Subscribe
Share
Share
Embed
Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
Watching TVPN.
Speaker 2:The Starship exploded during a test in Texas, a setback for Mars' 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 eighteen months or something or maybe even more. It's really hard because, like, 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.
Speaker 1:But realistically, skill issue?
Speaker 2:Realistically true. Skill issue. If you build an even faster rocket, you could get there no matter what. You just pilot steer it around like it's a GT three RS around the Nurburgring. No problem.
Speaker 2:So the explosion occurred during a static fire test. 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, and it looked like in any other scenario, there would be a bunch of technicians there, but fortunately, they're able to do everything remotely, which is great.
Speaker 2:And then Starship faces pressure to meet deadlines for NASA's moon mission and Mars exploration. So there's a big, 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 it's, and we hope that they can get back on track. SpaceX make making an enormous bet on Starship, which which stands roughly four four hundred feet tall at liftoff as it tries to break ground with new reusable rockets. And the the paradigm of of Starship, it's not just a bigger rocket.
Speaker 2: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 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.
Speaker 2:Humanity's built a rocket that's roughly on par. We've we've gotten to the moon before. The 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?
Speaker 2: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 a hat for $200? Like, that's the challenge. It's 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 Yeah. You know Frequency.
Speaker 2:Engineering, system. So, so good luck to Elon rebuilding and the entire SpaceX team. I'm sure it's a huge challenge right now. Meta Oakleys are coming. This, Shiel says, this makes sense.
Speaker 2:Luxottica owns both Oakley and Ray Ban, and Meta is reportedly investing $5,000,000,000 for a 4% stake. Luxottica is a fascinating business story. The founder, Leo Del Vecchio's, family still owns one third. The guy was an orphan who became a metal worker making parts for glasses, ultimately becoming the largest listed company in Italy.
Speaker 1:It is really interesting to think about how if if Meta can basically corner all of the most iconic, all of the most iconic frames, which they can do through Luxottica, they do figure out some type of exclusive over time through that investment and effort.
Speaker 2:Does Luxottica just own all the major brands? All of the peoples, everything?
Speaker 1:Every time you buy glasses, you think you're buying some unique brand heritage, Luxottica.
Speaker 2:It's interesting. We should dig more into that company because they don't create all the Well, yeah, that's lot of Sunglass Hut retail stuff.
Speaker 1:I mean, they are big glasses and that created the opportunity for Warby Parker Because
Speaker 2:they They're the ones that manufacture everything.
Speaker 1:You know, basically this entire, you know, Luxotti who had verticalized from brand to production to the actual, medical side as well. Interesting.
Speaker 2:Also, good news in OpenAI world, even though they're they're going through the some battles with Microsoft. They scored a $200,000,000 US defense contract. So they're working with the DOD. The most unhinged picture. I know.
Speaker 2:How did this photoshoot happen? Like, this doesn't this looks like he's about to go on stage, and he has a lav mic, and it's from a low angle. But, like, what lighting scenario created this photo? It's amazing, but it's very impressive. Anyway, great selection by Nick.
Speaker 1:Beating the, you know,
Speaker 2:arms dealer evil tech arms Yep.
Speaker 1:Yep. Dealer allegations with this picture.
Speaker 2:Yeah. If you're if you're a founder, you gotta be careful how the angles people photograph you. But at a certain point, if you're on stage, they're gonna take photos of any direction. But, yeah. And if they take enough photos, they'll get every single expression.
Speaker 2:So get ready. Other news, Meta finally put ads into WhatsApp, in January 2012. They said, we don't sell ads, which is still live. But this is why we love them and this is why Zac is undefeated. WhatsApp should have ads.
Speaker 1:The backbone of the Internet.
Speaker 2:It's the backbone of the Internet. And Signal says that's why he's an Apple fanboy because they don't do ads. Well, does have a huge ads business.
Speaker 1: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 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 any.
Speaker 2:Felt like this was already happening. I felt like this leaked like five years ago.
Speaker 1:How much was it? $20,000,000,000 acquisition? Of course, they were gonna put some ads in at some point.
Speaker 2:Of course. Senator, we sell ads. Any it over. Tyler. How are you doing over there?
Speaker 3:What's up, guys? In in the back of the Maybach. It's pretty chill back here.
Speaker 2:You got
Speaker 1:a little desk set up.
Speaker 2:Yeah. Got Wi Fi. You're productive. Ready to productive. The the the big news that we're having him dig into is Cluly.
Speaker 2:Yep. They are okay. Something happening.
Speaker 1:Something might happen today.
Speaker 2: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.
Speaker 1:It's more that we don't have time. Yes. We're too busy podcasting, but Tyler has time. Many people are starting to call after his Windsurf review. People are starting to call him the MKBHD of enterprise software.
Speaker 2:Yeah. People have been saying that.
Speaker 1:So, today he's gonna be trying out Cluely. Gonna be helping you're gonna see how how easily he can cheat on some hard hitting questions that we're gonna be asking him.
Speaker 2:So state of affairs, Tyler, where are we on the Cluely install so far? Have you paid for it? What's the experience been like so far?
Speaker 3:Yeah. I mean, I I'm ready to go I played around with it for maybe like two minutes just to make sure it's working.
Speaker 2:Okay.
Speaker 3:So I wanna get my live reaction when we start. Okay.
Speaker 1:Well, spin it up, pay for it. Yes. Let's get on the top tier.
Speaker 2:Are there
Speaker 1:multiple check back in a little bit.
Speaker 2:Yeah. Yeah. We're gonna be peppering you with questions that only Cluly could answer.
Speaker 1:Yep.
Speaker 2:What's the popular what's the population of Iran? Go. Go.
Speaker 3:Eighty nine million. Eighty two? Wait. I don't have it running right now.
Speaker 2:You gotta have it running. You failed. You failed your technical
Speaker 1:failed the first test. Well, get it, get it fixed, and we'll circle back in a bit.
Speaker 2:Get it to
Speaker 1:Get it together.
Speaker 2:Guess a question, guess a number between one fifty randomly. We're gonna quiz Tyler now if he's ready. Is he good to go?
Speaker 1:He's ready. I got a thumbs up.
Speaker 2:I'm I wanna ask, how much money, has been invested in Shenzhen. I'm trying to talk into the mic, but not
Speaker 1:Not give it all away.
Speaker 2:Yeah. Yeah. Okay. So I am looking this up. Oh, no.
Speaker 2:I used o three pro, so it's gonna be twelve minutes. Damn it. Okay. New new new tab. I will have to use four o for this cause I need a quick so he's investing 1,000,000,000,000, right, to compete with China's Shenzhen manufacturing hub.
Speaker 2:I wanna know how close that gets us. Wait. This is weird. I don't know. One of the 9,000,000,000, more than 25,000,000,000.
Speaker 2:This does not seem right.
Speaker 1:I have some I have some I have some various stats here. I think it's gonna be pretty hard to pin down the exact
Speaker 2:When quiz Tyler on on on this question.
Speaker 1:Tyler, since 1980s, how much foreign direct investment has there been in Shenzhen?
Speaker 4:Let me think here. I would say since nineteen eighties, over 100,000,000,000. Estimates range from 100,000,000,000 to 150,000,000,000. And Shenzhen is a major global manufacturing and tech hub.
Speaker 3:Wow. Wow. That's so smart.
Speaker 2:It's actually kind of pulls off.
Speaker 1: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.
Speaker 1:So there's about $100,000,000,000 of local funds. 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 $65,000,000,000 of cumulative foreign direct investment. But who knows?
Speaker 1:And then run rating, I guess around $10,000,000,000 But also, does this count what Apple is doing? That's like another form of investment. Anyways, this might be an answer that clearly, I guess, got pretty close.
Speaker 5:It was pretty good.
Speaker 1:Pretty good.
Speaker 2:That was good. I have I have a follow-up. So, you know, the iPhones made over in China often flown via seven forty seven to America faster than shipping on a cargo ship. How many iPhones fit inside of a seven forty seven?
Speaker 4:Alright. Let me think here. I'm gonna say I would say about two to three million in a seven forty seven. You know? So okay.
Speaker 4:So seven forty seven max payload is about a 140,000 kilograms.
Speaker 2:Okay.
Speaker 4:Each iPhone box is about half a kilogram.
Speaker 2:Okay.
Speaker 4:So I would say, you know, a practical range of iPhones is probably 1.5 to 2.5 per flight. But, obviously, it depends on, you know, packaging, pallets, cargo layout, you know, all that kind of stuff.
Speaker 2:That's pretty good. I mean, ChatGPT here has 9,600,000, but I think that's including, like, every inch of the plane, including, like, the passenger It's
Speaker 1:very possible
Speaker 2:that that's more accurate. Actually. I think that might be more accurate.
Speaker 1:Is clearly
Speaker 2:Goated. It might be.
Speaker 1:Think to ask Roy, who's coming on the show later today.
Speaker 2:Yeah. This is I'm I'm So so press report. The the chat GPT estimate had the usable internal volume as passenger plus cargo, and I it feels like you used just the cargo number. Is that correct?
Speaker 4:I believe. Yes. I I think so. Okay. Oh, I see.
Speaker 4:ChatGPT estimate 9,600,000.
Speaker 2:Oh, oh, it's streaming through?
Speaker 4:Yeah. Yeah. Okay. So I I was doing just the just the cargo, I think. This
Speaker 2:is fantastic. It actually works pretty well. Alright. I I'm impressed so far.
Speaker 1: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.
Speaker 2:Yeah. Yeah. This is great. Andre Karpathy chimes in. He says, very interesting to think about.
Speaker 2: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, matter 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 is in trying to think this through and chart the impact of AI on labor market so far. EG, I was curious to look for radiologists and if I'm getting this right, the US Bureau of Labor Statistics sites 29,530 US radiologists in 2021 and then up to, let's go to Tyler.
Speaker 2:How many radiologists does the US Bureau of Labor Statistics claim there have been in 2023?
Speaker 3:Okay. Come back to me in thirty seconds.
Speaker 5:Okay.
Speaker 2:We'll be back. Think he's actually I think he's working. And so I just when I just hit him with random questions, not quite
Speaker 1:He's not in the Zoom. So clearly he's not running.
Speaker 2:Oh, okay. Okay. He's not in the Zoom. Okay. Well,
Speaker 1:yeah. That was your first mistake, Tyler.
Speaker 2:Yeah. Always keep Cluelly on. Always keep Cluelly on. Does Cluelly have the ability to to just prompt it directly or or or do you have to be on a Zoom?
Speaker 3: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 Chatty Bitty interface.
Speaker 5:Sure. But you
Speaker 3:can also just pull audio, like, just from in person. Like, if if I was sitting across from you, it'd be fine. I'm not sure it'll be able to hear you from in the car.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 4:But because
Speaker 2:it doesn't have the I'll
Speaker 3:get back on the Zoom.
Speaker 2:Okay. Well, we'll come back to you with that.
Speaker 1:The audience will have to wait to find out how many radiologists we have.
Speaker 2:Everyone's waiting with bated 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 development, streamline issues, projects, and product roadmaps.
Speaker 2:If you're building clearly, get on Linear. Nikki Dabir, building
Speaker 1:up Linear's customer list looks like a tier one venture firm's portfolio page. Got Ramp, OpenAI, Cursor, Runway, Perplexity.
Speaker 2:I normally make the joke of, like, the next oh, when we talk to Sam Allman, we're gonna pitch him linear, but it's like, oh, too late. Boom is on there too. That's cool. I I always make jokes about, like, using linear for other stuff, and you're like, no. It's just for software.
Speaker 2:And look at Boom. They're using it for everything. Fantastic. Yeah. Anyway, let's go.
Speaker 2:Tyler, what are you got?
Speaker 1:Question Radiologist expert. We're interviewing you for a job as a data analyst, you know, covering radiology.
Speaker 2:Yes. So the question is, how many radiologists does the US Bureau of Labor Statistics claim exist in The United States in 2023?
Speaker 4:Let me think about this.
Speaker 2:I'm noticing a tell.
Speaker 3:I'm gonna estimate maybe 31 to 34,000 radiologists. Oh, really?
Speaker 5:Least from at least from
Speaker 3:2023, I would say. But, yeah, that that's my best guess.
Speaker 2:That's your best guess. It's 31,960. Think you got the job.
Speaker 3:Wow. Might be goaded. Okay.
Speaker 2:I have another question for you. Pop quiz off the top of your head. What's the GDP of India?
Speaker 4:Off the top of my head. Let's see.
Speaker 3:I'm gonna say 3,700,000,000,000.0.
Speaker 2:Wow. It's really it really sells it that you that you're touching your face so I can tell that your hands aren't on the keyboard.
Speaker 3:You can tell that I'm thinking.
Speaker 2:Yeah. Yeah. You're you're just thinking about it. Yeah. Yeah.
Speaker 2:You gotta be a good actor. 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 this is gonna be the modern tell.
Speaker 1:No it's good. I'd you're a great actor and Cluelly might actually
Speaker 2:Or maybe he's not using Cluelly and he just knows all this stuff off the top of his head.
Speaker 1:It's very possible. Tyler needs to use Cluelly to figure out.
Speaker 4:I'm on.
Speaker 2:Oh, okay. I think we got a feedback loop here. Can we hear you? How much is the Hisense 100 inch TV cost? Hisense.
Speaker 4:Let me think. I'm gonna say typically, I would say around 3 to $5,000. Obviously, price varies by region and model.
Speaker 2:This sounds so natural. This sounds so natural. 100 inch. Yeah. Yeah.
Speaker 2:I I I think Apple should do it.
Speaker 1:Do it.
Speaker 2:It'd be great.
