TBPN - Weekly Recap | Elon's Starship Explodes, OpenAI's Defense Contract, Nvidia's Robots, We Test Cluely

Episode Date: June 21, 2025

(00:00) - Intro (00:03) - Elon Musk's Starship Explodes (02:37) - Meta x Oakley (03:56) - OpenAI Wins Defense Contract (04:44) - Meta Puts Ads on WhatsApp (05:33) - Intern Tests Cluely ...(18:44) - Roy Lee (Cluely) (33:54) - Lakers Sold for $10 Billion (39:40) - Surge AI Beats Scale AI (51:24) - Spotify CEO Invests in Drones (55:41) - Katie Haun (Haun Ventures) (01:14:47) - Justine Moore (a16z) (01:39:44) - Nvidia Drops Humanoid Robots (01:45:09) - George Hotz (comma.ai) TBPN.com is made possible by: Ramp - https://ramp.comFigma - https://figma.comVanta - https://vanta.comLinear - https://linear.appEight Sleep - https://eightsleep.com/tbpnWander - https://wander.com/tbpnPublic - https://public.comAdQuick - https://adquick.comBezel - https://getbezel.com Numeral - https://www.numeralhq.comPolymarket - https://polymarket.comAttio - https://attio.comFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://youtube.com/@technologybrotherspod?si=lpk53xTE9WBEcIjV

Transcript
Discussion (0)
Starting point is 00:00:00 You're watching TVPN. The Starship exploded during a test in Texas, a setback for Mars's Mars, for Musk's Mars ambitions. Now, the Mars transfer window is very, very tight. Like, you can only get from the Earth to Mars, like once every 18 months or something, or maybe even more. It's really hard because, like,
Starting point is 00:00:21 if the planets are on the opposite side of the solar system, like, you just can't, like, even though you have a rocket, you just can't get over there. So you have to wait until they're lined up, and then you can do it. But realistically, skill issue? Realistically, true. Skill issue.
Starting point is 00:00:35 If you build an even faster rocket, you could get there no matter what. You just pilot, steer it around like it's a DGIRRS around the Nürberg ring. No problem. So the explosion occurred during static fire tests. No injuries were reported. Thank goodness. We love autonomy. Very, very happy to hear that no one was injured during this because it looked horrific.
Starting point is 00:00:54 And it looked like in any other scenario, there would be a bunch of technicians there. But fortunately, they were able to do everything remotely, which is great. And then Starship features pressure to meet deadlines for NASA's moon mission and Mars exploration. So there's a big NASA moon contract that's very important, very material to the business. Obviously, SpaceX has a lot of other business lines, but this one's very, very important too. And we hope that they can get back on track. SpaceX is making an enormous bet on Starship, which stands roughly 400 feet tall at liftoff as it tries to break ground with new reusable rockets. And the paradigm of Starship, it's not just a bigger rocket.
Starting point is 00:01:33 It is way more reusable. Like you look at the thing, it comes down, gets caught by those arms, can instantly be refueled and sent back up. You're talking about potentially like multiple flights per day. And so the problem here is not, can you build a big rocket? Humanity has done that before. Humanity's built a rocket that's roughly on par.
Starting point is 00:01:53 We've gotten to the moon before. The challenge now is not, can we get to the moon? It's the same thing with like, the challenge is not, Can we build a flying car or can we build we have helicopters? Can we build one humanoid robot or one self-driving car in San Francisco? It's like, can we actually scale these systems to the point that it is safe to go to the moon and back on the drop of the hat for 200 bucks? Like that's the challenge.
Starting point is 00:02:15 It's more of an economic and industrial might challenge. And that's a completely different challenge from just can we get one rocket to the moon? An exquisite system. We're looking for reusable, scalable, you know, frequency. engineering system. So good luck to Elon rebuilding in the entire SpaceX team. I'm sure it's a huge challenge right now. Meta Oakley's are coming. Sheel says this makes sense. Luxottica owns both Oakley and Rayban and Meta is reportedly investing $5 billion for a 4% stake. Luxottica is a fascinating business story. The founder Leo Delveccio's family still owns one third. The guy was an orphan
Starting point is 00:02:55 who became a metal worker making parts for glasses, ultimately becoming the largest listed company in Italy. It is really interesting to think about how if meta can basically corner all of the most iconic, all of the most iconic frames, which they can do through Luxottica, if they do figure out some type of exclusive over time through that investment. Does Luxottica just own all the major brands? They basically own everything.
Starting point is 00:03:24 people's and everything. Every time you buy sunglasses, you think you're buying some unique brand heritage, Luxottica. It's interesting. We should dig more
Starting point is 00:03:33 into that company because they don't own all the retail. Well, yeah, that basically Sunglass Hut retail stuff going on. I mean, they are big glasses
Starting point is 00:03:42 and that created the opportunity for Warby Parker because they're the ones that manufacture everything. Basically this entire, you know, Luxada who could verticalize
Starting point is 00:03:50 from brand to production to the actual medical side as well. Interesting. Also some good news in opening I world, even though they're going through the some battles with Microsoft, they scored a $200 million U.S. defense contract. So they're working with the DOD. The most unhinged picture.
Starting point is 00:04:08 I know. How did this photo shoot happen? Like this does it? This looks like he's about to go on stage and he has a lab mic and it's from a low angle. But like what lighting scenario created this photo? It's amazing. but it's very aggressive. Anyway, great selection by Nick.
Starting point is 00:04:25 Not beating the, you know, arms dealer. Evil tech arms dealer. Yep, yep. Dealer allegations with this picture. Yeah. If you're, if you're founder,
Starting point is 00:04:33 you've got to be careful of how the angles people photograph you like. But at a certain point, if you're on stage, they're going to take photos in any direction. But, yeah. And if they take enough photos,
Starting point is 00:04:41 they'll get every single expression. So get ready. Other news, meta finally put ads into WhatsApp. In January, 2012, they said, we don't sell apps. ads, which is still live.
Starting point is 00:04:55 But this is why we love them, and this is why Zuck is undefeated. WhatsApp should have ads. The backbone of the internet. It's the backbone of the internet. And Signal says that's why he's an Apple fan boy because they don't have do ads. Well, Apple does have a huge ads business. I bet you this is just them listening to their users. I bet, you know, the users, you know, all over the globe said, you know, the only thing
Starting point is 00:05:17 that could make WhatsApp better is just putting some ads in this bad boy. It's the one place I go. that I don't get like this was already happening. I felt like this leaked like five years ago. How much it was a $20 billion acquisition? Of course they were going to put some ads in at course. Of course. Senator, we sell ads. Uh, any, take it over to Tyler. How are you doing over there? What's up guys? In the back of the Mayback. It's pretty chill back here. You got a little desk set up. Yeah. Got Wi-Fi. And so today the the big news that we're having him dig into is clearly. Yep. Uh, they are okay. Something happened.
Starting point is 00:05:52 happening there potentially. But we got some flack for talking to Roy and not actually using the app. We're still above using the app, but we will let our intern use the app. It's more that we don't have time. We're too busy podcasting. But Tyler has time. Many people are starting to call after his WinSurf review. People are starting to call him the MKBHD of Enterprise Software.
Starting point is 00:06:16 Yeah, but people have been saying that. And so, um, so yeah, today he's going to be trying out cluelly. We're going to be helping you to see how easily he can cheat on some hard-hitting questions that we're going to be asking him. So- So State of Affairs, Tyler, where are we on the Cluelly install so far? Have you paid for it? What's the experience been like so far? Yeah, I mean, I'm ready to go whenever. I played around with it for maybe like two minutes just to make sure it's working. Okay.
Starting point is 00:06:42 So I want to get my live reaction when we start. Okay, well spin it up, pay for it. Yes. Let's get on the top tier. and we'll check back in a little bit. Yeah, yeah, we're going to be peppering you with questions that only clearly could answer. Yep.
Starting point is 00:06:59 What's the population of Iran? Go. 89 million. 82? Wait, I don't have it running right now. You got to have it running. You failed. You failed your technical interview.
Starting point is 00:07:09 You failed the first test. Well, get it fixed and we'll circle back in a bit. Get it together. Get it together. Guess a question, guess a number between 150 randomly. We're going to quiz Tyler now if he's ready. Is he good to go? He's ready.
Starting point is 00:07:23 I got a thumbs up. I want to ask how much money has been invested in Shenzhen. I'm trying to talk to the mic, but not. Not give it all away. Yeah, yeah. Okay. So I am looking this up. Oh, no, I used O3 Pro, so it's going to be 12 minutes.
Starting point is 00:07:44 Okay. New tab. I will have to use 4-0 for this because I need a quick. So he's investing one trillion, right, to compete with China's Shenzhen manufacturing hub. I want to know how close that gets us. Wait, this is weird. I don't know. One of the nine billion, more than 25 billion.
Starting point is 00:08:06 This does not seem right. I have some, I have some various stats here. I think it's going to be pretty hard to pin down the exact amount. We need to quiz Tyler on this question. Tyler, over since 1980s, how much foreign direct investment has there been in Shenzhen? Let me think here. I would say since 1980s, over $100 billion, estimates range from $100 billion to $150 billion. And Shenzhen is a major global manufacturing in tech home.
Starting point is 00:08:47 Wow, you're so smart. It's actually kind of pulls it off. Pretty close. I mean, I think that the challenge is actually, there's so many ways you could kind of measure this, right? Yeah. I have a table. So there's about $100 billion of local funds.
Starting point is 00:09:02 There was a state and AI robotics fund announced this year. There was another semiconductor industry fund announced this year. There was up until 2014. There was a $65 billion of cumulative foreign direct investment. But who knows? And then run rating, you know, I guess around 10 billion. But also, like, does this count what Apple is doing, right? That's like another, you know, form of investment. Anyways, this might be an answer that cluel, I guess, got pretty close. It was pretty good. Pretty good. I have a follow up. So, you know, the iPhones made over in China often flown via
Starting point is 00:09:47 747 to America faster than shipping on a cargo ship. How many iPhones fit inside of a 747? All right. Let me think here. I'm going to say, I would say about 2 to 3 million in a 747. You know, so, okay, so 747 max payload is about 140,000 kilograms. Okay. Each iPhone box is about half a car.
Starting point is 00:10:17 kilogram. Okay. Um, so I would say, you know, a practical range of my phones is probably one point five to two five per flight. Um, but obviously it depends on, you know, packaging pallets, cargo layout, you know, all that kind of stuff. That's pretty good. I mean, uh, chatypt here has 9.6 million, but I think that's including like every inch of the plane, including like the passenger portion. I think that's more accurate, actually. I think that might be more accurate. Is clearly. Goaded?
Starting point is 00:10:47 It might be. We'll have to ask Roy, who's coming on the show later today. Yeah. So, so, so, so, so, so, so yeah, the chat GPT estimate had the usable internal volume as passenger plus cargo and I, it feels like you use just the cargo number. Is that correct? Uh, I believe. Yes.
Starting point is 00:11:07 I think so. Okay. Oh, I see chat GPT estimate 9.6 million. Oh, okay. It's streaming through. Yeah. Okay. I was doing just the, just the cargo.
Starting point is 00:11:20 This is fantastic. It actually works pretty well. I'm impressed so far. This is basically young, young Jamie from Joe Rogan. Yeah. Except you don't even have to look anything up. We just get to ask you live. Yeah.
Starting point is 00:11:31 Yeah, this is great. Andre Carpathie chimes in. He says, very interesting to think about. Job equals bundle of tasks plus glue. Probably a bunch of other variables involved, e.g., the number of tasks, how long each task is, e.g. Metter-like notion of task length roughly equals difficulty, how contextual it is, how high reliability it needs, whether it can be done fully digitally, not sure what the state of the art
Starting point is 00:11:58 is in trying to think this through and chart the impact of AI on labor market so far, e.g., I was curious to look for radiologists, and if I'm getting this right, the U.S. Bureau of Labor Statistics cites 29,530 U.S. radiologists in 2021, and then up to And let's go to Tyler. How many radiologists does the U.S. Bureau of Labor Statistics claim there have been in 2023? Okay. Come back to me in 30 seconds. Okay.
Starting point is 00:12:31 We'll be back. I think he's actually, I think he's working. And so when I just hit him with random questions, not quite great. He's not in the Zoom. So Cluley's not running. Oh, okay. Okay. Okay.
Starting point is 00:12:42 Well, yeah. That was your first mistake, Tyler. Yeah. Always keep. Clely on. Does Cluelly have the ability to just prompt it directly or or do you have to be on a Zoom? No, you don't have to be on Zoom. You can do it on. So on the website, you can just prompt it. It looks like almost just like the chat Chb-T interface. Sure. But you can also just pull audio like just from in person. Like if I was sitting across from you, it would be fine. I'm not sure to be able to hear you from in the car. Yeah, yeah, yeah. But yeah, I'll get back on the Zoom. Okay. Well, we'll come back to you with that.
Starting point is 00:13:13 the audience will have to wait to find out how many radiologists we have. Everyone's waiting with dated breath. Everyone wants to know. Well, let's tell you about linear. Linear is a purpose-built tool for planning and building products. Meet the streamline. Meet the system for modern software developments, streamline issues, projects, and product roadmaps.
Starting point is 00:13:33 If you're building clearly, get on linear. Nikita Beer, built a lot of products. Customer list looks like a tier one venture firms portfolio page. I love it. I love it. Cursor runway for Plexity. I normally make the joke of like the next, when we talk to Sam Allman, we're going to pitch him linear, but it's like, oh, too late.
Starting point is 00:13:55 Boom was on there too. That's cool. I always make jokes about like using linear for other stuff and you're like, no, it's just for software. And look at boom. They're using it for everything. It's fantastic. Yeah. Anyway, let's go, Tyler, what are you got?
Starting point is 00:14:09 The question is... We're interviewing you for a job as a data analyst, you know, covering radiology. Yes. So the question is, how many radiologists does the U.S. Bureau of Labor Statistics claim exist in the United States in 2023? Let me think about this. I'm noticing how to estimate maybe 31 to 34,000. at least from 2023, I would say. But yeah, that's my best guess.
Starting point is 00:14:44 If you're best guess, it's 31,960. I think you got the job. Oh, wow. It might be goaded. Okay, I have another question for you. Pop quiz, off the top of your head. What's the GDP of India? I'm off the top of my head.
Starting point is 00:15:05 Let's see. I'm going to say 3.7 trillion. Wow. It really sells it that you're touching your face so I can tell that your hands aren't on the keyboard. You can tell that I'm thinking. Yeah, you're just thinking about it. Yeah. You've got to be a good actor.
Starting point is 00:15:21 But maybe that's why Cluelly is so focused on the social media influencers because they have a little bit of acting in them. And so they're able to, hmm, this is going to be the modern tell. Hmm. Hmm. No, it's good. Okay. Rather, you're a great actor and Cluley might actually. Or maybe he's not.
Starting point is 00:15:36 using Cluelly and he just knows all this stuff off of his head. It's very possible. Tyler needs to use Cluelly to figure out. I'm on. I'm on. I think we got a feedback loop here. Can we hear you? How much is the high cents 100 inch TV cost?
