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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN.
Speaker 2:Today is Tuesday, March 31, 2026.
Speaker 1:Boy, we're
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Speaker 2:Let's pull it up. Linear, of course, is the system for modern software development. 70% of enterprise workspaces on linear are using agents.
Speaker 1:Alex Pruden Yes. From Project 11. Gonna be talking about Google's Quantum news.
Speaker 2:The crypto quantum crash. Say that three times fast.
Speaker 1:Crypto quantum crash. Then we have Qasar from Applied Intuition. Yes. Absolutely. Very excited to catch up with him, an absolute dog.
Speaker 1:But then we have Sebastian Mallaby
Speaker 2:Yes.
Speaker 1:Releasing his new book, The Infinity Machine, An Insider Account of Deep Mind.
Speaker 2:Got it pulled up
Speaker 1:right there. Super intelligence.
Speaker 2:I'm a huge fan of Sebastian You might have read More Money Than God. You might have read The Power Law, 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, not a history of an entire industry.
Speaker 2:But very excited to talk to Sebastian Mallaby.
Speaker 3:And then we have Forrest from Somos raising a $40,000,000 round.
Speaker 1:Then Dino from Ceronic, Will from Whoop, Jannick from Public, Ryan from Crosby, and Chris Yu. He's working on a spinout from Rivian.
Speaker 2:Oh, very exciting.
Speaker 1:Already has a billion dollar valuation.
Speaker 2:There we go. Well, friend of the show, our president here at TBPN, Dylan Abracado, headed to the TBPN newsletter, you can sign up for at tbpn.com, and wrote a fantastic essay summarizing a trend that we've been discussing with him around 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
Speaker 1:And Dylan's from Long Island Yes. New York, so John is going to be I'm going to do it in a Dylan Abercato impression.
Speaker 2:Memes are changing. That became abundantly clear during the Oscars a few weeks ago. When Conan tried to create a new Leonardo da cartel
Speaker 1:accent that was. Announcer
Speaker 2:to go alongside the classic Leo memes. In doing so, especially by using TFW, that feeling when, and the blocky white font 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.
Speaker 2:Look at what's happening with the Harry Potter reboot. When the trailer first dropped, the reaction to the new Snape played by Ghanaian, sorry. Ghanaian. He's from Ghana. Ghanaian.
Speaker 2:English actor Papa Isidu was predictably and unfortunately negative. According to the LA 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 DripWart's The School of Drip, the narrative has started to shift. Have you seen any of these? I think I've seen DripWart's, but can we pull up the original, the quote unquote original Snape versus black Snape MMA match because I have not seen this one, and I think it is illustrative of what Dylan is talking about here.
Speaker 2:Snape v. Snape in the UFC ring. While we pull that up, let me tell you about Plaid. Plaid powers the apps you use to spend, save, 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 livestream, 30 plus destinations.
Speaker 2:If want you to multistream, go to restream.com. So let's take a look at Snape v Snape in the UFC ring. Any luck?
Speaker 1:Here we go. I just dropped it in.
Speaker 2:Cool. And we have 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 done a complete one eighty. Here we go. Really photorealistic.
Speaker 2:Does this does this are there any, red flags here as a UFC enjoyer? Does this feel like
Speaker 1:a proper UFC actual video quality.
Speaker 2:It's so bulky. Yeah. The video quality is insane.
Speaker 1:Wait. But old Snape won.
Speaker 2:In the fight?
Speaker 3:Yeah.
Speaker 2:Okay. I think I it just okay. Wait. How 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.
Speaker 2: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. And so you're 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.
Speaker 1: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 be 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. It's interesting. On on x, it's still very easy for an image to go viral. But if you think about, you know, Instagram, YouTube like a standalone image just can no longer actually get that escape velocity.
Speaker 2:I mean, what about dripped out pope? Remember that?
Speaker 1:Yeah. A little bit. But but people are just spending so much time in the in the short form feeds. And Yeah. Can go in there, but they're certainly
Speaker 2:Yeah. Yeah. I mean, I guess even some of the the the dripped out Pope or what was it? Was it Balenciaga Pope? I don't remember what the name was.
Speaker 1:Dylan At Pope. Says Yeah. 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.
Speaker 1:Didn't see that because I was sleeping. But this might have worked twelve years ago. That playbook is over. Today, Enraged fans and communities will, if you're successful, take your characters or moments and turn them into something much bigger, entire cinematic universes. Yeah.
Speaker 1:Yeah. I'm I'm just very impressed by the the overall quality of of those outputs.
Speaker 2:The Oscar selfie, I remember this. 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 Meryl Streep, you like it.
Speaker 2:If you're a fan of Brad Pitt, you like it. And so you're you're amplifying all of the ultimate collab post. And this has become a format that's been used time and time again. It's effective. We we did a little bit of it at the Super Bowl.
Speaker 2:Was fun. It works. But now the future is AI. Let's pull up the DripWart School of Drip video. I want to watch this one.
Speaker 2:Because I I saw a clip of this, I didn't see the whole thing. Let's see if we can play this.
Speaker 4:That's Harry Potter. Are you really Harry Potter my g? Type shit. Type shit. Type shit.
Speaker 4:Type shit. None of that. None of that, bro ski. We're all here on the Maybach Express for one reason and one reason only. And that's to go to drip watch the school of drip.
Speaker 2:The May back pulling the train is pretty good.
Speaker 4:Hey, man. I know, kid. I'm a fast little kid. I'm go crazy. I'm go I don't.
Speaker 4:Run.
Speaker 2:And there's and there's the new Snape character. So, yes, very effective. I was I I was reflecting on this and thinking about how it's not just AI videos that are unlocked as the new meme format. Like twenty years ago, video editing was extremely difficult. Like, you had to do it on a desktop.
Speaker 2: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, we were I was talking to Brandon about this. Good guy Greg was one of these or 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.
Speaker 2:And that would be the template and then somebody would put white text with black, like 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 it could be like generated on On
Speaker 5:the MS Paint.
Speaker 2:It was it was it was free to generate it, basically. Yeah. Then we got video editing, you know, CapCut, Instagram, Reels has an editor called Edits and all of a sudden it became easy for someone to take a Vibreel and put different text over it. I send you a bunch of these where I'll find some crazy Vibreel and I'll just recontextualize it with a new Yeah. New caption basically.
Speaker 2:And so the classic one is like those four those four jets and the new Top Gun and it's like when when you and the boys all drive somewhere in separate cars or something like that. You know, it's an example. 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, s a a m, something like that.
Speaker 2:We've been experimenting that with this with the simulators. There's TBPN simulator, Jeremy Gaffan simulator. There are more simulators coming. And all of a sudden we, you know, 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, maybe millions of dollars to get anything reasonable.
Speaker 2: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.
Speaker 2:You don't have a lot of other responsibilities that are going to creep in. But 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 the J mail suite from Riley Walls as another software as a meme moment
Speaker 1:Yeah.
Speaker 2:Where he's making a commentary on the Jeffrey Epstein saga and all of that, but he's instantiating the the 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 it get 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 Well, let me tell you about Cognition. They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team.
Speaker 2:And let me tell you about Labelbox. Oops. Sorry. Labelbox. RL environments, voice, robotics, evals, and expert human data.
Speaker 2:Labelbox is the data factory behind the world's leading AI teams. So there is a whole bunch of hack news going on. 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 tech companies are like, don't launch while my kids are out of school and we're going on vacation. I think I actually think this is my real theory.
Speaker 2: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 things that are more like reflective in Strathecari. Ben Thompson hasn't heard of a fifty year retrospective on Apple.
Speaker 2:It's not driven by a news item. Like, it's not like Apple launched a new product this week, so Ben Thompson is taking a step back and 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, etcetera. 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.
Speaker 2: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.
Speaker 2:Also, if you built this 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 virus, so be careful out there. And I'm sure people will be responding. The recommendation from Feros, 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.
Speaker 2:Socket analysis confirmed that this was malware. Plain Crypto JS is an obfuscated dropper loader that de obfuscates embedded payloads and operational strings at runtime, dynamically loads FSOS and exec sync to evade static analysis, executes decoded shell commands, stages and copies payload files into OS temp and Windows program data directories, deletes and renames artifacts post execution to destroy forensic evidence. So very risky.
Speaker 3:I would say like if you have installed this, you should just like freak out, basically.
Speaker 1:Should and and and if you break your computer, that's like the first thing you should do. Just like try to slam
Speaker 2:it Yeah. Over Take the computer, throw it in the lake. Throw it in the ocean.
Speaker 1:That's how you should start. I concur.
Speaker 2:I mean, practical yeah. I mean, there is going to be some sort of, like, power law response here where of the people that 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, Mercur was targeted. But I don't know if
Speaker 1:that's But I don't was that Yeah. My understanding is that The crazy thing is you have you have this, like, Claude code Mhmm. Leak that
Speaker 2:That was completely separate. Nothing Even
Speaker 1:though even though I do believe they use Axios in Claude code Okay. I saw something on that. Sure. Sure. Sure.
Speaker 1:And you have the Merkor leak Yep. Which is Well,
Speaker 2:it's not a leak. It's a ransom
Speaker 1:It's a ransomware
Speaker 2:Yeah. Someone stole some data.
Speaker 1:Yeah. They stole a bunch of data and now they're trying to, you know, get bids on it. Mhmm. We'll we'll get to that in a little bit. Okay.
Speaker 1:And then there's there's this Axios supply chain attack. Yeah. Anish 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 a 100,000,000 times a week.
Speaker 1: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.
Speaker 1:Over a 173,000 other code packages plug into it. It's everywhere. The attacker stole a lead developer's login for NPM. Think of it as an app store, but for code that programmers use. Once inside, they swapped the developer's email to an autonomous ProtonMail account and uploaded the poisoned version by hand.
Speaker 1:That jumped past every security check the project normally runs before new code goes live. And this was not a rush job. The stackers staged the malware at least 18 before pulling the trigger. They built separate versions for Windows, Mac, and Linux. They poisoned both the current version and an older one within thirty nine minutes of each other, casting the widest net possible.
Speaker 1: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 crypto JS 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.
Speaker 1:When a developer installed Axios, this fake package quietly ran the malware on its own. When a smaller package called UA Parser JS got hijacked back in 2021 with about 8,000,000 weekly downloads, the security world treated it like a four alarm fire. Axios has a 100,000,000 over 12 x the exposure with a 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, ad companies everywhere to pull and install the bad version before anyone can react.
Speaker 1:If you or your team run Axios, freak TF out. No. Lock your version to one point fourteen point zero. 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 one hundred and forty two eleven two zero six seventy three.
Speaker 6:Mhmm.
Speaker 1:Karpathy had some context if you want to go through this, John.
Speaker 2:I will. But first, I'll tell everyone a very important message from CrowdStrike, which is super relevant today. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches.
Speaker 2:And I'll also tell everyone about Cisco. Critical infrastructure for the AI era, unlock seamless real time experiences and new value with Cisco. So Andra Karpathy said, new supply chain attack this time for NPM Axios, the most popular HTTP client library with 300,000,000 weekly downloads. That's a lot. Scanning my system, Andre Carpathi says he found a use imported from Google Workspace CLI from a few days ago when I was experimenting with Gmail, gCal CLI.
Speaker 2:The installed version luckily resolved to the previous version, the unaffected one point one three point five, 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 pwned. It is possible to personally defend against these to some extent with local settings, e. G. Release age constraints or containers or etcetera. But I think ultimately the defaults of package management projects, PIP, NPM, etcetera, 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.
Speaker 2:So very, very crazy, 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 for defense as well, showing one example below where dev and review caught the attack within an hour of its release, text minorly edited for anonymization. So I was debating this with Tyler earlier.
Speaker 2:The question is, like, how does this update diffusion of of coding agents, diffusing diffusion of vibe coding? Is this I was I was sort of saying, is this bullish for cursor, windsurf, you know, 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 I'll let you explain how you were saying that maybe this is actually bullish for just more token generation, more code gen.
Speaker 3:Yeah. I mean, clearly, like, there just needs to be more code review. Right?
Speaker 1:Okay.
Speaker 3:It would the the package was still seen within seven minutes by an automated system. Right?
Speaker 1:That's true.
Speaker 3:So, like, yeah. I I think people will just like, there's gonna be much more of an emphasis, 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 Yeah.
Speaker 3:You have code review. But if you're just doing it solo, maybe you don't do as much code review. Right? Yeah. But it just becomes
Speaker 2:you know I imagine that.
Speaker 3:More embedded within the agents. Right? You talk to Codex, you
Speaker 7:talk to Cloud Code.
Speaker 3:Yeah. There's already like every single
Speaker 1:I just think it's bullish overall for cyber security. Like, think every cyber security company will probably do well. People are on edge already. Yep. And Everyone's even even though this type of attack has happened for years Yep.
Speaker 1: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 gonna release a lot of new products. I think the question that I have is like, why seven minutes? Right?
Speaker 1:Like Yeah. If
Speaker 2:Why not check it before it's merged in in the first place?
Speaker 1:Yeah. Yeah. Or or just like, you know, these are machines. So theoretically, they can be constantly monitoring versus like
Speaker 2:Yeah. I don't know. And and the question is, I I I we're gonna be digging into this story more over the next few days. But I'm I'm interested to know, like, it's found in seven minutes. When is it actually rolled back?
Speaker 2:If you look at 300,000,000 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 tens of thousands. Just doing like a rough ballpark on what seven minutes means over a week of 300,000,000 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 it was discovered in seven minutes and then it took them another twenty minutes to roll it back and stop serving the contaminated package?
Speaker 2:Understanding the scope of this because it's very clear that as Andrej Karpathy explained like he was actively using it every single day and yet was not caught in that seven minute window. And so he was clean. And understanding the scope and scale of the impact is very much determined by how many 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.
Speaker 2: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 Eleven Labs, build intelligent real time conversational agents, reimagine human technology interaction with Eleven Labs. So moving on.
Speaker 8:More hacks. Last
Speaker 2:night. More leaks. What's going on?
Speaker 1:Last night Yes. Pod code, source code
Speaker 6:It's leaked.
Speaker 1:Leaked via map file in
Speaker 2:the
Speaker 1:npm registry. There's just a link to
Speaker 2:Wait. Someone's just actually do not click a link. If somebody ever says, hey, got some really great source code here. Just click this link. Probably don't click it.
Speaker 2:Let other people screenshot it. There's plenty of meta analysis over here. Seems seems messy, seems unfortunate. Heart goes out to the folks who are are dealing with the situation. At the same time, Codex is open source.
Speaker 2:It's not the end of the world, but it did reveal a bunch of things about the road map and also some of
Speaker 1:April the fools.
Speaker 2:Journal April fools. That is the worst part. We love a secret surprise April fools joke. I love a good joke. And nothing spoils joke like hearing about it a day early.
Speaker 2:But much more importantly, there are lots of there are lots of other critiques of the way Claude code is implemented. What are
Speaker 1:the I don't this their business at all No. Because people are using Claude code to make other products Yeah. And then also having to take basically a fork Yeah. Of Claude code, maintain that, try to be shipping features against it, which is, again, I think it's the it's it's not seems to not be legal at all to just fork the code base just because it's out there.
Speaker 2:Oh yeah, you can't just like steal it.
Speaker 1: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.
Speaker 2:Understand some of the secrets. What's special? But at the end of the day, all of these tools, especially something like Claude code that's so new, like, it's more of like the process and
Speaker 1:It's more bad for for the overall brand of vibe coding.
Speaker 2:Totally. Totally. Yeah. Yeah. It's rough.
Speaker 1:It and the the, you know, the the irony here is that every time Anthropic has released any feature related to cybersecurity, all the big cyber companies have been selling off, you know, tens of billions of dollars.
Speaker 2:Yeah. Yeah. Yeah. The question of, like, yeah, does this build trust in, like, using Vibe Yeah.
Speaker 1:So overall Security. Overall, it it hurts some trust. But but again, you know, very obviously gonna get through this.
Speaker 2:Yeah. So the how it started, how it's going is, of course, landing like a ton of bricks. In the in the last thirty days, a 100% of the contributions to Claude code were written by Claude code, and the how it's going is that it leaked the source code, which is not what you want to have happen.
Speaker 1:Yes. Angel says, Mythos is so good at security that Claude Source Code got leaked.