Speaker 1:Tim, do it. 100
Speaker 2:inches would be a good a good, like, you know, differentiator too because a lot of brands that, you know, the 55, 65, 75, it's gotten all confusing. It was just like, you know, if you're going with Apple, you're getting a 100 inch TV.
Speaker 1:Yeah. And it's like
Speaker 2:and it's just amazing, amazing quality. The intern Cam's still active. I wanna go to Tyler for one last pop quiz. Oh, is he on? Okay.
Speaker 2:I wanted to ask you. Yeah. What's the capital of Michigan?
Speaker 4:The capital of Michigan.
Speaker 6:Didn't you
Speaker 2:go to school there?
Speaker 3:I think it's Lansing.
Speaker 2:I think you're maybe leaning on clearly too much at this point.
Speaker 4:Don't know. I don't know if you're
Speaker 1:cheating using your brain or I can't really assess the product. You know, you
Speaker 2:have too much Yeah. What's your knowledge on Michigan? What what's your name?
Speaker 3:My name. Let me think here. It's like the, that paper that just came out. Right?
Speaker 2:Oh, yeah. Yeah. Yeah. Yeah. Yeah.
Speaker 2:Do you think that, based on your use of Pluto, do you think it'll make you smarter, or do you think, you'll take your foot off the gas?
Speaker 1:I mean,
Speaker 2:I was let
Speaker 3:me think about that, actually. I I think probably the latter, honestly. I mean, it's just like I just don't need to think 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.
Speaker 2:Okay.
Speaker 3:But even then, you know, once they get o three in here, it's really like everything's covered So
Speaker 2:We have reasoning. Did you get a feeling for what model was under the hood?
Speaker 4:I don't know.
Speaker 3:I think I could probably check, but I'm not sure right now.
Speaker 2:It's so weird interacting with somebody using Clueless. Like like every answer is like, and then you don't know if they're reading Cluely or not.
Speaker 1:Or just actually thinking. Well, anyways, people should go try the product. Yeah. Know?
Speaker 2:Make your
Speaker 1:own I I really think that anytime Roy gets a negative comment, please just, you know, use the product for five five plus hours and then you can have an opinion.
Speaker 2:The the the message to Andreessen, no crying in the casino because, you know, Roy Lee, there's probably a viral video of him going to the casino soon.
Speaker 1:Pretty soon.
Speaker 2:You know, that's gonna make a lot of people angry.
Speaker 1:So talking about spacking again. Yeah. So I think Louie's a good target. I bet. I bet
Speaker 2:it's not the craziest target out there.
Speaker 1:Not the craziest, you know, Chamath and Mr. Beast. Yeah. Holdco.
Speaker 2:Yeah. There's a lot of revenue there. It's growing. You know? Yeah.
Speaker 2:The market needs a pure play AI. They love viral.
Speaker 1:A pure Roy play.
Speaker 2:Yeah. Yeah. There's no pure play.
Speaker 1:Well, have some more breaking news apparently. Break it down.
Speaker 2:Next up, we have Roy from Cluelly, the man himself. Third time in the studio, third time on TBPM.
Speaker 1:Get the
Speaker 2:to the stream.
Speaker 1:Get that hammer ready.
Speaker 2:Ready. Let's bring him in. Let's hope he's ready. Roy, give us the news. Here's the headline number.
Speaker 2:How are you doing?
Speaker 5:Thank you, Jake. How much
Speaker 2:did you raise?
Speaker 4:15,000,000 fucking dollars. Oh,
Speaker 1:clean hit. Clean hit.
Speaker 2:Congratulations. Thank you, Jake. Why'd you raise money? I thought you're printing so much money you didn't need to raise ever. What happened?
Speaker 6:We're printing money, but we need more money.
Speaker 2:We're trying
Speaker 4:to every single day, we're looking for things to spend money on.
Speaker 2:Okay. Okay. Uses of the funds. What are you gonna spend on first?
Speaker 1:14,000,000 for brain computer interface development.
Speaker 4:Exactly. Exactly. We we have whatever you thought the viral content, you thought this was cool, bro. We're doing 10 x this.
Speaker 2:Okay. More videographers, more more
Speaker 5:after effects artists.
Speaker 6:Looking for editors, more engineers, more everything, please.
Speaker 2:Mas. Mas. Yes. Let's go. Yeah.
Speaker 2:What's the morning routine like now over at Cleaning HQ?
Speaker 6:Everybody wakes up and we swipe on Hinge for thirty minutes. It's mandatory. Everyone swipes on TikTok and Instagram for an hour just to make sure the viral senses are refreshed.
Speaker 4:Okay. We we we all do cold plunges and we're we're we're ready
Speaker 6:to hit the day with with caffeine.
Speaker 1:If you if you cold plunge, though, does it negate, like, the the brain rot? Like, do you get to or is it is that intentional of, like, relogging, like, know,
Speaker 6:in We we we we scroll to keep our viral up, but after that, it's time to get to work. We're a serious company. Know? We're not just we're not just trolling over here.
Speaker 2:Okay. That's good to hear. Talk to me about the Hinge use case. I wanna hear, Clue's desktop app. You're not in the App Store.
Speaker 2:If I'm if someone's using Hinge on their phone, how are they gonna take advantage of Cluely now or in the future?
Speaker 6:I mean, every single time you screenshot something and ask ChatGPT 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 and and and give you information out of it. Why can chatbiteeth.com not use this? Why is the main AI use case not already aware of what's going on on your screen? We think this is crazy.
Speaker 2:Yes. But it's locked down for privacy reasons on the iPhone. So the question is, like, what user interface innovation are you gonna 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?
Speaker 6:I would 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 I like like, whatever it is, I think this technology is growing super fast.
Speaker 6:Like like, I think I think phone like, in five years, I would question whether phone is the dominant consumer use case.
Speaker 2:Okay. I I I I get that you're BCI pilled. It still feels a few years out. The Meta Ray Bans feel very much here today. Have you looked into those APIs?
Speaker 2:How developer friendly is the Meta Ray Ban 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 gonna have a really hard time on iOS. No matter how cracked your engineers are, Apple is just gonna say, no.
Speaker 1:I think I think Roy, if anybody could risk
Speaker 2:Tim Cook. Cook, I I I won't I won't put it past you, but it feels like the Meta Ray Ban ecosystem might be a little bit more open. What are what's your read on the Meta Ray Ban or the Meta Glasses rollout? They just had an announcement this today.
Speaker 6:My read is that there is way more money in in 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 a desktop assistant, and there's way more money and way more value in this than people think. We're still gonna be using computers in a few years. Maybe we'll be using something else, but, like, like, bro, these sales Oracle, Adobe, these guys move slow as fuck, bro. Like, they will
Speaker 2:be Yes. Yes.
Speaker 4:BlackBerry still, bro. Like, they are moving slow. We're have
Speaker 6:computers among a bunch of enterprise value for the next few years, and we'll be here to capture all of that.
Speaker 2:Yeah. So, I mean, I I I get that the it I mean, it feels like this is going towards enterprise note taking, enterprise assistant, and and 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 we're having our intern demo clearly today. And you could see that if we're on a call, just 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.
Speaker 2: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 Cluelie users adopt the product? It feels like the logical cases at work on the desktop.
Speaker 6:Yeah. Well, of of course I mean, the question is how are Cluel users using the product?
Speaker 2:Yes.
Speaker 6:Most people it it is most helpful in a meeting. Right now, there's no product on the tool that gives you live assistance during a meeting. Yes. That's where all the prosumer and enterprise values most prosumer and enterprise values being derived. Other than that, we have the gigantic consumer, the most viral use case ever of literally cheating, bro.
Speaker 6:Like like like
Speaker 2:Yeah. Yeah.
Speaker 6:Yeah. Answers your questions. And, like, what even when you're doing homework, I mean, like, just immediate, bro. Like, do all your homework, you're doing quizzes, assignments, when you're watching lectures, bro. Immediate, bro.
Speaker 6:It's immediate help.
Speaker 1:Immediate. On-site. Yeah, yeah, yeah. Yeah. Got to give a shout out to the whole team.
Speaker 1:We're 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.
Speaker 2:Yeah. We would never.
Speaker 1: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 for five, ten hours and then come back and let me know if you feel the same way?
Speaker 2:I think that's the right way.
Speaker 1:Get a user out of it. Talk about the process for for the round. You you did you you raised the seed round not very long ago. I'm you know, did this come inbound? I
Speaker 6:will say right now to all the VCs watching, if you ever are trying to get
Speaker 4:in a round, you get
Speaker 6:me an email thread and you say, hey. Let me loop in my assistant, and we'll schedule a call in two weeks. You are not getting allocation, and I wake up every single 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.
Speaker 6:Your whole job is to find the alpha and invest quick and early. Why are
Speaker 4:you looping an assistant in two weeks? My partners, Brian and Eric, they came with stakes and Coke Zeroes to the house.
Speaker 1:Stakes and Coke Zeroes.
Speaker 6:You guys. This is how investors need to be. Your job is to find the fucking album, bro. Why are you looping in this system? There was a there was a preempt, and I think all rounds, you need to preempt.
Speaker 5:Like, fuck the fuck, bro.
Speaker 2:A preempted founders. If you're not
Speaker 1:getting preempted, shut company
Speaker 4:Even if you're running out of money, if you're
Speaker 1:not getting preempted, just shut the company down.
Speaker 2:Shut the company down. That's scary.
Speaker 4:All the all the
Speaker 6:accounts are going so quick. Companies go so quick.
Speaker 4:All VCs don't have two weeks to loop in your system.
Speaker 2:Okay. What is your underlying motivation for building this company?
Speaker 6: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, in even in five, ten years, bro, if we keep growing at this rate, like, we'll be on the next ship to Mars. We'll all be living a 400 years old, and I'll be jacked till I die. And in that universe, bro, like, these companies will converge into super companies.
Speaker 6:And these super companies is gonna be me versus Elon versus Sam competing to be guardian of the fucking galaxy, bro.
Speaker 4:And it's I'm I'm gonna be on top.
Speaker 2:Okay. Sounds like you're power hungry. There's been a criticism
Speaker 1:Which can be a strength.
Speaker 2:A strength. The the the there's clearly a subtweet 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?
Speaker 4:The only two things
Speaker 6:I I really care about in my life are working on is working on something that I find interesting and getting the work seen by people. Yes. These are Elon Musk. These are my inspirations. Like, these people are known by every living conscious human being in the world.
Speaker 6:Man, this guy founded Apple. This guy did Tesla. Bro, like, it's it's the coolest shit ever. Four thousand years ago, bro, you wanted to hunt big fucking woolly mammoths and bring him back to tribe. There's no more woolly mammoths.
Speaker 6:There's only startups. Okay.
Speaker 1:So So you're not beating the allegation.
Speaker 2:Wait. Wait. But but but the more precisely, if if the best path for Cluely forward is your interns getting up getting tons of social media views, you step out of the limelight because you're managing the company. People know Cluely, but they don't know Roy Lee. Is that still a win for you?
Speaker 6:Of course. At one point, the company becomes undistinguishable from the founder. Yes. It happened with every single big company, and it's what it's what what will happen with Cluely.
Speaker 2: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 Cluely because of you and the and the viral stunts that you've pulled. And so you're kind of inverting it. And the and the question that the the haters are asking of you is that is this is the long term goal to build a great product or to build the brand of Roy Lee? Bro, it is to change the world in
Speaker 6:a meaningful way, and you don't change the world by going viral a million times. You change the world by genuinely building a world changing product. Technology changes the world. I will I will build great technology, and every person in the world will watch me do it.
Speaker 1:Okay. Amazing. How how big are you going on the content side? Do you wanna get a single video with a 100,000,000 views? Are you are you going that big?
Speaker 1:Is that is that kind of the wrong framework to think about it? But But I imagine you're going to have more, you know, budget than ever, and, you know, it's easy now to get a million views on X on a video. Is 100,000,000 views on YouTube the next, you know, challenge?
Speaker 6:I will tell you right now, and this might be the the most logical thing I I say on here, but the biggest societal shift in maybe human history happened about five years ago when TikTok surpassed 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 100 x. As a result, there is 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 100 times. Yeah.
Speaker 6:Because there's 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 scents. Yep. We know. We independently all have 20 ideas a day that we know will go viral.
Speaker 6:And this extrapolated out over a year will literally generate a billion views a month. And if you're someone who
Speaker 4:thinks a billion views a month is
Speaker 6:not gonna to to some money, like, bro, you're retarded. Gonna go back to school, bro.
Speaker 2:A billion views a month. Is that is that, like, 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?
Speaker 6:I have no idea, but I'll tell you right now, like like, Super Bowl ads, it's it's it's all old. Like, this is the old meta. The new meta is in content, in short form, and nobody seems to have captured the the gigantic delta in generating more viral content.
Speaker 1:I still think it'd be funny if you forced a 127,000,000 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 cluelly.com and sign up for Cluelly today. So don't count it out. But anything else you want to share while you're here?
Speaker 1:I know it's a big day for you. The timeline's blown up. You you not very many people have the stones to to launch a series a on a Friday, a summer Friday.
Speaker 2:To go head to head against Meera too.
Speaker 1:Yeah. Yeah.
Speaker 2:And you pulled it off.
Speaker 6: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.
Speaker 6: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.
Speaker 4:And if
Speaker 6:you can't have then
Speaker 2:you Stick with us. Stick with us for a minute. I wanna play your fundraising video live on the stream. And then if we have any questions from that, I wanna ask you. Please.
Speaker 2:Please. So let's play Pull it up. Video.
Speaker 6:Mister Lee, Columbia University has found you guilty of academic integrity violations. Do you have anything to say?