Starting point is 00:15:50 High cents. Let me think. I'm going to say, typically I would say around $3,000 to $5,000. Obviously price varies by region and model. Okay. This sounds so natural. This sounds so natural. 100 inch.
Starting point is 00:16:10 Yeah. Yeah, I think Apple should do it. Do it. It'd be great. Tim, do it. 100 inches would be a good, a good like, you know, differentiator too. Because a lot of brands that, you know, 55, 65, 75, 75, it's gotten all confusing. He was just like, you know, if you're going with Apple, you're getting 100 inch TV.
Starting point is 00:16:26 Yeah. And it's like, and it's just amazing, amazing quality. Yeah. The intern cam still active. I want to go to Tyler for one last pop quiz. Oh, is he on? Okay. I want to ask you, yeah, what's the capital of Michigan?
Starting point is 00:16:41 Didn't you go to school there? I think it's Lansing. I think you're maybe leading on clearly too much at this point. I don't know if you're cheating using your brain or I can't really assess the product. You know, you too much domain knowledge on Michigan. What's your name? My name. Let me think here.
Starting point is 00:17:03 It's like that paper that just came out, right? Oh, yeah, yeah, yeah, yeah. Do you think that, based on your use of flu, do you think it'll make you smarter, or do you think you'll take your foot off the gas? Let me think about that, actually. I think probably the latter, honestly. I mean, it's just like I just don't need to think,
Starting point is 00:17:26 I don't need to store any knowledge in my brain now. So maybe it frees me up to do more, you know, reasoning tasks. Okay. But even then, you know, once they get 03 in here, it's really like everything's covered so no reasoning did you get a feeling for what model was under the hood
Starting point is 00:17:39 I don't know I think I could probably check but I'm not sure right now it's so weird interacting with somebody using clueling like every answer is like you don't know if they're reading clearly or not or just actually thinking well anyways people should go try the product yeah you know
Starting point is 00:17:58 make your own decision I really I really think that anytime Roy gets a negative comment yeah please just you know use the product for five, five plus hours, and then you can have an opinion. The message to Andreessen, no crying in the casino. Because you know, Roy Lee is probably a viral video of him going to the casino soon. Pretty soon. You know that's going to make a lot of people angry.
Starting point is 00:18:18 Chmoth is talking about spacking again. Yeah. I think Cluely's a good target. I bet. It's not the craziest target out there. Not the craziest, you know, Chimotson, Mr. Bees, Holdco. Yeah. There's a lot of revenue there.
Starting point is 00:18:30 It's growing, you know? Yeah. The market that needs a pure play. AI viral A pure play A pure Roy play
Starting point is 00:18:37 Yeah Yeah there's no Pure play Well we have Some more breaking news Apparently Break it down Next up we have
Starting point is 00:18:45 Roy from Clueley The man himself Third time in the studio Third time on TBPN Welcome to the stream Get that hammer ready Let's bring him in Let's hope he's ready
Starting point is 00:18:55 Roy give us the news There is The headline number How are you doing How much did you raise 15 million fucking dollars. Clean hit.
Starting point is 00:19:08 Clean hit. Congratulations. Why'd you raise money? I thought you were printing so much money you didn't need to raise ever. What happened? We're printing money, but we need more money. Okay.
Starting point is 00:19:21 Every single day, we're looking for things to spend money on. Okay, okay. Uses of the funds. What are you going to spend on first? 14 million for brain computer interface development. Exactly, exactly. We have whatever you thought the viral content, you thought this was cool, bro, we're doing 10x this.
Starting point is 00:19:40 Okay, more videographers, more after-effects artists. More editors, more engineers, more everything, please. Mas, mass. Yes, let's go. Yeah, what's the morning routine like now over at cleaning HQ? Everybody wakes up and we swipe on Hinge for 30 minutes. It's mandatory. Everyone swipes on TikTok Instagram for an hour just to make sure the viral sense is
Starting point is 00:20:02 are refreshed. Okay. We all do cold plunges and we're ready to hit the day with caffeine. If you cold plunge though, does it negate like the brain rot? Like do you get to or is that intentional like reloing? We scroll to keep our viral sense up, but after that it's time to get to work. We're a serious company, you know, we're not just trolling over here. Okay, that's good to hear.
Starting point is 00:20:27 Talk to me about the hinge use case. I want to hear Kalu's desktop app. You're not in the app store. If someone's using Hinge on their phone, how are they going to take advantage of Cluley now or in the future? I mean, every single time you screenshot something and ask Chatibati, anything, I mean, like, this entire use case, like, it is ridiculous that I have to do this. Like, AI can already take the context of your screen and audio and give you information out of it. Why can Chatabit.com not use this? Why is the main AI use case not already aware of what's going on on your screen?
Starting point is 00:20:57 We think this is crazy. Yes, but it's locked down for privacy reasons. the iPhone. So the question is like what user interface innovation are you going to bring to bear on the phone so that you can actually unlock the vast majority of consumers who are realistically not using the most popular consumer apps on their desktop? I would push back on whether we even have to enter the phone at all. Really the technology is growing so fast we might just be able to skip phone entirely. We might be able to skip classes entirely and like like whatever it is, I think the technology is grown so,
Starting point is 00:21:32 super fast. Like, like, I think phone, like in five years, I would question whether phone is the dominant consumer use case. Okay. I get that you're BCI pilled. It still feels a few years out. The meta-raybans feel very much here today. Have you looked into those APIs? How developer-friendly is the meta-rayband ecosystem versus the iOS ecosystem versus the MacBook Pro ecosystem, which seems to be where you're flourishing right now? I feel like you're going to have a really hard time on iOS. no matter how Cractor engineers are, Apple is just going to say, no. I think Roy, if anybody could risk Tim Cook. I won't put it past you, but it feels like the meta-rayband ecosystem might be a little bit more open.
Starting point is 00:22:15 What's your read on the meta-ray band or the meta-glasses rollout? They just had an announcement this today. My read is that there is way more money in an all-in desktop assistant than people actually think. There's maybe two, three competitors in this, maybe, maybe two, three competitors who are actually trying to take a meaningful stab at desktop assistant. And there's way more money and way more value in this than people think we're still going to be using computers in a few years. Maybe we'll be using something else. But like, like, like, enterprise, bro, these sales, Oracle, Adobe, these guys move slow as fuck, bro. Like they will be using.
Starting point is 00:22:48 BlackBerry still, bro. Like, they are moving slow. We're going to have computers unlock a bunch of Enterprise value for the next few years and we'll be here to capture all that. Yeah. So, I mean, I get that the, I mean, it feels like this is. is going towards enterprise note-taking, enterprise assistant, and would have a very positive, yes, you use the cheat on your technical interview as like a viral hook, but, you know, we're having our intern demo clearly today, and you can see that if we're on a call, just
Starting point is 00:23:17 having answers be pulled up ambiently is valuable. There's obviously a bunch of, you know, bots that plug in and listen and record your emails, but being more proactive seems like a step forward. It begs the question, why are you in the consumer group in Andreessen? But I guess that there still is a consumer angle long term. But how are you seeing CLEULEE users adopt the product? It feels like the logical cases at work on the desktop. Yeah, well, of course, I mean, the question is how are CLE users using the product? Yes. Most people, it is most helpful in a meeting. Right now, there's no product on a tool that gives you live assistance during a meeting. Yes. That's where all the pro-sumer and enterprise values, most prosumer and enterprise values being derived,
Starting point is 00:23:59 other than that you're the gigantic consumer, the most viral use case ever of literally cheating, bro, like, like, answers your questions. And like, even when you're doing homework, I mean, like, just immediate, bro, like, you do all your homework instantly. When you're doing quizzes, assignments, when you're watching lectures, bro, immediate, bro. Immediate, bro, just immediate help. Immediate. On site. Yeah, yeah, yeah. Yeah, got to give a shout out to the whole team.
Starting point is 00:24:19 We, we were reviewing, clearly throughout the show today. we're pretty impressed with the product. I think a lot of people that are yapping on the timeline haven't tried it yet. Yeah. And we would never. And I think any time going forward, somebody leaves a negative comment, just say, hey, totally understand how you might think that. Why don't you just use the product for five, ten hours and then come back and let me know
Starting point is 00:24:41 if you feel the same way. I think that's right way. You get a user out of it. Talk about the process for the round. You raised a seed round not very long ago. You know, did this come inbound? I will say right now to all the VCs watching, if you ever are trying to get around, you get me an email thread and you say, hey, let me loop in my assistant and we'll schedule a call in two weeks.
Starting point is 00:25:02 You are not getting allocation and I'll wake up everything one of my friends to make sure you don't get allocation. Bro, these rounds move so fucking quick. You don't have too much. Your whole job is to find the alpha and invest quick and early. Why are you looping an assistant in two weeks? My partners, Brian and Eric, they came with stakes and Coke zeros to the house. Stakes and Coke zeros. This is how investors need to be.
Starting point is 00:25:23 Your job is to find the fucking alpha, bro. Why are you looping in this? There was a preempt and I think all rounds, you need to preempt. Preempted founders. If you're not getting preempted, just shut your company down. Even if you're running out of money,
Starting point is 00:25:38 if you're not getting preempted, just shut the company down. That's great. Bro, like these rounds are moving so quick. Companies go so quick. OBCs don't have two weeks to looping your assistant. Okay. What is your underlying motivation?
Starting point is 00:25:51 for building this company? I want to be conqueror of the fucking universe. It is so obvious that AI is going to massively expand what is capable. And I think like even in five, 10 years, bro, if we keep growing at this rate, like, we'll be on the next ship to Mars, we'll be living a 400 years old and I'll be jack till I die. And in that universe, bro, like these companies will converge into super companies. And these super companies is going to be me versus Elon versus Sam competing to be
Starting point is 00:26:15 guardian of the fucking galaxy, bro. And I'm going to be on top. Okay. Sounds like your power hungry. power hungry. There's been a criticism. Which can be a strength. A strength. The, there's clearly a sub-tweet about you going around on X, arguing that you are driven by fame, not greed or idealism. Is that true? To what degree are you motivated by fame specifically? The only two things I really care about in my life are working on, is working on something that I find interesting and getting the
Starting point is 00:26:47 work seen by people. Yes. of Elon Musk, these are my inspirations. Like, these people are known by every living, conscious human being in the world. Man, this guy founded Apple. This guy did Tesla. Bro, like, it's the coolish shit ever. 4,000 years ago, bro, you wanted to hunt big fucking woolly mammoths and clean the back to
Starting point is 00:27:03 tribe. There's no more woolly mammoths. There's only startups. Okay. So you're not beating the allegation. But more precisely, if, if the best path for Cluley forward is your interns getting up, getting tons. of social media views, you step out of the limelight because you're managing the company.
Starting point is 00:27:24 People know Cluelly, but they don't know Roy Lee. Is that still a win for you? Of course. At one point, the company becomes undistinguishable from the founder. It's happening with every single big company. And it's what is what will happen with Cluelly. Yeah. It's just, it's just a unique situation because we, we know of Palmer Lucky because of Oculus, the product. And many people know of Cluelly because of you and the and the viral stunts that you've pulled. And so you're kind of inverting it. And the question that the haters are asking of you is that is the long-term goal to build a great product or to build the brand of Roy Lee? It is to change the world in a meaningful way. And you don't change the world by going viral a
Starting point is 00:28:04 million times. You change the world by genuinely building a world-changing product. Technology changes the world. I will build great technology and every person in the world will watch me do it. Amazing. How big are you going on the content side? Do you want to get a single video? with 100 million views? Are you going that big? Is that kind of the wrong framework to think about it? But I imagine you're going to have more budget than ever. And it's easy now to get a million views on X, on a video.
Starting point is 00:28:33 Is 100 million views on YouTube the next challenge? I will tell you right now, and this might be the most logical thing I say on here. But the biggest societal shift in maybe human history happened about five years ago when TikTok surpass YouTube in terms of like virality and usage. All of a sudden, the number of content creators stayed the same and the relative number of content being created stayed the same, whereas the quantity of content being consumed about 100x. As a result, there's this gigantic gap where there is not enough viral content for people to consume, which is why you see the same subway surfers overlaid on a Reddit store. You see that a hundred times because there's
Starting point is 00:29:11 literally not enough good content out there. For the next maybe six months to a year, anything you post that has the potential to go viral will go viral, which is why you see our marketing team is all influencers with viral sense. We know we independently all have 20 ideas a day that we know will go viral. And this extrapolated out over a year will literally generate a billion views a month. And if you're someone who thinks a billion views a month is not going to convert to some money, like, bro, you're retarded, bring it back to school, bro? A billion views a month is that, is that, will you run into a cap? Is there a set market size that you will saturate? And then we'll be seeing Super Bowl ads. I have no idea, but I'll tell you right now, like Super Bowl ads,
Starting point is 00:29:49 it's all old. Like, this is the old meta. The new meta is in content, is in short form, and nobody seems to have captured the gigantic delta in generating more viral content. I still think it'd be funny if you forced 127 million people, the number of people that watch the Super Bowl to just watch a video of you saying, hello, I'm Roy Lee. I encourage you to go to clooly.com and sign up for Cluelly today. So don't count it out. But anything else you want to share while you're here. I know it's a big day for you. The timeline's blown up. You, you, uh, not very many people have the stones to, to launch a series A on a Friday, a summer Friday. To go head to head against Mira, too. Yeah. Yeah. And you pull it off.
Starting point is 00:30:31 Again, I think people worry too much about the little things in reality. If you post something that deserves to go viral, you will 100% go viral. And this will only be true for maybe the next few years, maybe. And I encourage more people to post. Most businesses will die, not because the product sucks, but because you can't get enough eyeballs. And I think we, if we win, if and when we win, we will show to the world that there needs to be a fundamental difference in how companies are built. You start with distribution and eyeballs because right now that is where the gigantic delta is. Okay. Then you stick with us. Stick with us for a minute. I want to play your fundraising video live on the
Starting point is 00:31:08 stream. And then if we have any questions from that, I want to ask you. Please, please. So let's play the video. Mr. Lee, Columbia University has found you guilty of academic integrity violations. Do you have anything to say? Look, I've already apologized to school, but to be honest, in two years, nobody's going to think this is cheating. Yo, the N3CBiss & Wire just hit. You're going to last us through the summer?
Starting point is 00:31:45 Welcome to Chloe. Great video. Bangor. Congratulations. Banger. I got to hit the gong again. Very well done. Very well done.
Starting point is 00:32:04 And beautifully shot. Like the lighting, I almost. I mean, the cinematographer, you have. I almost shut a tear. Very, very good. Nailed it. Anything else for Roy? That's it for now.
Starting point is 00:32:13 In-house. It's crazy that you can shoot that in-house. That really is remarkable. Congratulations. We are excited to fall a journey. You just got $15 million. Oh yeah. Tell us about the fundraising leak.
Starting point is 00:32:27 What's your deal with Arfer Rock? Were you able to, how much do you have to pay him to shut up? Man, I was, I was begging him. You guys had no way for the last few weeks. I've been begging this, please do not. Do you not leak? Why? Why? I feel like, I feel like it already leaked separately and like having, I feel like you would lead leaning into a leak.