Speaker 2:Okay. Let's I don't know. Should I this is like, you know, you you didn't get to watch the Super Bowl, you have it DVR ed at home. Do you want spoilers? Should we review the April fools joke or should we leave it unspoiled so that we can enjoy it tomorrow?
Speaker 2:What do you think?
Speaker 1:I mean, it's not it's not it's cool. It's very cool.
Speaker 2:You've already read it?
Speaker 1:I read through it. But it's not it's not to my Were you bouncing off? I don't think we're getting a knee slapper out of it. Okay. It's very it's very cool.
Speaker 1:Okay. And I think it'll be cute.
Speaker 2:Okay. Well, then we can move on. What else what else did we learn? Tukey summed it up here. Do you understand what just happened to Anthropic?
Speaker 2: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, are people that are downloading it every single minute.
Speaker 2:And so if even if it's only up there for a minute, someone's gonna get it. And then all they need to do is send it to somebody, zip it, and post the link on X, and it goes viral. 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.
Speaker 2: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.
Speaker 3:Aren't floor plans public on like Zillow?
Speaker 2:Oftentimes. They're not I
Speaker 1:would always say we can probably skip over this, John. If you scroll down this account, just kind of post like the same format every single time. So we can skip this.
Speaker 7:Let's go
Speaker 2:over to alert emoji. You attention.
Speaker 1:Let's go over to Lisan. Yes.
Speaker 2:Yes.
Speaker 1:Yes. A few takeaways from the Claude code leak. Anthropic is actively using Mythos for development.
Speaker 2:Okay.
Speaker 1:They are already a capybara v eight. We learned last week that capybaras are Extremely deadly. But can be deadly in the right context. Capybara still has issues. The foreshadowing is crazy.
Speaker 1:We
Speaker 2:were talking about how how the Faustian bargain that is getting up a capybara as a pet seems so cute, but it can bite you. And it seems like that might be what happened.
Speaker 1:Capybara has 1,000,000 token context window and Cool. Task
Speaker 2:Numbat is another interesting code name tagged with at model launch. Remove this section when we launch Numbat. Fennec seems to be fit the Fennec Fox. Fennec Fox is very cute, but also not a domesticated animal. How about we get some golden retriever code names?
Speaker 2:How about big fluffy poodle? That's a good code name for your your themed AI model. Anyway, let me tell you about Console. Console builds AI agents that automate 70% of IT, HR, and finance support giving employees instant resolution for access requests and password resets. And let me also tell you about Lambda.
Speaker 2:Lambda is the super intelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
Speaker 1:Says hot take Anthropic leaked Claude code intentionally to get a Nerdosphere code review it would have never gotten if they had just open sourced it.
Speaker 2:Oh, that's actually true. Way more attention.
Speaker 1:You don't leak your entire feature roadmap and you don't do I mean, it's it's it's funny and I'm sure they'll make the most of this.
Speaker 2:This is four d chess right here.
Speaker 1:But The four d chess. I'm not seeing the four chess.
Speaker 2:I'm seeing the four d chess now. I'm convinced. This is I I mean, we're in completely uncharted territory for marketing stunts and pre releases and sneaky footage that is 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.
Speaker 2:Everything's on the table. This could be an April fool's joke. This could be a stunt to draw to drive attention to an open source move. Although, Tyler, you said that Dario is not a fan of open source at all. Right?
Speaker 2:He's like against Yeah. Dario is unilaterally.
Speaker 3:He doesn't wanna do open source.
Speaker 2:I I feel like open source. I 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.
Speaker 2:They've implemented it. 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 if I'm a if I'm a computer scientist
Speaker 7:Yeah. But if all the research
Speaker 3:is already commoditized and
Speaker 2:Yeah. I guess you could just use the other ones. It doesn't really have a benefit. Maybe.
Speaker 1:Yeah. So has anyone has anyone at Anthropic has anyone at Anthropic commented on this at all? I seen anything.
Speaker 3:I haven't seen anyone.
Speaker 2:Yeah. What is undercover mode?
Speaker 1:That is a way to contribute to projects without letting people know
Speaker 2:Mhmm.
Speaker 1:That you're using Claude Coat. Oh, interesting.
Speaker 2:That's a hack.
Speaker 1:Gurgley over at Pragmatic Engineer says this Gurgley, 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.
Speaker 2: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 Primeagen. The last time Anthropic in their infinite PhD level wisdom leaked their own source code.
Speaker 2:February 25, that happened? I missed that entirely. They d m c a'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 you did that because it sounds like you might get a legal letter.
Speaker 2:Again, a DMCA is not is not like an actual lawsuit.
Speaker 3:Unfork. Unfork. Fucking fork it.
Speaker 2:And and people are of course making a joke that the codec source code has been leaked in full here and they're linking to the GitHub because codecs is open source, which is which is cool. I don't know. It's it's interesting. And more and more people are building their own harnesses. There were some interesting data that Opus performs extremely well better than in clogged code in cursor on some benchmarks.
Speaker 2:And so there there is this new this new paradigm of like, you know, how can you add different value when you're building a harness. So what else?
Speaker 1:Yes. Certainly, there's other plenty of other companies that are building harnesses that are gonna 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.
Speaker 1:And so that's not that hasn't been hurting Codex's progress and growth. So Yeah. End of the day, ultimately, I would say I would I'm assuming very very embarrassing for the Yeah. For the individual that ultimately contributed to this, but they will get past it.
Speaker 2:Well, we will put the the blame squarely on the AI model so they can take it. Dax is getting line of code mugged, LOC mugged because Clog code open source is Clog code source is 512 lines of code, whereas open code, his project is only one eighteen lines. And so he's got to get those numbers up.
Speaker 1:And GT mogs everyone with over 50,000,000,000 lines of code.
Speaker 2:He doesn't have 50,000,000,000 lines of code. GT, Gary Tan will be coming on the show hopefully this week and we will get the full scoop on how he's using Gstack and other models, which should be fun. Before we move on, let me tell you about Turbo Puffer, serverless vector and full text search built from first principles in object storage. They're fast, 10x cheaper, and extremely scalable. And let me also tell you about vibe.co, where D2C brands, b to b startups, and AI companies pick channels, advertise on streaming TV.
Speaker 2:Pick channels, target audiences, measure sales just like on Meta.
Speaker 1:Zach says NDAs are a great way to keep your corporate secrets safe from one or two beers, but not three beers.
Speaker 2:Why is there a community note on this? Oh, this joke was posted before on Instagram. It's a little joke theft. Interesting.
Speaker 1:Got him.
Speaker 2: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
Speaker 1:the original post was an NDA is a lock and three beers is a key.
Speaker 2:Okay. Well, yeah. Toned it down for the the timeline. Anyway, there is news out of out of Google. A Google paper warns that warns crypto on quantum risk ahead of 2029 timeline.
Speaker 2: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 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 may be lower than earlier estimates had suggested. In a Google research blog post, this is from Bloomberg, the researchers said that a future quantum computer could break elliptic curve cryptography, a form of public key encryption used across much of the market.
Speaker 2:Their latest estimate points to a 20 fold reduction in the quantum computing hardware needed to break what's known as ECDLP two fifty six, a mathematical problem that helps secure crypto wallets and transactions. 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 quantum cryptography or PQC. I'm sure this will 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.
Speaker 2: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. 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.
Speaker 2:That same month, Christopher Wood, global head of equity strategy at Jefferies, 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, making the rounds, rising as much as 2.6% to $68,300. I'm not sure where it is today, but, Jordi, I'm sure you can pull that up. Even so, the researchers said the time left before such machines arrived still appears longer than the time needed to move public blockchains to post quantum cryptography. However BTC is currently at 67.
Speaker 2:67. So slightly off of yesterday. A lot of this stuff has been discussed ad nauseam in the crypto community years. I I remember hearing about Quantum potentially breaking Bitcoin as far back as 2016.
Speaker 1:So you're saying you were already in that kind of like post Quantum
Speaker 2:Yes. 100%. I was locked in. No.
Speaker 1:Yeah. But I was aware.
Speaker 2:I was
Speaker 7:aware of it.
Speaker 1:One concern
Speaker 2:Yeah.
Speaker 1: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
Speaker 2:Mhmm.
Speaker 1: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 Bitcoin because the incentive for Sure. A certain team would just be to go around and find these wallets that were maybe 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 is destroys Bitcoin Yeah. The the price would go down and then you the the the hack, you know, the the hacker wouldn't get any benefit from it.
Speaker 2:Yeah. It's interesting. What are quantum stocks doing on this news? Quantum.
Speaker 1:Probably ripping.
Speaker 2:They rip on everything. SciQuantum? Is that one of them? Psy Quantum?
Speaker 3:Yeah. Rigetti's up 8%.
Speaker 2:Okay. There we go. Oh, Psy Quantum's private privately held. There's another one, D Wave. Right?
Speaker 2:D Wave. Are they public? Yeah. They're up 10% today, But they're down 12% over the past five days. But and 25% over the last month.
Speaker 2:And 42% over the last six months. But they're up 88% over the past year. Let's go. D Wave is a $5,000,000,000 company.
Speaker 1:Yeah. There's apparently a bull market in Nick on our team's email inbox. Oh, yeah? Quantum companies
Speaker 2:Really? That won't
Speaker 1:come on and Okay. Talk about.
Speaker 2:Well, we do have someone coming on. Right? We have Alex Pruden 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.
Speaker 2:It was this, and it's from research Google, research. Google, which we will go through. Max the VC 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.
Speaker 2: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. 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.
Speaker 1:Also to everyone else.
Speaker 2:Yeah. Yeah. I I I don't know. I mean, how do how do property rights if somebody if somebody does have a quantum computer 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.
Speaker 1:Do you ever really own code?
Speaker 2:I don't know. Nick also said, And the craziest thing is that the quantum AI the Google quantum AI paper is maybe not even the most concerning quantum paper released today from Project 11 who's coming on. Shor's algorithm is possible with as few as 10,000 reconfigurable atomic qubits. So this will be interesting to dig into further. The within minutes, with 500,000 physical qubits, Google is now more confident on a twenty twenty nine post quantum transition.
Speaker 2: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. Code review for the age of AI, more important than ever. Graphite helps teams on GitHub ship higher quality software faster.
Speaker 2:So there's a lot of news about this quantum story.
Speaker 1: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.
Speaker 2:It's ridiculous. Dan Shipper says, the first thing I've seen that could make Bitcoin go to zero or allow competitive coins to to to catch up. So other 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.
Speaker 2:So the chance that NASA lands on the moon, we were tracking this yesterday. The missions are starting to happen. Before 2028 on call sheet is now at 14%. Before 2027 is at 4.7%. So they are racing.
Speaker 2:Of course, this Artemis two mission is not boots on the ground on the moon. It is rocketing around the moon. We'll have more about this tomorrow.
Speaker 1:They're just going to check They're it
Speaker 2:going be gone for ten days. They're going to be in space for ten days. And will be will be very interesting. Britton Grail 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, four k live streams, laser beams to make sure it's low latency. Super a lot of fun.
Speaker 2:Super chats would be good. We gotta 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
Speaker 1:gonna be a twenty four seven like Yeah. Perpetual stream that's always on Yeah. Even when the astronauts are taken asleep?
Speaker 3:Yeah. Taking a little nap?
Speaker 1:Yeah. Yeah. Okay. Yeah. Okay.
Speaker 1:Yeah. It's gonna be funny. All the conspiracy theorists are gonna be sitting there watching it very closely and then pausing and then There was
Speaker 2:a glitch.
Speaker 1:There. Did you see that glitch?
Speaker 2:That was that was VFX. That was AI. No. This is my butt mark. I will believe that it's real if I see an astronaut put three fingers in front of their face.
Speaker 1:Yep.
Speaker 2:Because this is the one thing that the AI can't do right now. If you're ever on a Zoom call with someone who you suspect of being fake, a scammer who said, hey, let's get on Zoom. Let's talk about some financial investment opportunity and you 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, look at the fingers. The fingers are perfect.
Speaker 2:It's fine. 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.
Speaker 2:So 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? I satisfy the task.
Speaker 2:You 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 you got to go like this. Show some There you the field. Good.
Speaker 2:You got three fingers in front of the face. This is the trick. This is the only way you'll survive in the in the future. Be careful out there. Merkur had a breach.
Speaker 2: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. They the the design of this. I didn't realize hackers did stuff like this.
Speaker 2:This is very interesting. But you know, it's like you think about the hackers They're
Speaker 9:kind of
Speaker 1:like cosplaying as hackers.
Speaker 2:They are.
Speaker 1:But they have
Speaker 2:like the green like the green text in the black terminal. It's like they're they're they're living the they it's 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 different questions in here.
Speaker 2:There's a database of candidate profiles, 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 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 like Equifax did because they have sensitive information, that could be very, very expensive.
Speaker 2:Well, we have had the Merkor folks on the show many times and are hoping that they get through this smoothly and
Speaker 1:everyone's Yeah. Absolutely brutal. I mean, it sucks. Sure. It sucks first and foremost for all the individuals Yes.
Speaker 1:Whose PII is now potentially floating out there.
Speaker 5:Totally.
Speaker 1:It's probably quite bad for their customers who Yes. Paid for paid for the, you know, some amount of this data and now it's just floating out there. Yeah. Yeah. And then, obviously, you know, unfortunate for the company.
Speaker 1:But it's still unclear. I was looking at Lapsus, which is Mhmm.
Speaker 2:Hacker group.
Speaker 1:Styled as l a p s u s with a money sign, 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 UK in 2022.
Speaker 2:Wow.
Speaker 1:According to City of London Police, at least two of the members were teenagers. Lapsus 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.
Speaker 1:The first major cyberattack attributed to LAPSIS was against the Brazilian Health Ministry's computer systems in 2021. Lapsus gained notoriety 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 Lapsus. Although the group had been considered inactive by April 2022, it is believed to have reemerged in September 2022 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 a conviction of two British members.
Speaker 2:It's also interesting because, like, they don't enforce they don't enforce, like, brand intellectual property around hacker collectives. Yeah. 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 the response and hopefully a good resolution that is resulting quickly.
Speaker 2:Let's move on to some good news. We will be having Sebastian Mallaby join the show at 12:30 today. But Colossus Magazine published an exclusive chapter from the book, which Tyler has there, the biography of Demes Axios from Google DeepMind. And he secretly built a hedge fund inside of DeepMind trying to beat Jim Simons. Google shut it down.
Speaker 2:So there's this interesting there's this interesting screenshot that Colossus shared. Axios Package Compromised Qasar 20 researchers to train high frequency trading algorithms and explore and explore the collaboration with the Wall Street behemoth BlackRock. It was not a project of which Google approved, but Hassabis, a five a five time world games champion at the International Mind Sports Olympiad, sick, found hoped he'd found another game that he could win. One day, I asked about the story of this trading project. I was told that Hassabis wanted to beat Jim Simons, the mathematician who founded the wildly successful algorithmic hedge fund Renaissance Technologies.
Speaker 2:Rentec operated in secret, which Demes loved, my acquaintance explained to me. Did the secret deep mind 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 DeepMind team, but
Speaker 1:Dave says, but did they rip SIGs?
Speaker 2:Oh, yeah.
Speaker 1:Could have been the missing ingredient. Jude
Speaker 2:Simons, he also
Speaker 1:Everything never wear
Speaker 2: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 I heard about the the potential of a Google hedge fund years ago. I don't know if it was related to DeepMind 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 a strategy, forex.
Speaker 2:There's so many different 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 should we could build a hedge fund here.
Speaker 2: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 at 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.
Speaker 1:Sophie says Google shutting down a deep mind hedge fund quit right before they were about to
Speaker 2:Straight diamonds. Big. It really is this meme. They they probably would have printed. Although, it's not like the high frequency trading firms are are not using AI or or not using I mean, Jane Street invested in a in a custom server company or custom silicon company, something along those lines, specifically for high frequency trading.
Speaker 2:They have a lot of AI researchers researchers there. And and you see this with a lot of labs saying, hey. Does anyone from the high frequency trading industry or quant finance wanna 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 excited about. I don't know.
Speaker 2:Anyway.
Speaker 1: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. Soleiman would lead DeepMind's applied side from within Google, while Haseebis would run research as an independent global interest company. For Soleiman, this was a triumph. Google had finally signed a complex term sheet granting most of what he wanted.