Speaker 3:Color grade. Well, color grade
Speaker 6:I've already apologized to school, but to be honest, in two years, nobody's gonna think this is cheating.
Speaker 5:Yo. The increase in wire just
Speaker 1:hit you. You're gonna last us through the summer?
Speaker 5:My Welcome to Chloe.
Speaker 2:Great video. Banger. Congratulations. Banger. I gotta hit the gun again.
Speaker 1:Very well done.
Speaker 2:Very well done. And beautiful beautifully shot. Like, the lighting. I mean, your cinematography, yeah, it's not too. Very, very good.
Speaker 2:Very, very good. Nailed it. Anything else for Roy?
Speaker 1:Yeah. That's it for now.
Speaker 6:In house studio.
Speaker 2:It's crazy that you can shoot that in house. That that that really is, remarkable. Congratulations.
Speaker 1:We are excited to follow the journey.
Speaker 4:Shit. You just got $15,000,000.
Speaker 2:Oh, yeah. Tell us about the fundraising leak. Well, what what's your deal with r four rock? Were you able to how much do you have to pay him to shut up?
Speaker 4:Man, I I was I was begging him. You guys have no way. For the last few weeks, I've been begging this man. Please do not leak. Do not leak.
Speaker 2:Why? Why? I feel like I feel like, it already leaked separately and, like, having I feel like you would be leaning into a leak. I was expecting, like, a collab almost.
Speaker 6:I think what whatever leak there could possibly be, I have very strong faith in my ability to make my announcement go more viral.
Speaker 2:Oh, sure.
Speaker 6:This video will go more viral than any leak would have even if I try.
Speaker 2:Yeah. Yeah. Yeah. That makes sense. You actually don't wanna take the gas out of the out of the tank.
Speaker 2:I love it. Thank you so much for stopping by. This is fantastic, and good luck.
Speaker 1:Congratulations to you and the team. Excited to watch you guys cook this summer. Yeah. And hopefully, the 15 mil makes it, you know, back, you know, August. Just remember, August, it's gonna be hard to get the autoresponders will be on.
Speaker 1:It's gonna be hard to be you know, get those twenty four hour meetings. Yeah. And so just make sure you got the runway to September.
Speaker 2:And and despite coming as a shock, IPO underwriters do not preempt. So at some point, you will have to stop with the preempt everything mantra.
Speaker 1:I don't know. There's some SPAC sponsors out there that
Speaker 2:Who knows? Maybe, yeah, maybe
Speaker 1:you'll get preemptive on SPAC in the fall. You know? I wouldn't be I wouldn't be surprised. So
Speaker 2:You're you're saying it as a joke. I I feel like it might be in the cards. We're we're we're gonna be tracking it. Thank you so much for stopping by.
Speaker 1:Great chatting with you.
Speaker 2:We'll talk to you later.
Speaker 1:Talk soon.
Speaker 2:Bye. In other news, the Los Angeles Lakers has been sold for 10,000,000,000 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, like, the the Wall Street Journal's framing this is like, this is the biggest deal ever. No one's ever done a deal like this.
Speaker 2: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 $10,000,000,000, like
Speaker 5:Billion dollars.
Speaker 2: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 a deck of corn. Congratulations to, to the Lakers.
Speaker 1:Mark Walter and
Speaker 2:the whole It's it's, it's fantastic. Major premium to the Boston Celtics who sold for 6,100,000,000.0, and now the Lakers is the most valuable sports franchise. But they just don't do enough volume. There's only a couple games. You know?
Speaker 2:They're not twenty four seven. Like, Instagram, does that ever go offline? No. No. There's always entertainment.
Speaker 2:Lakers, they're still doing seasons. They need to have twenty four hour basketball if they wanna really get there.
Speaker 1:For sure. Clock, it's like endurance endurance basketball. It's just a week long game. You know? Gotta always have five players on the court.
Speaker 2:Just constantly. Running up. It's the only option. Jeanie Buss and her family who have owned the Los Angeles Lakers since Jerry Buss bought the team in 1979. Wow.
Speaker 2:On Wednesday, agreed to sell majority control of the story team to Mark Walter, the sports investor. And I and I looked at the, the the return on investment of owning the Lakers for that forty years, slightly under S and 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. Just diversification, bros. DCA, bros.
Speaker 2:Undefeated again. Well, if you're trying to DCA
Speaker 1:Well, the
Speaker 2:Do it on public.com, investing for those who take it seriously, multi asset investing, industry leading yields that are 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 hear it for Cadillac. Let's go.
Speaker 2:Let's hear it
Speaker 1:for Cadillac. Yes. Congratulations. John, you know,
Speaker 2:front at all.
Speaker 1:But John front run the, the Cadillac f one team and got a Cadillac for himself over there. You can see
Speaker 2:the black to have an American f one team in the business now. Yeah. Yeah. We've we've fallen off, but we're coming back.
Speaker 1:You're not gonna be able to get one of these in the whole country.
Speaker 2:I don't think so. They're gonna be too popular.
Speaker 1:F one team Yeah. You know, gets out on
Speaker 2: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 77,000,000,000 when the Celtics sold in March. The $6,100,000,000 valuation exceeded the previous record valuation set for a sports team by the 6,050,000,000.00 sale of the NFL's Washington commanders in 2023. He purchased the Lakers for 67,000,000 in '79 1979. The team transformed from franchise uprooted from Minnesota into one of the winningest and most valuable
Speaker 1:sports properties. They were founded.
Speaker 2:That's where the lake the lake name comes from. Interesting. 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, they they just brought them to LA and kept the name. But that's what Lakers means.
Speaker 2:Yeah. Wow. Bus, the Bus family oversaw the creation of Showtime and presided over the NBA's last three peat. A listers like Jack Nicholson and Leonardo DiCaprio have become fixtures at the games. And when they sell merch, they need to pay sales tax.
Speaker 2:They should get on numeral.com numeralhq.com. John. Sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. You know all the
Speaker 1:different things. Championships since 1980. Their rosters have boasted many of basketball's brightest stars. Magic Johnson, Kareem Abdul Jabbar, Kobe Bryant, Shaquille O'Neal, and LeBron James. LeBron James' son have all worn the Lakers purple and gold.
Speaker 2:I love it. Such cool yeah. The the father son duo. I mean, I feel like that should have been a bigger, like, national news story. It's such a cool thing.
Speaker 2:I 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 Yeah. That you could be playing Well basketball
Speaker 1:your son. You could have earned a better return by D. C. Yang into the into the into the stock market.
Speaker 2:That's not why people own these assets, though.
Speaker 1:Owning the Lakers for a number of decades, I imagine, was absolutely priceless. So, great investment.
Speaker 2:You get the owner's box.
Speaker 1:Great run.
Speaker 2:Yeah. All the perks, you have to add those in. What do you get perks from DCA ing into the
Speaker 1:I like how, Lakers legend Magic Johnson hit the timeline said, just like I thought when the Celtics sold for 6 b, I knew the Lakers were worth 10 b.
Speaker 2:Go. The confidence of Magic Johnson. Great investor too. He's got a bunch of bunch of good stuff in the portfolio. More news on the Scale AI, transaction.
Speaker 2:So it's closed. I believe that Alex Wong has a badge at Meta and shows up to work at at in Palo Alto and and clocks in at at MetaHQ now. Scale AI is still an ongoing concern. It's still a 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 AI will primarily be working with Meta and that other Foundation Model Labs might not want to do business with with Scale AI anymore. Unclear if they can separate out the businesses.
Speaker 2:If they can separate them out 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, at at which point, 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 that, OpenAI said, hey, we're not training we're we're we're not using Scale AI for data anymore, because it's too aligned with our competitor, LAMA, maybe. But everyone's trying to
Speaker 1:Yeah, a lot of this is very predictable. 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, we're totally going to retain all of our customers, right? Like people aren't just gonna immediately churn off. And no, they were smart enough to know what would happen.
Speaker 1:And there was an article I think yesterday about OpenAI, you know, ending their relationship with scale.
Speaker 2:From what
Speaker 1:we knew, like, they hadn't been doing much
Speaker 2:Yep.
Speaker 1:For a while. Yep. That's part of the reason why Merkor had
Speaker 2:been And they also brought
Speaker 5:a big
Speaker 2:function in 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 makes sense for a business of that size, but
Speaker 5:Yeah.
Speaker 2:We'll see. So the, 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. 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.
Speaker 2: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 OpenAI hire 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 14,300,000,000.0 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. This is fascinating.
Speaker 2:I didn't know this. 1,000,000,000 in sales last year, bigger than Yeah. So Chen startup has won customers like Google, OpenAI, and Anthropic.
Speaker 1:It's such a testament to the idea that like, sure, you can bootstrap, but it's so incredibly hard to have any hype around your business if you're bootstrapped because you're not having, your investors aren't hitting the timeline for you on a daily basis. And also, 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.
Speaker 2:So this is, I mean, this is crazy, crazy stats. So Chen is 37. He has no investors and has bootstrapped the five year old startup entirely by himself, which has a 110 employees in offices in New York and San Francisco. The company generated more than $1,000,000,000 in revenue last year. Surge has told employees a previously reported figure that exceeds the $870,000,000 scale generated in revenue, during the same time period.
Speaker 2: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 surge keeps after paying its workforce of mostly contractors. So there is a question about, like, the margin 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.
Speaker 2:But at the same time, even if it's 200,000,000 in, like, you know, like, net revenue, that's still a huge business. I I it's hard to imagine Surge not being a fantastic business if they haven't had to raise money. They have a 110 employees, and they're used by Google and all these major foundation model apps. So, it seems like a fantastic business. But if Surge could earn evaluation from investors similar to the one Scale received for 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.
Speaker 2:Interesting. I'm very interested to see what, 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.
Speaker 2:Contractors hired by, like, by companies like Surge grade the responses from AI models and write thousands of questions and answers in fields like programming, math, and law to feed those AI models. And so, you know, if you're I I I wonder if this is gonna 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, twenty or fifty or one 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 distills what you do excellently. Yeah. I don't know.
Speaker 2:I don't know if it'll go that way. I'm I'm interested to talk to people about it. As AI models, so Surge's subsidiary, Data Annotation 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. Serge justifies the prices with its reputation for industry leading work.
Speaker 2:Indeed, one former scale employee said Serge 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 backed Handshake readily acknowledged that Chen is the number one player. So I'm excited to talk to Garrett Lord today about this exact topic. 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 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.
Speaker 2:He'd also raised 1,500,000,000.0 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 time to his exit perfectly given the traction of Surge, which had grown larger than Scale without outside capital 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's spokesperson said the company still behind profitable. But wasn't burning a ton of money. Like I think they had They
Speaker 1:were efficient.
Speaker 2:They raised 1,500,000,000.0 and they still had like almost a billion in cash. So they in like trouble or anything, but at the same time it was like not a wildly profitable, not a wildly lean business, but I don't know.
Speaker 1:What a it's absolutely fascinating how these two businesses
Speaker 2: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 years ago, but it was certainly like pre chat GPT that all these companies got started.
Speaker 2:And then they realized, like, some of them got started in self driving car annotation, all sorts of stuff like that. But, 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. Like, he's just, like, going from one to the next.
Speaker 2:That's insane. He was developing recommendation and search algorithms and helping gather the data needed to train them. Despite the hefty resources of those companies, Chen 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 correct could correctly classify businesses, telling the difference between restaurants and grocery stores, for instance.
Speaker 2:To do so, they needed 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.
Speaker 2:The data was complete junk. Wouldn't say which vendor Facebook had used. In 2020 in 2020, he left Twitter to found Serge and picked up some of his first customers, executives from Airbnb's and 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 Dogpatch neighborhood and the Mission District, talking up his startup. To get search 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.
Speaker 2:Fortuitously, Chen focused on language modeling. Scale by contrast started out using more visual data for autonomous vehicles, which we talked about Wow. Just as those types of models began to grow in importance. Less than a year later, OpenAI 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 and Digital Search So
Speaker 1:they're putting out research papers with OpenAI and still manage to stay this under the radar.
Speaker 2: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 revenue, zero funding.
Speaker 2:Scale founded in 2016 has a 100 870,000,000 in 2024 raised oh, the this this says funding raised, but this is clearly valuation or something because it says 17,400,000,000.0, which is not what they raised. Turing has 300,000,000 annualized, raised $225,000,000.
Speaker 1:Invisible It's interesting Turing too initially was like a marketplace to just hire developers.
Speaker 2:And I
Speaker 1:think they pivoted into
Speaker 2:Data labeling.
Speaker 1:Data labeling.
Speaker 2: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. For instance, companies randomly insert questions that have no correct answers or make sure labelers agree on the right answer to a question.
Speaker 2:So, obviously, you scaffold up these these, these these, like, responses so that everything's, like, double checked, and then you can kind of see if people are are messing around. But, wow, what what a beast of a business. I have no idea how big this thing is. Amazing. Over in defense tech world, Andoroll has partnered with Rheinmetall, the German, the German defense tech company, prime, really, to manufacture barracuda and fury over there.
Speaker 2:That's very exciting. And then we also touched on, Spotify founder Daniel Ack. Leading
Speaker 1:Guess when Ryan Mittal was founded.
Speaker 2:The way you're saying that makes me think it's like 1650.
Speaker 4:I'm putting you on the I'm putting you on
Speaker 1:the spot like Tucker put a Yeah. His name
Speaker 2:on Tucker? How can you possibly report on the news if you don't know when it was founded?
Speaker 1:This is this is the best bit earlier. I have to read
Speaker 2:it out. Yeah. Read the
Speaker 1:Muffin Man. Tucker. Do you know the Muffin Man? The muff Ted goes, the muffin man?