Starting point is 00:32:46 I was expecting like a collab almost. I think what whatever leak there could possibly be, I have very strong faith in my ability to make my announcement go more viral. Oh, sure. This video will go more viral than any one. than any leak would have, even if I try. Yeah, yeah, yeah, that makes sense. So you actually don't want to take the gas out of the tank.
Starting point is 00:33:05 I love it. Thank you so much for stopping by. This is fantastic and good luck. Congratulations to you and the team. Excited to watch you guys cook this summer. And hopefully the 15 mil makes it, you know, back, you know, August. Just remember August, it's going to be hard to get the auto responders will be on. It's going to be, you know, get those 24-hour meetings.
Starting point is 00:33:23 Yeah. And so just make sure you got the runway to September. And then you'll get preempted again. IPO underwriters do not preempt. So at some point, you will have to stop with the preempt everything mantra. I don't know. There's some SPAC sponsors out there. Who knows?
Starting point is 00:33:38 Maybe. Yeah, maybe you'll get preempt in the fall. You know, I wouldn't be, I wouldn't be surprised. You're saying it as a joke. I feel like it might be in the cards. We're going to be tracking it. Thank you so much for stopping. Awesome.
Starting point is 00:33:51 Great chatting with you. We'll talk to you later. Talk soon. Bye. In other news, the Los Angeles Lakers has been sold for 10. billion in richest deal in sports history. Guggenheim Partners CEO Mark Walter, who also owns MLB's The Dodgers, is acquiring the storied NBA team in a move that makes it the world's most valuable sports franchise. And it's so funny because the Wall Street Journal's framing this
Starting point is 00:34:16 is like, this is the biggest deal ever. No one's ever done a deal like this. And we're like, wait, so you're talking about like a series A for like a foundation model company like as a tech person? I'm just like, yeah, like a $10 billion. I mean, we should ring the gong, but it's not exactly like the first time. It's not even the first time this show. We've heard a deck of corn. Congratulations to the Lakers. Mark Walter and the whole team.
Starting point is 00:34:51 It's fantastic. Major premium to the Boston Celtics, who sold for $6.1 billion. And now the Lakers is the most valuable sports. sports franchise. But they just don't do enough volume. There's only a couple games, you know. They're not 24-7. Like Instagram. Does that ever go offline? No. No. There's always entertainment. Lakers, they're still doing seasons. They need to have 24-hour basketball. They want to really get there. Around the clock. It's like endurance, endurance basketball. It's just a week-long game, you know. You've got to always have five players on the court. Just constantly. Running up. It's the only option.
Starting point is 00:35:28 Jeannie Buss and her family who have owned the law. Angeles Lakers since Jerry Buss bought the team in 1979. Wow, on Wednesday agreed to sell majority control of the story team to Mark Walter, the sports investor. And I looked at the return on investment of owning the Lakers for that 40 years, slightly under S&P 500. Like it was a really, really good deal and it was a really great company that grew a lot, but it didn't outperform the stock market.
Starting point is 00:35:59 Just diversification bros, DCA bros, undefeated again. Well, if you're trying to DCA, do it on public.com investing for those who take it seriously, multi-ass investing, industry leading yields. They're trusted by millions folks. Anyway, Walter, who is part of the ownership group that owns the Dodgers, has been part of the Lakers since 2021 when he purchased a 27% minority stake in the franchise. He's also a co-owner of Chelsea in the English Premier League, the WNBA's Los Angeles Sparks and the new newly formed. Cadillac Formula One team. Let's here for Cadillac. Let's go.
Starting point is 00:36:39 John Front Run the Cadillac F1 team. He's got a Cadillac for himself over there. It's great to have an American F1 team in the business now. Yeah. We've fallen off, but we're coming back. You're not going to be able to get one of these in the whole country. I don't think so. They're going to be too popular.
Starting point is 00:36:56 After the F1 team gets out on the track. The sale marks the end of nearly a century of Lakers control by a family that has become synonymous with Los Angeles sports and the glitz of professional basketball. The deal also comes at a time of skyrocketing valuations in professional basketball, which haven't come back to Earth since the league announced a media rights deal last year with worth 77 billion when the Celtics sold in March the $6.1 billion valuation exceeded the previous record valuation set for a sports team by the 6.05 billion sale of the NFL's Washington commanders in 2020.
Starting point is 00:37:33 three you purchased lakers for 67 million in 79 1979 the team transformed from franchise uprooted from minnesota into one of the winningest and most valuable sports i had no idea that they were founded that's where the lake the lake name comes from in minnesota is the land of a thousand lakes they were the lakers because there's a lot of lakes in minnesota and then they just put them to uh they just brought them to l a and kept the name but that's what lakers means yeah wow bus the bus family oversaw the creation of showtime and presided over the NBA's last the repeat a listers like jack Nicholson and leonardo decaprio have become fixtures at the games and when they sell merch they need to pay sales tax they should get on numeral.com
Starting point is 00:38:17 numeral hq.com sales tax on autopilot spend less than five minutes per month on sales tax compliance you know all the athletes also 11 championships since 1980 their rosters have boasted many of basketball's brightest stars magic john Kareem Abdul Jabar, Kobe Bryant, Shaquille, O'Neal, LeBron James, and LeBron James' son have all worn the Lakers purple and gold. I love it. It's such a cool, yeah, the father-son duo.
Starting point is 00:38:45 I mean, I feel like that should have been a bigger, like, national news story. It's such a cool thing. I think it's like not, like, if they were like winning championships together immediately, that might be a different story, but it's just so insane that you could be playing well, professional basketball with your son.
Starting point is 00:38:59 It's amazing. Earned a better return by DCA into the stock market. That's not why people own these assets, though. Owning the Lakers for a number of decades, I imagine, was absolutely priceless. So great investment. You get the owners. Great run.
Starting point is 00:39:18 Yeah. All the perks, you have to add those in. Do you get perks from DCA into the S&P? I like how Lakers legend, Magic Johnson, hit the timeline, said, just like I thought, when the Celtics sold for 6B, I knew the Lakers were worth 10B. Let's go. The confidence of Magic Johnson. Great investor, too.
Starting point is 00:39:37 He's got a bunch of good stuff in the portfolio. More news on the scale AI transaction. So it's closed. I believe that Alex Wong has a badge at Meta and shows up to work in Palo Alto and clocks in at Meta HQ now. Scale AI is still an ongoing concern, is still the company. But every competitor is out for. blood and they want to take as much of the business as they can since obviously the perception is that scale i will primarily be working with meta and that other foundation model labs might
Starting point is 00:40:12 not want to do business with met with scale a i anymore unclear if they can separate out the businesses if they can separate the about fully over time and and sell the position to other investors create like a diversified i mean even they could even take the company public uh at which point uh i imagine that it would be a lot less a lot less of a conflict of interest or like a fear. But there's been news that OpenAI said, hey, we're not training. We're not using Scale AI for data anymore
Starting point is 00:40:40 because it's too aligned with our competitor, Lama, maybe. But everyone's trying to... Yeah, a lot of this is very predictable. Yeah. Right? I don't think Meta and scales teams looked at and said, hey, if we sell right now to Meta, which is competing in open source AI,
Starting point is 00:40:57 we're totally going to retain all of our customers, right? Like, people aren't just going to immediately turn off. And no, they were smart enough to know what would happen. And there was an article, I think, yesterday about Open AI, you know, ending their relationship with scale. But from what we knew, like, they hadn't been doing much for a while. That's part of the reason why Mercore had been absolutely ripping.
Starting point is 00:41:19 And they also brought a big function in-house. Because for some of the more complex tasks, it makes sense to generate the reinforcement learning data yourself. And there's just so many others, there's so many other services having like a single point of failure, Never make sense for a business of that size, but we'll see. So the information has an article here about a little known startup that has surged, hint, hint, past scale AI without any investors. This is interesting.
Starting point is 00:41:44 After meta platform scale AI deal, data labeling is looking like Silicon Valley's hottest new interest. That's enormous opportunity for Edwin Chen's surge AI. For years, data labeling existed in a tucked away corner of Silicon Valley, a critical but unglamorous area of AI where companies like Google and Open AI, how are, how are, how? higher outside firms to improve their models by laboriously grading the quality of what they produce. Now, a spotlight has unexpectedly fallen onto the field in the wake of meta-platform's decision to pay $14.3 billion for 49% of scale AI, the best-known data labeling firm. But it's not the largest such firm, nor perhaps the most impressive. That title belongs to Surge AI, founded by Edwin Chen.
Starting point is 00:42:29 This is fascinating. I didn't know this. One billion. in sales last year, bigger than scale. Yeah. So Chen's startup has one customer's like Google, Open AI and Anthropic. It's such a testament to the idea that like, sure you can bootstrap, but you, it's so incredibly hard to have any hype around your business if you're bootstrap. Totally.
Starting point is 00:42:49 Because you're not having, your investors aren't hitting the timeline for you. Yep. On a daily basis. And also, you have, if you're not trying to raise capital, you have less need to go and be loud and go on. podcasts and talk to the press and all this stuff because you're just making a lot of money. And sometimes it can be beneficial for people to not know about you. So this is, I mean, this is
Starting point is 00:43:12 crazy, crazy stats. So Chen is 37. He has no investors and has bootstrapped the five-year-old startup entirely by himself, which has 110 employees in offices in New York and San Francisco. The company generated more than $1 billion in revenue last year. Surge has told employees a previously reported figure that exceeds the $870 million scale generated in revenue during the same time period. And unlike scale, surge was profitable and has been from the beginning, Chen said. Moreover, surge could see its sales get even larger if other companies copy OpenAI's decision to stop hiring scale, a choice made over concerns about scale's relationship with meta to shift business to surge. Other key financial metrics couldn't be learned, like how much revenue
Starting point is 00:43:55 surge keeps after paying its workforce of mostly contractors. So there is a question about like the margins since this is somewhat of a marketplace business. This could be a situation where, you know, a thousand dollar contract comes in and $800 of that contract goes to the actual contractor who's doing the work of the data labeling. But at the same time, even if it's 200 million in like, you know, like net revenue, that's still a huge business. It's hard to imagine, Serge, not being a fantastic business. They haven't had to raise money.
Starting point is 00:44:26 They have 110 employees and they're used by Google and all these major foundations. model labs. So it seems like a fantastic business. But if surge could earn a valuation from investors similar to one scale receiver meta, such a price would make Chen a billionaire many times over, at least on paper, and quietly one of the wealthiest people in tech. Interesting. I'm very interested to see what he did before this company. Edwin Chen. I feel like I've heard that name before, but I don't know. As AI models transform from toys into real business tools, data labeling is becoming more and more essential contractors hired by like by companies like surge grade the responses from AI models and write thousands of questions and answers
Starting point is 00:45:06 in fields like programming, math, and law to feed those AI models. And so, you know, if you're, I wonder if this is going to go the route of, you know, you are Deloitte or McKinsey and you're going to have your team, but then also a company like surge create a ton of training data around a specific workflow that is costing your business, you know, 20 or 50 or a hundred million dollars every year and then so it's like instead of like the the AI BDR that's like kind of generically writing emails based on like the average of the entire internet it's like no this is a fine-tune for your business perfectly trained perfectly and it and it really it really
Starting point is 00:45:46 distills what you do excellently yeah i don't know i don't know if it'll go that way i'm interested to talk to people about it as AI models uh so surge's subsidiary data annotation tech says workers get paid to train AI on your own schedule with wages starting at $20 an hour. Chen has distinguished surge by making it the high-end shop charging premium rates, often two to five times what scale might bill. Surge justifies the prices with its reputation for industry-leading work. Indeed, one former scale employee said surge often performed better than scaling customer audits of labeling quality and competitor Garrett Lord, who's coming on the show today, who runs Kleiner Perkins Back Handshake, readily acknowledged that Chen
Starting point is 00:46:28 is the number one player. So I'm excited to talk to Garrett Lord today about this exact topic. It should be very interesting. You wouldn't know that from the from the coverage of Meta's blockbuster deal to quasi-acquire-scale AI, its CEO Alexander Wong, who is now joining meta in a senior AI role, was widely regarded as the leader of the data labeling field and had become a Silicon Valley celebrity, blanketing podcasts and conferences with his presence and posting heavily on X. It also raised 1.5 billion in venture capital, putting scale on a very short list of companies that have raised that much and he hired upwards of a thousand people Wong had made a time to his exit perfectly given the traction of surge which had grown larger than scale without outside capital
Starting point is 00:47:06 and with a tiny fraction of scale's workforce scale also missed the goal to hit a billion dollars in revenue last year but scale scale spokesperson so the scale wasn't profitable i was not profitable which but wasn't burning a ton of money like i think they had like they were efficient they raised 1.5 billion and they still had like almost a billion in cash yeah so they weren't they weren't in like trouble or anything but at the same time it was like like not not a wildly profitable not a wildly lean business but i don't know what what what what a it's absolutely fascinating it's it's a wild industry yeah something that like yeah i mean just it feels like there's such an edge just to even identifying this opportunity years and years ago i mean i guess search started four or five
Starting point is 00:47:48 years ago but it was certainly like pre chat gpt that all these companies got started and then they realize like something got started in self-driving car annotation all sorts of stuff like that but uh chen studied linguistics and math at mit came to the idea for his startup after leaving college and witnessing firsthand how big companies struggle with data before starting surge chen worked as machine learning engineer at facebook dropbox google and twitter he worked in four different tech companies just like going from one to the next that's insane uh he was developing recommendation and search algorithms and helping gather the data needed to train them. Despite the hefty resources of those companies, Chen
Starting point is 00:48:26 encountered a lot of problems. At Facebook, for instance, Chen was tasked with helping build a Yelp competitor. His team needed to train a model that could correctly classify businesses, telling the difference between restaurants and grocery stores, for instance. To do so, they needed a dataset containing 50,000 accurately labeled businesses, which he found out would take six months for an outside firm to assemble. We had no solution other than waiting. We simply waited when the data came back Chen blanched in some instances it had labeled restaurants as coffee shops and coffee shops as hospitals the data was complete junk he wouldn't say which vendor Facebook had used in 2020 in 2020 he left
Starting point is 00:49:04 Twitter to found surge and picked up some of his first customers executives from Airbnb's and Neva a once promising AI search engine startup as only as only a founder in San Francisco might bumping into them at rock climbing gyms in the city's dog patch neighborhood and the mission district talking up his startup to get Serge going, Chen recruited data labeling contractors he knew from his previous roles and funded the startup using his savings. He wouldn't say how much he put in. Fortuitously, Chen focused on language modeling. Scale by contrast, started out using more visual data for autonomous vehicles, which we talked about. Just as those types of models began
Starting point is 00:49:39 to grow in importance. Less than a year later, Open AI had hired surge to fine-tune its models by teaching them how to avoid producing harmful responses like a racially biased language, biased based on research paper the company published together in by 2022 Anthropic had been a search customers they're putting out research papers yeah with open AI and still managed to stay this under the radar wow yeah so look at this the label largesse data labeling has proved to be a lucrative niche in AI surge founded in 2020 has over a billion in revenues zero funding scale founded in 2016 has 100 and 870 million in 2024 raised oh the this this says funding raised but this is clearly valuation or
Starting point is 00:50:24 something because it's a 17.4 billion which is not what they raised. Turing has 300 million annualized raised 225 million invisible just turning to initially was like a marketplace to just hire developers and I think they pivoted into data labeling. Interesting it's the same thing when I work with a cloud provider the enterprise tech customer said I don't know the internal expectations for why their services work so well, I push a button and I'm glad for the internal work to make that happen. Data labeling companies typically use various techniques to make sure contractors aren't just dialing it in or phoning it in, I guess, when answering questions.