Speaker 1:Haseebis was equally pleased. The plan guaranteed him an astronomical 15,000,000,000 in Guden Qasar 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. 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.
Speaker 2:That's hilarious. That's great saying. I don't want this part of my brain to grow. It's so funny that that that, you know, you're you're going through two years of negotiation. They're like, k.
Speaker 2:You're gonna be you're gonna be have so much funding to build AGI. $15,000,000,000. You're like, oh, so like a seed round for like a NeoLab? Like, great. Like, oh, so like one data center from a NeoCloud or something like it's like it's like the numbers have gotten so so big that 15,000,000,000 does not feel like anywhere near enough at this point.
Speaker 1:Colossus, hit up. Hit me, Let
Speaker 2:me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases, more while Railway automatically takes care of scaling, monitoring, and security.
Speaker 1:Tell me what the Elon Colossus shares, Elon has spent a decade trying to control an AI lab. He tried to absorb DeepMind into Tesla in 2014 and OpenAI in 2018. When that failed, an intern spoke up. It did not Interesting. Okay.
Speaker 1:Let's read through this. He also tried to control x AI to
Speaker 2:some degree. Well, doesn't he control x
Speaker 1:Well, he controls it, but at what cost? Right? All all seven cofounders.
Speaker 2:True. True. True. That's what you're referring to.
Speaker 3:Got it.
Speaker 1:Anyways, from from the book, pushing back against Musk's obsession with the race against Google and DeepMind, Brockman added, it doesn't matter who wins if everyone dies. Musk responded the next morning at 03:52AM. He confronted Brockman with a proposal that recalled Pichai's pitch. OpenAI should spin into Tesla. Initially, OpenAI's team could accelerate Tesla's development of autonomous vehicles.
Speaker 1: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. It just isn't zero. Back in 2014, Musk had Skyped Hasebis from a closet in LA
Speaker 2:What a funny a funny answer.
Speaker 1:Proposing that Tesla or SpaceX should absorb DeepMind. 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 Brockmann and Sotzkever to take his side. Together, the three told Musk that OpenAI would not attach itself to Tesla.
Speaker 1:At an all hands meeting on the Top Floor of a converted truck factory that housed OpenAI, Musk announced to the employees that he was quitting the lab scornfully I adding that
Speaker 2:Raptors. I need a I need a new Ford Raptor potentially every day. We gotta put this lab above a
Speaker 1:truck factory. This is amazing. Scornfully adding that OpenAI would have to sprint faster to stay relevant. Yep. I guess they did.
Speaker 10:Guess they did.
Speaker 1:Hoping to lure away some researchers, he declared there was a much better chance of building AGI at a strong business like Tesla. Showing courage or perhaps just youthful innocence, an intern asked Musk 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 wanna do? The intern demanded.
Speaker 1:You're a jackass, Musk retorted. Then he stormed out of the meeting.
Speaker 2:That
Speaker 1:intern? Tyler Cosgrove.
Speaker 2:No. That intern was Steve Jobs. Just kidding. That intern was Taylor Swift. It is it is my interesting read on this is like it's it's crazy that Elon was interested in in basically buying all of DeepMind, absorbing all of DeepMind.
Speaker 2:And then four years go by and he's like, I'm still I still want a lab. I want to absorb all of OpenAI instead of just incrementally adding to an internal lab at Tesla, just one researcher at a time. Like, he was able to assemble working
Speaker 1:on self driving.
Speaker 2:Yeah. He and he was able to assemble eight cofounders 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.
Speaker 2: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. It's like the Supercharger Network or 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.
Speaker 5:I don't know.
Speaker 2:Yeah. It it is just like an interesting Well. It's an interesting strategy, I suppose. Let me tell you about the New York Stock Exchange. Want to change the world, raise capital at the New York Stock Exchange.
Speaker 2: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 today. And without further ado, we have our next guest in
Speaker 1:Let's it.
Speaker 2:The restream waiting room. Let's bring in Alex from Project 11 to the TBPN. Alex, how are
Speaker 9:you doing?
Speaker 8:I'm doing great. It's great to be here, guys.
Speaker 2:Is it over, or are we back? What's going on? How bad is it? Tell it to me. Do you have it to me straight?
Speaker 2:How long do I have?
Speaker 8:Well, according to Google, you have until 2029.
Speaker 2:Okay. That's, like, forever. Upshot. That's forever in my mind.
Speaker 8:Yeah. Although maybe not forever if you think about blockchains that take a long time to change. Bitcoin's last, upgrade took four years, and that's twenty twenty nine's less than four years away.
Speaker 2:So Yeah. That seems really risky. Take us through, like, what actually changed?
Speaker 1:Because I Before we get into that, a little context, we'd love we'd love some background on on you and Project 11, and then we'll get into all the papers.
Speaker 8:Yeah. All good. Yeah. So me, I'm a former army of Green Beret. Got out or I got really interested in Bitcoin, working in The Middle East.
Speaker 8:Got out, went to tech thanks. Nice nice sound effect. Got out, went to Stanford, and then he got a job working in Venture First, then, entered the blockchain space at a company called Alio. Mhmm. Whereas after five years before getting really excited about solving this quantum problem at blockchain space.
Speaker 8:So that's what led me to founder of Project eleven. So Project eleven, I kinda gave it away. It's all about securing digital assets on blockchains into the post quantum future. Right? So, the the way I like to to frame it is that what quantum computers threaten is the underlying foundation of cryptography that all blockchains are built on.
Speaker 8:Yeah. Right? So it's that level that we have to fix. Mhmm. 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 Project eleven's all about.
Speaker 1:Just to put it into perspective, when did you found Project 11? You said it was five years. You spent five years at the last company. When did when did you actually get started on this?
Speaker 8:October 2024. So just over, I guess, almost a year and a half ago.
Speaker 1:And what was what was the general dialogue around quantum and the risk to crypto at that time?
Speaker 8:That it wasn't real. That quantum computers were always gonna be twenty years away. Oh. That, you know, that no one had to pay attention. There were bigger things to worry about.
Speaker 8: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. Right? 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 Foundation, and a Stanford cryptography professor all pound the table and say, we cannot wait to migrate anymore, then people are gonna start paying
Speaker 2:Okay. What actually changed? Because it doesn't seem like the 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, ten years away from what we thought we needed. So is this a new algorithm, a new stack of code?
Speaker 2:Or is it new math? Like what changed that we got this 20x increase in efficiency in terms of cryptography breaking via quantum computers?
Speaker 8:Yeah. A couple of things. So first off, these two papers are not necessarily about a quantum computer that's bigger or more capable. Right? So this is they're about what is what it takes to break cryptography.
Speaker 8:Right? And so what changed? So one of the things that changed was that interestingly, physicists
Speaker 1:and,
Speaker 8:you know, kind of quantum cryptographers that looked at this problem for a long time studied an algorithm called RSA. Mhmm. It's not worth defining, but it's kind of an older cryptographic algorithm. But that's not what really any blockchains use. Right?
Speaker 8: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 RRSA. Got So that is 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, as as you guys may or may not be aware, as your audience may or not be aware, are kinda, you know, they're very fragile, generally.
Speaker 8:So to be useful, they need to have what's called error correction applied. Mhmm. And that error correction can kinda result in a lot of overhead. You need to have tons of physical qubits to get to you mentioned logical qubit to get one logical qubit. Well, this Caltech paper basically showed, hey.
Speaker 8: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 qubits. Maybe we just need a handful to make one logical qubit. So that their the title of their paper, actually, the headline is you may only need 10,000 physical qubits to break short to run Shor's algorithm. And by the way, they demonstrated last year 6,000 qubits.
Speaker 2:Okay. So we're close. Yeah.
Speaker 8:That's you know, no one can put a timeline on it, but how how fast do you think you can close that gap
Speaker 5:Yes.
Speaker 8:Is the question.
Speaker 2:Okay. Is it possible, Jordy was throwing out the idea of someone having a secret quantum computer going around the blockchain siphoning Bitcoin from, you know, cold wallets that haven't been
Speaker 1:I'm not I wasn't implying that it exists yet. Just implying the incentive of Yeah. If somebody were to create one of these. But but but Yeah. The way you're reacting, I'm imagining it's like if if somebody does it, it'll be Google first, which is maybe a good thing.
Speaker 1:I don't know.
Speaker 8:It's like it's really hard to know how it's gonna play out. I I read a whole blog post on our on our blog on project11.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?
Speaker 2:Yeah.
Speaker 8:You know, because why do people want quantum computers generally? Well, they're great for science. Two, like, you can imagine governments that wanna do espionage might want the ability to break cryptography too.
Speaker 2:Yep.
Speaker 8:They probably don't wanna reveal what they have, certainly not if it's China or Russia. Yeah. Right? And, you know, and but and private companies, maybe not Google, but maybe some of these pure play quantum companies. Like, how are they gonna make money?
Speaker 8:Well, one way would be to recover Satoshi's Bitcoin as if it were buried treasure. Right? Like, oh, it's buried treasure. Satoshi's not here. It's mine
Speaker 2:now. Yep.
Speaker 8:Right? So, I mean, that could be another scenario. So, look, I think that the there is just a whole bunch of uncertainty about how this is gonna play out, about who's gonna 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 and we pursue this, you know, with solving this problem very vigorously is because everything's on the line here.
Speaker 8:And we have to solve it for these chains like Bitcoin to have a feature.
Speaker 1:Yeah. Is there generally low optimism right now that Bitcoin developers will be able to react quickly enough?
Speaker 8: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. Mean, I their greatest strength is the fact that there's no single party that says how it works or how it should work. Right?
Speaker 8:And this is 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 in the face of a crisis like this that demands a massive technical effort to overhaul.
Speaker 2:Mhmm.
Speaker 8: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. That's just, know, someone at Google can make that decision snap. Right? In Bitcoin, because it's a distributed community, everyone's kinda first has to agree there's even a problem, then everyone has to agree on the solution. But I think there's examples of of, places where blockchains, like, you know, I'll I'll take Ethereum, have done amazing things.
Speaker 8:Right? So one is they they transitioned from an old system of consensus called proof of work to a new system called proof of stake. It took four years to be sure, but it involved thousands of people all over the world, and they did it. They did it. The blockchain's been running.
Speaker 8:Ethereum is the second largest 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.
Speaker 1:What about the rest of the digital world? Because if if if Bitcoin is having problems, then so many other kind of core institutions and companies, organizations, I imagine, would have issues as well. Maybe maybe because they are centralized, there's, you know, easier to react, easier to kind of lock things down, but still need to upgrade overall encryption.
Speaker 8: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 one reason is obvious. I mean, Satoshi, Satoshi's Bitcoin, so if 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 has moved.
Speaker 8:There's a bunch of lost coins. 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 in, you know, in market terms.
Speaker 2:So Yeah.
Speaker 8:That's just a huge incentive that, like let's take let's take the counterexample of, you know, if someone wanted to hack into a bank or something. You know, as you pointed out, banks are centralized. They can kinda react. Also, the cryptography the way that banks implement this cryptography is just kind of one of many layers of security. Right?
Speaker 8:So it's kinda this breaks like, theoretically, someone tried to wire all the money out of my account, my bank would
Speaker 1:call me.
Speaker 2:Yeah. No. They literally have tape drives where, you know, they have 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. Exactly.
Speaker 2: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, that's better than the chaos that we're in.
Speaker 8:That's it. And that's not true for Bitcoin.
Speaker 1:Right?
Speaker 8:All I need is one signature and all of Satoshis or Coinbases or Binance's Yeah. Bitcoin is mine. There's no fallback. There's no anything. And that's how it was designed.
Speaker 8:Right? Yeah. That's the point. That was the point. Permissionless finance.
Speaker 8:Yeah. That was so Yeah. That's the challenge.
Speaker 2:So what is the state of the more faster moving coins, faster moving 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.
Speaker 2: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 a new project, there is a bit of a white space to say, we're the ones that are taking this particular feature most most most seriously.
Speaker 8:Yeah. Look. I mean, it's kinda hard to know how things are gonna play out, but the white space that we're occupying is we wanna be the bridge
Speaker 2:Okay.
Speaker 8:For digital assets to the post quantum future.
Speaker 5:Okay.
Speaker 8: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 stablecoins have value. Yeah. And I think, overwhelmingly, they would like to keep the things that they already value and just make them secure.
Speaker 8:Yeah. So that's what we focus on. Right? 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 part of it.
Speaker 8:So, mean, I we really focus all the way across. We've done work with Solana, Solana Foundation. We did the first post quantum test set for them. We've worked with a few other protocols as well. We designed actually a new novel post quantum algorithm designed for blockchains with the founder of Zcash.
Speaker 8:We've done that too. We collaborate with EF, and we're doing we're getting ready to launch our own post quantum wallet as well.
Speaker 2: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 licensable 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.
Speaker 2:Like, we're just following the Solana standard, and so we're just gonna mirror that over onto, you know, whatever chain we're working on?
Speaker 8:Yeah. I think there will be diffusion. I think there will be, you know, sort of consensus, if you will, around a certain subset of post quantum algorithms. Mhmm. But I don't think it's just, you know, one and done because Solana is a very different system than Bitcoin.
Speaker 1:Right?
Speaker 8:Bitcoin's digital gold. It's sort of meant be slow. Yep. You know? And there's no apps on it.
Speaker 8:Solana's 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 of some of the experiments we ran with Solana. Mhmm.
Speaker 8:And, and look. This is one of the challenges. Right? And this is again, why why we keep saying this is like time to start us now because we don't know how long it's gonna take to migrate because, you know, these new algorithms, there's trade offs 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's secure, all this stuff.
Speaker 8:So
Speaker 1:Have you tried to 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 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. Mhmm.
Speaker 1:But, do you think that's that's factoring into price at all?
Speaker 8:Totally. I mean, the way I would put it is, I think if this risk didn't exist, Bitcoin would be priced significantly higher. So I think exactly what you said is right. You're like, oh, I'm not gonna 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 and Chamath has said this exact thing.
Speaker 8:He's like, hey. Was this really digital gold? Can we without with this quantum threat hanging over everyone's head? So I I think if that threat was removed, then, know, you remove this cloud over that ecosystem and potentially, you know, you have a lot more people coming in and therefore price would be up.
Speaker 1:Yeah. And the the the 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. Uh-huh. What what what countries have the most kind of advanced quantum projects outside of The US? I can guess, you know, China's, you know, investing heavily here.
Speaker 1:Do they have their own retail quantum companies that are trading like crazy?
Speaker 8:What's going on
Speaker 2:over there? Yeah.
Speaker 8:First off, I I think, definitively, the leaders, both companies and research is American. So I think we should be proud to be an American here. Mhmm. But look, 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 a lab at Tencent and at Baidu and a few other places.
Speaker 8: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?
Speaker 8:You're not allowed to talk about it anymore. And that's the state of things. It's it's kind of a I don't wanna 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 adviser to Project 11 that tracks generally resource estimates across the world, and and their view is that China may be six to twelve months behind at most.
Speaker 8:Oh. And so this is yeah. Exactly. That's not that far.
Speaker 2:Yeah. That's really quick.
Speaker 8: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, care as much about the philosophical principles of Bitcoin and decentralization Mhmm. If it serves their purposes to do otherwise? I don't think we can. And so I think, again, back to the fundamental problem, uncertainty.
Speaker 8: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.
Speaker 2:Well, thank you for everything that you're doing. Thank you for your service both here and before. Project11.com is the website. Correct?
Speaker 8:Yep. Yep. Should go check eleven. All spelled out.
Speaker 2:Yep. Fantastic. Thank you so much for taking the time to come chat with us. We'll talk to you soon.
Speaker 1:The breakdown. Have a good one.
Speaker 8:Great to be here, guys. Thanks.
Speaker 2: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 Qasar Younis in the restream waiting room from Applied Intuition.
Speaker 2:He's the founder and CEO of the company and we'll bring him in in just a second.
Speaker 4:We need
Speaker 1:little bit of time.
Speaker 2:We need a little bit ahead of schedule. A little bit ahead of schedule.
Speaker 1:We need a little bit of time.
Speaker 2: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. Allbirds just sold for $39,000,000. The company was once worth over $4,000,000,000 with d to c darling. Followed this company closely because I was building a d to c company at the same time.
Speaker 2:I was like, wow. They are really getting big. But it 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.