Speaker 2:The muffin man?
Speaker 1: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? This is a post from Zach Stewart.
Speaker 2:He's a real gotcha.
Speaker 1:Really, really good. Anyways, you can still give you permission to comment on
Speaker 2:rhymetal. Even
Speaker 1:though you don't know. 1889.
Speaker 2:I was not I I knew it was really old. 1889?
Speaker 1:Dusseldorf.
Speaker 2:Okay. I was I was pretty far off with sixteen fifty, but but over a 100 years. I mean, yeah, that that that's the same I it's general General Atomic is part of, like, this roll up and the and the and and it came out of, like, I 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 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 100 before Palmer Luckey was born.
Speaker 2:Yeah. 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 Yeah. How legacy they are. Like, it's not just like If
Speaker 1:you're in the game for a while, you know, decades after after you start the company, your your greatest enemy will will be born. Yep. They'll have to grow up a little bit.
Speaker 2:Yep.
Speaker 1:They'll have to learn the game. Yep. And then they're gonna come for you.
Speaker 2:Wild. So, yeah, Spotify founder Daniel Ek is leading a $600,000,000 funding round into the German defense startup, Helsing. This is the this is kind of more of the annual equivalent over in Europe, valuing that four year old company at 12,000,000,000. The the business makes Battlefield AI drones, submarines, and robo fighter pilots. It's now one of Europe's most valuable startups.
Speaker 1:And they're using some renders here, John.
Speaker 2:Renders? Image.
Speaker 1:They're render maxing.
Speaker 2:They're render maxing.
Speaker 1:Happens. It is a cool render. Yeah. Look at the water there. It's definitely a render.
Speaker 2:Who knows? It's hard to tell these days. It's it's so, it's be we're beyond the uncanny valley. And so, Helsink is is expanding from its origins in artificial intelligence to produce its own drones, aircraft, and submarines as part of a bigger push for, locally made and and owned, defense products for European countries and and really companies all over the world. Crazy.
Speaker 1:It was founded in 2021 Wow. By Torsten Riehl, a video game entrepreneur. Gunbert Scherff, a former German defense ministry official, and Niklas Kohler, an AI researcher. And, they have partnerships with Saab already, as well as Mistral.
Speaker 2:Yeah. And tons of American venture capitalists in the deal. You got Lightspeed, Xcel, and General Catalyst.
Speaker 1:Condor's cooking.
Speaker 2:They've raised over 1,370,000,000.00. 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, X said, 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.
Speaker 2:Up next, we have Catherine Hahn from Hahn Ventures coming in the studio to talk about the stable coin bill. The genius bill is slated to pass on the front of The Wall Street Journal today and is very
Speaker 1:excited about and establishing national innovation for US stable coins.
Speaker 2:We had her on the show, and, yeah, we're excited to talk to her. So welcome to the show. How are doing, Katherine?
Speaker 1:What's going on?
Speaker 7:Hi. How are you guys?
Speaker 2:We are great.
Speaker 1:Big twenty four hours.
Speaker 2:Congratulations, I think, in order, but please get us up to speed on what's actually happening and where, where things are in Washington.
Speaker 7: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 Katie.
Speaker 2:Let's update the let's update the Chiron. Katie Holland.
Speaker 7:So, thanks for having me on, guys. Actually, I literally just walked off a plane. I was down at the CO2 conference
Speaker 1:Oh, wow. Nice.
Speaker 7:Where I was talking to a lot of founders, crypto and non, and everyone loves your show. So I Fantastic. Happy to be here.
Speaker 1:Well, thanks for
Speaker 7:making time. Yeah. Thanks. I think congratulations are in order. I don't know if I would say that yet.
Speaker 7:I mean, first of all, the bill passed through the senate. Great 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 DC circuit, that article three, that other branch of our government left the SEC no choice.
Speaker 7:The courts don't always get it right, but sometimes they do. And the 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 ETFs in this country today for Bitcoin and for ETH. And I think of this as a bit a similar thing. Now here we have another branch of government stepping in.
Speaker 7: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 has 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 we can discuss today, is there's another very important bill. And I'm not gonna slap a percentage on and say which bill is more important, but that's the market structure bill.
Speaker 7:Mhmm. And to me, that's really the transformational bill, for the crypto industry.
Speaker 1:Okay.
Speaker 2:So break
Speaker 1:yeah. Break that down for us.
Speaker 7:Yeah. So there's one bill, stablecoin 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 prepolitical. And I think I don't want it to be the case that this industry is too political on one side or the other.
Speaker 7: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 stablecoin bell and the market structure bell. And the stablecoin bell obviously paves the way for a regulatory framework for stablecoins in this country. So that's that.
Speaker 7:Then there's another bell, the market structure bill, 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 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.
Speaker 7:And we've seen courts across the country weigh in on that question. Mhmm. And and that's because we don't have legislation. And Yeah.
Speaker 6:So
Speaker 7:Gary Schensler said it was also clear, and, of course, it wasn't also clear.
Speaker 1:Yeah. So what what's the what's the timeline there? What what are the different players? What do people want out of it? What what is the core, you know, kind of, crypto industry and both on the investor side and and company side want out of it?
Speaker 1:And and what are what who who would who would not want it to go through at least how the the crypto side has it in mind?
Speaker 7:Look. I think 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? Yeah.
Speaker 7:Someone just described it to me as 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?
Speaker 3:And the
Speaker 7:thing about after a field, you know, after a field goal, the other side gets the ball back.
Speaker 2:Yeah.
Speaker 7:And I think Congress really operates in kind of six to ten year windows.
Speaker 2:Yep.
Speaker 7:And, you know, it's on their mind, reform, regulatory clarity for crypto right now. And I think the transformational bill for crypto right now is very much that market structure bill. Yeah. We also want that stablecoin 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.
Speaker 7:And worst case, you end up getting the stablecoin bill only. But I do think that's not the most desirable outcome for the 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.
Speaker 7:Yeah. 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. Mhmm. And do we wanna have another ten 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 in a patchwork of different answers throughout the country, or do we want congress to answer that question for us now? Yeah.
Speaker 7: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's not a monolith. It's a broad new asset class, and stablecoins are a very big important piece of that asset class and a growing piece.
Speaker 7:As you guys saw, I shared with you the stats, you know, almost a quarter of a trillion dollars. I think you banged the gong for that stat. Locked in supply, growing enterprises across the world integrating Stablecoins. 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 Stablecoins is, well, what are the rules?
Speaker 7:So this bill that was passed yesterday on 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.
Speaker 1:What's your how would you how do you think about big companies getting excited about stablecoins and thinking or or institutions and being like, there's a lot of potential here. We should create our own stablecoin versus we should just figure out how to leverage this technology? Where where do you see the kind of line and and opportunities?
Speaker 7:Well, look, we already have two very dominant stablecoins, right, already today. Tether, USDT, and then we
Speaker 4:have
Speaker 7:USDC. So clearly, that's not winner take all. I mean, those two are both growing and they both have market share. So we think there will be stablecoins like those that will have network effects. But we also think at the same time, there are some businesses that are just so big And if they launch their own stablecoin, we could also see that too.
Speaker 7:I don't think we see a world where everyone I think we get asked this question all the time. Is there gonna be a world where every company has their own stablecoins? Yeah. We don't think so. We could be wrong, but that's not the view of how we see this evolving.
Speaker 7:We do see
Speaker 1:We had we had Aaron Aaron Frank from Lightspeed on earlier, and he was comparing certain companies would launch a stablecoin, and they'd it maybe would feel like Kohl's cash where it's like Yeah.
Speaker 7:Yeah. Good point. I don't have any of that nor do I. I don't have any of that. And and that's the thing.
Speaker 7:If I did, would you wanna use it on other platforms? Right?
Speaker 2:I mean, every bank could launch a Visa network competitor theoretically, but that doesn't necessarily make sense.
Speaker 1:Yeah. So so in your mind, is the is the broader market structure build the kind of thing that could catalyze a massive amount of new activity? And and from my view, you know, stablecoins have been getting adoption. There are a bunch of exciting use cases. We have a public American stablecoin, you know, issuer in Circle now.
Speaker 1: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. Is that the right framework?
Speaker 7:I think that is the right framework because, like I said, stablecoin is a big important piece of the pie and 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 wanna see it? I don't think it's a monolith. I think crypto as grows to a multi trillion dollar asset class, like any multi trillion dollar asset class, you have different factions.
Speaker 7: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 I think that's a little I see why they might think that if they think that it's this or nothing, but I don't I think that's a false choice. Mhmm. I think that we can have both, and this is an a really opportune moment to have both. And I think the the question that has beleaguered the industry really has been the question over securities, commodities, which agencies are gonna have jurisdiction.
Speaker 7:I think that's a bigger question, and I think it would be a real shame if we let this moment go to waste. You know, the irony too. So you have some stablecoins that were only stablecoin companies who were like, yep, Genius Act and move on. They don't wanna get dragged into this broader kind of a more omnibus package. Right?
Speaker 7:Yeah. 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.
Speaker 7:And with 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. Yeah. And it's very much part of it. 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.
Speaker 7: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, had they because of abuse potential abuses or or who are opposed to the crypto industry. They cite abuses.
Speaker 7:They cite fraud. They cite speculation. They cite Trump coin. And I I get all of those criticisms, but I'll tell you what. Had the market structure belt been passed, that would have answered a lot of those questions.
Speaker 2:Totally.
Speaker 7:The irony is if you would have had the market structure belt, you wouldn't have had a lot of the blowups that you've had in the past several years in the century. Is
Speaker 1:crypto truly coming home to 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 actually have an office stateside. Are are you seeing more and more momentum there with with some of this positive regulatory movement? Or is it or are you still seeing momentum around, places offshore, Singapore, I
Speaker 7:think look. Everywhere that you're gonna wanna develop does is going to have some rules that you're gonna have to follow. When I hear founders who say there is no regulate it's often not skimpy theor that there is no regulatory regime whatsoever. Sorry, Balaji, if you're watching. But I am seeing that onshoring a bit.
Speaker 7: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, but, you know, there's a lot going for The US.
Speaker 7: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.
Speaker 5:Mhmm.
Speaker 7: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 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.
Speaker 7:And and you saw courts carving back on that. So I think that was already we're in a dangerous spot, but the courts were maybe gonna save us, but you don't only wanna rely on litigation to save you, of course, because then you've already lost. But I think hiring talent is important. I think, you know, 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.
Speaker 7: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 gonna see more and more synergies emerge in use cases over time. And I'm gonna say what they are because, you know, we've seen that before in crypto. Yeah. A lot of overpromising, under delivering on use cases.
Speaker 7: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.
Speaker 7:So I am optimistic about the state of crypto in The US, but also elsewhere, and we invest in companies. We invested in Squads. We've announced that.
Speaker 1:Awesome.
Speaker 7:And I know Stepan, one of the founders of Squads watches your show. But Stepan'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 US.
Speaker 1:Awesome. Awesome.
Speaker 2:I I I wanna talk about the longer tail of regulation because it seems like the stablecoin bill is very straightforward, like the least the the the the least ambiguity there. Then you have the the 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 tail 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 fear, phase of? Because you have NFTs, crypto gaming, there's, you know, prediction markets. There's so many different crypto applications that trying to kind of do them all at once.
Speaker 2: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?
Speaker 7:View on that is is no because we can't just but we can't have an NFT bill, a bill for bank contracts
Speaker 6:or Yeah.
Speaker 2:Yeah. Yeah.
Speaker 7: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 two thirty. It applied broadly to platforms, and I think we need something similar here.
Speaker 7:So on the one hand, I would say it can't be so specific that it's like, okay. If you're a, you know, events contract platform, it's this rule. And if you're an NFT player because, again, we don't even know yet what will be created Mhmm. Really at the end of the day. We've seen some early use cases with product market fit.
Speaker 7:Obviously, chief example of that is Bitcoin. But what if we had had this conversation, guys, back in 2010? And you said, okay. We've got Satoshi's white paper, and there's this thing called Bitcoin. Let's pass some crypto regulation.
Speaker 7:It would have just been for Bitcoin. And that would have been a mistake because then couple years later on the scene, we have ETH. Then a few years later, we have Solana. So I think what we need to do so you don't wait for the end state
Speaker 2:Mhmm.
Speaker 7:To have any regulation. Right? You don't do regulation by I can tell you what we don't do. We don't do regulation by enforcement. Mhmm.
Speaker 7:You don't wait till the end state of things, but nor do you wanna get so with such specificity today and do the the current state of regulation by the end state of regulation. Mhmm. That you can't do either. And so I think what you have are some guiding principles, 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.
Speaker 7:So it's not like it's so specific. Yeah. It talks about and I think look. I think you have people like Hester Peirce, who's SEC commissioner, has written and given speeches on this of what that ought to look like. What is a decentralization test?
Speaker 7: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? Mhmm. And and and sure you're gonna have some outliers and new technologies emerge that you're like, okay. Does this fit neatly in the bill?
Speaker 7: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. Yeah. We do notice and comment. We do things like advisory opinions.
Speaker 7:Certain bodies, by the way, do do advisory opinions, not judges. And then if if all else fails, you do go and sometimes seek article three, 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, we were only getting unfair regulation by enforcement. And I say unfair because Gary Gensler basically picked what should have been the best companies equipped on the poster children for compliance and brought enforcement actions against them.
Speaker 7:And then the complete spectacular disasters didn't bring anything. So until after the fact. And so I think regulation by itself
Speaker 4:gotta have you we gotta
Speaker 1:have you and Gary on the show to to hash it out. I'm sure you guys have
Speaker 2:This is fantastic. Funny conversation about helping out.
