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The starship exploded during a test in Texas. A setback for Mars is Mars for Musk's Mars ambitions. Now the Mars transfer window is very, very tight. Like you can only get from the Earth to Mars like once every 18 months or something, or maybe even more. It's really hard because like if the planets are on the opposite side of the solar system, like you just can't, even though you have a rocket, you just can't get over there. So you have to wait until they're lined up and then you can do it.

But realistically skill issue, realistically true skill issue.

If you build an even faster rocket, you could get there no matter what. You just pilot, steer it around like it's a GT3RS around the Nurburgring, no problem. 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 were able to do everything remotely, which is great. And then Starship features pressure to meet deadlines for NASA's moon mission and Mars exploration. So there's a big, 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 is making an enormous bet on Starship, which stands roughly 4, 400ft tall at liftoff as it tries to break ground with new reusable rockets. And, and the paradigm of Starship, it's not just a bigger rocket, it is way more reusable. Like you look at the thing, it comes down, gets caught by those arms, can instantly be refueled and sent back up. You're talking about potentially like multiple flights per day. And so the problem here is not can you build a big rocket? Humanity has done that before. Humanity's built a rocket that's roughly on par. We've gotten to the moon before. The challenge now is not can we get to the moon? It's the same thing with like, the challenge is not can we build a flying car or can we build, we have helicopters, can we build one humanoid robot or one self driving car in San Francisco? It's like, can we actually scale these systems to the point that it is safe to go to the moon and back on the drop of a hat for 200 bucks like that's the challenge. It's more of an economic and industrial might challenge. And that's a completely different challenge from just can we get one rocket to the moon. An exquisite system. We're looking for reusable, scalable, you know, 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 Oakley's are coming. This shield says this makes sense. Luxottica owns both Oakley and Ray Ban and Meta is reportedly investing $5 billion 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 Met Metal worker making parts for glasses, ultimately becoming the largest listed company in Italy.

It is really interesting to think about how if Meta can basically corner all of the most iconic. All of the most iconic frames which they can do through luxottica. If they do figure out some type of exclusive over time through that investment.

And does luxottica just own all the major brands and everything?

Every time you buy something is all glasses. You think you're buying know some unique brand heritage.

Luxottica, it's interesting. We should, we, we should dig more into that company because they, they don't own all the retail. Well, yeah, that basically Sunglass hut retail stuff going.

I mean they are big glasses and that created the opportunity for Warby Parker.

Yep. Because they're the ones that manufacture everything.

You know, basically this entire, you know, Luxada had verticalized from brand to production to the actual medical side as well.

Interesting.

Also some good news in OpenAI world. Even though they're, they're going through the some battles with Microsoft, they scored a $200 million US defense contract. So they're working with the DOD.

The most unhinged picture I know.

How did this photo shoot happen? Like this does it. This looks like he's about to go on stage and he has a lav mic and it's from a low angle. But like what lighting scenario created this photo? It's amazing but it's very aggressive. Anyway, great selection by Nick beating the.

You know, arms dealer. Evil arms.

Yep, yep.

Dealer allegations with this picture.

Yeah. If you're, if you're a founder, you got to be careful how the angles people photograph. But at a certain point if you're on stage, they're going to take photos in any direction. But yeah and if they take enough photos, they get every single expression. 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 Zucky's undefeated WhatsApp should have ads.

The backbone of the Internet.

It's the backbone of the Internet. And Signal says that's why he's an Apple fanboy, because they don't do ads. Well, Apple does have a huge ads business.

I bet you this is just them listening to their users. I bet the users all over the globe said 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.

Like this was already happening. I felt like this leaked like five years ago.

How much? It was a $20 billion acquisition. Of course they were going to put some ads in at some point.

Of course, Senator. We sell ads.

Take it over to Tyler.

How you doing over there?

What's up, guys? In the back of the Maybach. It's pretty chill back here.

You got a little desk set up? Yeah, got wi fi.

The big news that we're having him dig into is Clulee. Yep, they are. Okay. Something happening? Something might happen today, but we got some flak for talking to Roy and not actually using the app. We're still above using the app, but we will let our intern use the app.