Speaker 2:Did you ever wear a pair of Allbirds? Would they ever pull you away from Bottega, get you in some Allbirds? You know, it's Australian wool. You know? It's kind of like Italian leather
Speaker 1:wool aspect.
Speaker 2:Australian wool. Yeah. There's something like that.
Speaker 1:No. I never I never owned Never a pair owned a pair? Birds.
Speaker 2:Not even if you're visiting San Francisco. It's a great it's a great It's
Speaker 1:a great sign of respect.
Speaker 2:Sign of respect.
Speaker 1:You ever did you ever have a pair? I had Probably did.
Speaker 2:Think I had one pair at some point. They were okay. They didn't I don't know. They they they sort of like look okay and were comfortable on day one, but then they sort of deteriorate a little quickly. This
Speaker 1:would be probably 2 to $3,000,000,000,000 company Mhmm. If the shoes had aura. Yeah. But they they had They
Speaker 2:should have released a lot.
Speaker 1:They actually had Aura. It seems like they potentially had negative Negative aura.
Speaker 2:Yeah.
Speaker 1:Yeah.
Speaker 2:And they got and the, I mean, the stocks suffered. They they had to pay the Aura tax.
Speaker 1:The Aura discount.
Speaker 2:Massive Aura loss. Yeah. Yeah. I mean, 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 putting the supply chain on display basically.
Speaker 2:It was the right fit at the time. But people are not not into it. The chat is not is not happy about
Speaker 1:Let's ask our dear friend
Speaker 2:Qasar Younis from Applied Intuition because he's here. He's on the TBPN UltraDome now. Qasar, how are doing?
Speaker 6:I'm doing great. How about you guys?
Speaker 2:We're doing great. Have to ask
Speaker 1:Thank you.
Speaker 2:Do you own a pair of Allbirds? What's your preferred shoe when you're walking around a factory like that?
Speaker 6:I don't own any Allbirds when you're in a factory. You have to wear. Yeah. Exactly. You have to have a steel there's no allbirds.
Speaker 2:Maybe they should. Maybe that's the comeback story for them. So they just they were worth 4,000,000,000. Now they're worth 40. Maybe the steel toe allbirds are what gets it done.
Speaker 2:There you go. A steel toe allbird would look fantastic. 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?
Speaker 6:Okay. Great. Yeah. I can hear you and I can see you okay.
Speaker 2:Okay. Fantastic.
Speaker 6:Exactly what's going on.
Speaker 2:Well, great to have you back on the show. I'd love for you to just reset with us for the the shape of the business, where the company is today, how big are you? Give us, you know, the broad strokes, then we'll go into the partnership today.
Speaker 6:Yeah. Thank you. Thanks again for having me. The company, Applied Intuition, we're a $15,000,000,000 company still doing what we were doing before, which is taking intelligence and putting it into physical machines. Mhmm.
Speaker 6:Today, we have our first ever physical AI day where we're bringing lots of investors 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 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.
Speaker 2:Yeah. I couldn't agree more. Talk about the the most recent partnership, LG.
Speaker 6:Yeah. LG InnoTech. We just we just announced this a couple of days ago. The I don't know how many of your viewers know, but LG provides
Speaker 2:in TVs. That's what you're doing. Yeah. The AI is going in the TV and I'm gonna be able to ask questions. That
Speaker 6:is not that is not what we're doing.
Speaker 2:Much more serious.
Speaker 6:I mean, what what's happening in the self driving space is there is the models are basically working and they're they're figuring it out. So really, there's an aggressive downward pricing pressure of how to make self driving cheaper. The the research kind of question is done, and now it's just an engineering question. And that's just another way of 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.
Speaker 2:Yeah.
Speaker 6:You know, they're they're entering the space as well. We're working together with them on self driving.
Speaker 2:Yeah. So, yeah. Take me through, and when when people think self driving, they always think Waymo, Tesla, but the the the the 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.
Speaker 2:I I know that it's very broad. What's in this partnership and then what else are you focused on? What's adjacent, and what's, you know, on the road map?
Speaker 6:Yeah. So I think what's different about us versus, let's say, vertical players like 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 were you guys were here for Physical AI Day, we do we take the same models and we put them in defense. We put them in commercial trucks.
Speaker 6:We're running driverless trucks in Japan right now that are going into commercial operations in the next quarter. We are running in mines. So both all the way from, you know, Arizona to Australia. So our hypothesis basically is these these these technologies, whether it's self driving or the underlying operating system, they're so expensive and they're so complex to build Yeah. And maintain.
Speaker 6:The only way that you really make this a viable business is that you actually spread this across lots of manufacturers 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 ten years old and we've preserved basically all the capital we've ever raised.
Speaker 2:That's amazing. We
Speaker 6:love it. Like b s. Yeah.
Speaker 2:It's crazy.
Speaker 6:The The the whole mantra is, you know, raise a lot of capital and Yep. And deploy. And we're a real AI company. We have real AI bills, and we've Yeah. We figured a commercial model, which is allowed to scale.
Speaker 6:We're we have over a thousand engineers, and so we're one of the, if not the biggest, physical AI companies on the planet. Yeah. That's obviously also commercially viable. So But it all goes back to that simple thing is like, you want to distribute all this cost across lots and lots of companies, lots and lots of verticals.
Speaker 1:What about shared learnings? Like, you a team that's working on mining, are they able to find a breakthrough or discover something you can apply to trucking in Japan? Is there a
Speaker 6:lot Absolutely. Of That that is the heart of the company. So there's all what you what you described as like shared learning kind of broadly, but there's also technical advantage. What we've seen is taking data, which is just obviously also not obvious, but taking really really diverse data from a mine actually makes our self driving car system better.
Speaker 2:Mhmm.
Speaker 6:And taking instead, you know, 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 Yeah. Core to our
Speaker 2:strategy. Yeah. I've heard so many stories about that where like there will be like exactly one instance of a 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 And these and scaled 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.
Speaker 6:Yeah. Maybe getting a level level lower just just so because I was me being an engineer bothers me to talk in pure generality. Yeah. You tend to mix that mis thing. Yeah.
Speaker 6:Getting to a level lower, what you're really talking about is anomaly detection.
Speaker 2:Sure.
Speaker 6:And it's not necessarily like, you know, you need to see the chicken running across the road in Thailand and that's gonna 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 the last kind of generation, I'm crazy to say last generation, but really large language models. Yeah. Large language models really improve with diversity of data.
Speaker 6:That is really like, you know, a kind of a big breakthrough. And of course, scaling laws. All of that stuff is being brought in to the physical world. Yeah. And and then we're we're powering
Speaker 2: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. Play out the counterfactual for me.
Speaker 2:You 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 is is that Yeah.
Speaker 2:Impossible?
Speaker 6:It's well, nothing is impossible. There were But, you know, I my my my undergrad was at this obscure school called the General Motors Institute. And as the name implies, it's really about automotive. It's like the West Point for automotive.
Speaker 2:Mhmm.
Speaker 6:And when you spend a lot of years in factories as as I have Yeah. There are some deep lessons that get imparted into you. And one of those lessons is, holy crap, these factories are extremely cost intent, like capital intensive, and they're extremely complex. Mhmm. And strengths of Silicon Valley are actually don't quite overlap with the strengths of building a large factory.
Speaker 2:Mhmm.
Speaker 6:Now, in terms of the core question, we had Marc Andreessen here today. We we, you know, we we talked about this. Marc was one of our first investors and has kind of been been along with us with the entire ride, I mean, all the way to the presentation today. And we asked him this question about vertical, horizontal, what do you see happening in AI? What do you see happening specifically in physical AI?
Speaker 6:And the punch line is, you know, we all of our values at Applied Intuition can be reduced down to two words, radical pragmatism. Mhmm. And if there are verticals that we think that we should be a bit more vertical in, we'll we'll we'll do that. And I think it's it's kind of a false trade off to say what we do in, you know, trucking is what we're going to do in construction, which
Speaker 2:Yeah.
Speaker 6: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.
Speaker 2:Mhmm.
Speaker 6:And each of these verticals are facing really really different problems. You take ag, you know, with the with the tracker behind me, the average American farmer is 58 years old. Mhmm. There's nobody coming to replace that person. And so what is gonna happen?
Speaker 6:Because, you know, if you take that person, their kids have 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 the on on their behalf. So he can run an entire farm with a, you know, with a swarm of machines.
Speaker 6:And that's not, you know, that's not too far into sci fi.
Speaker 2:That's true.
Speaker 6:One of the key components here that, you know, we're doing and we believe is you need to abstract that hardware and software away. We we as technologists, you look at like your laptop and your phone and you kind of take for granted the miracle that exists. Android runs on thousands of hardware devices flawlessly. Yeah. So that's also something that Applied does.
Speaker 6:We're just abstracting the hardware and software. Once you do that, you can make every machine, you know, intelligent.
Speaker 1:Have you tried to estimate the economic impact assuming you guys, you know, stay at the, you know, at at the current kind of improvement rate or accelerate as the technology kind of starts to diffuse in in some of these industries like trucking and and mining Yeah. And agriculture. Like, what what are the downstream impacts? I mean, there's such a debate right now around what what what impact will AI have on the economy? So much of the economy is like moving physical things around, producing things
Speaker 6:Yeah. So shipping them. Let's let's yeah. Exactly. Let's separate a little because economy is such a generalization.
Speaker 6:So Yeah. When you're talking about like, you know, Code Complete and white collar workers, very different than, you know, trucking where there is a huge labor shortage. It's very different than in mining where, you know, people don't wanna go live in kind of remote areas doing twelve 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.
Speaker 6:Yeah. It's a very different calculus than a kind of, you know, I think what the normal narrative is. And and then we're super obviously excited about that. Let's take defense as a particular example. It's a very salient example.
Speaker 6:We don't need more war fighters in harm's way. We need less war fighters in harm's way. Yeah. And no war fighter wants to go out in in into that ecosystem where autonomy is really becoming the dominant thing. And so so I think the way to think about this impact in the physical world is it's a lot less resistance.
Speaker 6:There's a lot more pull. 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 the
Speaker 2:I'm asking you
Speaker 1:to I'm asking you. I want I want the biggest number. Want the biggest number.
Speaker 6:The numbers are absurd and ridiculous. I but there but I I can tell you this much. If you think about, you know, the way I think about yeah. I used to be a Y Combinator before I was the COO and and and Yeah. You know, ran the firm and funded lots of interesting companies.
Speaker 6:And one of the analogies I used to use to help founders understand market potential, market size is, yeah, I grew up in Detroit. You're sitting in the Detroit Metro Airport, and you're sitting in a gate, and you look around. How many of those people are, like, really deeply using Claude code? I mean Sure. Frankly speaking, not many.
Speaker 6:Not a lot will probably be using something like ChatGPT Sure. Some variant of that, maybe Gemini. But how many of those people drive? Many of those people work at construction sites? How many of those people ride in buses?
Speaker 6:How many of those people serve in our armed forces? The point is a much, much larger group. And I I like it that I I feel a little again, the engineer in me feels a little awkward saying these kind of you know, pitching these things, 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 of 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.
Speaker 6:In physical AI, you've got to kind of know what's going on in the car business. And I'm not saying, you know, I'm not, you know, gatekeeping and saying you had go to the General Motors Institute to build technology for the car business, but you bet your bottom dollar, it helps. Yeah. And and we're doing that across a bunch of industries. I think it's I think it's you know, I'm I'm as confident about the company as ever before.
Speaker 6:You know, the question we always get asked this question, why the hell did you raise all this money, you know, almost a billion dollars, and it's gonna keep plowing it away in the bank account? We're doing it for a simple simple reason, because we can 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 worked. It's not to, you know, promise the future that we won't, but that's Those are kind of debates we have every single day.
Speaker 2:Yeah. That makes a ton of sense. Well, thank you so much.
Speaker 1:I just want to say I can see the path to a 100 and then $1,000,000,000,000 in in run rate. I agree. I can see.
Speaker 6:Well, I mean, Waymo, you know, a company that we we we love them. They're a local you know, we're 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 a $126,000,000,000. Oh.
Speaker 2:Shout
Speaker 6:out guys. I mean, we have so many friends there.
Speaker 2:I'm not
Speaker 6:I'm not trying to talk poorly about
Speaker 2:this. But
Speaker 1:No. We love Waymo too. It's it's very what they're you
Speaker 6:know, 15 that we're at and a 120 I think I think
Speaker 2:we got room to run.
Speaker 6:Massive, massive. Yeah. Got room to grow.
Speaker 1:Tell tell Mark. Tell Mark you're ready.
Speaker 2:You're ready for the big one.
Speaker 6:Believe believe me. The the the everybody wants to share, you know, it's somewhere I feel like a faux guas where they wanna get peep keep putting money, you know, money into the company. We we don't need
Speaker 2:That is the best analogy for a venture capitalist. Yeah. Stuffing the goose.
Speaker 6:We we we have our own we have our own farm, you know, and we're we're making our own money, so that that's really great. And frankly speaking, I mean like I said, Waymo is great, but it's just robo taxis.
Speaker 2:Yeah. Yeah.
Speaker 6:And and So much it's much go to go Warren, Michigan. Yeah. And you just go go to the party store shop in the corner and say, hey, aren't 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 gonna be.
Speaker 2:Yeah. Well, thank you so much for taking the time to come chat with us. Thanks. Have a great rest of your day.
Speaker 1:I'll talk to
Speaker 2:you soon.
Speaker 6:Guys. Thanks.
Speaker 2:Yeah. Bye. See you. Let me tell you all about public.com investing for those that take it seriously. We got stocks, options, bonds, crypto, treasuries, and more with great customer service, and we're talking to them later today.
Speaker 2:But first, we have Sebastian Mallaby. He is the author of The Infinity Machine. Sebastian, how are you doing?
Speaker 5:I'm doing great. Thank you.
Speaker 2:Thank you so much for So great to have you.
Speaker 1:This has been We're very much You've been on on John's Radar for a long time. Dream guest list for a long time.
Speaker 2:We met maybe four years ago at a 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. I asked you what's your next book going to be about?
Speaker 2:Because you had selected Venture Capital. Venture Capital had done very well. And I presumed 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.
Speaker 2:Is there anything I should read into that?
Speaker 5:Well, I always kick the tires on a few ideas before I I settle on one. And, I think it took me from the parallel coming out in February, of 2022 to somewhere around the summer, maybe August, when I already settled on AI. And then it took me another, I don't know, three months to get the courage up to go and pitch Demes Axios 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? Chatty PT came out.
Speaker 5:So what I thought was maybe a fringe subject
Speaker 6:Yeah.
Speaker 5:Went mainstream super fast.
Speaker 2:Super fast. What was the response with the team? What was the process? Obviously, he's extremely busy. He also sleeps at very random times.
Speaker 2:We can get into that. But what was your actual interaction? How much time did you spend? What was the research process like?
Speaker 5: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 Yeah. That means you're way too important not to have a book about you, and it's gonna happen.
Speaker 5:So you better get used to it.
Speaker 2:Yeah.
Speaker 5:And also, if you're gonna upend our lives, you know, change the way we think about ourselves as humans because it's a rival form of machine intelligence, you know, you better explain your motives to people. Otherwise, they're not gonna accept it. So that was the pitch. He agreed.
Speaker 2:Yeah.
Speaker 5: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, 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, by far the most fascinating person I've ever written about.
Speaker 2:Wow. That's 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 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. I love that type of storytelling, but this goes a little bit of a different direction.
Speaker 2:So how did you how did you think about balancing all the different perspectives that you could bring to his story?
Speaker 5:Yeah. I mean, I always wanna do the personality, the 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 is boring if it doesn't mean anything. Yeah. So you have to link it to larger stuff that's going on in capitalism and how society is gonna change and all that.
Speaker 5:And, I mean, in this case, because Demes is who he is and he would just riff in these extraordinary paragraphs of, like, storytelling and and theoretical stuff and, you know, it's just so fascinating. But I did give him the microphone more than I have in any other book. I mean, I basically quote 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 Demes talking. And I'd never used the first person really before in my other books, but in this case, those thirty plus hours I had talking in a pub with this extraordinary man, that was the gold dust I had.
Speaker 5:To really make the most of it, I did have these passages of us talking together Yeah. Which kind of intersperse the more analytical or narrative bits of the book. You know, how after the transformer model dropped, what was Ilias Sass gave us reaction and why did OpenAI get ahead? You know, I cover all that stuff as well.