Speaker 7:Yeah. Thanks having me.
Speaker 1:We'll talk to you. A good rest your day.
Speaker 8:Cheers. Bye bye.
Speaker 2:Up next, we have Justine Moore from Andreessen Horowitz. Incredible map knowledge dropped a fantastic Newmark map alert. Around AI image, AI video models. We're gonna have her take us through it.
Speaker 5:To the show.
Speaker 1:How are
Speaker 2:you doing? Can you hear us?
Speaker 1:Can you hear us? Hello.
Speaker 8:Oh, I can hear you guys now. Sorry.
Speaker 1:There we go.
Speaker 2:Hey. Hey.
Speaker 1: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 and come on the show.
Speaker 2:So we're on a incredibly bullish on market maps. I find them extremely interesting, and I think they got a bad rep a couple years ago. But I'm glad that you've stayed the course.
Speaker 1:You're pro strongly pro market map.
Speaker 8:Yes. The people love market maps. It's like you can guarantee a popular tweet if it has a market map in it.
Speaker 2:Absolutely. And I think people got kinda sick of like, oh, like, we know the playbook. We've seen it, but there's a playbook for a reason. It works. Yes.
Speaker 2: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?
Speaker 8:Yes. So I mostly do AI creative tools here at a sixteen z, so I spend, like, all my time testing all of the image, video, audio, etcetera. And, obviously, the past few months in particular, video has been, like, the thing. Yeah. There's been, like, v o three, obviously, which was a massive moment with adding the audio for the generations.
Speaker 8:Yeah. Heidra around the talking characters. Yep. The new mini max model, the new ByteDance model, SeedDance, which is in the arena already outperforming v o three. So it just felt like a good time to refresh sort of what's going on in the video space.
Speaker 8:Mhmm. 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 where it's either text to video or image to video. Most places do both where they actually take your input, generate have their own proprietary model that generates the video for you. So that's the the VOs, the Clings, the Runways, the Pikas.
Speaker 8:And then there's also now this emergence of what I call, like, multimodal apps, places like Crea and Flora and Visual Electric that enable you to run a bunch of models in one place. So 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.
Speaker 8:So that's sort of the distinction between talking avatars and lip sync.
Speaker 2: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, for example. Are you seeing a lot of that? Or, like, I guess, how how 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.
Speaker 2:And it might land as a consumer product, but it also might land as a b two b play.
Speaker 8:Most people are not at all rigorous and often don't even know at the beginning. Yeah. So what we actually saw with the first generation of AI video was it was only researchers making these, like, magical models.
Speaker 2:Yep.
Speaker 8:And they had no idea what the use cases were gonna be. 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. Mhmm. 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?
Speaker 8:How do you create workflow? And and therefore, do you go into 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 head avatar like holding your product and describing it.
Speaker 8:And that's something that like a v o three or a cling, the general video model companies won't do today.
Speaker 2:Yeah. Where are you seeing the strongest, like, low churn adoption of these tools? Because just personally, like, v o three was the thing that got me to subscribe to Yeah. Google Pro Max 25, which we can go into the names and how difficult it is to access these. But but other than that, there there haven't I haven't seen that many where, like, we've seen the ASMR storm troopers or something.
Speaker 2:But but it hasn't been clear to me that someone's building, like, the next Pixar, and they're actually thinking about it like mister 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.
Speaker 2:We see the Studio Ghibli moments go viral. So where where is, like, the true long term value playing out right now?
Speaker 8: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 Wonder Studios, Dream Studios. There's there's probably, like, 20 of them now. Yeah.
Speaker 8:One called Paracosm. That's that's really cool. 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
Speaker 2:Yep.
Speaker 8:And make content. I think the problem now in 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. Yeah. 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 characters.
Speaker 8:I don't know if you guys
Speaker 2:No. I don't know this. I haven't seen this.
Speaker 8:Brain rot characters are huge. So Okay. I can't even say the names here because they will sound ridiculous. Okay. It's people basically making images of, like, an animated talking baseball bat and, like, a ballerina whose head is, a cup of cappuccino
Speaker 2:Okay. Okay.
Speaker 8:And a shark who wears sneakers.
Speaker 2:Okay. But they're starting to build, like, a cinematic universe.
Speaker 8:Oh, it's massive. Yeah. Accounts have, like, millions of followers.
Speaker 1:The world isn't ready for Italian brain rock.
Speaker 2:Wait. So so so is it is it, is it, like, decentralized in the sense that, like Yes. I could just go and participate in this, like, broader trend?
Speaker 8:So yes and no. I would say there were a couple accounts that originated the first few characters. Mhmm. And then other people started participating using the hashtags remixing.
Speaker 2:Okay.
Speaker 8: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.
Speaker 2:The canon.
Speaker 1:They have Bombadieri Bombadero Crocody Crocadillo, which is a bombardier.
Speaker 8:Crocodile plane that he shoots bombs.
Speaker 2:This sounds like yeah. Yeah. Super, super viral.
Speaker 7:Yes.
Speaker 2:Your kids probably love it. It's wild. Before we go into more of the consumer side, talk to me about some of the, the more, like, niche, like, b to b use cases because I remember when, like, GPT 3.5 and we got four four, GPT four dropped. There were still, a lot of hallucinations, but you saw companies that were just like, yeah. Like, sure.
Speaker 2: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 in a in a video workflow, things like what runway was doing in the old days of just, like, green screening or the the stuff that, like, artists aren't gonna really get upset about because it just feels like a better, more advanced tool. Yeah. Are are a lot of these companies building tools like that, or is all the focus just on, let's one shot the next Oscar film?
Speaker 8:Yeah. It's a great question. There 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 OpenAI or whoever to play it in the game of, like, let's train the largest one shot best video model. Yep.
Speaker 8:So a lot of them are focusing on verticals like, Luma, which is a company we've invested in, did this really cool tool where you can upload, like, a a nine 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 dimensions of your video really fast.
Speaker 2:Yeah. Yeah.
Speaker 8:Or there's companies
Speaker 2:that just like a practical tool, but super useful for a bunch of creators that are filming vertical content probably, and they wanna distribute in a horizontal format, so they just do that.
Speaker 8:Yes. Exactly.
Speaker 4:Ton of
Speaker 2:that makes a ton of sense.
Speaker 8:Or or something like Higgs Field that it has all these really special effects, like motion laurels essentially. So you can take, like, an image of a car and just say, like, this is it. Like, here's a template of what a car explosion looks like. Make this specific car explode.
Speaker 5:Oh, okay.
Speaker 8:And then on the b to b side, we've seen a lot around, like, how do you scale marketing or l and or, like, executive presence type content? So, like, know, tools like Descript now allow you to take a video of someone talking and then change the word that they're saying
Speaker 2:Mhmm.
Speaker 8:By changing, like, cloning their voice Yep. Having them the the voice say the new word and then doing a new lip dub.
Speaker 2:Lip sync. Yeah.
Speaker 8:So you could have your CEO sending what looks like a personalized holiday message to, like, every single customer or something like that.
Speaker 2:Yep. Or maybe something worse with a phishing scam, but I'm sure we'll get it at some point.
Speaker 4:What do you what do you think,
Speaker 1:the long term ambitions of companies like Google with Vio and ByteDance with their model? What do you think they want out of this category? They obviously have a massive edge. I saw Anish was posting about Google's edge or YouTube's edge around IP with Vio. You can generate
Speaker 2:Yeah. Was going on there?
Speaker 8:That's crazy. The Disney thing.
Speaker 2:Is that like a real deal or is that just a beneficiary of like some sort of relationship?
Speaker 1:Yeah, then I want to get a sense of do Google and ByteDance, 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? What is this market? Is there a generalized market in the long run of just generating funny videos for the average consumer? Or is it gonna all be verticalized out where I want to generate ads?
Speaker 1:I maybe want to generate customized messages, but I I wanna understand like, this is a good overview of all the of the ways that you can generate content, but like how does the market structure evolve?
Speaker 8:Yes. Okay. Question, I have not talked to Google's IP lawyers and I'm not an IP lawyer. But my understanding is Google
Speaker 1:But this is legal advice.
Speaker 8:Right? Yeah. Exactly. This is
Speaker 2:And financial advice.
Speaker 1:All of the above.
Speaker 8:Our compliance team is gonna love this.
Speaker 2:Yeah. They're gonna
Speaker 1:love it. Sarcasm.
Speaker 8:You can I 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 what can be posted on various Google properties? And if that content gets monetized, how it ends up going to the end rights holder. Yep. And so that's sort of the the working theory right now about like why VO three can generate IP content and not get sued when a lot of other people are struggling with that.
Speaker 2:Yeah.
Speaker 8:In terms of the market dynamics, it's so fascinating the question around Google and ByteDance and eventually I think Facebook I hear is gonna do more in video soon as well. 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, AI is such a massive shift in consumer behavior that, like, you want if if you wanna own the interface to consumers, you probably wanna own text, image, and video generation as well. Mhmm. And they have the resources in terms of data.
Speaker 8:Like YouTube, for example, is a perfect example of this.
Speaker 2:Yeah.
Speaker 8:They have a ton of compute. They have a ton of money, and they can hire the best researchers to build the best models.
Speaker 2:Yeah.
Speaker 8:I think the question as you sort of alluded to is like, do they 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? My honest take on it so far has been like it takes so long in the big company product teams to get stuff done 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 gonna figure out if they can catch up with some kind of cool new consumer app later.
Speaker 2:Yeah. Yeah. Mean, I
Speaker 1:My question is like how much, what will the market actually look like for the average consumer wanting to generate images and video or will it just be something that people default to ChatGPT 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, etcetera.
Speaker 2:I mean, it seems like it's a killer killer moat for Google Cloud platform to have v o three as an API even if Google can't figure out how to productize it fully. It's like they do seem to have a real moat. I wanna get into that about, YouTube is obviously an incredible training data resource. Yeah. You mentioned that there was another company that that just surpassed them.
Speaker 2:Was it Tencent, you said?
Speaker 8:ByteDance.
Speaker 2:ByteDance. That's right. So I I have a question about that because, obviously, with CodeGen, GitHub has a lot of public repos that people can probably just scrape. 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 a flight and and train somewhere in Malaysia or something.
Speaker 2:Yeah. You can't do that with YouTube. Like, it's just too much data. And so my question is is how durable how much should we be thinking about a durable data moat 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.
Speaker 2:But I don't know. There's so many other there's so many other ways to attack any of these model developments Totally. That there's a lot of different options.
Speaker 8: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 Sure. We've seen companies like OpenAI will Yep.
Speaker 8:Will scrape YouTube as well to train their models.
Speaker 2:Yeah.
Speaker 8:I think ByteDance also, like, you know, here we think of YouTube and Facebook and whatever here in The US, I mean, as Yeah. As being the big host of content. But, like, there's all these massive companies in China, like ByteDance who have their own, have have their own user generated content on, like, their version of TikTok and their version of YouTube and their version
Speaker 2:of these reposts of American videos over there. So it's not like even has a unique flavor. Probably can generalize pretty well. Right?
Speaker 8:Totally. Though yeah. Like, I was one of the very early users of all of 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 US models.
Speaker 2:That makes a ton of sense.
Speaker 8:Oh, okay. The other 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. Mhmm. Because essentially, you can't just feed a video into a video model and assume it can understand what's going on and and pull out the relevant info.
Speaker 8: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's interacting with the background. Yep.
Speaker 8:And that quality data is what drives quality in the video models.
Speaker 4:Mhmm.
Speaker 8: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 these dense labels for the video data.
Speaker 2:Yeah. Well, how does Midjourney fit into all of this now? It's such an interesting company because Yeah. No venture dollars, this, like, behemoth kind of quietly hiding in a Discord server still. I saw some examples of video.
Speaker 2:It looks fantastic. Seemed like they hadn't added audio yet, but how how do they fit into the whole the whole piece? Because it seemed like early on, they they developed a really great, feedback loop for the data that maybe wasn't happening with some of the other model providers.
Speaker 8:Yeah. So the mid journey model came out this morning, really conveniently, like, ten minutes after I put out my market map without mid journey video because it's not yet available. Yeah. I was just playing around with it too. It's it's really cool.
Speaker 8:They do image to video. Okay. And they and so they don't do text to video, which is actually sort of easier. They can start with their the super high quality images that they generate on the platform and then animate those. I think they have, a low motion and a high motion setting.
Speaker 8:From what I've tested so far, it's 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. Mhmm. 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.
Speaker 2:Yep.
Speaker 8:That sort of thing requires a very, very large and costly, usually, like, text to video model that is more difficult to train. Whereas mid journey, I mean, I 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 and fine tune it on all their own data.
Speaker 2:Yeah. Yeah. I've noticed v o three 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
Speaker 1:it'll get kind of mixed up. Yes. But yeah. Are you, as as all these different models have progressed, I always remember, Brad and Trevor McFedrys and just how early he was to to what I think will be this like new wave of
Speaker 2:Is that Lil Makayla?
Speaker 1:Yeah, Lil Makayla, which was like basically CGI So very early, think we're going 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, like how bullish are you on sort of like entirely AI creators getting getting real adoption following turn followings turning into real businesses? I'm I'm sure you've you've followed a bunch of them already.
Speaker 8:Yeah. I'm I'm personally super excited about it because it kind of separates the content from the character. Like, now, you know, before AI, if you were on Instagram, like, you were both the character and the person coming out with the content. And so you had to, like, look in a way and present yourself in a way and in a way that was, like, interesting to the Instagram algorithm. And now it's like anyone with a good idea can create a compelling character.