It's more that we don't have time. 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.

Yeah, but people have been saying that.

So today he's going to be trying out Cluly. We're going to be helping you see how. How easily he can cheat on some hard hitting questions that we're going to be asking him. So.

So state of affairs. Tyler, where are we on the Clulee install so far? Have you paid for it? What's the experience been like so far?

Yeah, I mean, I'm ready to go.

Oh, really?

Ever?

I played around with it for maybe like two minutes just to make sure it's working.

Okay.

So I want to get my live reaction when we start.

Okay, well, spin it up, Pay for it.

Yes.

Let's get on the top tier.

And.

We'Ll check back in a little bit.

Yeah, yeah. We're going to be peppering you with questions that only Cluley could answer.

Yep.

What's the popular. But what's the population of Iran go?

89. Million 82. I don't have it running right now.

You got to have it running. You failed. You failed.

You failed the first test. Well, get it fixed and we'll circle back in a bit. Get it to get it together.

Guess a question. Guess a number between 1 and 50 randomly. We're gonna quiz Tyler now if he's ready. Is he good to go?

He's ready. I got a thumbs up.

I want to ask how much money has been invested in Shenzhen. I'm trying to talk into the mic but not.

Not give it all away.

Yeah, yeah. Okay. So I am looking this up. Oh no. I used O3 Pro. So it's gonna be 12 minutes. Dammit. Okay. New. New. New tab. I will have to use 4. Oh for this because I need a quick. So he's investing 1 trillion, right. To compete with China's Shenzhen manufacturing hub. I want to know how close that gets us. Wait, this is weird. I don't know. One of the nine billion. More than 25 billion. This does not seem right.

I have some. I have some very. I think it's going to be pretty hard to pin down the exact.

We need a quiz. Tyler, on this question.

Tyler. Since 1980s, how much foreign direct investment has there been in Shenzhen?

Let me think here. I would say since 1980s, over 100 billion. Estimates range from 100 billion to 150 billion. And Shenzhen is a major global manufacturing and tech hub.

Okay. It's actually kind of pulsating.

Pretty close. I mean I think that the challenge is actually. There's so many ways you could kind of measure this, right?

Yeah.

I have a table. So there's about 100 billion of local funds. 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 billion of cumulative foreign direct investment. But who knows. And then run rating, I guess around 10 billion. But also does this count what Apple is doing? That's another form of investment. Anyways, this might be an answer that Cluley I guess got pretty close.

It was pretty good. That was good. I have a follow. You know the iPhones made over in China often flown via 747 to America faster than shipping on a cargo ship. How many iPhones fit inside of a 747? All right, let me think here.

I'm going to say I would say about 2 to 3 million in a 747. You know, so okay, so 747 max payload is about 140,000 kilograms.

Okay.

Each iPhone box is about half a kilogram.

Okay.

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, that kind of stuff.

That's pretty good. I mean, ChatGPT here has 9.6 million, but I think that's including like every inch of the plane. Including, like the past.

Very possible.

I think that's more accurate, actually. I think that might be more accurate.

Is clearly goated.

It might be.

We'll have to ask Roy, who's coming on the show later today.

Yeah, this is. I'm so, so impressed. So, yeah, the CHAT GPT estimate had the usable internal volume as passenger plus cargo. And I. It feels like you use just the cargo number. Is that correct? I believe. Yes, I think so. I see.

ChatGPT estimate 9.6 million.

It's streaming through.

Yeah, yeah.

Okay.

So I was using just the. Just the car going.

This is fantastic. It actually works pretty well. I'm impressed so far.

This is basically young Jamie from Joe Rogan, except you don't even have to look anything up. We just get to ask you live.

Yeah, yeah. This is great. Andre Karpathy chimes in. He says, very interesting to think about. Job equals bundle of tasks plus glue. Probably a bunch of other variables involved. For example, the number of tasks, how long each task is. For example, meta, like notion of task length roughly equals difficulty. How contextual it is, how high, 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 markets. So far. For example, I was curious, curious to look for radiologists. And if I'm getting This right, the U.S. bureau of Labor Statistics cites 29,530 U.S. radiologists in 2021. And then up to. And let's go to Tyler. How many radiologists does the U.S. bureau of Labor Statistics claim there have been in 2023?