Speaker 2:Yeah.
Speaker 5:But I do have these passages where you see events through Demes' eyes because and I think it's worth doing because he's so unusual.
Speaker 2:What was your understanding of AI or view on AI in 2022 before you meet Demes for the first time? Were you aware of the doom arguments? Were you a believer in the technology? Did you think it was twenty years away, a hundred years away, two years away? Like where did you where were you before this book?
Speaker 2:Because I feel like it probably changed you.
Speaker 5:Yeah. You know, I had met Demes before at tech conferences. Mhmm. Because of the power law and writing about venture capital, I would go to tech conferences in Europe and he would sometimes be there. And I I I actually cheekily, you know, raised the issue of hedge funds and especially, you know, the one Renaissance Technologies, the the main CEO, Peter Brown, had done a PhD with Jeff Hinton about AI back in the day.
Speaker 5:And, of course, I knew that Dennis would know that. And so I said, you know, do do you know these guys who use deep learning and applied it to markets? And and that got his attention. So I I talked to him a bit. So I I knew that he was amazing.
Speaker 5:I knew that the technology was ripe in the sense that he produced this string of breakthroughs, you know, AlphaGo defeating the human Go champion Mhmm. Then AlphaZero, which was even stronger, then there was AlphaFold, which won him the Nobel Prize Yeah. 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 they dealt with they dealt with insane amounts of data, crazy combinatorial spaces. Like in Go, there's three hundred and sixty one first moves you can make.
Speaker 5:Okay? That's way more than chess.
Speaker 2:Yeah.
Speaker 5: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, the title of the book, and hence my enthusiasm for writing about it. And, you know, so I I knew it was breaking out. I knew Demes was amazing. What I didn't know is it was gonna break out literally the week after I met him and pitched him on the idea.
Speaker 1:What what has surprised you about how the industry overall has evolved since you started meeting with Demes? Because in some ways, I have to imagine you kind of maybe maybe it hasn't been that surprising at all even though a lot of the the growth is is impressive. But do you feel like you had a view into the future from those first conversations in the pub?
Speaker 5:Yeah. I mean, I think, you know, I was lucky that the meetings were bookended by, you know, going to see Demes sort of maybe the third meeting or something. Chatty Peejee 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.
Speaker 5: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.
Speaker 5:And then after that comes the merger between Google Brain and Mountain View and the DeepMind team in London. So the two kind of halves of Google's AI talent base are are united. And then I think you get what, you know, a business school professor is in the future gonna write about. It's kinda like a textbook case in how you make a merger successful. Mhmm.
Speaker 5:Because everyone knows that 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 in the middle of this knockdown, drag out, you know, capitalist fight over building LLMs, this is this is gonna you know, most people said this is gonna fail. And I would come to Silicon Valley while I was doing the book, checking with my friends at, you know, different venture capital shops, and they'd all say, game over. OpenAI has won. And, you know, the surprise is that within two and a half years, Demises Arbes', you know, Google DeepMind model, Gemini Yeah.
Speaker 5:Was doing better on the rankings than the OpenAI model. So that was an incredibly fast comeback.
Speaker 2:Yeah. How do you think about the importance of being, like, a business person or a deal guy in AI? It feels like Demes has this quote, he doesn't want to grow that part of his brain referring to some legal negotiations
Speaker 11:that Solomon. Took a number of
Speaker 2:Oh oh, is that Massafa? That was No.
Speaker 5:Actually, that that that was Dennis said. Yeah. I don't want part of this this part of my brain to grow Right. And so take away these legal briefs.
Speaker 2: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 marshal an extra 10,000,000,000 of compute actually does unlock a new capability and is almost in the research track. And I'm wondering how you perceive the relative importance or Demes' perception of the relative importance of these sort of like business dealings that might be more critical path to AGI than the Demes of 2021 might think?
Speaker 5:You know, I would say that the single most important business relationship in the world today is between Sundar Pichai, you know, CEO of Google, and Demes Axios Package, who's running the AI Yeah. Brain trust. Because, you know, Sundar has Demes' back. He deals with providing the resources, you know, supporting the notion that you're gonna spend all these tens and maybe hundreds of billions on compute. You know, that's Sundar's that's what he delivers.
Speaker 5:Yeah. And he gives Demes 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, Demes, we've got to a point where building a product like Gemini is in fact advancing the progress towards AGI. There's not a there's no tension between the two. If you had stopped your AGI research ten years ago and taken a sidetrack to build some widget, yeah, that would have been a waste of time.
Speaker 5:Mhmm. But now that it's so mature and you're actually to build the next LLM, you've gotta kinda figure out, you know, a reasoning model, then it's gonna be agentic, and then you're gonna be scaling it even more, and all this is stuff that we've seen. And this is genuine scientific progress as well as product advance.
Speaker 2: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 becoming a believer in the Demes world view of the impact of AGI, what artificial intelligence will do. That mindset has to diffuse through Google. The ChatGPT viral moment clearly had an impact.
Speaker 2:I'm sure agentic coding has had a similar impact. But what has Demes' role been in being the culture carrier of that belief in AI progress internally?
Speaker 5:Well, I think he's used all his sort of visionary communication skills to unite the Mountain View team and and the and the London team. Mhmm. And I think the the the one sort of organizational contribution he's made, which is sort of super powerful, is that from a long time ago, DeepMind 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.
Speaker 5:You could publish papers and all that. You know? Go go go find what you wanna find. And then there were moments when Demes 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. And so he did this repeatedly with, you know, AlphaGo and AlphaFold.
Speaker 5:And this was about his judgment, scientific taste being applied to knowing when, know, you the moment was ripe to to really go for it. And once he decided that, there was, you know, the blue sky research 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.
Speaker 5:You had to be contributing to the main one. And that drives towards, you know a team is driving in a united way towards an outcome. And I don't think Google Brain had that. Google Brain had, you know, much more of the bottom up stuff. Mhmm.
Speaker 5:And there was no strike team component. And but and and so Demes brought this strike team idea, and it came from video game design. You know, earlier in his life, he'd been a a builder of video games, and he, in fact, started a company doing that. Yeah. And so this was like how you ship product, and and that's been a key insight for Gemini.
Speaker 1:Yeah. Google and Gemini have every 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 DeepMind given that they have something very real to lose? Right? It's not just about the, you know, maybe Dennis' personal desire to be at be, you know, be at the forefront of this research.
Speaker 1:But if you're not successful, then you you lose one of the greatest business you have the potential to lose or or have your kind of core business
Speaker 2:Google Search.
Speaker 1:Threatened. Yeah. Google
Speaker 2:Search Oh, sure.
Speaker 1:In in such a big way. Yeah.
Speaker 5: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 wanna support its reputation.
Speaker 5:And so I think they were more worried about, you know, releasing a chatbot, fast. And so they had they had prototypes of a chatbot in the 2022, and they didn't wanna release, and then OpenAI went ahead and did it. And so that kind of forced their hand, but their first instinct was, is it gonna hallucinate? This is gonna do bad stuff. We can't afford that hit to our reputation.
Speaker 5:And, you know, Demes 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're still it it still went viral, you know, so we should be less inhibited. But but that was an example of how being at Google could be a kind of inhibition in moving ahead.
Speaker 2:How do you how does Demes and he's always told a very optimistic story about AI. I I love him as a science communicator, as a as a as an optimist. How has he interfaced with the effective altruist community, more of the AI doom crowd. Does he because he doesn't talk about it that often, but does he think about it often?
Speaker 5:He does think about it. In fact, you know, he met his cofounder Shane Legg at an AI safety lecture. Mhmm. Right? They bonded it in a safety lecture.
Speaker 2:Yeah.
Speaker 5:And so right from the beginning, safety has been a big part of the agenda. And when Demes sold his company to Google in early twenty fourteen, part of the deal was you're not gonna use this technology for weapons ever, and you're gonna have a special independent oversight kind of committee, you know, which will decide on AGI deployment because we don't want that to be just up to the corporate board of of Google.
Speaker 1:Mhmm.
Speaker 5:Now, you know, he's he's slipped on some of these things, particularly the military stuff. 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.
Speaker 5:He's doing terribly badly as a sort of AI steward, as as making it safe. It's just it it turns out that there's a race dynamic. The race dynamic includes China. Yeah. You know, how do
Speaker 9:you
Speaker 5:control this technology when everybody is racing to jam it out the door?
Speaker 1:Yeah. It was interesting. Last week, we were talking about how, you know, Bernie Sanders has come out with a with a push to to pause data center development and he quotes Demes and some other lab leads talking about how they would agree to a pause if other countries were were kind of in agreement on it. But it's difficult. Bernie obviously left out the fact that I don't think any lab lead could see China pausing on development.
Speaker 1:Yeah. How has 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 it was Months ago. Six weeks ago exactly.
Speaker 1:And then then and 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?
Speaker 5:You're you're you're completely right. Everybody has their own definition, and so my solution is not to have that discussion. I mean, who cares what, you know, this You could say right now it's Gemini is artificial. It's general. It's intelligent.
Speaker 5:Game over. But Yeah. You know, just a definition thing. I think the other one, is sort of usually frugal is is AI conscious? Could it become conscious?
Speaker 5:What is consciousness? Nobody has a good idea. So Yeah. Let's just sidestep those things.
Speaker 2: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. 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.
Speaker 5:That's interesting.
Speaker 2:It was just an interesting thought experiment. I don't know that anyone's actually run the run the test. I don't know that I would even accept it if they did, but it is something to think about.
Speaker 1:Did did you feel an acceleration in your personal writing process due to AI?
Speaker 5:I felt an acceleration in my learning process, 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, you know, recently, there's been less publication, but, you know, certainly up to about 2022, you could go see a scientist either at DeepMind or one of the rival labs and and just have a conversation with the 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?
Speaker 5:That was a super efficient way of getting up to speed, and I didn't worry that it might be wrong because I was gonna speak to the human and cross check it. But that that was helpful.
Speaker 1:Do you think Demes' having a having a home base in The UK is in what ways do you think it would have helped or or hurt the company so far? Like, has it been beneficial from the talent war standpoint? I'm sure I'm sure lab US some of the other lab leads have taken a trip out to The UK to
Speaker 2:Mark Zuckerberg's hoping hosting nightly dinners for AI leads at his house, is just a couple blocks from all the other labs. Can't do that if you're in the researchers are in The UK.
Speaker 5:Right. Yeah. I mean, there is movement across The Atlantic, but I think the deal is if you're in London, it's a little harder to recruit people. But once you've got them, they're probably stickier than they would be if
Speaker 1:Yeah.
Speaker 5:If you're in Mountain View or somewhere. Yeah. You know, I think Demes has stayed in London because, actually, he is weirdly patriotic. You know, he comes from this mixed up sort of, you know, Greek heritage father, a Singaporean Chinese mother. In a way, that makes him a typical Londoner Yeah.
Speaker 5: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 maybe 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 DeepMind office in London, you know, you go past the sort of public spaces like this kind of fountain with toddlers playing in it, and there's a 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 are playing soccer.
Speaker 5:And then you get to the Dibbein office, and it it's hard to imagine you'd find that as on the way to the, you know, the the Apple Yeah. Headquarters or something. And, you know, it's it's just a different vibe.
Speaker 1:Could you ever see Demes as CEO of Google, or would you have to do too much paperwork?
Speaker 5:You know, this gets to the heart of the dichotomy about Demes. 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 wanna retire to the Princeton Advanced Institute of Advanced Studies and and do what Einstein and Oppenheimer did before me and go there. And that you know, I think he really means it when he says that. Yeah.
Speaker 5:At the same time, he also wants to be in command of, you know, an AI lab, and he he likes the capitalist competition. Mhmm. So if he had the opportunity to be chief executive of the whole of Google, I suspect he's too competitive to say no, but but who knows? I mean, there is that science side. So I it's genuinely unpredictable.
Speaker 5:He he probably doesn't know himself.
Speaker 2:Were you left personally That's new. Optimistic after this process about just our AI future broadly, net positive impact from AI?
Speaker 5:I mean, clearly, there's a lot of upside, especially in medicine and pharmaceutical discovery. I think you have to be honest and say there's also downside, significant downside. And as I continued to do the research for this project, you know, I I 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 than humans. Obviously, that they will be. Yeah.
Speaker 5:But whether they whether machines have a motivation to harm humans, and he is very persuasive in arguing that they will. I mean, my point was, look, 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.
Speaker 5:So why would they attack us? Why are you so worried, Jeff? And Jeff is like, well, you know, imagine you've got this super powerful AI, and it's gonna be attacked by the enemy AI, and you have to defend it. So you tell the AI, if you see a cyberattack coming, you've got to fight back. You've got to defend yourself.
Speaker 5:And now all of a sudden, you've given your AI a survival instinct. Yeah. And so don't tell me that evolution has to happen as it happened to humans. The evolution can happen in a machine way.
Speaker 2:Mhmm.
Speaker 5:But these systems are gonna wanna survive, and they're gonna be more intelligent than us. Mhmm. 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.
Speaker 5:And I I I think that's how humans generally respond to all technology. And if we didn't take that trade and move forward with both the excitement and the scariness of technology, you know, we if we didn't take that, we'd be still living in caves.
Speaker 2:Yeah.
Speaker 5:So in some sense, the story of Demes is like, you know, the story of all of us, but magnified 10 x.
Speaker 2:There's a documentary that was just released or might be releasing right now that features an interview with Demes, the AI doc. And it it it spends more time talking to all the different lab leads and voices in the industry, more focused on the doom question. 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.
Speaker 2:And I'm wondering if you got any vibes any that everything will collapse, that this is just not financially viable.
Speaker 5:No. My view is that there's no AI bubble, 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, you we had the first chatbot 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 video and pictures, and then they went to reasoning models, and now we're getting agentic models.
Speaker 5:And now next, there's gonna be, you know, world models that will be built into these things. This is a lot of progress in just three and a half years. So I think it's it's accelerating in progress, and therefore, it's not a bubble. Mhmm. But what is true is that it's super expensive to develop.
Speaker 5:And if you're not attached to a really deep pocket like, you know, Demes is attached to Sundar, you're in trouble because I don't think OpenAI can raise enough money to bridge from today when they have a 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. And so I think, you know, OpenAI has been running two simultaneous experiments. One is with a new frontier technology, and the second is how deep are global capital markets? And they already raised, you know, 41,000,000,000 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.
Speaker 5:But can you pull that trick, like, on a bigger scale every year until 2030 when they hope to break even? No. And that's why they're cutting
Speaker 1:Except for except for right now. What? They just raised the 100 and The 100
Speaker 10:and 10.
Speaker 5:20 But if you look at the 100, it's kind of smoke and mirrors. That's that's you know, lot of that is contingent on you you get this money if you go public. You get this money in the future. You get this money in kind in terms of, you know, compute or something. The 100 wasn't really a 100.
Speaker 2: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 a tension between the the industry and Google. This is like the foundational, like, myth of of the AI industry and AI labs broadly, although they, of course, have fractured many, many times at this point.
Speaker 5:Yeah. I mean, you know, of course, there's always rivalries. Right. You know, one might say people will gang up on Nvidia. Know, that's the occupational hazard of being the leader.
Speaker 5:Right?
Speaker 2:Yeah. Right.
Speaker 5: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.
Speaker 1:Yeah. That makes sense. Last question from my side, then we'll we'll let you go. Did you have any takeaways or kind of ideas around the diffusion of physical AI and robotics? Did anything stand out?
Speaker 1:Do you have a strong opinion there? Right now, it feels like we've entered the sort of software singularity, But we we just had Qasar from Applied Intuition on, 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.
Speaker 5:Yeah. 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 chatbots. And so robotics is being improved by this technology, and, you know, I fully expect to see a huge breakthrough, you know, over over the next two or three years with the capability of robotics. And so I think that's that's going to be the the big story. I kind of agree with the guy from Qasar you had before that, you know, the movement of atoms is going to be affected as much as as anything else.
Speaker 5: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 is enormous.
Speaker 2:Yeah. Well, thank you so much for coming and joining the show. Was a pleasure talking to you. The book is The Infinity Machine. Available everywhere books are sold.
Speaker 2:Thank you so much.
Speaker 1:Fantastic cover too.