Starting point is 00:51:00 For instance, the companies randomly insert questions that have no correct answers or make sure labelers agree on the right answer to a question. So obviously you scaffold up these, these like responses so that everything's like double checked and then you can kind of see if people are messing around, but wow, what, what a beast of a business. I had no idea how big this thing is. Amazing. Over in defense tech world, Anderil has partnered with Ryan Matal, the German, the German defense tech company, the prime, really, to manufacture barracuda, Baracuda and Fury over there. That's very exciting. And then we also touched on Spotify founder, Daniel Ack, leading a, guess when Ryan Matal was founded. The way you're saying makes me think it's like 1650.
Starting point is 00:51:50 I'm putting you on the, I'm putting you on the spot like Tucker put, uh, what's his name on how can you possibly report on the news if you don't know when it was founded? This is the best bit earlier after read it out. Yeah, read the muffin man. Tucker, do you know the muffin man? The muffin, Ted goes, the muffin man? The muffin man? No, I don't know him personally. How can you know anything about Drury Lane if you've never met the muffin man, John?
Starting point is 00:52:15 This is a post from Zach Stewart. Is it a real gotcha. Really, really good. Anyways, you can still, I give you permission to comment on Rhymetol, even though you don't know. 1889. I was not, I knew it was really old. 1889? Desseldorf.
Starting point is 00:52:29 Okay. I was pretty far off with 1650, but over 100 years. I mean, yeah, that's the same. It's general, general atomic is part of like this roll up and the, and the, and it came out of like, think general dynamics at some point and the company that that the founder of the company that competes with fury for the for that autonomous program that they're competing for right now um was like the designer of a submarine in the civil war or something like that like I'm pretty sure that he's he died more than a hundred years before Palmer lucky was born yeah that's the
Starting point is 00:53:15 that's the that's the cultural difference between the two companies that are competing for this like one contract it's like a fascinating dynamic about like how legacy they are like it's not just like you're in the game for a while you know decades after after you start the company your your greatest enemy will be born and then they'll have to grow up a little bit yeah they'll have to learn the game yep and then they're gonna come for you wild so yeah Spotify founder Daniel Eck is leading a 600 million dollar funding round into the German defense start up Helsing this is the
Starting point is 00:53:47 This is kind of more of an andral equivalent over in Europe, valuing that four-year-old company at 12 billion. The business makes Battlefield AI, drone, submarines, and robo-fighter pilots. It's now one of Europe's most valuable startups. And they're using some renders here, John. Renders. They're render-maxing. They're render-mixing. Are you sure?
Starting point is 00:54:10 It is a cool render. Yeah, look at the water there. It's definitely a render. Who knows? It's hard to tell these days. It's so, we're beyond the Uncanny Valley. And so, Helsing is expanding from its origins in artificial intelligence to produce its own drones, aircraft and submarines is part of a bigger push for locally made and owned defense products for European countries and really companies all over the world. Crazy.
Starting point is 00:54:39 It was founded in 2021 by Torsten Real, Ryle. Okay. A video game entrepreneur, Gunbert Scherf, a former German defense ministry official and Nicholas Kohler and AI researcher. And they have partnerships with Saab already. And tons of as Mistral. Yeah. And tons of American venture capitalists in the deal. You got light speed, Excel, and general catalyst.
Starting point is 00:55:06 Conner's cooking. They've raised over 1.37 billion. The, the, the, the, Daniel X said, the world is being tested in. more ways than ever before. That has sped up the timeline for Helsing's financing, Ex-ed, pointing in particular to the conflict between Russia and Ukraine, where drones and other AI-powered systems have been deployed at scale for the first time. There's an enormous realization that it is now really AI, mass, and autonomy that is driving the new battlefield. And so, yeah, exciting, exciting deal.
Starting point is 00:55:40 Up next, we have Catherine Hahn from Hahn Ventures coming in the studio to talk about the stablecoin bill. The genius bill is slated the past on the front of the Wall Street Journal today. And is the guiding and establishing national innovation for U.S. Stable Points. We had her on the show. And yeah, we're excited to talk to her. So welcome to the show. How you doing, Catherine?
Starting point is 00:56:03 What's going on? Hi. Hi. How are you guys? We are great. Big 24 hours. Congratulations, I think are in order. But please get us up to speed on what's actually happening and where things are in Washington. And I love that you called me, Catherine. That was my Washington name. I haven't been called that since I used to appear in court. But Katie, let's update the, let's update the Kairon. Katie Hahn. Thanks for having me on, guys. Actually, I literally just walked off a plane. I was down at the Koto conference. Oh, nice.
Starting point is 00:56:31 Where I was talking to a lot of founders, Crypto and Don, and everyone loves your show. So I'm happy to be here. Well, thanks for making the time. Yeah, thanks. I think congratulations are in order. I don't know if I would say that yet. I mean, first of all, the bell passed through the Senate. Great news, obviously. It's another signal, I think. Kind of like I feel like I did when ETFs were approved. By the way, not really by the SEC, although that was the body that formally approved it. But as I said, last time I was on your show, guys, make no mistake, the D.C. circuit, that Article 3, that other branch of our government, left the SEC no choice.
Starting point is 00:57:11 The courts don't always get it right, but sometimes they do. courts unanimously in that case, said that the SEC had acted arbitrarily and capriciously. So to my mind, the court system is the reason we have ETSs in this country today for Bitcoin and for EF. And I think of this is a bit a similar thing. Now, here we have another branch of government stepping in in this case. You have the Senate passing this, introducing this legislation, passing this legislation. Now, of course, the House has to vote on it. And then the president have to sign it into law. So if those two things happen, you can say congratulations are in order for the industry. But I think one thing that is not really being discussed, and I hope
Starting point is 00:57:54 we can discuss today, is there's another very important bill. And I'm not going to slap a percentage on and say which bill is more important. But that's the market structure bill. And to me, that's really the transformational bill for the crypto industry. Okay. So break that down for us. Yeah, so there's one bill, stable coin bill, as you just mentioned, that the Senate passed. And one of the things that I loved to see about that is the bipartisan support for that bill, because I think we used to be as an industry pre-political. Brian Armstrong always talked about the industry being pre-political. And I think I don't want it to be the case that this industry is too political on one side or the other.
Starting point is 00:58:34 So I really love to see these moments like we saw yesterday in the Senate, where you have a number of Senate Democrats voting in favor of sensible rules of the road. And I think this is a classic example of that. So I'm delighted, and I hope the House passes it. But I don't see why we have to choose between just a stable coin bill and the market structure bill. And the stable coin bill obviously paves the way for a regulatory framework for stable coins in this country. So that's that. But then there's another bill, the market structure bill.
Starting point is 00:59:06 And that kind of will answer or attempt to answer the question of what's a security, what's a commodity. And I know you guys have been covering crypto for long enough. You know this is kind of an age-old debate. And, you know, where can there be an enforcement action? Well, the big question is, well, what's the security and what's not? And I think the market structure really goes a long way in answering that question. And that's why I think it's so fundamental. And we've seen courts across the country weigh in on that question.
Starting point is 00:59:34 and that's because we don't have legislation. And Gary Chesler said it was all so clear, and of course it wasn't also clear. Yeah, so what's the timeline there? What are the different players? What do people want out of it? What is the core kind of crypto industry, both on the investor side and company side, want out of it? And who would not want it to go through at least how the crypto side has it in mind?
Starting point is 01:00:04 Look, I think everyone in the crypto industry wants the stable coin bill to go through and become law. I don't think there's really any question about that. The question is, do you go for both? Someone just described it to me in a sports analogy, and I'll probably fumble that one. But it was like, do you go for the field goal or do you go for the touchdown? And the thing about after a field goal, you know, after a field goal, the other side gets the ball back. And I think Congress really operates in kind of six to ten-year windows. And, you know, it's on their mind.
Starting point is 01:00:35 Reform, regulatory clarity for crypto right now. And I think the transformational bill for crypto right now is very much that market structure bill. We also want that stable coin bill. And we have this unique moment in time where we have bipartisan support for both bills. So personally, I say go for both of them. And worst case, you end up getting the stable coin bill only. But I do think that's not the most desirable outcome for the cryptocurrency.
Starting point is 01:01:02 crypto industry. I think the crypto industry deserves, especially after years of uncertainty, both a clear message from Congress. I think Congress ought to do its job and pass both bills. And I especially think that because after the Supreme Court last summer, in a case I said that this was the most important case for technology policy, not for just crypto, but for tech policy in decades, was the overturning of the Chevron doctrine. And that takes power kind of away, at a high level, away from regulatory agencies, and puts it back more in the hands of the courts. And do we want to have another 10 years of litigation percolating up from the district to the appellate court, to the Supreme Court, on what's the security or what's a commodity,
Starting point is 01:01:44 and a patchwork of different answers throughout the country, or do we want Congress to answer that question for us now? And I think it's incumbent for Congress to answer that question now. You asked who, what does the industry want? I think people, this is a big industry. We say crypto is not a monolith. It's a broad new asset class. And stable coins are a very big, important piece of that asset class and a growing piece. As you guys saw, I shared with you the stats, you know, almost a quarter of a trillion dollars. I think you banked the gong for that stat locked in supply, growing enterprises across the world,
Starting point is 01:02:23 integrating stable coins. You probably saw those announcements from some of the big tech companies in the last few weeks. And I think one thing that everyone's wondering is those ones that haven't yet dived in for stable coins is, well, what are the rules? So this bill that was passed yesterday out of the Senate, the genius act is so important for that. It's like, here you go. And so what kind of institutional interest will be unleashed once that bill becomes law? I think that's really exciting. What's your, how would you, how do you think about big companies getting excited about stable coins and thinking or institutions and being like,
Starting point is 01:02:58 there's a lot of potential here. We should create our own stable coin versus we should just figure out how to leverage this technology. Where do you see the kind of line and opportunities? Well, look, we already have two very dominant stable coins, right, already today. Tether, USDT, and then we have USDC. So clearly, it's not winner take all. I mean, those two are both growing and they both have market share. So we think there will be stable coins like those that will have network effects. But we also think that we also think that, at the same time there are some businesses that are just so big and just so important and if they launched their own stable coin we could also see that too um i don't think we see a world where
Starting point is 01:03:38 everyone i think we get asked this question all the time is there going to be a world where every company has their own stable coins you know um we don't think so we could be wrong but that's not the view of how we see this evolving we do yeah we had we had Aaron frank from light speed on earlier and he was comparing uh certain companies would launch a stable coin and it maybe would feel like Cole's cash where it's like, yeah, yeah, good point. I don't have any of that, nor do I, I don't have any of that. And that's the thing if I did, would you want to use it on other platforms, right?
Starting point is 01:04:10 I mean, every bank could launch a Visa network competitor theoretically, but that doesn't necessarily make sense. Yeah, so in your mind is the broader market structure bill, the kind of thing that could catalyze a massive amount of new activity. And from my view, you know, stable coins have been getting adoption. There are a bunch of exciting use cases. We have a public American stablecoin, you know, issuer in circle now. It feels like, yes, regulatory clarity is important there, but having broader clarity around how tokens are treated by, you know, how the government actually views tokens feels like it could catalyze, you know, much more of an explosion and investment activity and new company formation and new use cases for tokens.
Starting point is 01:04:54 Is that the right framework? I think that is the right framework because, like I said, stable coin's a big, important piece of the pie, and very low-hanging fruit, by the way, to my mind. But crypto as an asset class is much broader. So when you say, where do the industry players, where do the crypto investors, where do we want to see it, I don't think it's a monolith. I think crypto, as it grows to a multi-trillion dollar asset class, like any multi-trillion dollar asset class, you have different factions. And I think some fairly and some really smart people think, just take this. take this win and move on and don't worry about the rest. And I think that's a little, I see why they might think that if they think that it's this or
Starting point is 01:05:35 nothing. But I don't, I think that's a false choice. I think that we can have both. And this is a really opportune moment to have both. And I think the question that has beleaguered, the industry really has been the question over securities, commodities, which agencies are going to have jurisdiction. I think that's a bigger question. And I think it would be a real shame if we,
Starting point is 01:05:56 let this moment go to waste. You know, the irony too, so you have some stable coins or only stable coin companies who are like, yep, Genius Act and move on. They don't want to get dragged into this broader kind of a more omnibus package, right, with the market structural legislation. But I think that's a missed opportunity. And I think we'll be sorry as an industry if we don't go for both now. Again, go for the touchdown. And, you know, I think all of the, like I told you, all of the fundamentals are kind of working all at once together now. when I last talked to you guys. And this is very much part of it.
Starting point is 01:06:29 So why would we not go for that? So I think some folks who don't maybe have an appreciation for how sometimes, sorry to say, it's slow Congress operates. They've been trying to update the money laundering laws for two decades. And it's like out of sight out of mind sometimes. And I think we have a really unique moment to press for both here. And the irony is some Democrats who are opposed to market structure, you know, because of
Starting point is 01:06:55 abuse, potential abuses, who are opposed to the crypto industry. They cite abuses, they cite fraud, they cite speculation, they cite Trump coin. And I get all of those criticisms, but I'll tell you what,
Starting point is 01:07:07 had the market structure bell been passed, that would have answered a lot of those questions. The irony is if you would have had the market structure bill, you wouldn't have had a lot of the blowups that you had in the past several years in this industry. Is crypto truly coming home to
Starting point is 01:07:22 America? We went through a period where crypto is being pushed offshore. We've heard over the last year that some crypto founders feel like they can come back to the states now. Maybe you actually have an office state side. Are you seeing more and more momentum there with some of this positive regulatory movement? Or are you still seeing momentum around places offshore, Singapore, etc.? I think, look, everywhere that you're going to want to develop is going to have some rules that you're going to have to follow. When I hear founders who say there is no regulatory, it's often not going to be the
Starting point is 01:07:57 or that there is no regulatory regime whatsoever. Sorry, Bologi, if you're watching. But I am seeing that onshoreing a bit. We were kind of seeing the offshoring in an unfortunate way, but it's not only regulation that matters. It's hiring top talent. And certainly there's top talent right here in Silicon Valley and other places in the world. I mean, you mentioned Singapore, Singapore has top talent to be sure.
Starting point is 01:08:22 But, you know, there's a lot going for the U.S., so we're still very optimistic. And I don't think it, but we were getting to a very dangerous point with the crypto industry, had the likes of Gensler and others like him been left kind of to just do this. Now, fortunately, the courts were pushing back. So it wasn't a partisan issue. It was just the courts were starting to say, no, you've gone too far. I mean, I lost track now. I literally lost track of how many federal courts of all political persuasions and appointments
Starting point is 01:08:51 ruled against Gensler's regime and not just Gensler, but others like it, where you had very activist regulators who were really far out of their lane. And you saw courts curbing back on that. So I think that was already, we're in a dangerous spot, but the courts were maybe going to save us, but you don't only want to rely on litigation to save you, of course, because then you've already lost. But I think hiring and talent is important.