Okay, come back to me in 30 seconds.

Okay. I think he's actually. I think he's working. And so when I just hit him with random questions. Not quite.

He's not in the zoom. So Cluli's not running.

Oh, okay. Okay. He's not in the zoom.

Okay, well, yeah, that was your first mistake, Tyler.

Yeah.

Always keep Cluley on.

Always keep Cluly on. Does Cluli have the ability to just prompt it directly or do you have to be on a zoom?

No, you don't have to be on zoom. You can do it. So on the website you can just prompt it. It looks like almost just like the ChatGPT interface.

Sure.

But you can also just pull audio, like just from in person. Like 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.

Yeah, yeah, yeah.

But I'll get back on the zoom.

Okay, well, we'll come back to you with that.

The audience will have to wait to find out how many radiologists we have.

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. If you're building Cluley, get on linear. Nikita Beer built a lot of products.

Customer list looks like a tier one venture firm's portfolio page. Got ramp. OpenAI cursor. Runway perplexity.

I normally make the joke of like the next. Oh, when we talk to Sam Allman, we're going to pitch him linear, but it's like, oh, too late. Wow. Boom is on there too. That's cool. I always make jokes about like using linear for other stuff. And you're like, no, it's just for software. And look at boom. They're using it for everything. It's fantastic. Yeah. Anyway, let's.

Tyler, what are you.

Tyler, the question.

Radiologist. Expert. We're interviewing you for a job as a data analyst covering radiology.

Yes. So the question is, how many radiologists do does the US Bureau of Labor Statistics claim exist in the United States in 2023?

Hmm, let me think about this.

I'm not.

I'm going to estimate maybe 31 to 34,000 radiologists. At least. At least from 2023 I would say. But yeah, that's my best guess.

It's 31,970. 60. I think you got the job.

Might be goaded.

Okay, I have another question for you. Pop quiz. Off the top of your head, what's the GDP of India?

Off the top of my head, let's see. I'm going to say 3.7 trillion.

It really sells it that you're touching your face so I can tell that your hands aren't on the keyboard.

You can tell that I'm thinking.

Yeah, yeah. You're just thinking about it. Yeah. You gotta be a good actor. But maybe that's why Cluley 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.

No, it's good. Either you're a great actor and Cluley might actually.

Or maybe he's not using Cluley and he just knows all this stuff off the top of his head.

It's very possible. Tyler needs to completely to figure out.

I'm on.

I'm on.

I think we got a feedback loop here. Can we hear you? How much is the hisense hundred inch TV cost? High sense.

Let me think.

I'm gonna say typically, I would say around 3 to $5,000. Obviously price varies by region and model.

This sounds so natural. This sounds so natural. Hundred inch. Yeah. Yeah. I think Apple should do it.

Do it.

It'd be great.

Tim, do it.

100 inches would be a good. A good like, you know, differentiator too. Because a lot of brands, you know, 55, 65, 75. It's gotten all confusing. Who is just like, you know, if you're going with Apple, you're getting 100 inch TV. But yeah, and it's like. And it's just amazing. Amazing quality. The intern cam still active. I want to go to Tyler for one last pop quiz. Oh, is he on? Okay. I wanted to ask you. Yeah. What's the capital of Michigan? Didn't you go to school there?

I think it's Lansing.

I think you're maybe leaning on clearly too much at this point.

I don't know if you're cheating using your brain or I can't really assess the product.

You have too much knowledge on Michigan. What's your name?

My name is. Let me think here. That paper that just came out, right?

Oh, yeah, yeah, yeah, yeah, yeah. Do you think that based on your use of clulid, do you think it'll make you smarter or do you think you'll take your foot off the gas?

Let me think about that.

Actually.