Speaker 2:Yeah. Beautiful cover.
Speaker 5:Yeah. Thank you for having me.
Speaker 2:We'll talk to you soon. Have a great rest of your week.
Speaker 4:Alright.
Speaker 2:Goodbye. Take care, guys. Let me tell you about fin dot ai, the number one AI agent for customer service. If you want AI to handle your customer support, go to fin.ai. And we will kick off the Lambda Lightning round.
Speaker 2:Let's see. Oh, look at this. We got everything. This is amazing. Let's bring in Forrest.
Speaker 2:Forrest from Somos. Welcome to the stream. How are you doing?
Speaker 10:Hello, guys. How are doing?
Speaker 2:We're doing
Speaker 10:great. Thanks for managing.
Speaker 2:First time on the show. Please introduce yourself.
Speaker 1:What a what a setup here.
Speaker 2:It's a great setup. Setup. Looks fantastic.
Speaker 10:A bunch of nerdy stuff from the the team, all the things we're building. No. I guess.
Speaker 1:I'm Forrest. Yeah. Break it down. Yeah. Kick it off.
Speaker 10:Let's see. Where do I start? 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 America and beyond. So very weird journey, making the fastest Internet in the world at the lowest cost is kind of a summary in a very short nutshell.
Speaker 1:Amazing. You have a lot of fans. I got a bunch of texts from investors that were excited for you to come on. What what were you doing before before we get into so much, what were you doing before this?
Speaker 10:Dude, I came to Medellin when I was like 18 years old, basically just dropped out of high school. I started building stuff and ostensibly came to visit a friend for a couple weeks and that was eight years ago and here I am. I I made websites, I kinda took a very nontraditional path and it's led me to doing a bunch of weird stuff here.
Speaker 1:That's actually a nontraditional path normally when somebody comes on and says they had a nontraditional path. It's like, you know, Stanford to a meta internship, a Google internship, a VC internship. But very, very cool. What yeah. Breakdown, like, you know, Somos, you're raising a series b today.
Speaker 1:What like, how long have you been at it? What what initially? I I 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 what's the backstory?
Speaker 10:No. I I came to Columbia in 2018. I got roped into helping people build this, like, blockchain incentivized blah blah blah back when everything was gonna be blockchain in, like, urban slums here in Medellin. 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, didn't know anything about telecom, and just started tinkering. First couple years were me, like, literally living in a slum here in Medellin, 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, and we just sort of assume that it's been solved, and really we haven't done engineering in the last like thirty years.
Speaker 10:It's it's the same underlying architecture that like John Malone was building in Cable Cowboy days.
Speaker 2:Yeah. Wow. Yeah. Every time I go travel to another country, always look up like who the biggest industrialists are and who the richest people in the world. It's always the people that built like the railroads, the mines, the telecom infrastructure, the the WiFi, the Internet, the power lines.
Speaker 2:It's always like the stuff that once you install it, it provides value.
Speaker 1:Yeah. It sounds like it sounds like you're doing a lot. What what is what is in your strike zone of of things that you want Somos to take on versus where do you work with external partners? Like what is what is the kind of core path?
Speaker 10:This is kind of the insanity of Somos. So we literally do everything from like we interface with the submarine cables. Built like a nationwide backbone crisscrossing the country. We like
Speaker 2:That's crazy.
Speaker 10:Make the the Wi routers like the things that go inside of the thing here is all PC
Speaker 1:that was just a pretty lamp.
Speaker 10:That's crazy. So so this is literally the router that goes in customers' homes. So some ugly blinky box, it's like a beautiful lamp.
Speaker 2:That's the lamp.
Speaker 1:You're like, does it have to be an ugly box?
Speaker 2:One thought of this.
Speaker 11:Dude, it's incredible. Like like
Speaker 10:the internet is like literally the most incredible machine humanity's ever built Yeah. And we're just relegated it to being this like ugly piece of infrastructure and kind of our our ideas like what if it was dope?
Speaker 2:That's amazing. So yeah. Like how how do you like how how does the coverage map like spread out? Everyone's familiar with those like AT and T and Verizon coverage charts of like the map of America. Do you have to go city by city, block by block?
Speaker 2:Yeah. There ways that you can like How do you actually scale out to reach an entire coverage area?
Speaker 10:So I literally have like a thousand plus employees cabling the streets. We have like linemen and installers and they're all at work directly for Somos and this is kind of the the insanity of what we're doing. It's been a bit of a like slow flywheel to get ramping but then Yeah. At the end of the day, you're 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.
Speaker 1:Yeah. What in what ways do you think it's easier to do in a place like Colombia than The United States and and and vice versa?
Speaker 10:Yeah. I I think this is one of the interesting things is, like, The US is kinda 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 a 100 gig connections in their home. So the kind of weird thing that has happened in The US is we sort of believe Comcast is sacred, we don't let people go build new infrastructure and we're almost there's a world where it's like ten years from now we're like, shit, The US has like third world internet infrastructure and what we thought of as the third world has infrastructure that lets us do all these crazy things that AI is enabling that you couldn't do before. So I think this was inversion happening kind of the same way as Yeah.
Speaker 10:There were no landlines in Africa. Yeah. We're we're kind of leapfrogging all the crappy old cable and just building internet as it was intended back in their ARPA days.
Speaker 2:That's amazing.
Speaker 1:How how do you get people to move to Colombia to What's work on your pitch? Not not saying anything wrong with Colombia, it's just it's it's a long way away. It's a it's a long it's a long flight. The time zone's not too bad but.
Speaker 10:It's 75 degree rather year round. We have awesome engineering. It's like San Francisco without the fog and we get to just build whatever the hell you want. It's kind of like cowboy western technology, Galt's Galt's in the middle of the the jungle.
Speaker 2:That's amazing. Last question for me. I'm sure you got asked this in all the VC pitches. How is Starlink rolling out? How is satellite Internet fit into this?
Speaker 2:Is that a competitor? Is that a complement? A lot of people in America sort of have both, but how how how does that fit into the picture?
Speaker 10:I think the big takeaway here is that I would sell your Comcast or Telefonica or Telemex 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 cities. 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.
Speaker 2:But the But realistically, like, if I'm on level if I'm on the 3rd Floor of a 15 story building in the heart of the city, like, you're gonna win on reliability, connectivity, speed, cost, all of that. Right?
Speaker 10: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?
Speaker 2:Okay. Yeah. So so, like like, basically unaffected by everything there because of physics. Always good news.
Speaker 1:Mutual friend Zach asked me to told me I should ask about how kind of AI is impacting impacting bandwidth bandwidth needs and how that that factors into the opportunity for you guys.
Speaker 10:Yeah. I think we're gonna look back and say, like, damn, the infrastructure we have currently is far under built 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, 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 in traditional telecoms.
Speaker 10: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.
Speaker 1:What other what other markets are are are on the road map?
Speaker 10:Yeah. We're heading to Mexico in the very near future, and I don't know. There's some interesting neighbors of Colombia that are becoming open again that might be a new place to expand to from from Colombia. So think Somos Caracas might be a thing in the future.
Speaker 1:Before we hit the gong, another mutual friend, Aaron, asked me to ask you about the high frontier. What's up what's up with that?
Speaker 10:Yeah. I mean, I am obsessed with this vision of the future as it used to be, and I I think one of things that's 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 gonna 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. Let's build all these amazing things from scratch.
Speaker 10:So it's like, build infrastructure, rebuild the world, make awesome things happen again.
Speaker 2:It's fantastic. How much did you raise?
Speaker 10:We just raised 40,000,000 in this round.
Speaker 1:There we go. Who who who came in? So
Speaker 10:Ribbit led this. We had bracket capital and then USB, and Y Combinator all kind of doubled down from the past.
Speaker 2:So I love it. What a great YC story too. Yeah. Fascinating company, fascinating industry. Just yeah.
Speaker 2:I love it.
Speaker 1:Did you did you pop up to the West Coast for the race or did you make everybody visit Oh.
Speaker 10:It's a little bit of both. Like, we get people to come down to Medellin and they're definitely not regretting when they come visit. So we have some fun adventures driving to the countryside.
Speaker 2:I love it. Well, thank you so much for taking the time.
Speaker 1:Great to meet you, Forrest. I'm sure you'll be back on soon.
Speaker 2:Have a great day.
Speaker 10:Cheers, guys.
Speaker 2: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 Ceronica. He's in the Rishi waiting room.
Speaker 2:Let's bring him in to the TBPN Ultra. Dino, how are you
Speaker 1:doing? Good,
Speaker 11:guys. How are you doing? Thanks for having me on.
Speaker 2:Thanks so much for joining.
Speaker 1:Great to finally have you on.
Speaker 2:Yeah. Give us the state of the union. What's going on with Ceronica?
Speaker 11:Yeah. Likewise. I mean, you may have seen today, we announced a $1,750,000,000 financing round.
Speaker 1:There we go. Over $9,000,000,000 financing round.
Speaker 12:Thank you.
Speaker 1:So do we need to build some ships? What's going on?
Speaker 11:We we gotta build some ships. We gotta build
Speaker 2:some ships.
Speaker 11:We're super excited for this. I mean, is a true true byproduct of the execution that the team has delivered on over the last, not just twelve months, but the last really thirty six months since we started the company. Mhmm. I mean, team is truly a plus. If you look at where we were just just a year ago, we came off a $600,000,000 financing round.
Speaker 11:What that let us go do is we opened our first shipyard. We launched Marauder, which is a 180 foot autonomous and unmanned ship. Wow. We then announced a multi $100,000,000 project into that shipyard to scale production of Marauder. And then, Coursera, which you see behind me right here, our small USB platforms, we've already taken production of those well into the thousands.
Speaker 11:So now, as we look forward, what we're gonna do over the next twelve, twenty four, thirty six months with this capital raise is we're gonna accelerate that. We're gonna accelerate the production, accelerate the deliveries of our vessels to The US and our allies around the world. We're gonna launch new products. We're gonna build new ships.
Speaker 2:Mhmm.
Speaker 11:And then we're gonna go and build new shipyards.
Speaker 2:Yeah.
Speaker 11:Right? We're gonna invest in the shipbuilding industrial base in this country to the tune of billions of dollars. We're gonna create thousands of jobs. And ultimately, we're gonna we're gonna unlock production rates that we haven't seen in this country since World War two and we're going do it in a very technology first, software first approach.
Speaker 2:You you mentioned USB. Is that unmanned surface vehicle?
Speaker 11:Unmanned surface vessel.
Speaker 2:Yes. Vessel. Got it. And then so walking through the use of boats used to transport people. Now we put equipment on them.
Speaker 2:How versatile are these vehicles? What are the different use cases? Are some weapons platforms or some just ISR capabilities? Like what is the range of of utilities that will that the the armed forces will get out of these USVs?
Speaker 11:Extremely versatile. The whole the whole point of the platforms we're building is actually for them to be modular by nature.
Speaker 2:Okay.
Speaker 11:Right? And actually, we actually try to change the acronym around a little bit. USB is like unmanned surface vessel. Yeah. You know, when you look in the past, it's really like a remote control platform.
Speaker 11:Yeah. Very similar to a Predator drone. Yeah. We use ASV, autonomous surface vessel, because what we're building at Saranac 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 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.
Speaker 2:Yeah.
Speaker 11:Right? How do you operate large numbers of vessels? How do you do 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 harm's way. Keeping people safe is very, very critical and a key point to what we're building here.
Speaker 2:I don't want to diminish the the 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 miss am I missing something there? Like what
Speaker 1:does it take after have people other boats that are trying to kill you.
Speaker 2:Okay. Okay. Maybe that's 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 fully autonomous?
Speaker 11:There's a lot of yeah. So the ocean's just a completely different environment altogether. So we deal with a lot of a lot of different challenges.
Speaker 4:Sure.
Speaker 11:One of the challenges that 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. Mhmm. It doesn't care about how the other 100 cars get to its end destination as well Sure. And how they're all working together collaboratively on a mission.
Speaker 2:Got it.
Speaker 11:Oh, and then you start throwing in six, eight, 10 foot seas Yep. High winds, enemy environments, some of the things that we're seeing now, and like, whether it's the Black Sea, The Middle East, that we're anticipating in the Indo Pacific. Like, those are very, very complex challenges that that we're solving at Ceramic.
Speaker 1:Yeah. What 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, totally independently? How does that does that work?
Speaker 1:Yeah. I mean, when you
Speaker 11:look at shipyards and 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 thirty, forty, fifty 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. But one of our one of our main projects and one of the thing a large part of this capital is gonna go towards is Port Alpha. Right?
Speaker 11:We have a shipyard in Franklin, Louisiana. I 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 to 10x the size of our existing yard, right, to bring on new scale, new capacity, and build rebuild the ship 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.
Speaker 11: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 at a scale that we haven't seen since World War two.
Speaker 2:What's the best way to get a job at Ceronica?
Speaker 11:You can apply on our website. I mean, we are hiring. We are growing. I I mentioned how amazing our team is. What we're doing is absolutely critical for the country.
Speaker 11: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, please please apply. Everything we're doing is absolutely critical. We grew the team from 200 to 1,300 people And over the last 12 that's that's only the beginning guys.
Speaker 2:That's amazing. Well, thank you so much for breaking it down. Have
Speaker 1:a Yeah. Great rest It's incredible of progress. The chat Absolutely. Says just put the s one in the in the SEC mailbox, Phoenix.
Speaker 2:Well, talk to you soon. Good to see you. Thanks, guys. You're so welcome.
Speaker 11:Following up.
Speaker 2:Let me tell you about Okta. Okta 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 Okta. And our next guest is already in the restream waiting room. We got Will Ahmed from WHOOP.
Speaker 2:WHOOP is back. How are doing? Good to see you again. Welcome back.
Speaker 12:Hey, guys. Thanks for having me.
Speaker 2:Give us the update. What happened? How are you doing?
Speaker 12:Things are good. Thank you. We we announced a round of financing today, our series g, $575,000,000 round. So dang. Yes.
Speaker 12:There we go. Thank you.
Speaker 2:Is this is this the capital you finally need to make a bust down whoop? Diamonds from the factory. That's what I'm looking for. Can you do anything
Speaker 6:for me?
Speaker 12:You know, we do we do have some we have some premium offerings in in the mix that are gonna be just right for you, actually. Very
Speaker 4:happy with the product
Speaker 2:development roadmap. He already wants a bus done. No. No. Seriously, give me give me updates.
Speaker 2:What what what's changed? Where do you want the product to go? And, yeah, I am interested to know, are more collaborations in the works? 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?
Speaker 12:Well, look, it's been an extraordinary twelve months for the business. You know, we we ended 2025 with over a 100% year over year growth, you know, 1,100,000,000.0 in bookings run rate to end the year. Our membership is growing around the world. We're operating in 60 markets. We've got WHOOP members in over 200 countries.
Speaker 12:We've launched medical grade technology now. We're coming out with blood tests around the world. And so WHOOP's 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.
Speaker 12:We've added now LeBron James is a new WHOOP investor. We've got Cristiano Ronaldo on the cap table, Virgil van Dijk
Speaker 2:Yeah. Matthew
Speaker 12:Vanderpool. 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, Collaborative Fund, IVP, Foundry Group, and and more. And then we've brought in some sovereign wealth funds from the GCC, proud to have Mubadala and QIA two point zero. So really some of the biggest funds in the world that are I think phenomenal long term partners.
Speaker 12:And then lastly to the point about health, you know, we've added the Mayo Clinic is an investor in WHOOP, one of the premier health institutions. There
Speaker 1:we go. That's a niche. That's a rare Pokemon adventure world. I haven't heard of them on
Speaker 2:a I'm ripping a lot of seed checks at YC Demo Day.
Speaker 12:Yeah, they haven't done a lot of investing, but we see a ton of synergies from a research and medical capability standpoint. And then we also have added Abbott as an investor and, know, really one of the best medical device makers also in the world. So it's 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.
Speaker 2:How do you think your marketing mix will change over the next few years? Because I'm I'm I'm seeing $575,000,000, LeBron James, Cristiano Ronaldo that has like crazy Super Bowl ad written all over it. At the same time, you're tech native. I could imagine going way further into AI generated personalized ads pushing the performance marketing further. Like, what appeals to you?
Speaker 2:How do you think you'll change? What will what will stay the same? What will change over the next few years from a marketing perspective?