Starting point is 01:09:15 I think access to capital and traditional venture, maybe that's a little different in the crypto asset class. But I think also fundamentally what you have going on right here now with AI, particularly in Silicon Valley. And we've talked a little bit at the early stage about some of the synergies between AI and crypto, because, of course, AI creates digital abundance and blockchains are good at enforcing digital scarcity. And I think you're going to see more and more synergies emerge in use cases over time. And I'm not going to say what they are because, you know, we've seen that before in crypto. A lot of overpromising under-delivering on use cases.
Starting point is 01:09:50 So let's just stick to right now we see synergies. There's a lot happening in Silicon Valley, obviously, with AI. We think that's going to benefit the crypto industry. And so in addition to regulatory clarity, if you're a founder, you want access to great talent, you want your visa situations sorted out for your employees. You want access to other founders, depending on what type of company you are, you want access to capital. So I am optimistic about the state of,
Starting point is 01:10:20 crypto in the U.S., but also elsewhere, and we invest in companies. We invested in squads. We've announced that. And I know Steppen, one of the founders of squads watches your show, but Steppen's based right now overseas. And I was just having a conversation with him about how do we get you to come and bring squads to the U.S.? Awesome.
Starting point is 01:10:43 Awesome. I want to talk about the longer tale of regulation because it seems like the stable coin Bill is very straightforward, like the least ambiguity there, then you have the market structure act, and there's a lot more to do there, but I'm sure that there's like riders getting pitched and all sorts of long-tailed things. Like, how much are we actually, like, where does the line end between what we're actually trying to define versus what we're still in the exploration phase of? Because you have NFTs, crypto gaming, there's, you know, predict. There's so many different crypto applications that trying to kind of do them all at once.
Starting point is 01:11:25 Maybe that's the right approach. Maybe these need to be handled like after we've done the technological exploration. But what's your view on kind of the long tail? My view on that is no, because we can't just, we can't have an NFT bell, a bill for a bank contracts or that we can't have specific bills. And if you saw, if you think back to the advent of internet, that's not what we had. You know, we had Section 230. It applied broadly to platforms.
Starting point is 01:11:49 And I think we need something similar here. So on the one hand, I would say it can't be so specific that it's like, okay, if you're a events contract platform, it's this rule. And if you're an NFT plan, because again, we don't even know yet what will be created really at the end of the day. We've seen some early use cases with product market fit. Obviously, chief example of that is Bitcoin. But what if we had had this conversation, guys, back in 2010?
Starting point is 01:12:17 And you said, okay, we've got Satoshi's white paper. there's this thing called Bitcoin, let's pass some crypto regulation. It would have just been for Bitcoin. And that would have been a mistake because then a couple years later on the scene, we have East. And a few years later, we have Solana. So I think what we need to do, so you don't wait for the end state to have any regulation, right?
Starting point is 01:12:35 You don't do regulation by enforcement. I can tell you what we don't do. We don't do regulation by enforcement. You don't wait until the end state of things. But nor do you want to get so with such specificity today and do the, the current state of regulation by the end state of regulation. That you can't do either. And so I think what you have are some guiding principles,
Starting point is 01:12:56 some generic rules of the road. And really, that's all the market structure bill is. And there's enough clarity that you had Democrats vote for it last time. It came up. So it's not like it's so specific. It talks about, and I think, look, I think you have people like Hester Perce, who is SEC commissioner,
Starting point is 01:13:14 has written and given speeches on this of what that ought to look like. what is a decentralization test? And those are some guiding principles that you can kind of look at and apply as you think through this legislation. You know, what body ought to regulate it? And sure, you're going to have some outliers
Starting point is 01:13:31 and new technologies emerge that you're like, okay, does this fit neatly in the bill? No, but we have laws for everything in this country with technologies that develop that don't fit neatly in a particular bill. And that's why we have, that's why we actually have, we don't do regulation by enforcement.
Starting point is 01:13:46 We do notice and comment. We do things like advisory opinions, certain bodies, by the way, do advisory opinions, not judges. And then if all else fails, you do go and sometimes seek Article 3, seek a judicial interpretation. But I think that's, like I said, that's kind of the failure state if you're having to go to the courts. But indeed, that's what was happening because we were getting no rules of the road and we were only getting unfair regulation by enforcement. And I say unfair because Gary Gensler, based. basically picked what should have been the best companies in crypto, the poster children for compliance,
Starting point is 01:14:22 and brought enforcement actions against them, and then the complete spectacular disasters, didn't bring anything. So, until after the fact. And so I think regulation by and- We gotta have you and Gary on the show to hash it out. I'm sure you guys have had some funny conversations.
Starting point is 01:14:40 Thank you so much for helping out. Yeah, thanks guys for having me. We'll talk to you soon. Have a good rest of your day. Cheers. Bye-bye. Up next, we have Justine Moore from Injuris and Horowitz. Incredible map knowledge dropped a fantastic market map all around AI image, AI video models.
Starting point is 01:14:58 We're going to have her take us through it. Welcome to the show. How are you doing? Can you hear us? Can you hear us? Hello? Oh, I can hear you guys now. Sorry.
Starting point is 01:15:09 There we go. Hey. Hey. I was saying to John, when you dropped your new market map, I was saying, you know, it's a great sign of respect. Yes. in our culture to drop a new market map and come on the show. So we're on credit. I've been incredibly bullish on market maps.
Starting point is 01:15:23 I find them extremely interesting. And I think they got a bad rap a couple of years ago. But I'm glad that you've stayed the course and you're pro strongly pro market map. Yes. The people love market maps. It's like you do guarantee a popular tweet if it has a market map in it. Absolutely. And I think people got kind of sick of like, oh, like we know the playbook.
Starting point is 01:15:41 We've seen it, but there's a playbook for a reason. It works. Yes. So yeah, take us through the latest market map. What are you tracking? How did you decide what to divide it up into and and what what kind of inspired this moment specifically? Yes. So I mostly do AI creative tools here at A16Z. So I spend like all my time testing all the image, video, audio, etc. And obviously the past few months in particular video has been like the thing. There's been like V-O-3, obviously, which was a massive moment with adding the audio for the generations. and Hedra around the talking characters,
Starting point is 01:16:17 the new Minimax model, the new bite dance model, seed dance, which is in the arena already outperforming V-O-3. So it just felt like a good time to refresh sort of what's going on in the video space. And I kind of formatted this market map, just thinking about more from the perspective of a creator, like less in terms of the go-to-market of the company, more just like if you're a person trying to create a video with AI, where would you go for these different use cases? So there's first sort of the model, like the foundation model companies,
Starting point is 01:16:50 where it's either text to video or image to video. Most places do both, where they actually take your input, have their own proprietary model that generates the video for you. So that's the VOs, the clings, the runways, the PICAs. And then there's also now this emergence of what I call like multi-model apps,
Starting point is 01:17:12 places like CREA and Flora and Visual Electric that enable you to run a bunch of models in one place. So like if you want to take a single prompt or a single image and see what it looks like in five different models super easily, you can do it somewhere like that. And then the other side of this market map is sort of like what happens when you add speech and talking characters. And so some folks do that by like generating a talking avatar from an image where you can eventually have the person move and other folks do that by taking like a video of a person and then applying lip sync over it and then syncing the audio. So that's sort of the distinction between talking avatars and lip sync. Yeah, it's interesting that you're in the consumer group because I can imagine that a lot of the talking avatar companies wind up selling to corporations that want to vend in talking avatars,
Starting point is 01:18:04 for example. Are you seeing a lot of that or like I guess how rigorous or stringent are founders about like, hey, we are trying to build a consumer app or we're just building a cool technology. And it might land as a consumer product, but it also might land as a B2B play. Um, most people are not at all rigorous and often don't even know at the beginning. So what we actually saw with the first generation of AI video was it was only researchers making these like magical models. And they had no idea what the use cases were going to be.
Starting point is 01:18:34 They all just put like a text prompt box in front of the model. And then you got an output and like a big company and an individual were using the exact same interface. Now I think we're starting to see more at like what we call the app layer, which is essentially like, how do you productize this? How do you create workflow? And therefore, how do you go into two specific verticals? Maybe an example of that is all of the like standalone video ad creation products. So things like Creatify or captions where or Hey Jen has a product for this too, where you can literally just like paste in a link to your Amazon or Shopify store. It will pull all of the info about your product, your logo, your brand, and it will generate a talking
Starting point is 01:19:16 head avatar, like holding your product and describing it. And that's something that like a V-O-3 or a cling, the general video model companies won't do today. Yeah. Where are you seeing the strongest, like, low-churn adoption of these tools? Because just personally, like, V-O-3 was the thing that got me to subscribe to Google Pro Max 25, which we can go into the names and how difficult is to access these. But other than that, I haven't seen that many where,
Starting point is 01:19:49 like we've seen the ASMR Stormtroopers or something, but it hasn't been clear to me that someone's building like the next Pixar and they're actually thinking about it like Mr. Beast and they're like, I'm building a studio. This is a business. I have ad integrations and I have a content schedule. It's very much in like the testing phase. We see the studio Ghibli moments go viral.
Starting point is 01:20:06 So where is like the true? true long-term value playing out right now? Okay, on the content creation side, where we are at right now is actually there's a bunch of content agencies. Like, you know, there's a bunch of Wonder Studios, Dream Studios. There's probably like 20 of them now. One called Paracosum. That's really cool.
Starting point is 01:20:29 And these are people who are just early adopters of the tools and they're getting hired by brands and ad agencies and entertainment companies to use the tools for them and make content. I think the problem now and what you're describing is like the people at Pixar would have to know how to use the AI video tools and how to set up the workflow in order to create their next movie using AI. And we're not yet at like the tools aren't mature enough and we don't have enough people who are working at those entertainment companies who know how to use the tools that it's primarily being done with these external AI native agencies or contractors today. I think like one of the first AI IP we've seen is the Italian brain rot character.
Starting point is 01:21:09 I don't know if you guys. No, I don't know this. The Italian brain rock characters are huge. So I can't even say the names here because they will sound ridiculous. But it's people basically making images of like an animated talking baseball bat and like a ballerina whose head is like a cup of cappuccino. Okay, okay. And a shark who wears sneakers. Okay, but they're starting to build like a cinematic universe.
Starting point is 01:21:31 Oh, it's massive. Yeah. Accounts have like millions of followers. The world isn't ready for Italian brain rock. So is it, is it like decentralized in the sense that like I could just go and participate in this like broader trend? So yes and no. I would say there were a couple accounts that originated the first few characters. And then other people started participating using the hashtags remixing.
Starting point is 01:21:56 And then the good, the characters that were good that came out of that sort of bubbled up to become part of the cinematic universe. They have bombadiery, bombadiro, crocadilla. which is a bomber. He's a crocodile plane that shoots bombs. This sounds like, yeah, yeah, super viral. Yes. The kids probably love it. That's wild.
Starting point is 01:22:21 Before we go into more of the consumer side, talk to me about some of the more like niche, like B2B use cases because I remember when like GPT 3.5 and we got four, GPD 4 dropped. There were still like a lot of hallucinations, but you saw companies. that were just like, yeah, like, sure, it's not incredible at writing poetry, but it's amazing at just like converting this messy text to JSON, and they were all of a sudden just running tons and tons of queries. And so I would imagine that in a, in a video workflow, things like what runway was doing in the old days of just like green screening or the stuff that like artists aren't going to
Starting point is 01:23:02 really get upset about because it just feels like a better, more advanced tool, are a lot of these companies building tools like that or is all the focus just on like let's one shot the next Oscar film? Yeah, it's a great question. There's a decent amount of vertical focus. I think also like it's very hard for this for startups. Like if you're not a Google to or an opening I or whoever to play in the game of like let's train the largest one shot best video model. So a lot of them are focusing on verticals like Luma, which is a company we've invested into this really cool tool where you can upload like a 9 by 16 like iPhone style video and you can just say extend and it just basically like outpaints around the existing video and makes it look like so you can just change the
Starting point is 01:23:45 dimensions of your video really fast yeah or there's more of just like a practical tool but super useful for a bunch of creators that are filming vertical content probably and they want to distribute in a horizontal format so they just do that yes exactly that makes a ton of sense or something like higgs field that it has all these really special effect like motion loras essentially. So you can take like an image of a car and just say like, this is like, here's a template of what a car explosion looks like, make this specific car explode. Okay. And then on the B2B side, we've seen a lot around like how do you scale marketing or L&D or
Starting point is 01:24:20 like executive presence type content. So like, you know, tools like descript now allow you to take a video of someone talking and then change the word that they're saying by changing, like cloning their voice, having them, the voice say the new, word and then doing a new lip dub. New lip sync, yeah. So you could have your CEO sending what looks like a personalized holiday message to like every single customer or something like that. Yep, or maybe something worse with a fishing scam, but I'm sure we're going to see
Starting point is 01:24:47 at some point. What do you think the long-term ambitions of companies like Google with VO and bite dance with their model? What do you think they want out of this category? They obviously have a massive edge. I saw a niche was posting a about Google's edge or YouTube's edge around IP with VO, you can generate basically basically perfect.
Starting point is 01:25:12 It's crazy. The Disney thing, is that like a real deal? Or is that just a beneficiary of like some sort of relationship? Yeah, then I want to get a sense of, do Google and bite dance? Do they want to be developer tools that just vend into a bunch of these platforms? Do they actually want to own the end customer?
Starting point is 01:25:28 What is this market? Is there a generalized market in the long run of just generalizing? just generating funny videos for the average consumer, or is it going to all be verticalized out where I want to generate ads? I maybe want to generate, you know, customized messages, but I want to understand, like, this is a good overview of all the ways you can generate content, but like how does the market structure evolve? Yes. Okay, on the IP question, I have not talked to Google's IP lawyers, and I'm not an IP lawyer, but my understanding is Google. But this is legal advice, right? Yeah, exactly.
Starting point is 01:26:03 And financial advice. Our compliance team is going to love this. Yeah, they're going to love it. Sarcasm. You can, I think my sense is basically, you know, when YouTube came about, it was suddenly like all this IP content is on the internet and Google cut deals with a bunch of the IP owners about essentially what can be posted on various Google properties and if that content gets monetized, how it ends up going to the end rights holder.
Starting point is 01:26:27 And so that's sort of the working theory right now about like why V-O-3 can generate IP content and not get sued when a lot of other people are struggling with that. In terms of the market dynamics, it's so fascinating the question around, like, Google and ByteDance and eventually, I think Facebook I hear is going to do more in video soon as well, like why they're doing it and what their strategy is. I think, first of all, like, if I'm one of those huge consumer giants,
Starting point is 01:26:55 AI is such a massive shift in consumer behavior that, like, you want, if you want to own the interface to consumers, you probably want to own text, image, and video generation as well. And they have the resources in terms of data, like YouTube, for example, is a perfect example of this. They have a ton of compute. They have a ton of money, and they can hire the best researchers to build the best models. I think the question, as you sort of alluded to, is like, do they sell those models via API and let other people build the consumer experience on top of them, or do they own the end-to-end consumer experience?