Speaker 8:Mhmm. And so I think some of those are human characters. I've already seen way too many examples in my Reels feed of OnlyFans models who promote themselves with AI avatars of themselves now, which works shockingly well. Yeah. There's some photorealistic human influencers, but honestly, some of the more interesting ones are things that could never be influencers before AI.
Speaker 8:So there's one called, like, raccoon stole my iPhone, and it's a it's an AI raccoon influencer. There's, like, AI capybara influencers. There's, like, mystical creatures. All of these things that just come out of people's imagination.
Speaker 1: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, Mountainhead, not Fountainhead.
Speaker 2:Oh yeah.
Speaker 1:Mountainhead, the movie, core overarching theme was that basically deep fakes or AI generated content had gotten so good that it was causing global unrest. Did resonate at all? It does feel like I now have multiple times a day I'm seeing content online and it's like getting, we're both in the community notes program. So it's like you see content community notes. One person says, it's not real.
Speaker 1:Look at this link. Was this image. They redid it. Another person says, it's real. Look at this link.
Speaker 1:So it's like, I just assume that everything's fake and made up unless I see it with my own eyes. But I'm curious if you if you, if it resonated all with you.
Speaker 8:So I've not I largely consume AI slop. So I've
Speaker 5:not seen
Speaker 7:the movie.
Speaker 8:I should watch it soon.
Speaker 1:You should watch the movie, the motion picture on slop.
Speaker 8:Yeah. Once they have that, I will watch the the full film. But it's so inter we talked about this a lot actually with audio models with the last, like, election cycle. Because video, I think, wasn't there yet to have convincing deepfakes. Mhmm.
Speaker 8: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, 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.
Speaker 5:Yeah.
Speaker 8: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.
Speaker 2: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, this the the the capital's burning or something, and it's from years ago or or just, you know, speed up a video, slow it down, edit it out. They would do this with various politicians, you know, cut out the ums and uhs and they'll sound sharper, add a bunch of gaps, and all of a sudden they sound like they're slower.
Speaker 1:Yeah. It even, you know, we're we're here in LA and and when all the imagery was coming out of the the protests from a couple weeks ago, it was like burning Waymo's. Yep. Kind of looks like something you generate with VO three. Totally.
Speaker 1:Just because it was so symbolic and just such a crazy image. And then, like, make an image of a guy with a Mexican flag riding it, doing burnouts around a a car that's on fire. And it's like, that looks like
Speaker 2:even and even the 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 and you drive around and be like, oh, there's not that much of
Speaker 8:other interesting thing is, like, even real footage can be manipulated. Totally. Like, any kind of story can be manipulated in a way like AI or
Speaker 1:Are you seeing, I think like, you know, there's exciting, companies like Worldcoin, you know, doing like proof of human. Are you seeing any infrastructure players trying to do like 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? You know, proving through the metadata and some type of like public, setting. Is there is there any pitches, from from that side?
Speaker 8:Yeah. So largely, honestly, today, that has come in two places. One is the model companies themselves will often watermark the content in some way, like the v o three generations has little v o three eleven labs, which is 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.
Speaker 1:That's cool.
Speaker 8:Which which is pretty cool. 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 wanna 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. 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.
Speaker 1:Yeah. Totally.
Speaker 2:Very cool. Well, thank you so much for stopping by. We could talk for another hour. I have so many more questions in the in our doc, but, we'll have to have you back. Thank you so much for stopping by.
Speaker 1:Thanks, Thanks, Justin.
Speaker 2:We'll talk to you soon.
Speaker 1:Great chatting. Have a
Speaker 5:good one.
Speaker 1:More breaking news. NVIDIA to drop humanoid robots that will produce NVIDIA GB 300 chips in q one of twenty twenty six. Nick says, holy based. Is so So NVIDIA Foxconn in talks to deploy humanoid robots at Houston AI server making plant.
Speaker 2:Wow, that is extremely I don't
Speaker 1:totally understand this. I guess Foxconn has been training the robots to pick and place objects and insert cables.
Speaker 4:Yeah.
Speaker 1:I don't know if this is marketing.
Speaker 2:We've asked
Speaker 1:a bunch of robotics experts about humanoids. And so far, I don't have the confidence that this is actually a super great use case for them.
Speaker 2:It's just the definition of what is humanoid. Because you you go to, like, a Ford f one fict f one fifty 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 it's humanoid now. You know?
Speaker 2:But, like, you could, like, retrofit every
Speaker 1:bicep definition. Totally.
Speaker 2:I mean, 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 the the three axis pick and place, you know, pick it up, put it over here, that type of stuff. Just going to humanoids is just it's like, well, will it have five fingers or will it have a just a grabber?
Speaker 2: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, can just have 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 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 And this seems like, you know, a step in the right direction in the sense that it's a very defined task. I think when people think humanoids they think some like my new Turing test is humanoid robotics will be here and when they can put up a six minute Nurburgring time in a manual.
Speaker 1:Yeah. Gated manual.
Speaker 2:In a gated manual. Because at that point, the they have to not just be a self driving car, but they have to be able to, you know, negotiate the, the the wheel and the stick shift so so efficiently and so quickly Yeah. That they are truly performing.
Speaker 1:Yeah. And a manual and a manual can be weirdly, like, probable probabilistic. Right? And that, like, you're like, you know, you can move the the
Speaker 2:Synthesize a lot of data.
Speaker 1:Yeah. It's not it's not like, you know
Speaker 2:Yeah.
Speaker 1:Perfect system. Right?
Speaker 2:It's You're not gonna you're not gonna put up a a sub seven minute Nurburgring time with the Joe Biden walk.
Speaker 1:That's right.
Speaker 2:You're gonna have to be moving fast. Those actuators are gonna have to be
Speaker 1:That's right.
Speaker 2:High speed. So, yeah, I I I I don't know where all this goes, 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, cool to see a lot of money pouring into the sector Yeah. From very big companies.
Speaker 1:So Foxconn will be announcing their robots in November and then deploying them shortly after in our year 2026.
Speaker 2:Mean, Foxconn seems like the right builder for this. Unitree is already like feels like it's scaling up to the point where, like, Unitree 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. 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?
Speaker 2:Or or should we do be just doing things that are more specified? Because if you're if you're if if the whole point of these humanoid robots is just AI server making, just assembly, just one one spot on the manufacturing line could probably be a much more specialized robot. But it will be cool to see. I'm sure we'll see a lot of viral videos about it. It'll be very cool.
Speaker 1:I invested in the company making robots for data centers.
Speaker 2:Oh, yeah.
Speaker 1:And they intentionally chose not to make it humanoid form factor.
Speaker 2:Which,
Speaker 1: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? You can
Speaker 2:use wheels. Mean, data centers have the most perfectly polished floors with like no dust at all. Like, it's it's the the the perfect environment for a wheeled use case. At the same time, you probably need to have a very specific actuator for like unplugging and plugging the cable back in. Yep.
Speaker 2: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 acts 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. We have our next guest in the studio, George Hotts. How you doing, George?
Speaker 2:It's good to hear from you.
Speaker 1:What's going on? Welcome.
Speaker 2:Can we hear you?
Speaker 5:Oh, can you hear it?
Speaker 1:Yes. Yes.
Speaker 2:I can hear you. Gotcha. Well, let's kick it off with something, simple. I wanna take your temperature on AGI timelines, p doom, the the easy and fun stuff.
Speaker 4:Don't know what AGI means, and I don't know what you mean by doom.
Speaker 2:No? Is are are are these terms just, like, entirely irrelevant? I mean, now we 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 the conversation maybe shifting to, like, the AI generating more economic value than humans. Is that a relevant metric to track?
Speaker 5:Machines have been generating more economic value than humans since the industrial revolution.
Speaker 2:Is there some is there some other metric that we that we should be tracking? Or is it just, like, irrelevant?
Speaker 5:You're just talking about, like, hype. Like
Speaker 2:Hype. I don't know.
Speaker 5:I mean, I I don't like, I I don't know what you mean. Like, you can talk about concrete things.
Speaker 2:Yes.
Speaker 5:The term, like, AGI means nothing. Right? Like, computers, everything that's a Turing machine is a general purpose computer. Is that what you call intelligence? I don't know what you mean.
Speaker 5:Is a linear regression intelligent? What if it's big enough? The Chinese group does know Chinese.
Speaker 2:Yep. What what I mean, what about your your decision to get on a spaceship traveling at point nine c away from the
Speaker 4:Oh, yeah.
Speaker 2:From the Earth? Like, how close are we to that? Are we closer than the last time we talked, which was, like, a couple years ago, and it seemed like it was maybe going to happen within your lifetime? Has it moved at all?
Speaker 5:Yeah. I don't know. I don't know if I'm actually gonna get that spaceship, but it's kinda like in an ideal world what I would wanna do. You know?
Speaker 2:Yep.
Speaker 5:Just just just back away and chill and don't look back. Actually, you can't look back.
Speaker 2:You can't look back.
Speaker 1:Never look back.
Speaker 5:They're all there.
Speaker 2:You need the you need the blast shield. Right?
Speaker 5:You need the information shield.
Speaker 2:Information shield? What do you mean?
Speaker 5:Oh, that's how they're gonna get you.
Speaker 2:Okay.
Speaker 5:Right? I mean, okay. So, like, here's a way you can think about AI. Right? Yeah.
Speaker 5:Imagine there were 10 CIA agents assigned to you. Okay. And they're running at a thousand x real time. So they're like hyper fast CIA agents that devote their entire lifespan to your day. Mhmm.
Speaker 5:And they're trying to manipulate you. Maybe to get you to buy things, maybe to get you to vote for a certain guy, whatever. But, like, that's what you're gonna be up against with AI. What we're currently building, what what what if you think about the biggest companies in AI, what they do is advertising. What advertising is is just manipulation of humans.
Speaker 5:So you're gonna have a team of CIA agents thinking about you and trying to manipulate you at all times, and now you see why you wanna head away at the speed of light. Right? Mhmm. Even CIA agents can't beat that.
Speaker 2:Is there is there some real world where there's, like, a capital war and I'm paying for a more powerful ad blocker?
Speaker 4:Yeah. I mean, that sounds good.
Speaker 5:Like, another question is kinda to say, like, okay. If you think that you either think the current, like, capital accumulation dynamics are gonna continue and that the rich are gonna continue to get richer. Mhmm. And if you believe that, the question is kind of, well, how many people are gonna survive in the future? How many people are gonna have any modicum of independence?
Speaker 5:Mhmm. Right? Like, you have some far AI people who think that there's gonna be a singleton. Right? Who think that there's gonna be literally one.
Speaker 5:Right? Yep. You know, some people maybe think it's 10. Some people, a 10,000. Some people think that all the humans will get to continue to exist as independent entities.
Speaker 5:Are they already independent entities? That's a question. Right?
Speaker 4:Don't
Speaker 2:know. Good question. I mean, if you were trying to put it in, the form of a bet, human population above or below 8,000,000,000 in 2030.
Speaker 5:Above, I think. I would
Speaker 1:just continue that normal trend.
Speaker 5:Oh, I didn't know what the trend says. Yeah. Just go with what the trend says. I I don't think there's gonna be any discontinuity as to any trends really. Well It's be like
Speaker 2:Yeah. I mean, I mean, at some point, but but the question is, like, how far out do you have to go until you start seeing these effects?
Speaker 5:What do you mean by human? Right? What about someone who lies in bed all day and watches TikTok? Are they human?
Speaker 2:Yeah. That is odd. They kind of drop out of society.
Speaker 1:I think I think, question that 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 look to look after their own safety in the context of AI. Is that at all?
Speaker 5:I just 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. Like, I don't know.
Speaker 2:Yeah. But, I mean, people still look to you as, like, an example of, like, someone who might have
Speaker 5:Answers? No. I don't have any answers.
Speaker 2:Not not necessarily answers. Just like
Speaker 5:But you can buy my shitcoin. Here. Did I show a shitcoin? You go. Just click this QR code, and you can buy a George Hotts coin, and that will give you answers.
Speaker 5:You will find satisfaction and fulfillment in your life after purchasing a George Hotts coin.
Speaker 2:Is that is that the end state? We all have our own coins, I guess.
Speaker 4:No. No. No. No.
Speaker 5:I I don't mean it like that. I mean, it, like, I think that a lot of people are like, they don't really know what they're looking for.
Speaker 2:Mhmm.
Speaker 5:And that vacuum is is a very, you know, it's very dangerous and it's gonna be filled by dumb shit and don't have that vacuum. Right? You gotta gotta stand for something, you know, or something. I don't know.
Speaker 2:Yeah. I mean, do do you think that there's a chance that someone is able to take a stand and and actually bend the arc of of AI progress in the way that I mean, it happened with nuclear. Right? Like like, nuclear development did stall. There was a stagnation in real world build out of nuclear capability on the energy side.
Speaker 5:Yeah. I mean, there's a few things about nuclear that make it different. Uh-huh. So nuclear, even as a weapon, is incredibly hard to deploy tactically. Mhmm.
Speaker 5:Right? So so if a country has has nuclear, weapons, they're aside from, like, a mutually assured idea, they're not all that useful. Yeah. 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.
Speaker 5:Yeah. Right? Russia has some tactical objectives they might wanna accomplish, but nukes aren't really gonna do it. Right? Mhmm.
Speaker 5:And then from a pure realpolitik perspective, not even from a, like, a oh, like a taboo moral perspective. Mhmm. Like, what do do you want an irradiated pile of rubble? Like, that's what you're gonna get. No.
Speaker 5:What you want is drones that are hyperspecific and can take out exactly who you want, can control areas. Right? So, like, as a military technology, nukes are not that good. AI is way better.