Speaker 12:Well, we never wanna 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 WHOOP. But we also now have a product that can detect whether you have AFib and tell you your blood 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.
Speaker 12:You know, one of the areas I would say of, maybe not weakness, but opportunity for WHOOP is brand awareness. You know, we don't have massive brand awareness around the world. And so this capital is gonna give us the gunpowder to really grow broadly internationally. And so you're gonna be seeing a lot of whoop wherever you consume content.
Speaker 1:Super Bowl ad incoming.
Speaker 2:Yeah. If you I mean, if you want to reach me specifically, maybe in a partnership with an athlete like Johnny Knoxville might work. Yeah. Just might make sense.
Speaker 12:We'll do a whoop live heart rate on some of the stunts.
Speaker 2:Stunts. I think that would do the trick.
Speaker 1:I'm curious like how Whoop like how do you guys think about improving accuracy at this point? Like I'm assuming like a lot of like so so much progress has been made over the last however many years, but there's still always incremental progress. Like, you can always be more accurate. How how do you think how do you think about how do you think about that? Is that Is that still like a top priority?
Speaker 1:Or are there other or is it accurate enough at this point that there's better things you can focus the core energy of the team on?
Speaker 12:I mean, 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 data sets grow in nature, more sensing, more capabilities, more medical approvals, the better. And I think that's gonna continue to expand our TAM. I think it's gonna continue to deliver deeper insights for our members.
Speaker 12:So we're gonna be leaning in pretty heavily on research and development. You're gonna see a lot of very powerful sensing coming from WHOOP in the years to come.
Speaker 2:How is the peptide boom affecting WHOOP?
Speaker 12: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 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 ten years ago, I would talk about health monitoring and people would say, well, that sounds like something niche for athletes. And now, 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.
Speaker 12:So there's just clearly been a cultural shift to care a lot about your health. And longevity has become one of the most common reasons that people use the product. Our HealthSpan score, the WHOOP age score has become the most screenshotted page in the WHOOP app. 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.
Speaker 2:Yeah. Yeah. That makes a lot of sense.
Speaker 1:Yeah. There's an interesting dynamic with the various health platforms where there's like kind of an incent there's like a weird incentive to like, you know, measures like say somebody's, you know, their chronological age versus their biological age make it like lower people are more likely to share. It's like I've seen I've seen some people have, you know, come in and say like, my biological age is 19.
Speaker 2:I I I did one test that said I had I had the mind of a five year old. It said it was tested testing my brain health and it said that I had the
Speaker 12:Is that good or bad?
Speaker 2:It's not. He's extremely young. I'm way over five. I assume it's good.
Speaker 12:I think we've built the most credible Yeah. 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. Mhmm.
Speaker 12:So here's a trivia question for you. What percentage of people on WHOOP do you think have a younger WHOOP age?
Speaker 2:Oh, interesting. I mean if it was perfect it would be fifty fifty I would think.
Speaker 1:70% because people that use whoop are much more likely to be
Speaker 2:Oh, true. Okay. Let's go with 70. What is it?
Speaker 12:It's 55%.
Speaker 2:55%. But what
Speaker 12:that means is 45% are older on whoosts. You know? Was that
Speaker 2:was They're early
Speaker 12:in the loop journey. Have done a lot, but this whole show is really dialed in. No. So so 45% are
Speaker 2:You feel
Speaker 9:like sorry to
Speaker 2:continue. Yes.
Speaker 12:So, you know, but that shows that like it's not just telling you what
Speaker 2:you want to hear. Yeah.
Speaker 12:It's, you know, it's going to push you.
Speaker 1:Yeah. Yeah. Yeah. And I and I only I only brought that up originally because I've I've seen some of these come out and I'm like, okay, there's zero shot. This person's biological age is lower than their chronological age.
Speaker 2:Based on the life
Speaker 1:of every platform, you know, platforms are just kind of every platform is gonna run their own kind of algorithm to determine that and not necessarily working with the Buck Institute.
Speaker 2:Yeah. Exactly.
Speaker 1:Yeah. Well, very cool. Fantastic. Congrats to the whole team. I feel like just in the last year Yeah.
Speaker 1:Just like the world has woken up to this kind of category
Speaker 2:and Yeah.
Speaker 1: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, some place like LA and you know, I'm sure it's like every tenth person has a Whoop band on but that means there's nine nine or so.
Speaker 12: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 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 that's a very gratifying thing. But you guys you guys owe me a question here.
Speaker 12:You haven't asked me.
Speaker 2:What is it? What's the question?
Speaker 12:Aren't you gonna ask me if the job's done?
Speaker 2:Oh, yeah. Is the job finished?
Speaker 12:Job's not done, guys. We gotta keep going. Thank you. Thank you for that.
Speaker 1:Great stuff. Congrats. Thanks.
Speaker 12:Well, I appreciate you guys. Keep it up. Thank you.
Speaker 2:We'll see
Speaker 1:you soon. I'm sure.
Speaker 2:Yeah. Get 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 soon, Will.
Speaker 2:Have a great one. Goodbye. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB.
Speaker 2:Don't just build AI. Own the data platform that powers it. Continuing our lightning round. You know who we got? The CEO of public.com.
Speaker 2:Jannick, how are doing?
Speaker 9:Hey guys, I'm doing well. How are
Speaker 1:you? We're doing fantastic. Look at
Speaker 2:that stuff in the background there. Well, I know.
Speaker 9:Do you recognize any of this stuff?
Speaker 2:Oh, yeah. Yeah. You got the whole head to toe. Head to toe.
Speaker 1:Head to toe.
Speaker 9:I don't recognize what Jordy is wearing. Don't think
Speaker 2:this is the new polo. New.
Speaker 6:Right there. Top on it.
Speaker 2:You got leave left. There's plenty of
Speaker 9:room on the walls. There's plenty of room on the walls.
Speaker 2:Anyway, enough about our merch. Let's talk about your business. Yes. Walk us through the launch today.
Speaker 9:Yeah. So today we launched AI agents for investing.
Speaker 2:Yes.
Speaker 9:The easiest, safest way to put AI agents to work directly inside your portfolio.
Speaker 2:Yeah.
Speaker 9: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? Yeah.
Speaker 9:So there's nothing to install from a security standpoint. Obviously, everything stays in a safe controlled environment because it's within the bridge.
Speaker 1:Can I install Axios?
Speaker 2:No, do not do that. That is such a niche joke. Everyone's going to think you're talking about the publication. Yeah.
Speaker 9:But I mean it's it's been really fun. 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?
Speaker 1:So John, relax. Yeah. I
Speaker 2:like the sound of
Speaker 1:that. Knew you were gonna do that.
Speaker 2:We got a little John in this studio.
Speaker 1:No. So so so make makes total sense. What like if people are like already signed up which they should be, how what what should they what what what's the first thing that that they should try to like set up or experiment with? Mhmm. Like what what what was your first few agents set up and and like continue to keep running?
Speaker 1:Because I'm assuming you can effectively like run them Yeah. You can retire them at different points.
Speaker 9:Exactly. Exactly. The first one I set up was 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.
Speaker 9:And so, today that didn't fire. Thank God. Yeah. You know, I have another one that just looks at my bank accounts and automatically sweeps any cash in excess of a certain amount
Speaker 2:I was
Speaker 9:just into my bond portfolio, so I'm always yield maxing. You wanna be yield maxing always, especially Yes. While rates are still high.
Speaker 2:Yeah. That makes sense.
Speaker 9:And and then I got some more advanced stuff. Like, I got one that scans the market for opportunities to write covered calls.
Speaker 2:Okay.
Speaker 9:Across my top positions. So if there's a low risk opportunity to make like $20 a month
Speaker 2:Yeah.
Speaker 9:Selling options premiums, I instructed it to just go ahead and place those orders. And so that just rolls every time all the time and I don't know
Speaker 2:that exact strategy was the first thing a private wealth manager ever pitched me in my career, like a decade ago. They were like, I 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
Speaker 1:on that guy
Speaker 2:after this launch. No, no, no. But so I I there are obviously like incredibly advanced things that you can do with these agents in in the market. I'm also interested in 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.
Speaker 2: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 money's flowing into the market. How easy is that these days?
Speaker 9: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?
Speaker 5:Like, you do all
Speaker 9: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, increase my position if valuations compress 15% from here. Yeah. You know?
Speaker 9:And it stays within my defined risk tolerances Yeah. And so forth. And so I think it changes how people think about and manage their portfolios in a pretty profound way. And and we do see it as user interface shifts like, you know, the the the interesting thing about this industry is every technology kind of had their model of brokerage. Right?
Speaker 9:Like, we started on the horn and then the dawn of the internet gave us the discount broker. With mobile came the neo broker. Yeah. And I think now with AI, it's the era of the AgenSci brokerage, but what's uniquely interesting about this shift is every previous shift was about streamlining the process and reducing the responsibility set of the broker, you know, to basically just trade execution, ultimately. Yeah.
Speaker 9:But it actually used to be much more full service to Jordi's point. There used to be a guy who used to call you, used to pitch all these kind of ideas, risk, you know, trade ideas, etcetera. I think with the agentic brokerage model, you're reversing back to that. Mhmm. 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 ten seconds.
Speaker 9:They can do tax loss harvest. They can can instantly analyze risk. Sure. And so it's it's a shift back to a world where the brokerage plays a luch, 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 a much bigger role through essentially AgenTic
Speaker 1:Jordy? Can it can can it pull in external data sources yet? I'm thinking like fear and greed index, like Yeah. Should I could I set something Even
Speaker 2:like unemployment
Speaker 1:rate If you have like max fear that you you want to buy days when Sure. When the Yeah.
Speaker 2:Yeah. Yeah. Fear index is high, but that might not be an an actual, like instrument in Yeah. That you can buy and sell directly.
Speaker 9:Yep. A 100%. Unemployment data, CPI, Fed cards, like one that people will be 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, it's a high growth tech.
Speaker 1:Yep. We like
Speaker 9:the sound
Speaker 12:of that.
Speaker 2:Alright. That makes sense.
Speaker 9:There we go. And And and so there's a lot of those. Yeah. CPI, like like the fear and greed one was requested today. Think that's coming in in the next couple of days.
Speaker 9:And so really, it's about getting all that into this natural language interface and just letting people kind of instruct AI to to do this on their behalf.
Speaker 2: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 to earnings ratio, market cap, the usual stuff.
Speaker 2:Yeah. But there's so much more that you can ask an 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?
Speaker 2:These things are perfect for LLMs and you can vend those in, but what are users actually using? What's adoption been like? What have the learnings been?
Speaker 9:Yeah. I mean, I I think one of the core tasks in application layer AI is to sort of figure out, obviously, what do users want to achieve Yeah. And then which model and kind of harness is best suited to achieve that purpose.
Speaker 2:Sure.
Speaker 9:But then also focus on, what are we uniquely able to deliver. Right? Yeah. So we know what you own. We know what you used to own.
Speaker 9:Yeah. We know what your risk tolerance is. Yeah. By the way, we also know the difference between what that actually is and what you said it was when it signed when you signed up.
Speaker 2:Yeah.
Speaker 9:And and and we have real time data feeds of everything. Right? Sure. And so I think as a product builder, those are like some of the situations where you can really create a magic moment that general purpose LLMs can't. Yeah.
Speaker 9:And I think a lot of that comes because we
Speaker 6:just have a lot of
Speaker 9: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, etcetera. Because we've been basically running a research assistant since 2023. Yeah. 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 into this.
Speaker 1:What's your theory right now? It's obviously day day one, but do you think in the future we'll 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 have even even you know, additional trading activity off of these single events. Like do you think this is something in the future 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 fashioned to be just like, you know, buying a stock yourself even with a button?
Speaker 9:Todd, I I actually think we will look back at like, Tables and Buy Buttons and feel that's a little antique, maybe already, twelve months from now. But I think the effect is things will get priced in faster for sure. On the institutional side, they've, you know, they've used some version of AI for the longest time. Right? But then at the same time, retail has gone from being like five to 25% of the market.
Speaker 9:And on the retail side, folks haven't been as fast to react always. Right? They haven't been that disciplined. They're not necessarily glued to the screen twenty four seven, and so, you know, they can't always react as quickly as they want to, and agents obviously change that. Right?
Speaker 9: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 a of sort of an alpha opportunity or an arb opportunity in the early early days. Mhmm. And then over time, it becomes more mainstream and that kind of fades away, and I would suspect that this follows something
Speaker 1:Yeah.
Speaker 9:Like a similar pattern
Speaker 4:at least.
Speaker 1:Yeah. I've just been thinking about it because 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
Speaker 6:Yeah.
Speaker 1:You see news and then you go to your broker and the right trade has already been made on your behalf. Mhmm. Exactly. And anybody that's not adopting this will just be like, well, missed kind of I missed opportunity unless you want to get out entirely.
Speaker 9:Totally. Speaking of ex, a fun one is that was from The US. If DJT says bye, just five.
Speaker 1:That's actually really smart. Very well. It
Speaker 9:backtests extremely well.
Speaker 2:What a crazy timeline we are in. Well, thank you so much for coming on and breaking it down for us.
Speaker 1:Great to see you. Miss
Speaker 3:you guys.
Speaker 2:Let's let's Miss you too.
Speaker 1:Sure to hang out. Let's hang soon.
Speaker 6:It's you too. Yeah.
Speaker 2:Alright. Bye.
Speaker 1:See you guys.
Speaker 2:Cheers. Cheers.
Speaker 4:Ciao.
Speaker 2:Let me tell you about Sentry. Sentry shows developers what's broken and helps them fix it fast. That's why a 150,000 organizations use it to keep their apps working. And without further ado, we have Ryan from Crosby. How you doing, Ryan?
Speaker 4:Welcome back. Hey, guys. Good to see you again.
Speaker 1:Dude, you're on you're on here like every week.
Speaker 2:It's getting Yeah.
Speaker 1:It's getting a bit much. Let me guess. One.
Speaker 2:You should just bundle fundraisers together into like series alphabet. Then we just do it I never
Speaker 4:get to see you guys in a I
Speaker 2:it is it is more strategic to break them up. But tell us what happened. How much did you raise? What's going on?
Speaker 4:We have two announcements. The first announcement is you've raised $60,000,000 led by Lux. Series b. And the second announcement thank you. The second announcement is we did some math last month and we have now closed contract worth over $1,000,000,000 for our clients.
Speaker 4:Woah. It's a big milestone
Speaker 5:for us. Okay.
Speaker 1:Okay. Billion dollars for the client. Was there like one sneaky $950,000,000?
Speaker 2:Did you get 1% of this new OpenAI round in there? Somebody was like, I'll get a review one clause and you're like, I'm getting no. It sounds like it sounds like there's a lot of lawyers using it.
Speaker 4:That's right. I mean, are small deals so it's a lot of velocity. Sure. I think definitely my corporate law friends are like, that's like one deal for me so that's not interesting. But for us that's a big number.
Speaker 2:That makes sense.
Speaker 6:So it's a
Speaker 4:really good milestone.
Speaker 2:Yeah. So yeah yeah. Take take us through, I mean, it sounds like like the the shape of the work that is being augmented by Crosby these days.
Speaker 4:Yeah. So, you know, we're about a year and a half into it. We announced our seed around two hundred and thirty days ago. We do commercial agreements. These are the sales agreements, MSAs, NDAs, VPAs for, like, fast growing AI companies.
Speaker 4: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 day of 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 and now even bigger clients who just wanna close faster.
Speaker 1:How 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 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 Yeah. For your own internal tools.
Speaker 1:But like, how how are you processing kind of what feels like will ultimate in the same way we saw with CodeGen where you have Yeah. 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, but how have you been kind of processing it?
Speaker 4:So, I mean, that's that is the question we have to ask ourselves every day. We think that cogeneration, 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, you know, not think about these sort of, like, AI copilots that are kind of like, you know, the equivalent of what Cursor was a year and a half ago when you kinda 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.
Speaker 4: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. We have more and more lawyers that were able to help us, you know, tune judges and 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, copilot, I think you're gonna face a lot of competition just from the models with no customization.
Speaker 1:Yep. Sorry. Wild. John's back. Yeah.
Speaker 1:Wild wild moment. What I'm assuming you'll also face competition from clients that are just like, hey, we can should should we should we have an in like, should we have an in house lawyer that we can, you know, speed up? Yeah. But but everybody's competing with everyone. But yeah.