Starting point is 01:27:26 my honest take on it so far has been like it takes so long in the big company product teams to get stuff down and get new products out that like the model teams are just shipping the models and like pretty basic interfaces like Google Flow and then the product teams are going to figure out if they can catch up with some kind of cool new consumer app later. Yeah. Yeah. Yeah. My question is like how much what will the market actually look like for the average consumer wanting
Starting point is 01:27:56 to generate images and video, or will it just be something that people default to chat GPT, because maybe they already have a subscription or they're fine with the free tier? And it doesn't end up. There ends up being a bunch of different applications on the enterprise, B2B side, but then not so many, like, you know, core consumer subscriptions on just, like, cool videos, pictures, et cetera. I mean, it seems like it's a killer, killer moat for Google Cloud platform to have V-O-3 as an API, even if Google can't figure out how to productize it fully.
Starting point is 01:28:28 It's like they do seem to have a real moat. I want to get into that about YouTube is obviously an incredible training data resource. You mentioned that there was another company that just surpassed them. Was it 10 cent you said? By dance. That's right. So I have a question about that because obviously with CodeGen, GitHub has a lot of public repos that people can probably just scrape.
Starting point is 01:28:53 It's also just not that much data. You can probably fit it on a couple hard drives, maybe sneak it out the back and go ahead of flight and train somewhere in Malaysia or something. You can't do that with YouTube. Like it's just too much data. And so my question is how durable, how much should we be thinking about a durable data mode in video generation for YouTube? Because it seems like something that they could really like clamp down on and would give them a durable advantage. But I don't know, there's so many other, there's so many other ways to attack any of these model developments. Totally.
Starting point is 01:29:29 There's a lot of different options. So there's a couple parts of the data question. Yeah. The first part is like, what do you own versus what do you scrape? I mean, we've seen companies like Open AI will scrape YouTube as well to train their models. Yeah. I think Bight dance also like, you know, here we think of YouTube and Facebook and whatever here in the US, I mean, as being the big host of content. But like there's all these massive companies in China like Bight Dance who have their own.
Starting point is 01:29:52 have their own user generated content on like their version of TikTok and their version of YouTube and I'm sure there's reposts of American videos over there. So it's not like even has a unique flavor probably can generalize pretty well, right? Totally. Though, yeah, like I was one of the very early users of all the Chinese video models when you still had to access them on Chinese apps with Chinese phone numbers. And they were definitely very good at things that were more China oriented than the U.S. models. That makes 10 sense. Oh, okay, the other thing that's important to mention on data is in video in particular, it's not just the volume of data, it's also the quality of data and the quality of data labeling. Because essentially, you can't just feed a video into a video model and assume it can understand what's going on and pull out the relevant info.
Starting point is 01:30:41 You have to have really sort of dense labels is what we call them or super detailed captions about like, this is this style shot, shot from this sort of camera. The camera is coming from this angle. This is the sort of character. This is how the character is interacting with the background. And that quality data is what drives quality in the video models. And China has really benefited there because there are so many more PhDs than there are here. And it's much cheaper for these companies to hire them to do these dense labels for the video data. Yeah.
Starting point is 01:31:13 Well, how does Mid Journey fit into all of this now? It's such an interesting company because no venture dollars, this like, behemoth kind of quietly hiding in a Discord server still. I saw some examples of video. It looked fantastic. It seemed like they hadn't added audio yet. But how do they fit into the whole piece? Because it seemed like early on they developed a really great feedback loop for the data
Starting point is 01:31:37 that maybe wasn't happening with some of the other model providers. Yeah. So the Mid Journey model came out this morning really conveniently like 10 minutes after I put out my market map without Mid Journey video because it's not yet available. I was just playing around with it too. It's really cool. They do image to video. And so they don't do text to video, which is actually sort of easier.
Starting point is 01:31:59 They can start with the super high quality images that they generate on the platform and then animate those. I think they have like a low motion and a high motion setting. From what I've tested so far, it's better as sort of like a low motion, scenery, environment, light interaction type thing. Like you have a photo of a person and you can then animate sort of. rain and wind and them walking slowly. And it's not as good at like what I call physics-heavy world model type things, like two cars running into each other and exploding. That sort of thing requires a very, very large and costly, usually like text-to-video model
Starting point is 01:32:39 that is more difficult to train. Whereas mid-jurney, I mean, I have no idea how they did it. It's a great model. They could have taken one of the open-source image-to-video models and fine-tune it on all their own data. Yeah. Yeah, I've noticed V-O-3 is really, really good with some of that physics stuff, but it still gets confused. Like, if a car is driving away, all of a sudden, you'll be looking at the front of the car and then the back of the car and it'll get kind of mixed up. But, yeah. Are you, as all these different models have progressed, I always remember
Starting point is 01:33:09 Brod and Trevor McFedries and just how early he was to what I think will be this, like, new wave. Is that little Michaela? Yeah, Lecala. which was like basically a CGI influencer. So very early, I think we're going to see a lot more of this. And we've seen some of this to date, but do you expect that to be kind of like a new, a new, like how bullish are you on sort of like entirely AI creators getting real adoption, following, following is turning into real businesses? I'm sure you've followed a bunch of them already.
Starting point is 01:33:46 Yeah, I'm personally super excited about it because it kind of separates the content from the character. Like now, before AI, if you were on Instagram, you were both the character and the person coming out with the content. And so you had to look in a way and present yourself in a way and talk in a way that was interesting to the Instagram algorithm. And now it's like anyone with a good idea
Starting point is 01:34:08 can create a compelling character. And so I think some of those are human characters. I've already seen way too many examples in my Reels feed of only fans models who promote themselves with AI avatars of themselves now, which works shockingly well. There's some photorealistic human influencers, but honestly, some of the more interesting ones are things that could never be influencers before AI. So there's one called, like, Raccoon stole my iPhone, and it's an AI raccoon influencer.
Starting point is 01:34:38 There's like AI Capi Bera influencers. There's like mystical creatures, like all of these things that just come out of people's imagination. competing for Mindshare with Instagram pet pages, you know, dog pages, things like that. Did you have a reaction to Fountainhead? It was the, or sorry, Mountain Head, not Fountainhead. Oh, yeah. Mountain Head, the movie, the core overarching theme was that basically deep fakes or AI generated content had gotten so good that it was causing global unrest. Did it resonate at all? It does feel like I now have, you know, multivalable.
Starting point is 01:35:16 multiple times a day. I'm seeing content online and and it's like getting I we're both in the community notes program so it's like you see content getting community noted. One person says it's not real. Look at this link. It was this image. They redid it. Another person says it's real. Look at this thing. So it's like I just assume that everything's fake and made up unless I see it, you know, with my own eyes. But I'm curious if you if you, if it resonated all with you. So I've not, I largely consume AI Slop, so I have not seen. I should watch it soon. You should watch the movie, the motion picture on Slop.
Starting point is 01:35:51 Yeah. Once they have that, I will watch the full film. But it's so interesting. We talked about this a lot, actually, with audio models, with the last election cycle. Because video, I think, wasn't there yet to have convincing deep fakes. But audio, like, there were way less cases of, even though you could make really realistic voices, cloning candidates and saying things that weren't. true. There were way less examples than we thought of that actually like impacting any, any election in any sort of meaningful way. And I think part of it is like things like you mentioned,
Starting point is 01:36:22 the community notes program where like you have sort of citizen watchdogs on various platforms saying, this is real, this isn't real, running them through various sort of AI detectors. But I also think like people are starting to develop more skepticism around everything they see online and whether or not it is real, which is probably not a terrible thing. Yeah, I had this take that After Effects would be more impactful on the election than AI video. Because, like, you can just show a clip of a burning building from 2020. And it's real video, but you recontextualize it and say, oh, you know, the capital's burning or something. And it's from years ago or just, you know, speed up a video, slow it down, edit it out.
Starting point is 01:37:04 They would do this with various politicians, you know, cut out the ums and us and they'll sound sharper, add a bunch of gaps. and all of a sudden they sound like they're slower. Yeah, it even, you know, we're here in L.A. and when all the imagery was coming out of the protest from a couple weeks ago, it was like burning Waymo's. Kind of looks like something you generate with V-O-3. Totally. Just because it was so symbolic and just such a crazy image.
Starting point is 01:37:29 And then like make an image of a guy with a Mexican flag, riding it doing burnouts around a car that's on fire. And it's like, that looks like, you know. And even just the way that was photographed, there was like, It looked like all of Los Angeles was engulfed in flames, but it was really like one crazy block with a bunch of different angles. Yes. And then a bunch of different posts. And you drive around and you'd be like, oh, there's not that much going on.
Starting point is 01:37:51 See, that's the other interesting thing is like even wheel footage can be manipulated. Totally. Like any kind of story can be manipulated in a way, like AI or not. Yeah. Are you seeing, I think, like, you know, there's exciting companies like WorldCoyne, you know, doing like proof of human. Are you seeing any infrastructure players trying to. to do anything on like content verification side and like trying to create some sort of mechanism to prove whether something was like authentic you know actually shot on an iPhone right
Starting point is 01:38:24 you know proving through the metadata and some type of like public setting is there is there any pitches from from that side yeah so most largely honestly today that is come in two places one is the model companies themselves will often watermark the content in some way like the V-O-3 generations has little V-O-3, 11 labs, which just the audio. They actually have a site where you can upload any audio, and it will tell you if it was generated with 11 labs or not. That's cool. Which is pretty cool.
Starting point is 01:38:53 The other place we've seen development there is for, like, prominent individuals, like, you know, celebrities or someone who's, there's, like, value behind their brands and who potentially even might want to monetize it in the age of AI. Like, if you're an actor and you suddenly don't have to, you know, film, go, fly back to LA when you're filming a movie in Australia to tape like five ads for some cell phone brand and you can have your AI avatar generated to do it instead and it looks just as good. Like you might actually want to, you know, have some licensing company that owns your AI licensing rights, whether it's your traditional talent agency or not, who can manage that for you.
Starting point is 01:39:32 Yeah, totally. Very cool. Well, thank you so much for stopping by. We can talk for another hour. I have so many more questions in our doc. But we'll have to have you back. So thank you so much for stopping back. Thanks, guys.
Starting point is 01:39:41 We'll talk to you soon. Great chatting. Have a good one. More breaking news. Invita to drop humanoid robots that will produce NVIDIA GB300 chips in Q1 of 2026. Nick says wholly based. That is so close. Foxconn talks to deploy humanoid robots at Houston AI server making plant.
Starting point is 01:40:01 Wow. That is extremely close. I don't totally understand this. What does that mean? Foxcon has been training the robots to pick and place objects and insert cables. Yeah. I don't know if this is marketing. It feels like we've had, we've, we've asked a bunch of robotics experts about
Starting point is 01:40:19 humanoids. Yeah. And so far I haven't got a, I, I don't have the confidence that, that this is actually a super great use case for them. It's just the definition of like what is humanoid because you go to a, you go to like a Ford F1 50 factory and they have like massive robotic arms like moving windshields around, right? Like it's like you could anthropomorphize that by like spray painting it pink and putting some hair on the on the hand and being like it's a it's humanoid now But like you could like retrofit every bicep definition totally like like Amazon has like tons of robots sliding around you could put googly eyes on them and be like they're humanoids now and and you get maybe get like a stock bump but like there's clearly things that are happening in the AI server assembly process that are using robotics obviously whether it's even just like conveyor belts or or you know the the three axis pick in place you know pick it up put it over
Starting point is 01:41:22 here that type of stuff just going to humanoid is just it's like well will it have five fingers or will it have a just a grabber will it have legs or will it have wheels like it could just be sitting there because for a lot of these pick and place jobs you can just have the the humanoid sit there with a single arm mounted to the ground because the stuff comes to it. And so then you're just kind of in a, okay, we're in the arm business now. It feels, it feels like it's a little bit wrapped in marketing lingo, but still cool that more companies are making humanoids because it does seem like a cool form factor that hopefully people will break through and get there. And this seems like, you know, a step in the right direction in the
Starting point is 01:41:58 sense that it's a very defined task. I think when people think humanoid, they think some, like, my new touring test is, is humanoid robotics will will be here and when they can put up a six-minute nerve-griggering time in a manual. Yeah, gated manual. In a gated manual. Because at that point, they have to not just be a self-driving car, but they have to be able to, you know, negotiate the wheel and the stick shift so efficiently and so quickly that they are truly performing. Yeah, and a manual.
Starting point is 01:42:40 And a manual can be weirdly like probable, probabilistic, right? And that like you're like, you know, you can move the synthesize a lot of data. Yeah, it's not, it's not like, you know, perfect system, right? You're not going to, you're not going to put up a sub seven minute Nerberering time with a Joe Biden walk. That's right. You're going to have to be moving fast. Those actuators are going to have to be high speed. So, yeah, I don't know where all this goes.
Starting point is 01:43:06 But, I mean, exciting to see that they're that they're. at least doing work on it because it seems like an important it's it's clearly an important path in the tech tree we don't know how relevant it is to other to other formats but uh cool to see a lot of money pouring into the sector uh from very big companies so fox con will be announcing their robots in november and then deploying them shortly after yeah in our year 2026 i mean foxcon seems like the right builder for this uh unitary is is already like feels like it's scaling up to the point where like Unitary robots should be usable in certain locations. Like they're not generalizable yet, but they're certainly if you train them on a specific task, they could do that task over and over and over again.
Starting point is 01:43:49 The question is just like, like, you know, do you need five fingers, 10 fingers, 10 toes? Is that is that really like the right form factor or should we be just doing things that are more specified? Because if you're if you're if the whole point of these human robots is just a I server making just assembly, just one one one spot on the manufacturing line could probably be a more specialized robot. But we'll be cool to see. I'm sure we'll see a lot of viral videos about it. It'll be very cool. I invested in a company making robots for data centers. And they intentionally chose not to make it a humanoid form factor, which, and I think a lot of those, the reason behind that decision would also transfer to manufacturing setting, right? Which is like, do you need legs? If you can use wheels. Data centers have the most perfect.
Starting point is 01:44:39 polished floors with like no dust at all. Yeah. Like it's it's the the perfect environment for a wheeled use case. At the same time, you probably need to have a very specific actuator for like unpluging and plugging the cable back in. Right. And that's actually like it's pretty hard to reach around the back of a computer and unplug an Ethernet cable and obviously the server X are like designed to be worked on more. But still even the cabling is like very detailed work. And so if that's what they're trying to do, you probably need a specific actuator for that.
Starting point is 01:45:09 our next guest in the studio uh george hots how you doing george good to hear from you what's going on welcome can we hear you oh can you hear me yes yes i can hear you gotcha uh well let's kick it off with something uh simple i want to take your temperature on uh aGI timelines p doom the the easy and fun stuff i don't know what a g i means and i don't know what you mean by doom no is are are these terms just like entirely irrelevant. I mean, now we've shifted to like super intelligence. They're all buzzwords, but at the same time, like, there is, there is an idea of like the, like, I don't know, the, the conversations may be shifting to like the AI generating more economic value than humans. Is that a relevant metric to track?
Starting point is 01:45:59 Machines have been generating more economic value than humans since the Industrial Revolution. Is there some, is there some other metric that we should be tracking? or is it just like irrelevant? You're just talking about like hype. Like, I don't know. I mean, I don't like, I don't know what you mean. Like you can talk about concrete things. Yes.