I think probably the latter, honestly. I mean, it's just like I just don't need to think. I don't need to store any knowledge in my brain now. So maybe it frees me up to do more reasoning tasks.

Okay.

But even then, once they get.03 in here, it's really like everything's covered, so no reasoning.

Did you get a feeling for what model was under the hood?

I don't know. I think I could probably check, but I'm not sure right now.

It's so weird interacting with somebody using Cluly. Every answer is like, you don't know if they're reading cluely or not or.

Just actually thinking, well, anyways, people should go try the product.

Yeah.

You know, make your own. I really, 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.

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.

Pretty soon.

You know, that's going to make a lot of people angry.

And so talking about spacking again.

Yeah.

I think Cluley's a good target. I bet.

I bet it's not the craziest target out there.

Not the craziest. You know, Chamatson, Mr. Beast, Holdco.

Yeah.

There's a lot of revenue there. It's growing. You know, the market needs a pure play. AI love viral play.

A pure Roy play.

Yeah, yeah. There's no pure play.

Well, we have some more breaking news, apparently. Break it down.

Next up, we have Roy from Clulee, the man himself. Third time in the studio, third time on tvpn. Welcome to the stream.

Get that hammer ready.

Ready. Let's bring him in. Let's hope he's ready. Roy, give us the news. Give us the headline number. How are you doing? How much did you raise?

15 million fucking dollars.

Clean hit. Clean hit.

Congratulations. Why'd you raise money? I thought you were printing so much money you didn't need to raise ever. What happened?

We're printing money, but we need more money every single day. We're looking for things to spend money on.

Okay. Okay. Uses of the funds. What are you gonna spend on first?

14 million for Brain computer interface development.

Exactly.

Exactly.

We have whatever you thought, the viral content. You thought this was cool, bro, we're.

Doing 10x this, okay? More videographers, more after effects artists, editors.

More engineers, more everything, please.

Moss. Moss.

Yes. Let's go. Yeah. What's the morning routine like now?

Over at clinic, everybody wakes up and we swipe on hinge for 30 minutes. It's mandatory. Everyone swipes on TikTok Instagram for an hour just to make sure the viral senses are refreshed. And we, we, we. We all do cold plunges and we're ready to hit the day with caffeine.

If you, if you cold plunge, though, does it negate? Like the brain rot? Like, do you get to. Or is it.

We scroll to keep our viral sense up, but after that, it's time to get to work. We're a Serious company. We're not just trolling over here.

Okay, that's good to hear. Talk to me about the Hinge use case. I want to hear Clulu's desktop app. You're not in the App Store. If someone's using Hinge on their phone, how are they going to take advantage of Cluli now or in the future?

I mean, every single time you screenshot something and ask ChatGPT anything, I mean, this entire use case, it is ridiculous that I have to do this. I can already take the context of your screen and audio and give you information out of it. Why can chatgpt.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.

Yes, but it's, it is locked down for privacy reasons on the iPhone. So the question is, like, what user interface innovation are you going to bring to bear on the phone so that you can actually unlock the vast majority of consumers who are realistically not using the most popular consumer apps on their desktop?

I would, 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 glasses entirely. And like, like, whatever it is, I think the technology has grown super fast. Like, like, I think phone, like in five years, I would question whether phone is the dominant consumer use case.

Okay, I get that you're bci pilled. It still feels a few years out the meta ray bans feel here today. Have you looked into those APIs? 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 going to have a really hard time on iOS no matter how cracked your engineers are. Apple is just going to say no.

I think, I think Roy, if anybody could.

Riz Cook. 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, what's your read on the meta ray band or the meta glasses rollout? They just had an announcement this today.

My read is that there is way more money in an all in desktop assistant than people actually think. There's maybe two, three competitors in this, maybe maybe two, three competitors who are actually trying to take a meaningful stab at a desktop assistant. And there's way more money and way more value in this than people think. We're still going to be Using computers in a few years maybe we'll be using something else. But like, like bro these sales, Oracle, Adobe, these guys move slow as fuck bro. Like they will be BlackBerry still bro. Like they are moving slow. We have computers unlock a bunch of enterprise value for the next few years and we'll be here to capture all that.