Speaker 2:How are you how are you tracking the legal education market? I've seen it I it seems very hard to predict for me. Like, there was this weird spike. I wanna say, like, it was maybe post ChatGPT where there were, like, more people signing up for a law school. Yeah.
Speaker 2:And that was, like, sort of contrarian based on the model capabilities like the AI SF 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 middle school for a lot of people, high school, definitely college, definitely law school. How will that how will that all trace through and how closely are you following it?
Speaker 4:I mean, think every industry is asking themselves, like, how do people get the entry level jobs to learn those skills and then become really good in senior and get leveraged by agents? I I went to law school at Stanford. I'm talking to a lot of professors there who are struggling with this question. 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 $70,000,000,000 in just profit just in 2025. That's just paid out to their partners.
Speaker 4:That's just salary. Paid out for lawyers. Then Good
Speaker 2:year. It's so good to hear.
Speaker 4:That was that was more money than Google spent on all their r and d. And so, like, our insight was
Speaker 2:Mogged.
Speaker 4: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 Sure. And for their clients, I actually think the legal industry gets a lot bigger. And so it's, like for a a person in law school today Yeah. It's a good time to be thinking like how can I just build better stuff?
Speaker 4:And that's just a new way of lawyers thinking.
Speaker 2:Okay. That's one way to put the profits to work. Let me put 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. Yeah.
Speaker 2:Maybe I, you know, contrarian in me wants to still hire associates just for the mentorship and building like a 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 Yeah. It's work that an AI agent like sort of could do and maybe they're a little bit more free, I I I'm actually incentivized to figure out how to accelerate them faster in their career, have them start working on larger, stickier deals that AI can't necessarily navigate just yet.
Speaker 4:Yeah. I mean, I buy the argument. Like, I think that there's two jobs for lawyers really to focus on right now.
Speaker 2:Yeah.
Speaker 4:One is just doing client facing work and being really good at being like, you know, talking to people Yeah. And understanding what their points of view are, and not being buried in the sort of paperwork like a 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.
Speaker 2:Yeah.
Speaker 4: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 of those jobs.
Speaker 1:Yeah. Yeah. Are you guys fine tuning any models, you know, based on fine tuning, like, source models, or is that not even you know, I've seen, like, Finn and and Notion have had some success with this. Is that even a good use of time right now? Because I'm assuming your guys', like, actual, like, inference costs are not that high relative to what you can charge clients even if you're using the frontier models.
Speaker 1:But how are you thinking about that?
Speaker 4:I think, again, if we just look at cogeneration as, like, the blueprint for the future, you see, like, a lot of the cogen companies got a lot of lift from just, like, you know, the main, you know, three big models.
Speaker 2:Yeah.
Speaker 4:And over time, you have to start fine tuning your models as you get scale, as you get data, 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 to models, building the right agent flows, like, just doing some reinforcement learning on, like, basically, you know, we work with really, you know, OpenAI and Thropic and Google's models. But, yeah, in a year and a half, as you get really specialized in use cases of Wah, I I I'm sure, like, we're going that direction. And part of the reason for this funding and doing it so quickly is to start investing in a research team that can can kinda push the boundaries there.
Speaker 2:That's very exciting. Well, congratulations on the funding round. I'm sure we'll see you. Let's just book it now. You just tell us and and
Speaker 4:Same time next month. Huge.
Speaker 1:Thanks, We'll
Speaker 2:talk to you soon. Have a
Speaker 1:great day. See you, dude.
Speaker 6:Thanks, guys.
Speaker 2: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. And without further ado, we have Chris And, also, how are you doing, Chris? I'm doing great. Taking the time.
Speaker 7:Yeah. Thanks for having me.
Speaker 2:Welcome to the show. Since this is your first time, please introduce yourself.
Speaker 7:Yeah. My name is Chris Yuen. I'm the cofounder and president of ALSO.
Speaker 2:Okay. Break it down for us. What is ALSO? Give us some of the corporate lineage, the strategy Yeah. The product.
Speaker 2:It's just sort of everything.
Speaker 7:Yeah. So, actually, before 2022, RJ and I bet, and we immediately hit it off on this one topic. And so that turned into me joining Ribian at the time Cool. With the, explicit mission to create a startup within a startup. And the entire thesis that we had, and that's this has turned into also with the 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.
Speaker 2:Yeah.
Speaker 7:But nearly none of them have been electrified yet. And so it's really taken the Rivian or Tesla playbook and applying it to these smaller form factors.
Speaker 2:Okay. Smaller form factors, that means everything from, hoverboard to a horse and carriage. What are you thinking?
Speaker 7:We're focusing on wheels first,
Speaker 8:but yeah.
Speaker 2:Okay. But yeah, yeah. Narrow down the product for me, the go to market, the quad and the pedal assisted electric bike, other timelines, shapes, sizes, ranges. Like, how do you think about narrowing down the product set? Because it is a really wide and diverse category.
Speaker 7:Totally. Yeah. So we think of it as, in a way, two phases of the business. Mhmm. Phase one of the business is how do we create a vertically integrated software defined EV platform Mhmm.
Speaker 7:But optimized for small form factors, and we've applied that to our first products. We call them EVs that you can pedal. K. And we announced those back in October. So one is a consumer ebike, and the other is a pedal quad, which we partnered with Amazon, to deploy soon.
Speaker 7:That's really exciting.
Speaker 5:Cool.
Speaker 7:But if you look globally, again, today, things move around in things like, two wheelers, like scooters, Bota Bota's, Tuk Tuk's, microcars, K trucks. 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 a tech forward 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
Speaker 2:Very cool.
Speaker 9:Thank you.
Speaker 7:We love that. Yeah. 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 gonna be an issue. Cost per mile is always going to be a factor.
Speaker 2:Yeah.
Speaker 7: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.
Speaker 2:Talk to me about I mean, I I love RJ. Rivian'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?
Speaker 7:It's all of the above. RJ and I talk about us as kind of like sibling companies, if if you will. 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, similar, terms of how a Rivian is built.
Speaker 7:Yeah. There are some commodities that are shared, so battery cells. Our first products actually use the same cell that are in Rivian r one, so that helps a lot from
Speaker 2:a scale I'm sure.
Speaker 7: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. 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 that's right for smaller scale products.
Speaker 2:Yeah. And with cars, you almost always wanna manufacture them where they're going. Like, that's why Yeah. Even even, like, the Japanese carmakers have facilities in America or Mexico because you just would drive the car as opposed to putting
Speaker 7:That's exactly right. I mean, if you look at a car, I mean, the size of tools necessarily Everything. Custom they are, tariffs, like, they all add to, like, you have to have your own factory in region.
Speaker 2:Yep.
Speaker 7:But if you look at any product south of a car, almost all of them are built with this contract manufacturing model.
Speaker 2:Okay. Talk about the name and the brand. Rivian has those delightful headlights. Yeah. Lot of different interesting brand decisions around Rivian.
Speaker 2:What are you taking? What are you thinking? And where does the name come from?
Speaker 7:That's so great. I I love it. We naming something is so hard. Yeah. 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.
Speaker 7:It's like, it's just cars or it's just not cars. Yeah. And for us, the approach is like whether it's a commercial enterprise or a consumer, it's all of the above Yeah. Most likely, meaning that I wanna use my r one 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. And so the transformation and electrification of transportation is also it requires all of the above in a way.
Speaker 7:And on kind of like how we present ourselves from a brand, you know, one 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. Yeah. So it's like we 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 may need to be. K.
Speaker 1:How do you think about competition with Chinese manufacturers? You know, Rivian Rivian's had the benefit of of not having to compete with all the Chinese manufacturers Yeah. In the I imagine micro mobility, you know, is not gonna be having the same kind of export restrictions. Know, how do you 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 at a loss for some amount of time.
Speaker 2:Yeah. The DJI story, basically.
Speaker 7:Yep. 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 and 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
Speaker 2:Yeah.
Speaker 7:Will exist in our space Sure. To some extent as well. But just to back up, I think one of the things that gets lost is there are tremendous number of products in this kind of, like, small, mobility or micro mobility space that are coming out of China for sure. But I think it's without debate that the vast majority of these products are commodity, like, relatively low quality white label type products. Yeah.
Speaker 7:That being said, there are a small handful that are really, really great products and using the latest and greatest tech. 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 would say, also, it's probably one of the only brands outside of China that you could say that
Speaker 2:Yeah.
Speaker 7:Of within this space. And so just purely from a product, feature quality and technical capability standpoint, we feel like we're very, very competitive.
Speaker 2:Okay. Product pitch. The Rivian r one t has a gear tunnel. It fits a snowboard. Electric longboard with a handle that flips up like a giant razor scooter that fits perfectly in the gear tunnel.
Speaker 2:Am I onto something?
Speaker 7:I love it. That that's not the first time we've heard that one.
Speaker 2:Oh, really? Okay. Yeah. The gear tunnel, it just 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 or like barbecue or something.
Speaker 2:Just I want an ecosystem around the gear tunnel. If it's 100%. Who knows how viable that is? Anyway, very fun. Jordy, anything else?
Speaker 1:Very cool.
Speaker 2:Thank you so much.
Speaker 1:I'm on the website right now. I'm interested. You're shopping. I'm shopping.
Speaker 7:I'm shopping. We'll hook you up. Just let us know.
Speaker 2:We will be very excited to ride these around. We've been doing we've been doing some office chair racing in the studio. This
Speaker 1:is apparently a whole That's what I want. I want an electric office chair.
Speaker 7:Oh, there you go. We have well, we have in house vertically integrated motors and mirrors. Can power we can soup those up.
Speaker 2:There you go. So just dumped up office chair. Adjust me to the left one inch.
Speaker 1:Yeah. Just a little joystick. Thanks for pilot
Speaker 2:me. You know, if if if you're not in the right shot, you're a little bit to like move you.
Speaker 1:That's actually you
Speaker 2:will have one or two customers for this if you
Speaker 7:Autonomous chair. I love it.
Speaker 2:Autonomous office chair? Hey, You're you have to leave the meeting. Go back to your desk. Drive you around. I think we're onto something.
Speaker 2:Cool. Thank you so much for taking the time
Speaker 1:to Great to meet Chris.
Speaker 3:Yeah. Thanks for having us on on our on
Speaker 6:the show. Thank you.
Speaker 2:You. We'll talk to soon. Goodbye. Let me tell you about app loving. Profitable advertising made easy with axon.ai.
Speaker 2:Get access to over 1,000,000,000 daily active users and grow your business today. What's up?
Speaker 1:Brad Yes. Adcock was on the show yesterday.
Speaker 2:Yes.
Speaker 1:He had some interesting comments about the state of AI.
Speaker 2:Okay.
Speaker 1:I disagreed strongly with many of them.
Speaker 2:Okay.
Speaker 1:But we have to cover this video Yes. From the Sean Ryan podcast. Yes. It's a new gate. Okay.
Speaker 1:It's calling it a telegate.
Speaker 2:Ad gate.
Speaker 1:Ad. Well, maybe that too.
Speaker 5:Who
Speaker 1:knows? So so he is hanging out with a figure robot
Speaker 2:Okay.
Speaker 1:On the Sean Ryan podcast.
Speaker 2:Oh, okay. And he went outside for it. Yeah. I was wondering because like Sean Ryan normally shoots not like very cinematic
Speaker 1:Yep.
Speaker 2:Whiskey bar. But he's outside and
Speaker 1:There's like a two minute video where they're hanging out with the robot.
Speaker 2:Yes.
Speaker 6:And then
Speaker 1:let's pull this up and I wanna get your Alright.
Speaker 2:Turn around.
Speaker 1:So this is the first time he tells it to turn
Speaker 2:is like we we basically the
Speaker 1:robot end of the video, it starts turning around, and then he says, turn around.
Speaker 2:And Nemo here says the video is the smoking gun that figures robots are teleoped. Again, I love teleop. Not a problem.
Speaker 1:But Brett has he always says he's
Speaker 2:not doing teleop.
Speaker 1:He'd never do teleop.
Speaker 2:I don't know. He says not autonomous. Notice how the robot starts turning around before Brett says, alright, turn around.
Speaker 1:Yeah. You can skip forward a little bit. And there's pull up pull up this other video that I'm actually on.
Speaker 2:There's another yeah. There's another video quoting this that shows it on repeat. Let's see.
Speaker 1:Now The other thing too is
Speaker 2:like we we basically the robot's almost all fully soft. It's by Vic. Vic. Quotria and said, yeah. Okay.
Speaker 2:Yeah. It's definitely not waiting for for the Okay.
Speaker 1:So it's very this one. Alright. It's very subtle, but you can see it's turning around, and then he says, alright.
Speaker 2:Turn Yes. But the steel man here Turn around. Premonition. Alright. Turn around.
Speaker 2:The robot knew what was gonna 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?
Speaker 2:The Also
Speaker 1:moment from yesterday that stands out to me is Yeah. 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 His personal focus. Focus.
Speaker 2:Yeah. It's like focus within an organization, like a specific like, the leaders that join that company can focus just on that problem. It was it was an odd an odd comment to sort of process. Yes. The I mean, I don't know.
Speaker 2:I I haven't watched the full the full interview with Sean Ryan. I wonder if if if he talks about whether or not this particular robot is teleop because it's totally reasonable that the company would have some teleopter 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, would say, hey. You know, this this one's Teleopt.
Speaker 2:Here here's a demo of what we're capable of when we're using Teleopt. 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.
Speaker 2:I mean, all of this, you know, the rubber meets the road when the 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 teleoped. That would be wild. You're like, wow. This is remarkable.
Speaker 2:I can give it the most complex I can give it the most complex vague instructions.
Speaker 7:It just does
Speaker 2:exactly what I got.
Speaker 1:If the figure robot can simply open a Diet Coke for John, we're a buyer. That's That is
Speaker 2:the that's the goalpost.
Speaker 1:I don't we don't need it to do everything.
Speaker 2:That's the goalpost.
Speaker 1:Just need it
Speaker 2:to Got a crack open a six pack of Diet Coke. Tyler, what do you think about the figure figure gate?
Speaker 3:I mean, it's hard to say just from that video, but I think broadly, like, people are probably, like, too against teleoperation generally.
Speaker 2:I agree.
Speaker 3:Because, like, you know, the lesson from Waymo is that, like, actually
Speaker 2:It's goaded.
Speaker 3:You know, part maybe if it's totally, like, 100% tele op, like, okay, that's not great. But if it's, like, partly, like, there's someone overseeing it Yeah. And maybe they're, like, pretty involved sometimes, it can be, like, extremely valuable. Like, Waymo's a great product, whatever.
Speaker 2:Yeah.
Speaker 3:Like, even just, like, deploying robots in dangerous locations, if it's fully teleoped, that's still, like, a great
Speaker 2:thing. Hugely valuable.
Speaker 3:And, like, clearly, the way we get fully autonomous robots is by starting out with with partially teleoped ones so you get the data. There's, like, a very clear loop there. So I think broadly people are too against.
Speaker 2:I completely agree. Yeah. Anyway, anything else we need to talk about? We've just learned a bunch of No. We talked about all
Speaker 1:We'll be back.
Speaker 2:We we we do have 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 LA court last week. And we posted the clip. 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.
Speaker 2:We we love the way he's living his life. We're huge fans of Mark Lanier, although do have some disagreement around the the legal findings. But a lot of people chimed in. Excel rotate Excel Raider said, by the way, this is the Lanier Theological Library in Houston, which is open to the public for touring. Incredible guy.
Speaker 2:Shares two amazing images of, what an amazing contribution to the community. And Eric Soufford 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.
Speaker 2:I mean just seems like seems like a fantastic lifestyle.
Speaker 1:We got him on the show.
Speaker 2: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 different tier, different ladder. That's where you want to go in life if you're successful.
Speaker 2:And he's done it. So congrats to him. Anyway, thank you so much for tuning in to TBPN today. Leave us five stars on Apple Podcast and Spotify. Sign up for newsletters at tbpn.com.
Speaker 1:A wonderful last few hours of your quarter.
Speaker 2:Yes.
Speaker 1:It's been an honor.
Speaker 2:See you tomorrow. Goodbye.
Speaker 8:Boeing Flashbang.
Speaker 2:Bye.