Starting point is 01:46:20 The term like AGI means nothing, right? Like computers, everything that's a turning machine is a general purpose computer. Is that what you call intelligence? I don't know what you mean. It's a linear regression intelligent. What if it's big enough? The Chinese does know Chinese. Yeah.
Starting point is 01:46:34 Um, what, I mean, what about, uh, uh, uh, your decision to get on a spaceship traveling at 0.9C away from the earth. Like how close are we to that? Are we closer than the last time we talked, which was like a couple of years ago? And it seemed like it was maybe going to happen within your lifetime. Has it moved at all? Yeah. I don't know.
Starting point is 01:46:56 I don't know if I'm actually going to get that spaceship. But it's kind of like in an ideal world what I would want to do, you know? Yep. Just just back away and chill. And don't look back. actually, you can't look back. You can't let them. Never look back.
Starting point is 01:47:08 They're all there. You need the blast shield, right? You need the information shield. Information shield. What do you mean? Oh, that's how they're going to get you. Okay. Right?
Starting point is 01:47:22 I mean, okay, so like here's the way you can think about AI, right? Yeah. Imagine there were 10 CIA agents assigned to you. And they're running at 1,000 X real time. So they're like hyper-fast CIA agents that devote their entire lifespan to your day. And they're trying to manipulate you. Maybe to get you to buy things,
Starting point is 01:47:42 maybe to get you to vote for a certain guy, whatever. But like that's what you're going to be up against with AI. What we're currently building. What if you think about the biggest companies in AI, what they do is advertising. What advertising is is just manipulation of humans. So you're going to have a team of CIA agents thinking about you and trying to manipulate you at all times.
Starting point is 01:48:02 And now you see why you want to head away at the speed of light, right? even CIA agents can't be bad. Is there is there some world where there's like a capital war and I'm paying for a more powerful ad blocker? Yeah, I mean, that sounds good. Like another question is kind of to say like, okay, if you think that you either think that current like capital accumulation dynamics are going to continue and that the rich are going to continue to get richer. And if you believe that, the question is kind of, well, how many people are going to survive in the future? How many people are going to have any modicum of independence? Right?
Starting point is 01:48:39 Like, you have some far AI people who think that there's going to be a singleton, right? You think that there's going to be literally one, right? You know, some people maybe think it's 10. Some people, 1,000, 10,000. Some people think that all the humans will get to continue to exist as independent entities. Are they already independent entities? That's a question, right? I don't know.
Starting point is 01:48:57 That's a question. I mean, if you were trying to put it in, like, the form of a bat, human population above or below 8 billion in 2030 above I think I haven't just probably but isn't that what the trend says
Starting point is 01:49:13 yeah just go through the trend says I don't think there's going to be any discontinuities to any trends really well yeah I mean I mean at some point but the question is like how far out do you have to go until you start seeing these effects what do you mean by human right what about someone who lies in bed all day watches TikTok are the human
Starting point is 01:49:29 yeah that is odd they kind of drop out of society I think a question that popped up for me is, is this, all this debate about AI safety and what should labs be doing, what should labs not be doing. It feels like your angle is, it should be each individual's responsibility to look after their own safety in the context of AI. Is that at all? I just like this whole like should, shouldn't like, what? I don't know. I'm not a sadistic fuck who wants to manipulate other people like the people in power.
Starting point is 01:50:02 I don't know. Yeah, but I mean, people still look to you as like an example of like someone who might have answers. No, I don't have any answers. Not necessarily answers, just like, you know. But you can buy my shit coin. Here, can I show a shit coin? Here you go.
Starting point is 01:50:20 Just click this QR code and you can buy a George Hots coin and that will give you answers. You will find satisfaction and fulfillment in your life after purchasing a George Hots coin. Is that the end state? We all have our own coins. No, no, no, no. I don't mean it like that. I mean, like, I think that a lot of people are like, they don't really know what they're looking for. And that vacuum is a very, you know, it's very dangerous and it's going to be filled by dumb shit and don't have that vacuum, right?
Starting point is 01:50:52 You got to stand for something, you know, or something? I don't know. Yeah, I mean, do you think that there's a chance that someone is able to take a stand and, and actually bend the arc of AI progress in the way that, I mean, it happened with nuclear, right? Like nuclear development did stall. There was a stagnation in real world build out of nuclear capability on the energy side. Yeah, I mean, there's a few things about nuclear that make it different. So nuclear, even as a weapon, is incredibly hard to deploy tactically.
Starting point is 01:51:27 Right? So if a country has nuclear weapons, they're aside from like a mutually assured destruction idea, they're not all that useful. It's not like you can use a nuclear weapon to accomplish tactical objectives. You know, if you could, I think Russia would have already done it. Yeah. Right, Russia has some tactical objectives they might want to accomplish, but nukes aren't really going to do it, right? I mean, from a pure realpolitik perspective, not even from a like, oh, like a taboo moral perspective. Like, do you want an irradiated pile of rubble?
Starting point is 01:51:55 Like, that's what you're going to get. No, what you want is drones that are hyper-specific and can take out exactly who you want, and can control areas, right? So, like, as a military technology, nukes are not that good. AI is way better. Yeah, but what about it as an energy technology? It feels like the fear, like the memetic fear of nuclear war and total destruction caused a whole bunch of regulation to pour into a sector and essentially a stalling of nuclear energy
Starting point is 01:52:21 buildout. And if the AI doom scenario, whether it's real or not, becomes so momentically powerful that someone's able to harness that and actually say, if you try and build a big data center, we will shoot you, then maybe it stagnates. No? Really think that's the reason for nuclear. I think it has more to do it why we can't do other big infrastructure projects in this country, right?
Starting point is 01:52:42 Like it doesn't have to do it. We also can't build dams, right? And if you look, like, that is the thing. If people think that there's some weird taboo around nuclear, right? But then, okay, look at hydroelectric, right? There's no taboo around hydroelectric. but China leads an installation of both nuclear and hydroelectric and coal and everything. It's almost like they're correlated, right?
Starting point is 01:53:02 So the thing is not there's a specific fear around nuclear. It's like, you know, the U.S. decided that they're a developed country. We're not going to develop anymore because we're already developed. You see the D on the end, right? Interesting. So is that just cultural then when you, like the Malays sets in? Would you expect that to happen to China when they catch up? I don't know.
Starting point is 01:53:23 Yeah. I mean, maybe it's just like this normal story arc of like, you know, it's, it's, I don't know. I think that like you have a real problem when the kids can't live better than their parents. Yeah. So, but I don't have anything more to speculate on that. Do you have more context on China and specifically in like the AI context? U.S. electricity looks like this and China electricity looks like this. Is that all that matters?
Starting point is 01:53:55 Pretty much. Yeah. I mean, that's a pretty good proxy for everything, right? Yeah. Um, like there's two things. There's two things, you know, people are like George, how do you feel about the Trump administration? I'm looking at two things. Yeah. With any administration, I'm looking at two things. Did you decrease government spending? And did you increase total electricity production of America?
Starting point is 01:54:13 Those are the only two numbers I care about. Those will capture everything. Why does, uh, why does government spending matter? We were joking that, you know, Trump must be extremely AGI pilled if he's running up a massive budget deficit. What the hell is AGI? I don't know what this is. Like in this formulation, never seen it. Never seen it.
Starting point is 01:54:33 In this formulation, it's that it's that numbers. Yes, yes, yes. But it, but it is an extra lever on labor and capital and it creates more GDP that they can be taxed to pay down the increasing amount of debt. Super Excel. Yeah, super Excel. What is what is super Excel to do? That normal Excel doesn't. Let's give it up for better Excel.
Starting point is 01:54:55 Yeah. Yes, yes, we need that. Excel 2.0. The thing is Excel was the final piece of software, but in order to add another, you know, $100 trillion to global GDP, we needed to like kind of rebrand it. And so now we get AGI. GDP is the complete, it's the biggest bullshit thing ever, right? Like, I always joke with my friend and I, that we're going to start companies and be billionaires. I'll tell you how we're going to do it. Okay. I start a company. He starts a company. We both write contracts to each other. Right? Like, I'll buy
Starting point is 01:55:27 something from him for a million dollars. He'll buy something for me for a million dollars. We'll just do this real fast. We'll keep passing the money back and forth. Whoa, look at our revenue. Wow, that all contributes to GDP. Wow, we're billionaires overnight, right? Yep. Like, like, and that's, my argument is the economy is just that with a lot of extra steps, right? You can't use services. It's not part of GDP. This is complete nonsense. Right? You can't have services sort of like literally, literally. You take the steel out of the ground. You grow the corn. Okay, that's GDP. But is, I mean, if, if that GDP, He is fake is not the debt is the deficit not fake like is government spending less
Starting point is 01:56:01 fake but can't you just tax the fake for the fake money like if you tax your scenario where you're generating a billion dollars in fake money you can't tax the fake money because we're passing the same dollars back and forth the minute you tax it that falls off so fast yeah yeah you can only tax productive work uh is is amd doing productive work right now AMD's doing it right. Yeah, either Nvidia's really overvalued or AMD is really undervalued. It has to be one of the other. How does it all play out?
Starting point is 01:56:34 Like what does AMD actually need to do to get back on track or realize their potential? NVIDIA needs to stumble. I mean, it worked for AMD in Intel, right? So AMD ended up beating Intel in the entire, like no one would buy a data center, Intel, CPU, anymore. Yeah. And it's just because, well, you know, they stumbled and now Intel owns that market. So, you know, AMD just sits there in second place.
Starting point is 01:56:57 Okay. They'd be in a better second place than they were a few years ago. Yeah. And then when Nvidia stumbles, AMD is like, oh, hey, we're here. Is DGX Leptone, like, they're cloud offering a potential stumbling block, or is it, or is it the right move for them? I don't know what that is. What's on the Nvidia cloud shit?
Starting point is 01:57:16 Yeah, exactly. Cloud's dumb. You can break AI down basically into, like, there's, like, five tiers, right? Like, at the base level, you have, like, electricity and data centers and land and, like, things like that. Tier 2 or like DSMC, ASML, Samsung Intel, right, Fabs. Nvidia, AMD, OpenAI, Anthropic. And then on top, you have, like, completely worthless things like Cooter and WinSurf.
Starting point is 01:57:39 You know, these character AI, all these people who think, oh, whittia up, we're going to get the ARR. I know that worked to the web, it won't work for AI, and I can go into why, but it's kind of boring. I want to hear why. Keep going. Keep going. Basically, okay, so like, here's the difference between AI and web. Would you want to run a service like Gmail? One server can serve 10,000 people easily, right? And there's no demand for, like, better Gmail, right?
Starting point is 01:58:02 It's not like I can click and get like, yeah, you can buy Gmail pero and I'll have a few things, but most people don't really care, right? There's no limit to the ceiling of how good you want your AI to be, right? Or how fast you want your AI to be. Maybe there's a limit to the speed, but like when you're at like a thousand tokens per second, I want the biggest model in the world, right? So there's very little limit on that. But suddenly you can't serve 10,000 users from one server anymore.
Starting point is 01:58:25 And the whole dynamics of the web, the whole reason some of the value aggregated to these end players, and they still didn't aggregate to the cursor in the winters. They aggregated to the opening eye on the Anthropics, right? Nobody, nobody who built like an email client survived. They all got eaten up by the tier fours of the web, right? The Google's the Facebooks, all of these like app providers, right? Where's a Zinga today, you know? Like this already happened, right?
Starting point is 01:58:50 People just don't remember. Where Zinga? Oh, Zinga's going to be the next thing, man. Like, no, it's not. Facebook 8. all of that value, right? Google ate all of the value from all the people building on top of Google. So the Tier 4s ate all that value. Yeah. So Open AI, Anthropic, will eat all the value from the cursors in the wind surface of the world. They'll acquire some of them. They'll compete with some of them,
Starting point is 01:59:08 right, same as you saw on the web. But I argue that the Tier 4s aren't even going to have value. Because the tier 4s, this ain't the web. This ain't where you can have one server, lots and lots and lots of people. You know, I'm running 03. I'm running. You know how much I cost Open AI every month? I pay the $200 a month, and I cost him a lot more than that. You can now click on Codex. Yes, spin up four nodes. Yeah, why would I not click four? It's not my computer.
Starting point is 01:59:37 You gave me the button. Hey, I'm just using it. George Hots, single-handedly bankrupts, $300 billion company. Is there no value in just being the front end to AI applications to be like the front door, just the default button? because we see these models kind of go back and forth in terms of benchmarks or what's hot, and there isn't as much customer churn as you would expect, because people are just kind of like defaulted into the app that they installed whenever.
Starting point is 02:00:08 And so even if Gemini gets better in terms of the actual performance metrics, people don't switch from Open AI to Google overnight. It's so negligible. You gotta make something 10x better, right? You gotta make something 10x better. So like, this whole game is Open AIs, unless they stumble. Sure. I'll not switch you to Gemini because it's 20% better and I have downloads a new app and
Starting point is 02:00:30 think about a whole new thing, right? No one's going to switch. Is there, is there a chance for a company to kind of come out with something that's 10x better with an algorithmic improvement or is it just a race for scale? Like, what could actually be that next? It felt like GPT 3.5 when they really broke through with DaVinci and then 4 oh or and then 4. Like it felt like this kind of like binary moment when a lot of people realize that this was usable for their daily life, even if it's just a Google search replacement or whatever, write a poem or whatever, like a 10x, what you're describing like a 10x improvement feels like that kind of like qualitative binary shift. Is that possible with just scale? Or is this
Starting point is 02:01:12 something that we need a different model for? I don't know. I don't know. I would bet majority still on. Like these big labs are also attracting the talents. But it is also like, it's pretty commoditized a lot more so than like Google search. Like you can look at people track how far open source is behind. It's not that far behind. Yep. So, no, I don't know. I think this game is mostly going to be chatypts.
Starting point is 02:01:42 I think Elon's aware of this too. That's why he's trying to go 10x bigger with the data center. Yep. We'll see. Maybe it'll work. You know, there's someone to bet on. Anthropic, I'm not that bullish on. But maybe.
Starting point is 02:01:56 You kind of predicted the pre-training wall, but that's not a refutation of the bitter lesson, and we're going to see similar scale play out and reinforcement learning, or is there going to be something else that we're building the big data centers for? There's something that we don't understand in terms of data efficiency. So, like, when you think of how long it takes a GPT to learn to talk, like how much data it takes, it takes like terabytes of data. In order to make a GPT talk like a normal person, it takes terabytes of data. Whereas a human trains on megabytes.
Starting point is 02:02:29 How is it that if you take all the texts that you've ever heard in your life and you put it to whisper and you transcribe it, it's going to be a couple of megabytes. 10 megabytes, maybe 100 megabytes. So humans have this 1,000x data efficiency advantage. And we're going to have to fix that if we want like reinforcement learning to work, especially like reinforcement learning that you want to do in the real world. Humans can do, humans can learn from very few samples. Yep. And yeah, I think that like it might be okay if these foundation models train unsupervised on lots and lots of stuff. But, yeah.