Yeah, so I mean I get that the, I mean it feels like this is going towards enterprise note taking enterprise assistant 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 Cluli 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. It begs the question why are you in the consumer group Andreessen But I guess that there still is a consumer angle long term. But how are you seeing Cluli users adopt the product? It feels like the logical cases at work on the desktop.

Of course. I mean the question is how are clue users using the product? Yes, most people it is most helpful in a meeting right now there's no product on the tool that gives you live assistance during a meeting. 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 like answers your questions and even when you're doing homework. I mean just immediate bro. Like you do all your when you're doing quizzes, assignments when you're watching lectures bro. Immediate bro. Immediate help.

Immediate on site. Yeah, yeah, yeah. Got to give a shout out to the whole team. We, we, we were reviewing clearly throughout the show today. We're pretty impressed with, with the product. I think a lot of people that are yapping on the timeline haven't tried it yet. Yeah and we would never and I think anytime going forward somebody leaves a negative comment, just say hey, totally understand how you might think that. Why don't you just use the product for 5, 10 hours and then come back and let me know if you feel the same way. Get a user out of it. Talk about the process for the round. You raised a seed round not very long ago. Did this come inbound.

I will say right now to all the VCs watching, if you ever are trying to get around you get me an email thread and you say hey, Let me loop in my assistant and we'll schedule a call in two weeks. 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. Your whole job is to find the alpha and invest quick and early. Why are you looping an assistant in two weeks? My partners, Brian and Eric, they came with stakes and Coke Zeros to the house direction.

Stakes and Coke Zeros.

This is how investors need to be. Your job is to find the fucking album, bro. Why are you looping in this?

It was a.

There was a preempt and I think all rounds. You need to preempt.

Preempted founders.

If you're not getting preempted, shut your company down. Even if you're running out of money, if you're not getting preempted, just shut the company down.

The company down. That's great. Companies grow so quick.

VCs don't have two weeks to loop in your system.

Okay, what is your underlying motivation for building this company?

I want to be conqueror of the fucking universe. It is so obvious that AI is going to massively expand what is capable. And I think like, even in five, 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 at 400 years old and I'll be jacked till I die. And in that universe, bro, like, these companies will converge into super companies. And these super companies is going to be me versus Elon versus Sam, competing to be guardian of the galaxy, bro. And I'm going to be on top.

Okay, sounds like you're power hungry.

There's been a Christmas, which can be a strength.

A strength. 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?

The only two things I really care about in my life are working on is working on something that I find interesting and getting the work seen by people.

Yes.

Elon Musk. These are my inspirations. Like, these people are known by every living conscious human being in the world, man. This guy founded Apple. This guy did test. It's the coolest shit ever. 4,000 years ago, bro, you wanted to hunt big fucking woolly mammoths tribe. There's no more woolly mammoths. There's only startups.

Okay, so.

So you're not beating the allegation.

But, but more precisely, if, if the best path for Cluley forward is your interns getting up, getting tons of social media views, you step out of the limelight because you're managing the company. People know, clearly. But they don't know Roy Lee. Is that still a win for you?

Of course, at one point the company becomes undistinguishable from the founder.

Yes.

With every single big company. And it's what, is what will happen with Cluli.

Yeah, it's just, it's just a unique situation because we, we know of Palmer Luckey because of Oculus, the product, and many people know of Cluli because of you and the, and the viral stunts that you've pulled. And so you're kind of inverting it. And, and the question that 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.

It is to change the world in 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.

Amazing.

How, how big are you going on the content side? Do you want to get a single video with 100 million views? Are you, are you going that big? Is that, is that kind of the wrong framework to think about it? But, but I, 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 million views on YouTube the next, you know, challenge?

I will tell you right now, and this might be the most logical thing I say on here, but the biggest societal shift in maybe human history happened about five years ago when TikTok 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 100x. 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 a hundred times 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. We know we independently all have 20 ideas a day that we know will go viral, and this extrapolated out over a year, will literally generate a billion views a month. And if you're someone who thinks a billion views a month is not going to convert to some money like, bro, you're retarded, bro, go back to school, bro.