Speaker 2:Yeah. But what about it as an energy technology? It feels like the the 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 build out. And if if if the AI doom scenario, whether it's real or not, becomes so memetically 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?
Speaker 5:Really think that's the reason for nuclear. I think it has more to do with why we can't do other big infrastructure projects in this country. Right? Like, it doesn't have to do with the new we also can't build dams. Right?
Speaker 2:Yeah.
Speaker 5:And if you look like, that's the thing. If people think that there's some weird taboo around nuclear. Right? But then, okay. Look at hydroelectric.
Speaker 5:Right? No taboo around hydroelectric. But China leads in installation of both nuclear and hydroelectric, and coal, and everything. It's almost like they're correlated. Right?
Speaker 5:Yeah. So the thing is not there's a specific fear around nuclear. It's like, you know, The US decided that they're a developed country. We're not gonna develop anymore because we're already developed. You see the d on the end.
Speaker 5:Right? Like
Speaker 1:Interesting. Yeah.
Speaker 2:Is that so so is that just cultural then when you or, like, the malaise sets in? Would you expect that to happen to China when they catch up?
Speaker 5:I don't know. I I yeah. I mean, maybe it's just, like, this normal story arc of, like, you know, it's it's
Speaker 4:I don't know. I don't know.
Speaker 5:I I think that, like, you have a real problem when the kids can't live better than their parents. Yeah. So
Speaker 4:but I I I don't have anything more to speculate on that.
Speaker 2:Did you have more context on on China and specifically in, like, the AI context?
Speaker 5:Like US electricity looks like this and China electricity looks like this.
Speaker 2:Is that all that matters?
Speaker 5:Pretty much. Yeah. I mean, that's a pretty good proxy for everything. Right?
Speaker 2:Yeah.
Speaker 5: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.
Speaker 5:Did you decrease government spending? Mhmm. And did you increase total electricity production of America? Those are the only two numbers I care about. Those will capture everything.
Speaker 2:Why does 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.
Speaker 5:Hell is AGI?
Speaker 2:I don't
Speaker 5:know what this is.
Speaker 2:Like, in in this
Speaker 1:formulation Never seen it. It.
Speaker 2:Like, formulation, it's that it's that it's that numbers. Yes. Yes. Yes. But but it but it's an extra lever on on labor and capital, and it creates more GDP that they can be taxed to pay down the increasing amount of debt.
Speaker 5:Super super excel.
Speaker 2:Yes. Super
Speaker 5:Excel. What is what is what is Super Excel do that normal Excel doesn't
Speaker 1:Let's give it up for better Excel.
Speaker 2:Yeah. Yes. Yes. We need that.
Speaker 4:Excel two point o. What? Yes.
Speaker 1:The thing is Excel was the the final piece of software. And then but in order to add another, you know, a $100,000,000,000,000 to to global GDP, we needed to, like, kind of rebrand it. And so now we get AGI.
Speaker 5:GDP is the the complete it's biggest bullshit thing ever. Right? Like, I always joke with my friend and I that we're gonna start companies and be billionaires, and I'll tell you how we're gonna do it. So I'll say, alright? I start a company.
Speaker 5:He starts a company. We both write contracts to each other.
Speaker 2:Yep.
Speaker 5:Right? Like, I'll buy something from him for a million dollars. He'll buy something from me for a million dollars. We'll just do this real fast. We'll keep passing the money back and forth.
Speaker 5:Woah. Look at our revenue. Wow. That all contributes to GDP. Wow.
Speaker 5:We made we're billionaires overnight. Right?
Speaker 2:Yep.
Speaker 5: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.
Speaker 5:Right? Can't you can't have services. No. No. Like, literally literally, you take the steel out of the ground.
Speaker 5:You grow the corn. Okay. That's GDP.
Speaker 2:But is it I mean, if if that GDP is fake, is not the is the deficit not fake? Like, is is government spending less that
Speaker 5:shit to people.
Speaker 4:It's not fake.
Speaker 2:But can you just tax the fake the fake money? Like, if you tax your scenario where you're generating a billion dollars in fake money
Speaker 5:You can't tax the fake money because we're passing the same dollars back and forth. Minute you tax it, that falls off so fast.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 5:You can only tax productive work.
Speaker 2:Is is AMD doing productive work right now?
Speaker 5:AMD's doing alright. Yeah. Either NVIDIA is really overvalued or AMD is really undervalued. It has to be one or the other.
Speaker 2:How does it all play out? Like, what what does AMD actually need to do to get back on track or realize their potential?
Speaker 5:NVIDIA needs to stumble. I mean, it works for AMD and Intel. Right? Like, so AMD ended up beating Intel in the entire like, no one would buy a data center Intel CPU anymore. Yeah.
Speaker 5:And it's just because, well, you know, they stumbled, and now Intel owns that market. Yeah. So, you know, AMD just sits there in second place.
Speaker 2:Okay.
Speaker 5:They're pretty they'd be at 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.
Speaker 2:Is is DGX Lepton, like, their cloud offering a potential stumbling block, or is it or is it the right move for them?
Speaker 5:I don't know what that is. What's an NVIDIA cloud shit?
Speaker 2:Yeah. Exactly.
Speaker 5:Clouds don't. Clouds don't. You could you could break AI down basically into, like there's, like, five five tiers. Right? Like, at the base level, you have, like, electricity and data centers and land and, like, things like that.
Speaker 5:Tier two are, like, TSMC, ASML, Samsung, Intel. Right? Fabs. NVIDIA, AMD, OpenAI, Anthropic, and then on top, you have, like, completely worthless things like Kurzor and Windsurf. You know, these character AI, all these people would think, woah, with the app, we're gonna we're gonna get the ARR.
Speaker 5:No. That worked to the web. It won't work for AI, and I can go into why, but it's kinda
Speaker 2:I want I want to
Speaker 1:hear why. Keep going. Keep going.
Speaker 5:Basically okay. So, like, here's the difference between AI and and web. Yeah. When when you wanna run a service like Gmail, one server can serve 10,000 people easily. Right?
Speaker 5:And there's no demand for, like, better Gmail. Right? It's not like it's not like I can click and get, like, yeah, you could buy Gmail Pro and 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.
Speaker 5:Maybe there's a limit to the speed, but, like, when you're at, a thousand tokens per second, I want the biggest model in the world. Right? Like so there there there's very little limit on on that. But suddenly, you can't serve one, 10,000 users from one server anymore. Mhmm.
Speaker 5:Right? 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 and the WinServs. They aggregated to the OpenAI and the Andropix. Right? Mhmm.
Speaker 5:Nobody nobody nobody who built, an email client survived. They all got eaten up by the the tier fours of the web. Right? The Googles, the Facebooks, all of these, like, app providers. Right?
Speaker 5:Where's Zynga today? You know? Like, this already happened. Right? People just don't where's Zynga?
Speaker 5:Oh, Zynga's gonna be the next thing, man. Like, no. It's not. Facebook ate all of that value. Right?
Speaker 5:Google ate all the value from all the people building on top of Google. So the tier fours ate all that value.
Speaker 2:Yeah.
Speaker 5:So OpenAI, Anthropic will eat all the value from the cursors and the windsurfs of the world. They'll acquire some of them. They'll Mhmm. Compete with some of them. Right?
Speaker 5:Same as you saw on the web. But I argue that the tier fours aren't even gonna have value because the tier fours are this ain't the web. This ain't where you can have one server serve lots and lots and lots of people. You know, I'm running o three. I'm running you know how much I cost to open AI every month?
Speaker 4:I pay the $200 a month, and I cost them a lot more than that. A codex
Speaker 5:you can now click on codex? Yes. Spin up four nodes. Yeah. Why would I not click four?
Speaker 5:It's not my computer. You gave me the button. Hey. I'm just using it.
Speaker 1:George Hotz single handedly bankrupts So it it is $300,000,000 company.
Speaker 2:No value in just being the the the front end to AI applications to be, like, the the the front door, just the the the default button because we see these we see these these these 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 are just kind of, like, defaulted into the app that they installed whenever. And so even if Gemini gets better in terms of the actual performance metrics, people don't switch from OpenAI to Google over the
Speaker 5:next It's so negligible. You gotta make something 10 x better. Right? You gotta make something 10 x better. So, like, the this whole game is OpenAI's unless they stumble.
Speaker 4:Sure.
Speaker 5:I'm switching to Gemini because it's 20% better. I have downloads a new app and think about a whole new thing. Right? No one's
Speaker 2:gonna switch. Is there is there a chance for a company to kind of come out with something that's 10 x 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 four o or and then four. 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.
Speaker 2:Like, a 10 x, what you're describing like a 10 x improvement feels like that kind of, like, qualitative binary shift. Is that possible with just scale, or is this something that we need a different model for?
Speaker 4:I don't know.
Speaker 5:I don't know. I would bet majority still on. Like, these big labs are also attracting the talents. Mhmm. But it is also, like it it's pretty commoditized, lot more so than, like, Google search.
Speaker 5:Mhmm. Right? Like, you can look at people track how far open source is behind. It's not that far behind.
Speaker 2:Yep.
Speaker 5:So, no. I don't know. I think this game is mostly gonna be ChatGPT's. I think Elon's aware of this too.
Speaker 2:Mhmm.
Speaker 5:That's why he's trying to go 10 x bigger with the data center.
Speaker 2:Yep.
Speaker 5:We'll see. Maybe it'll work. You know? There's there's someone to bet on. Anthropic, I'm not that bullish on, but maybe.
Speaker 2:You kinda predicted the, the pretraining wall, but that's not a refutation of the better lesson, and we're gonna see similar scale play out in reinforcement learning, or is there gonna be something else that we're building the big data centers for?
Speaker 5:There's something that we don't understand Yeah. In terms of data efficiency. Mhmm. So, like, when you think of how long it takes a GPT 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.
Speaker 2:Okay.
Speaker 5:Whereas a human trains on megabytes.
Speaker 2:Yeah.
Speaker 5:Right? How is it that if you take all the text that you've ever heard in your life and you you put it to Whisper and you you transcribe it, it's gonna be a couple megabytes, 10 megabytes, maybe a 100 megabytes. Yeah. So humans have this thousand x data efficiency Mhmm. Advantage.
Speaker 5:And we're gonna have to fix that if we want, like, reinforcement learning to work, especially, like, reinforcement learning that you wanna do in the real world. Humans could do humans can learn from very few samples.
Speaker 2:Yep.
Speaker 5:And, yeah, I think that, like, it might be okay if these foundation models train unsupervised on lots and lots of stuff. But yeah.
Speaker 2:Is that is that something that somebody's working on just like a 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.
Speaker 5:Like, has there ever been a breakthrough? Right? Like, think GBGs are a breakthrough.
Speaker 4:Well, they weren't.
Speaker 5:Like, you just if you watch the the world, it was
Speaker 2:just it was all just Smooth curve.
Speaker 5:But but but but what I will say about AI scaling laws Yes. Oh, man. You see, like, people get excited about AI scaling laws, but here's a pitch that'll kill your excitement immediately. Ready? AI scaling laws.
Speaker 5:You can put in exponentially more money to get linear returns.
Speaker 2:Yeah. Exactly. Do you you believe that the real value is investing in in humanoid robotics then? Have you heard this theory? So so it it so, I mean, if you if you put exponential more money into humanoid robotics, assuming that they work and assuming you can Right.
Speaker 2:You you can like, you make sanctions as many robots. You get 10 times as much output.
Speaker 5:Anyone anyone who wants a humanoid robot has never worked in a factory in their life.
Speaker 2:Okay.
Speaker 5:Right?
Speaker 2:Break it down.
Speaker 5:Wants a humanoid. Yo. Yo. It's gonna walk around. It has legs.
Speaker 5:Right? No.
Speaker 4:But here's what I want. Yeah.
Speaker 5:Yeah. Because we got a laugh track. Alright. Can you show me a robot arm that's capable of putting a screw in something?
Speaker 1:Probably. Yeah.
Speaker 5:Put the screw in the thing.
Speaker 2:Yeah. No. No. No.
Speaker 5:Not like you carefully jigged up the screw and had a screw dispenser, 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
Speaker 2:screwdriver. No. We're no. No. We're we're we're not close, but also it feels like we're not far.
Speaker 2:It feels like that's what?
Speaker 1:Five years? Ten years? I feel like humanoids 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 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 they very well might work for some things. And, like, they just humanity might brute force it because we saw it in a sci fi movie
Speaker 2:No.
Speaker 1:You know, thirty years ago.
Speaker 2:Why? Why? Why are we coached
Speaker 5:on human? This is as dumb as self driving cars wise. Right? And nobody learns their lesson, and people like Kyle Vogel should be ashamed of themselves. Like, they really should.
Speaker 5:These people who go and raise large amounts of money for another thing that, like, they should know they should know better.
Speaker 2:Mhmm.
Speaker 5:Right? Here's basically like, remember in 2012 when Google said that, you know, my my my 12 year old daughter would never have to get her driver's license?
Speaker 2:Yeah.
Speaker 5:Come on. That's nonsense. Right? And, like, now, okay, they shipped Waymo. Mhmm.
Speaker 5:It's in a few new cities. Mhmm. They're teleoped. Right? People don't have
Speaker 1:How how teleoperated are they in your opinion? Is it is it effectively one to one?
Speaker 5:It's more than one to one. There's probably about I would say there's 1.2 operators per car, but it's not they don't have a steering wheel and pedals. Yeah. It is it is an autonomous system Yeah. That they're probably doing some higher level inputs on.