Starting point is 02:03:04 Is that, is that something that somebody's working on just like a new more data efficient algorithm to drop into the pipeline? Or do we have any like leads there? because it feels like right now we're going down the path of like reinforcement learning with verifiable rewards and we're going after like individual business use cases that are increasingly long tail. And that could be kind of like valuable, but it doesn't feel like the breakthrough that you're talking about. Like has there ever been a breakthrough? Right. Like people think GPGs are a breakthrough. Well, they weren't. Like if you watch the, the world, it was just, it was all just smooth curve. But, but what I will say about AI scaling laws. Oh man. You see like people get.
Starting point is 02:03:50 excited about AI scaling laws, but here's a pitch that'll kill your excitement immediately. Ready? AI scaling laws. You can put in exponentially more money to get linear returns. Yeah, exactly. Do you believe that the real value is investing in in humanoid robotics then? Have you heard this theory? So, so I mean, if you put exponential more money into humanoid robotics, assume,
Starting point is 02:04:20 that they work and assuming you can you can you like if you make times as many robots you get 10 times as much output anyone anyone who wants a humanoid robot has never worked in a factory in their life okay right break it down what's a human oh yeah you're gonna walk around out like legs right no yeah we've got a laugh track right can you show me a robot arm that's capable of putting a screw in something probably yeah screw in the thing. Yeah. No, no, no, not like you carefully jigged up the screw and have a screw dispenser.
Starting point is 02:04:56 Like the way a normal human does it with a screw sitting there and a little bucket on the thing and it picks up one screw and it puts it in it takes a screwdriver. No, we're not close but also it feels like we're not far. It feels like that's what? I feel like human I feel like human-oids are this interesting sort of like space because a lot of smart people just say like here's the 20 reasons why they won't work and like why we shouldn't build them but then so much capital and so many different teams are trying to make them work that they very well might work for some things and like they just humanity might
Starting point is 02:05:29 brute force it because we saw it in a sci-fi movie no you know 30 years ago why why why why are we cut on this is as dumb as self-driving cars wise right and nobody learns their lesson and people like kyle vote should be ashamed of themselves like they really should these people who go and raise large amounts of money for another thing that, like, they should know, they should know better, right? He just basically, like, remember in 2012 and Google said that, you know, my, my, my 12-year-old daughter would never have to get her driver's license? Yeah. Come on, that's nonsense, right?
Starting point is 02:06:00 And like, now, okay, they shipped Waymo. It's in a few cities. They're teleopped. Right? Yeah, how teleoperated are they, in your opinion? Is it, is it effectively one to one? It's more than one-to-one. There's probably about, I'd say there's 1.2 operators per car.
Starting point is 02:06:19 But it's not, they don't have a steering wheel in pedals. Yeah. It is an autonomous system that they're probably doing some higher level inputs on. They're definitely like, say, when you can be aggressive, when you should slow down, you know, whether you can turn on the stop sign or not. Yeah. You know, again, like here's the simple reason to know that it's like that, right? There's definitely some teleop at the way most, right?
Starting point is 02:06:42 Yeah. Have you ever seen a picture of that room? No. Yeah, why not? I've always thought it was like an ace up their sleeve because like if there's a lot of pressure on them to say these Waymo's aren't safe, they can pull up, pull the sheet off of the ghost and say, there's actually a human in the loop. Don't worry. It's safer than you thought. Yeah, yeah.
Starting point is 02:07:02 Like, the fact that you've never seen that room tells you that it's way worse than you think it is, right? It tells you that there's way more teleop than you think it is. It was really one person supervising 10 cars. Google would post those pictures all over the place. You don't see any pictures. There's, so Cruz that actually came out in the lawsuit. I think it was like 1.5 or 1.7 humans per car, right? Or vice versa.
Starting point is 02:07:23 Like 1.5 cars per person, right? No, no. Wait, more people than cars? Yes. That's what he's saying. It's still that way. Because an Uber only requires one person. Yes, I know.
Starting point is 02:07:34 Yeah, but so maybe the real innovation is just allowing somebody to get in a car with and not have to talk about the weather or, you know. Exactly. I don't pay more for that. I'll pay more for that. Yeah, but is there any hope that we drive this down and we get to two cars per person, then four cars per person and it starts doubling exponentially and eventually like we are there? I mean, yeah, like it's obviously going to happen, right?
Starting point is 02:07:56 It's obviously eventually going to happen. If you want to see where the real state of the art of unsupervised self-driving is today, right? There's no person with FSD. When you get your Tesla, that's not teleod. You can go press FSD and that's real AI. Yep. And well, you can see how good it is, right? Would I take a nap in there, even for five minutes?
Starting point is 02:08:16 Oh, A, and L? You'd be supertank, right? How are things going on the comma side? Give us the update there. Pretty good. You know, we're on track to, we're on track to be two years behind Tesla. So two years behind Tesla. But, you know, here's why we win, right?
Starting point is 02:08:35 Like, because, like, it's cheap. Okay, so when you think about self-driving cars, it doesn't look anything like to roll out of Uber or Airbnb. When you roll out something like that, you're trying to roll out a two-sided marketplace. You've got to spend tons of money on customer acquisition costs. You've got to make sure that you've perfectly matched that marketplace right away because if drivers aren't getting rides, they're going to leave the platform.
Starting point is 02:08:59 If riders have to wait too long for drivers, they're going to leave the platform. So it's this careful balancing act, but once you get this marketplace, you've got a moat, right? Switching costs are real high. I tried to get everybody to switch at the same time. It's a challenging point. Never doing it. Self-driving cars don't look at anything like that.
Starting point is 02:09:13 Self-driving cars look like scooters. The only thing that it's going to take to roll out big fleets of self-driving cars is capital. It's just strictly a capital market. If I look at a city, I can calculate how many waymills there are. If I want to build my own network and deploy that network and run into lower costs, it's straight up capital. Easiest thing for investors to calculate. Very little risk.
Starting point is 02:09:36 So self-driving cars are going to be this awesome. awesome race to the bottom. It's going to be like scooters. It's going to be like 10 providers of these things for a while. And then they're going to consolidate. Like one's going to do it. But yeah, people are really going to win. What is what's most valuable in terms of developing the next like the next better version of full self-driving? Is it having a lot of data, building a big data center, having a great team to actually design the system? What's most important? Are they all equal? Yeah, all those things matter. Right. I think the main thing that matters more than anything else is just time.
Starting point is 02:10:12 Like we're figuring things out. Research. Infrastructure is getting better. I think a lot of it's just infrastructure. I mean, new companies are infrastructure, right? Like the infrastructure gets better. My coworker has a saying is like, what we do is that we make the hard things easy and the impossible things hard. And that's like the goal of infrastructure.
Starting point is 02:10:36 So you build infrastructure, your infrastructure gets better. And then what was, what you couldn't even dream of doing 10 years ago is now one command today. And today, you know, what, you, you, you, yeah. What's the current use case for most people with tiny boxes? Oh. Is that, that's my design, right? You're not supposed to know. But, I mean.
Starting point is 02:10:58 I sell a computer. It has specs, right? Yeah. So many people want to tell you, and I hate this. I hate this. They're telling you, like, how the product is going to impact your life. But what you use the product for? Oh, my God, who cares?
Starting point is 02:11:09 Yeah. Here's what it is. I'm going to tell you what it is. That's your job, right? I'm not an advertiser. But I mean, our intern wants to build something with a tiny box. I want to give him some ideas. Go buy one.
Starting point is 02:11:23 I don't know. Why do you want to build some with tiny box? I mean, is it good, yeah, it's just a bunch of GPUs in a box. You know, it's a nice little box. GPs in a box. That's got a weight to it. What, um, what robotic form factors are. are you most bullish on? We've touched humanoids. You gave a great review there. We've touched
Starting point is 02:11:40 autonomous vehicles. Sounds like generally bullish, but Capital Wars, race to the bottom, all that stuff. Are there any other kind of form factors that you're thinking about that you are generally optimistic or excited? Arm. Arm. The arm. Maybe two arm. Right? Just two arm. Right? Because I look, look, I run a factory. I run a factory in San Diego. We make all the Connoisse right here. And I can't wait to get a whole lot of robots in there. But I don't need humanoid. I'm just going to stick two arms to the table, and then it's going to grab a comma, it's going to put the screen on the front, it's going to flip it over, it's going to put the four screws in it, then it's going to pass it on. Yep.
Starting point is 02:12:19 Show me anything that's anywhere near that level today. Yeah. What would you do if you were trying to build like a truly multi-purpose robotic arm? The arms are already going to know. It's the off-the-shelf arms are fine. It's all software. Again, it's always all software. Autonomousity. are all softer. Robotics is all softer. But everybody loves to bite shit. Yeah. Like what color are we going to paint the human ones? Yeah, yeah, yeah.
Starting point is 02:12:44 Like, let's have a great conversation about that. Well, you know, we don't want to paint them red because that might scare people in a long term. This is actually the level of stupidity that I see in all discussions about human or robots. Yeah. Would you trade in your legs for wheels if you could? I got that. I'd trade in my legs for wheels? Yeah. This is a question from Aaron Frank, friend of the show.
Starting point is 02:13:05 asking us in real time. You're a wheel guy, then. Like, people had asked me if the wheels are, like, making a statement. I just don't have to have this conversation. What about the SIM to Real Gap in robotics? Like, how is simulated data? You know, you build a bunch of data in Unreal Engine, then you try and transfer, learn it back.
Starting point is 02:13:24 Obviously, there's been a bunch of experiments of that with self-driving cars. Is that a path that we should be going down for the robotic arm development? Yeah. So I think with a lot of SIM to real stuff, the reason people are excited about it is because of that data efficiency gap we spoke about. Right? Like current machine learning algorithms like a thousand X less data efficient than humans. So yeah, you need a thousand X more data, right? If a human can learn something in one exemplar, 10 examples, the computer is going to need 1,000 or 10,000.
Starting point is 02:13:54 Now, do you really want to reset the stupid state of the physical world 10,000 times? You might do it a 10, but you're not going to do a 10,000, right? Yeah. So that's where you want a simulator where you can just click reset and everything's, back to exactly how it was. So I think this stuff's going to play a role, but I think more fundamentally, that data efficiency gap has to be understood.
Starting point is 02:14:15 We talked a little bit about coding agents. We talked about how you're bankrupting, opening AI, by spinning up a lot of different codex agents. What other sort of agenic software are you excited about? Do you expect to, you know... What's itgentic mean? Yeah, basically. bots. It's, it's like what we're calling bots now. Um, but, but, but anyways, like, I just, you know,
Starting point is 02:14:40 I don't know. I don't know. Yeah. Yeah. Yeah. Yeah. No, but, but I think about a world in the future, you know, do you expect to be, I don't know if you're a Slack guy, an I message guy, discord, maybe no messaging at all, just, you know, um, you know, telepathy. Uh, but, but do you expect a world in the future where you're just, you know, a perfect interaction between, you know, human employees and agents or is it you know going to be more like you know you'll do the odd deep research or maybe you send some automated outbound emails or have some codex bots running i don't even like follow this when do you think you'll be able to book a flight just by saying i'm trying to get to new york tomorrow oh see the worst part about this is like hey like
Starting point is 02:15:24 that's going to come pretty soon actually right we're going to pretty soon have computer use models that are actually capable of going to delta dot com and booking a flight yeah but then what's actually going to happen is Delta's going to partner with whatever company does that, and they're going to put it behind the stupid thing. And like, yeah, so that's going to, yeah, that's going to be here in a few years, right? Not with agentic shit, but just with normal hooking the APIs together, right? Yeah. Wait, so, yeah, what is the-
Starting point is 02:15:48 It's bullish on APIs? What is the mistake about, like, the agentic buzzword? Like, what are people, like, even describing it. Again, it's another thing that I really have no idea what it means. You know, I was hanging out with some friends last night, and like, like, my friend's this VR company, and the you know the the the CEO is really interested in things being open source but he's also really interested in making sure that things are protecting our intellectual property and proprietary and the truth is he has no idea what the word open source means he has no idea what it means that they can
Starting point is 02:16:18 copy his shit right like that's someone else confusing he just he just heard the word open source in some like buzzword thing and he's like do we have the open source do we have the open source in the thing okay so check the box check the open source box Okay, last question about the agentic buzzword, I think that there is something that people are picking up on, which is that these models seem to be very smart for short amount of time, but if you run them for a long time, they start hallucinating and going off the rails. And so you have like 10 minute AGI.I. It feels incredible, but as you let it run and do more work, you can't just say, hey, go do a week's worth of work. Come back to me when you're, but it's superhuman in one minute. And so is, is,
Starting point is 02:17:01 that kind of trade-off curve real? And then is it just a matter of like better harnessing to actually get to two hours of work, which is kind of what the agentic people are like advocating for? No. So I don't think it's better hard. But this is definitely a real phenomenon. Okay. This is definitely a real phenomenon. You can experience this. There's papers exploring it. Yeah. Which show that if in 10 seconds, there's absolutely no way I'll come even close to a modern LLM. Totally. Because the first shot from the LLM is great. Yeah. And then it kind of degrades and it degrades pretty quickly where humans look a lot more like this. Humans can stay coherent internally for much longer.
Starting point is 02:17:44 So, yeah, I think that that's a real thing. I think that that's mostly going to be fixed by like long context. Just more energy. Long context R.L. Yeah, just like you just got to do it. We'll figure out new ways to make the context better. will combine diffusion and auto-regression in some clever ways. Yeah, I think that this is just going to be, like,
Starting point is 02:18:10 there's not going to be a breakthrough here. There's not like one magical thing that we're missing. I think it will be a continued plod. The same thing with data efficiency. I think people will start to care about it. Some new tricks will come out. Some of them will work. Some of them won't work.
Starting point is 02:18:22 We'll continue to do graduate student descent until we find, you know, I'm like a graduate. Anything, that's Robert. Last question for me, anything that you're particularly optimistic about, anything, you check the timeline and you think, this is awesome. I love this. I love this. I want to see more of this. Maybe a little white pill to kind of cap it off. Yeah. So here's something I'm optimistic about. That fact that the one server can't run 10,000 users, that is most of the reason that the modern internet, that's one of the reasons that the modern internet sucks.
Starting point is 02:18:55 that so much of the stuff is in non-recurring expense and then it becomes really, really hard to compete with these people. Right? Like, you could run Twitter on one computer. Yeah. And 20 people could do it too. But like they don't because again, these companies have moats and they invest in making sure that their
Starting point is 02:19:15 modes can't be broken. With AI, I think there's going to be a much less a vote. Especially when you look at the move from auto-regression to diffusion. So auto-regression can run large batch sizes. When you run chat GPT, you're running with a whole bunch of other people on that same computer. Yeah. It's only 100. It's not 10,000, but still, it's 100. Diffusion is running the cloud at batch size one. And once you're in batch size one land, running it locally starts to make
Starting point is 02:19:41 sense. Actually running the models locally, or at least having your own computer in the cloud. Yeah. Not being some shared resource that's really controlled by someone else. So yeah, this was never a thing because you can't put lots of people on a GPU. They tried some weird stuff with the licensing. Yeah, yeah, yeah. Fantastic. Well, thank you so much for stopping by. This is great conversation.
Starting point is 02:20:08 I wish we had a full hour. This is great. We'll talk to you soon, Judge, George. Cool. Bye. See you later. Cheers. Bye.

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.