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?

I have no idea. But I'll tell you right now, like, super bowl ads, it's all old. Like, this is the old meta. The new meta is in content is in short form, and nobody seems to have captured the gigantic delta in generating more viral content.

I still think it'd be funny if you forced 127 million people, the number of people that watch the super bowl, to just watch a video of you saying, hello, I'm Roy Lee. I encourage you to go to Clulee.com and sign up for Clulee today. So don't count it out. But anything else you want to share while you're here, I know it's a big day for you. The timeline's blown up. You. Not very many people have the stones to. To launch a series A on a Friday, a summer Friday, to go head.

To head against Mira, too.

Yeah. Yeah.

And you pull it off again.

I think people worry too much about the little things. In reality, if you post something that deserves to go viral, you will 100% go viral. And this will only be true for maybe the next few years, maybe. And I encourage more people to post. Most businesses will die not because the product sucks, but because you can't get enough eyeballs. And I think we. If we win, if and when we win, we will show to the world that there needs to be a fundamental difference in how companies are built. You start with distribution and eyeballs, because right now, that is where the gigantic delta is. And if you can't have that, then.

You stick with us. Stick with us for a minute. I want to play your fundraising video live on the stream, and then if we have any questions from that, I want to ask you, please, please. Let's play video.

Mr. Lee, Columbia University has found you guilty of academic integrity violations.

Do you have anything to say? Color grade?

I've already apologized to school, but to be honest, in two years, nobody's gonna.

Think this is cheating.

Yo, the Andreeson wire just hit. Think it'll last us through the summer.

Welcome to Clueless.

Great Video. Congratulations, banger. I gotta hit the gong again.

Very well done.

Very well done and beautiful. Beautifully shot. Like the lighting. I mean, the cinematographer you have.

I almost shed a tear.

Very, very good. Good. Very, very good. Nailed it. Anything else for Roy?

That's it for now.

In house studio.

It's crazy that you can shoot that in house. That really is remarkable. Congratulations.

We are excited to follow the journey.

We just got $15 million.

Oh, yeah. Tell us about the fundraising leak. What's your deal with R for Rock? Were you able to. How much do you have to pay him to shut up.

Man? I was, I was begging him. You guys have no idea. For the last few weeks I've been begging this man, please do not leak.

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.

I think what, whatever leak there could possibly be. I have very strong faith in my ability to make my announcement go more viral.

Oh, sure.

This video will go more viral than any leak would have. Even if.

Yeah, yeah, yeah. That makes sense. You actually don't want to take the gas out of the. Out of the tank. I love it. Thank you so much for stopping by. This is fantastic. And good luck.

Congratulations to you and the team. Excited to watch you guys cook this summer and hopefully the 15 mil makes it, you know, back, you know, August. Just remember August, it's going to be hard to get. The autoresponders will be on. It's going to be hard to, you know, get those 24 hour meetings.

Yeah.

And so just make sure you got the Runway to September.

And this might come as a shock. IPO underwriters do not preempt. So at some point you will have to stop with the preempt everything mantra.

I don't know, there's some SPAC sponsors out there.

Who knows, Maybe.

Yeah, maybe you'll get preemption SPAC in the fall. You know, I wouldn't be. I wouldn't be surprised. So you're.

You're saying it as a joke. I feel like it might be in the cards. We're. We're going to be tracking it. Thank you so much for stopping by.

Great chatting with you.

We'll talk to you later.

Talk soon.

Bye. In other news, the Los Angeles Lakers has been sold for 10 billion in richest deal in sports history. Guggenheim Partners CEO Mark Walter, who also owns MLB's the Dodgers, is acquiring the storied NBA team in a move that makes it the world's most valuable sports franchise. And it's so funny because like the Wall Street Journal's framing this is like this is the biggest deal ever. No one's ever done a deal like this. And we're like wait, so you're talking about like a series A for like a foundation model company? Like as a tech person I'm just like, yeah, like $10 billion. Like billion dollars. 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 decacorn congratulations to.