Speaker 5:They're definitely, like, say, when you can be aggressive when you should slow down, you know, whether you can turn to the stop sign or not. Yeah. You know, again, like, here's here's the simple reason to know that it's like that. Right? There's definitely some Kelly off at the Uemos.
Speaker 5:Right? Yeah. Have you ever seen a picture of that room? No. Yeah.
Speaker 5:Why not?
Speaker 2:I've always thought it was an ace up their sleeve because, like, if if there's a lot of pressure on them to say these Waymo's aren't safe, they can pull pull the the 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.
Speaker 5:Yeah. Yeah. Like, you the fact that you've never seen that room tells you that it's way worse than you think it is. Right?
Speaker 2:Okay.
Speaker 5:Tells you that there's way more teleop than you think it is. If it was really one person supervising 10 cars, Google would post those pictures all over
Speaker 4:the place.
Speaker 2:Yes. Yes.
Speaker 5:Yes. Any pictures. There's so Cruise that actually came out of the lawsuit, I think it was, like, 1.5 or 1.7 humans per car. Right?
Speaker 2:Or or vice versa. Like, right, 1.5 cars per person. Right? No. No.
Speaker 2:Wait. More people than cars?
Speaker 5:Yeah. That's what he's saying.
Speaker 2:That's It's that because an Uber only requires one person.
Speaker 3:Yes. Yeah.
Speaker 1:But but so so maybe the real innovation is just allowing somebody to get in a car with and not have to talk about the weather or or, you
Speaker 5:know Exactly. I'll pay more for that. I'll pay more
Speaker 4:for that.
Speaker 2:Yeah. But I mean, is there any hope that we drive this down and we get to two cars per person and four cars per person? It starts doubling exponentially and eventually, like, we are there.
Speaker 5:I mean, yeah. Like, it's obviously going to happen. Right? Yeah. It's obviously eventually gonna happen.
Speaker 5:If you wanna 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 Teliak.
Speaker 2:You can
Speaker 5:go press FSD, and that's real AI.
Speaker 2:Yep.
Speaker 5:And, well, you can see how good it is. Right? Yep. Would I, take a nap in there even for five minutes? Go a and l.
Speaker 4:Yeah. You'd be super. Right?
Speaker 2:How are things going on the comma side? Give us the update there.
Speaker 5:Pretty good. You know? We're we're we're on track to we're on track to be two years behind Tesla. So There you go. So so two years behind Tesla.
Speaker 5:But, you know, here's why we win. Right? Like, because, like, it's cheap. Okay. So when you think about self driving cars, it doesn't look anything like the rollout of Uber.
Speaker 5:Mhmm. Right? Or Airbnb. When you roll out something like that, you're trying to roll out a two sided marketplace.
Speaker 2:Mhmm.
Speaker 5:You gotta spend tons of money on customer acquisition costs. You gotta make sure that you've perfectly matched that marketplace right away because if drivers aren't getting rides, they're gonna leave the platform. If riders have to wait too long for drivers, they're gonna leave the platform. So it's this careful balancing act. But once you get this marketplace, you've got you've got a moat.
Speaker 5:Right? Switching costs are real high. Trying to get everybody to switch at the same time at the selling point and never do it. Self driving cars don't look anything like that. Self driving cars look like scooters.
Speaker 5:The only thing that it's gonna take to roll out big fleets of self driving cars capital. Right? It's just strictly a capital market. You could just I can if I look at a city, I can calculate how many waymos there are. If I wanna build my own network and deploy that network and run at a lower cost, it's straight up capital.
Speaker 5:Easiest thing for investors to calculate. Very little risk. So self driving cars are gonna be this awesome race to the bottom. Right? It's gonna be like scooters where there's gonna be, like, 10 providers of these things for a while, and then they're gonna consolidate.
Speaker 5:Like, one's gonna do it. But, yeah. People are really gonna win.
Speaker 2: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?
Speaker 5:Yeah. All those things matter. Right? I think the main thing that matters more than anything else is just time. Mhmm.
Speaker 5:Like, we're figuring things out with research. Infrastructure is getting better. I think that a lot of just infrastructure. Mean, our new companies are infrastructure, right? Like the infrastructure gets better.
Speaker 5:My coworker has this saying, he's 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. So you build infrastructure, your infrastructure gets better. And then what was what you couldn't even dream of doing ten years ago is now one command today.
Speaker 4:And
Speaker 5:today, you know, what what you you you yeah.
Speaker 2:What's the current use case for most people with tiny boxes? Uh-huh. Yeah. Is that that's my design. Right?
Speaker 2:You're not supposed to know? But I mean
Speaker 4:So, like, I sell the computer. It has specs. Right?
Speaker 5:Like Yeah. So many people wanna tell you, and I hate this. I hate this. They're telling me, like, how the product is
Speaker 7:gonna impact your life or
Speaker 5:what you're use the product for. Oh my god. Who cares?
Speaker 2:Yeah.
Speaker 5:Here's what it is. I'm gonna tell you what it is. That's your job. Right? I'm not an advertiser.
Speaker 5:Advertiser.
Speaker 2:But, I mean, like, I mean, our intern wants to build something with a tiny box. I wanna give him some ideas.
Speaker 4:Go buy one.
Speaker 2:Don't know. Why
Speaker 4:do you wanna build something with a tiny box?
Speaker 5:I mean, is it good? Yes. Just a it's a bunch of GPUs in a box. You know?
Speaker 4:It's a
Speaker 5:nice little box.
Speaker 1:GPUs in a box.
Speaker 5:Weight to it.
Speaker 2:What to it.
Speaker 1:Robotic form factors are you most bullish on? We've touched humanoids. You gave a great review there. We've touched, autonomous vehicles. Sounds like generally bullish, but Capital Wars race to the bottom, all that stuff.
Speaker 1:Are are there any other kind of form factors that you're thinking about that you are generally optimistic or excited Arm. Arm.
Speaker 5:The arm? Arm. Arm.
Speaker 2:Right? Just
Speaker 5:two arm. Right? Because I look. Look. I run a factory.
Speaker 5:I run a factory in San Diego. Make all the combos right here. And I can't wait to get a whole lot of robots in there. But I don't need humanoids. I'm just gonna stick two arms to the table, and then it's gonna grab a comma.
Speaker 5:It's gonna put the screen on the front. It's gonna flip it over. It's gonna put the four screws in it, then it's gonna pass it on.
Speaker 2:Yep.
Speaker 5:Right? Show me anything that's anywhere near that level today.
Speaker 2:Yeah. What what, what would you do if you were trying to build, like, a truly multipurpose robotic arm?
Speaker 5:The arms are already good enough. It's the off the shelf arms are fine. It's all software. Again, it's always all software. Autonomous vehicles are all software.
Speaker 5:Robotics is all software. But everybody loves to butt shit.
Speaker 2:Yeah.
Speaker 5:Like, what color are we gonna paint the humanoid?
Speaker 4:Yeah.
Speaker 5:You know? Like like, let's have a great conversation about that. Well, you know, we don't wanna paint them red because that might scare people in a long term. This is actually the level of stupidity that I see in those discussions about humanoid robots.
Speaker 2:Yeah. Would you
Speaker 1:would you trade in your legs for wheels if you could? Got that.
Speaker 4:Would trade in
Speaker 5:my legs for wheels?
Speaker 1:Yeah. Is a question from Aaron Frank, friend of the show. He's asking us in real time.
Speaker 5:You're a wheel guy then. Like, people would ask me if the wheels are, like, making a statement. I just don't wanna have to have this conversation.
Speaker 2:What what what about the sim to real gap in robotics? Like, how how is how is simulated data? You know, you you build a bunch of data in Unreal Engine, then you try and transfer learn it back. 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 for the robotic arm development?
Speaker 5:Yeah. So I think with a lot of Sim2Real stuff, the reason people are excited about it is because of that data efficiency gap we spoke about. Yeah. Right? Like, current machine learning algorithms are, like, a thousand x less data efficient than humans.
Speaker 1:Mhmm.
Speaker 5:So, yeah, you're gonna need a thousand x more data. Right? If a human can learn something in one example or
Speaker 1:Mhmm.
Speaker 5:10 examples, the computer is gonna need a thousand or 10,000. Now do you really wanna reset the stupid state of the physical world 10,000 times? You might do it at ten, but you're not gonna it 10,000. Right? Yeah.
Speaker 5: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 gonna play a role, but I think more fundamentally, that data efficiency gap has to be understood.
Speaker 1:We talked a little bit about coding agents. We talked about how you're bankrupting OpenAI by spinning up a lot of different, Codex agents. What, what other sort of AgenTik software are you excited about? Do you expect to, you know
Speaker 5:What's AgenTik mean?
Speaker 1:Yeah. Basically, bots. It's it's it's like what we're calling bots now.
Speaker 4:What's a bot?
Speaker 1:But but anyways, like, I just, you know
Speaker 4:You mean,
Speaker 5:like, don't know Star Trek?
Speaker 1:Yeah, yeah, maybe. Alright. 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 iMessage guy, Discord, maybe no messaging at all, just you know, know Telepathy. Telepathy. But do you expect a world in the future where you're just perfect interaction between human employees and agents or is it gonna be more like you'll do the odd deep research or maybe you send some automated outbound emails or have some codex bots running?
Speaker 5:Don't even, like, follow this.
Speaker 2:When do you think you'll be able to book a flight just by saying I'm trying to get to New York tomorrow?
Speaker 5:See, the worst part about this is like, hey, like and that's gonna come pretty soon actually.
Speaker 2:Okay.
Speaker 5:Right? We're gonna pretty soon have computer use models that are actually capable of going to delta.com and booking a flight. Yeah. But then what's actually gonna happen is Delta's gonna partner with whatever company does that and they're gonna put it behind the stupid thing and like yeah. So that's gonna, yeah, that's gonna be here in a few years.
Speaker 5:Right? Not with agentic shit, but just with normal hooking the APIs together. Right?
Speaker 2:Yeah. Wait. So yeah. What is the
Speaker 1:It's bullish on APIs.
Speaker 2:What is the mistake about, like, the agentic buzzword? Like, what what are people, like, even describing again?
Speaker 5:It's another thing that I I really have no idea what it means. You know? I I was hanging out with some friends last night and, like Yeah. Like, my friend's in this VR company and the, you know, the the CEO is really interested in things being open source. Sure.
Speaker 5: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. Yeah. He has no idea what it means that they can copy his shit. Right?
Speaker 5:Like, that someone else confused. He just he just heard the word open source in some, like, buzzword thing,
Speaker 4:and he's like, do we have
Speaker 5:the open source? Do we have the
Speaker 2:open source in the thing? Okay. So Check the box.
Speaker 1:Check the open source box.
Speaker 2:Okay. But let's protect our IP. Last question about the agent 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 kind of going off the rails.
Speaker 2:And so you you have, like, ten minute AGI. 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 that kind of trade off curve real?
Speaker 2: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?
Speaker 5:No. So I don't think it's been a hard but this is definitely a real phenomenon. Okay. This is definitely a real phenomenon. You can experience this.
Speaker 5:There's papers exploring it
Speaker 2:Yeah.
Speaker 5:Which show that if in ten seconds, there's absolutely no way I'll come even close to a modern LLM.
Speaker 2:Totally.
Speaker 5:Because the first shot from the LLM is great.
Speaker 2:Yep.
Speaker 5:And then it kind of degrades and it degrades pretty quick. Whereas humans look a lot more like this. Humans can stay coherent internally for much longer.
Speaker 2:Mhmm.
Speaker 5:So, yeah, I I think that that's a real thing. I think that that's mostly gonna be fixed by, like, long context.
Speaker 2:Just more energy?
Speaker 5:Long context RL. Okay. Yeah. Just like you just gotta do it. We'll figure out new ways to make the context better.
Speaker 5:We'll combine diffusion and and auto regression in some clever ways.
Speaker 4:Mhmm.
Speaker 5:Yeah. I I think that this is just gonna be a like, there's not gonna be a breakthrough here. There's not, like, one magical thing that we're missing. Yeah. I think it will be a continued plot.
Speaker 5:The same thing with data efficiency. I think people will start to care about it. Mhmm. Some new tricks will come out. Some of them will work.
Speaker 5:Some of them won't work. We'll continue to do graduate student descent until we find that.
Speaker 1:No? I'm trying find that. Anything Let's
Speaker 2:wrap it.
Speaker 1: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.
Speaker 1:I wanna see more of this. A little maybe a little white pill to kinda cap it off.
Speaker 5: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 that's one of the reasons that the modern Internet sucks. That that that so much of the stuff is in non recurring expense, and then it becomes really, really hard to compete with these people. Right?
Speaker 5:Like, you could run Twitter on one computer.
Speaker 2:Yeah.
Speaker 5:Alright? 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 moats can't be broken. With AI, I think there's gonna be a much less of a moat, especially when you look at the move from autoregression to diffusion. So autoregression can run-in large batch sizes.
Speaker 5:When you run ChatGPT, you're running with a whole bunch of other people on that same computer.
Speaker 2:Yeah.
Speaker 5:It's only a 100. It's not 10,000, but still it's a 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 sense. Actually running the models locally or at least having your computer in the cloud.
Speaker 5:Yeah. But not being some shared resource that's really controlled by some
Speaker 2:Yeah.
Speaker 6:Else.
Speaker 5:So, yeah, this was never a thing because you can't put lots of people on a GPU. That makes sense. Some weird stuff with the licensing.
Speaker 2:Yeah. Yeah. Fantastic. Well, thank you so much for stopping by. This is a great conversation.
Speaker 1:I wish we had a full hour. This is great.
Speaker 2:We'll talk to you soon, George. Cool. Bye. See you later. Cheers.
Speaker 2:Bye.