command is coming before Brett even says it, starts turning around before. So that would be one possible solution. But yes. Who knows? Also, the moment from yesterday that stands out to me is I said, why build a separate AI lab focused on personal superintelligence outside of your company that is trying to sell some combination of intelligence in the physical world? And he said, I really value focus, which I thought was fascinating given that he is diverting his.

Starting point is 03:04:40 his personal focus. His personal focus. Yeah, it's like focus within an organization, like a specific, like the leaders that joined that company can focus just on that problem. It was, it was an odd comment to sort of process. Yes, the, I mean, I don't know. I haven't watched the full, the full interview with Sean Ryan. I wonder if, if he talks about whether or not this particular robot is teleop, because

Starting point is 03:05:05 it's totally reasonable that a company would have some teleopped robots, some, autonomous robots and sort of mix and match them based on the particular demo. Obviously, if you're doing some sort of prescripted stunt dance or parkour scenario, you might prescript that. And then ideally you would say, hey, you know, this one's teleopt. Here's a demo of what we're capable of when we're using teleop. Here's a demo of what we're capable of when we're fully autonomous, when we're, you know, partially, you know, remote controlled or something like that, somewhere in between. I don't know. We'll see. You know, people will continue to dig in.

Starting point is 03:05:41 I mean, all of this, you know, the rubber meat the road when the robots are out in the wild. When people get them and they start shipping and people can see, unless you buy one and it's secretly telling you out, that would be wild. You're like, wow, this is remarkable. I can give it the most complex, I can give it the most complex vague instructions and it just does exactly what I do. If the figure robot can simply open a diet cook for John, we're a buyer. That's the goal post We don't need it to do everything That's the goal post

Starting point is 03:06:11 Just need it to do one thing really well A six pack a Diet Coke Tyler what do you think about The figure Figure gate I mean it's hard to say Just from that video But I think broadly like

Starting point is 03:06:21 People are probably like Two against teleoperation generally I agree Because like you know the lesson from Waymo Is that like actually It's goaded You know part Maybe if it's totally

Starting point is 03:06:32 Like 100% teleop Like okay that's not great But if it's like partly There's someone overseeing it And maybe they're, like, pretty involved sometimes. It can be, like, extremely valuable. Like, Waymo is a great product, whatever. Yeah.

Starting point is 03:06:43 Like, even just, like, deploying robots in dangerous locations, if it's fully teleopt, that's still, like, a great thing. H hugely valuable. And, like, clearly, the way we get fully autonomous robots is by starting out with partially telop one, so you get the data. There's, like, a very clear loop there. So I think broadly people are too against.

Starting point is 03:07:00 I completely agree. Yeah. Anyway, anything else we need to talk about? There's a bunch of place. We'll be back tomorrow. We do have one follow-up to yesterday. So we did a little deep dive from the Wall Street Journal on Mark Lanier, the lawyer who successfully argued that META and YouTube are addictive in the L.A. court last week. And we posted the clip.

Starting point is 03:07:23 A lot of people enjoyed learning about him. And in particular, the fact that he has a menagerie that contains lemurs and llamas, as well as a 120-person train. We love the way he's living his life. were huge fans of Mark Lanier, although do have some disagreement around the legal findings, but a lot of people chimed in. Excel Rader said, by the way, this is the Lanier Theological Library in Houston, which is open to the public for touring. Incredible guy, shares two amazing images of, you know, what an amazing contribution to the

Starting point is 03:07:57 community. And Eric Suford, quote, tweeted our post and said, this is true. I grew up down the street from his property, and he hosted a high school, graduation party for one of my friends. He recently bought an adjoining horse ranch and built a seminary on it. So a lot of people coming out in support of Mark Lanier. And yeah, I mean, just seems like, seems like a fantastic lifestyle. We'll get him on the show. Fantastic menagerie. And he really reset, you know, everyone's, everyone focuses on, oh, are you flying private? Are you, are you post-economic? Like, menagerie is clearly just a

Starting point is 03:08:30 different tier, different ladder. That's where you want to go in life if you're successful. And he's done So congrats to him. Anyway, thank you so much for tuning in to TBPN today. Leave us five stars on Apple Podcasts and Spotify. Sign up for a newsletter at TBPN.com. We hope you have a wonderful last few hours of your quarter. Yes. It's been an honor.

Starting point is 03:08:48 See you tomorrow. Goodbye. Oh, wing flashbang. Bye.

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