The Lakers Mark Walter and the whole team.

It's fantastic. Major premium to the Boston Celtics who sold for 6.1 billion. 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, they're not 24, seven like Instagram. Does that ever go offline?

No, no.

There's always entertainment. Lakers, they're still doing seasons. They need to have 24 hour basketball. They want to really get there around the clock.

It's like endurance, endurance basketball. It's just a week long game, you know, got to always have five players on the court just constantly running up.

It's the only option. Jeannie Buss and her family who have owned the Los Angeles Lakers since Jerry Buss bought the team in 1979. Wow. On Wednesday agreed to sell majority control of the storied 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 40 years slightly under S&P 500. Like it was a really, really good deal and it was a really great company. It grew a lot but it didn't outperform the stock market. Just diversification. Bros. DCA Bros. Undefeated again. Well, if you're trying to DCA do it on public.com investing for those who take it seriously. Multi asset investing industry leading yields. They're trusted by millions, folks. Anyway, Walter, who is part of the ownership group that owns the Dodgers has been part of the Lakers since 2021 when he purchased a 27% minority stake in the franchise. He's also a co owner of Chelsea in the English Premier League, the WNBA's Los Angeles Sparks and the new newly formed Cadillac Formula one team. Let's hear for Cadillac. Let's go. Congratulations John.

You know front John front run the, the Cadillac F1 team and got a Cadillac for himself. Over there you can see the black.

It's great to have an American F1 team in the business now.

Yes.

Yeah, yeah. We've fallen off, but we're coming back.

You're not going to be able to get one of these in the whole country.

I don't think so. They're going to be too popular.

The F1 team, you know, gets out.

On 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 record rights deal last year with worth 77 billion. When the Celtics sold in March, the $6.1 billion valuation exceeded the previous record valuation set for a sports team by the 6.05 billion sale of the NFL's Washington Commanders in 2023. He purchased the Lakers for 67 million. In 79. 1979, the team transformed from franchise uprooted from Minnesota into one of the winningest and most valuable sports.

I had no idea that they were founded.

That's where the lake, the lake name comes from. 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 just brought them to LA and kept the name. But that's what Lakers means. Yeah.

Wow.

Bus. The Buss family oversaw the creation of Showtime and presided over the NBA's last three people compete. 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. They should get on numeral.com humoralhq.com John Sales Tax on autopilot. Spend less than five minutes per month on sales tax compliance.

You know, they have won 11 championships since 1980. Their rosters have boasted many of basketball's brightest stars. Magic Johnson, Kareem Abdul Jabbar, Kobe Bryant, Shaquille O' Neal, LeBron James and LeBron James his son have all worn the Lakers purple and gold.

I love it. It's such a cool idea. 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. I think it's like not like if they were like winning championships together immediately, that might be a different story. But it's just so insane that you could be playing well professional just because.

You could have earned a better return by dcing into the, into the. Into the stock market.

That's not why people own These assets.

Though owning the Lakers for a number of decades I imagine was absolutely priceless. So great investment, get the owner's box, great run.

Yeah, all the perks. You have to add those in. What do you get perks from dca?

I like how Lakers legend Magic Johnson hit the timeline. Said just like I thought when the Celtics sold for 6B, I knew the Lakers were worth 10.

Let's 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 so it's closed. I believe that Alex Wong has a badge at Meta and shows up to work in Palo Alto and clocks in@MEDA HQ. Now scale AI is still an ongoing concern, is still the company, but every competitor is out for blood and they want to take as much of the business as they can. Since obviously the perception is that Scale AI will primarily be working with Meta and that other foundation Model Labs might not want to do business with Scale AI anymore. Unclear if they can separate out the businesses, 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 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 not using Scale AI for data anymore because it's too aligned with our competitor Llama maybe, but everyone's trying to yeah.

A lot of this is very predictable. I don't think Meta and Scale's 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 going to immediately turn off and no, they were smart enough to know what would happen. And there was an article I think yesterday about OpenAI ending their relationship with Skale, but from what we knew like they hadn't been doing much for a while. That's part of the reason why Merkor had been and they also brought a.

Big function in house because for some of the more complex tasks it makes sense to generate the reinforcement learning data yourself. And there's just so many others, there's so many other services having like a single point of failure never makes sense for a business of that size. But we'll see. So the information has an article here about a little known startup that has surged hint hint past Scaly without any investors. This is interesting. After Meta Platform, Scaly Ideal data labeling is looking like Silicon Valley's hottest new interest. That's enormous opportunity for Edwin Chen's Surge AI. For years, data labeling existed in a tucked away corner of Silicon Valley, a critical but unglamorous area of AI where companies like Google and OpenAI hire outside firms to employ improve their models by laboriously grading the quality of what they produce. Now a spotlight has unexpectedly fallen onto the field in the wake of Meta Platform's decision to pay 14.3 billion for 49% of scale AI, the best known data labeling firm. But it's not the largest such firm, nor perhaps the most impressive. That title belongs to Surge AI founded by Edwin Chen. This is fascinating. I didn't know this. 1 billion in sales last year. Bigger than Scale. Yeah. So Chen startup has won customers like Google, OpenAI and Anthropic.

It's such a testament to the idea that like sure, you can bootstrap, but you, it's, 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 have, if you're not trying to raise capital, you have less need to go and be loud and go on podcasts and talk to the press and all this stuff because you're just making a lot of money and sometimes it can be beneficial for people to not know about you.

So this is crazy, crazy stats. So Chen is 37, he has no investors and has bootstrapped the 5 year old startup entirely by himself, which has 110 investors employees in offices in New York and San Francisco. The company generated more than $1 billion in revenue last year, Surge has told employees, a previously reported figure that exceeds the $870 million scale generated in revenue during the same time period. And unlike Scale, Surge was profitable and has been from the beginning, Chen said. Moreover, Surge could see its sales get even larger if other companies copy OpenAI's decision to stop hiring Scale, a choice made over concerns about Scale's relationship with Meta to shift business to Surge. Other key financial metrics couldn't be learned, like how much revenue 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. But, but at the same time, Even if it's 200 million in net revenue, that's still a huge business. It's hard to imagine Surge not being a fantastic business. They haven't had to raise Money, they have 110 employees and they're used by Google and all these major foundation model labs. So seems like a fantastic business. But if Surge could earn a valuation 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. 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. 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 wonder if this is going to go the route of, you know, you are Deloitte or McKinsey and you're going to have your team, but then also a company like Serge create a ton of training data around a specific workflow that is costing your business, you know, 20 or 50 or $100 million 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, like the average of the entire Internet, it's like no, this is a fine tuned for your business. Perfectly trained perfectly. And it, and it really, it really distills what you do excellently. Yeah, I don't know, I don't know if it'll go that way. I'm interested to talk to people about it as AI models. So Serge's subsidiary data annotation tax 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 2 to 5 times what scale might bill. Surge justifies the prices with its reputation for industry leading work. Indeed, one former Scale employee said Surge often performed better than scale. And 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 Lore 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 the leader of the data labeling field and had become a Silicon Valley celebrity, blanketing podcasts and conferences with his presence and posting heavily on X. It also raised 1.5 billion in venture capital, putting Scale on a very short list of companies that have raised that much. And he hired upwards of a thousand people. Wong had made timed 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 Scale spokesperson said the company wasn't profitable, was not profitable, which, but wasn't burning a ton of money. I think they had efficient. They raised 1.5 billion and they still had like almost a billion in cash.

Yeah.

So they weren't, they weren't in like trouble or anything, but at the same time it was like, like not, not a wildly profitable, not a wildly lean business.

But I don't know what, what, what a. It's absolutely fascinating, these two businesses.

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 and then 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, just like going from one to the next. That's insane. Uh, he was developing recommendation and search algorithms and helping gather the data needed to train them. Despite the hefty resources of those companies, Chen 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. To do so, they needed a data set containing 50,000 accurately labeled businesses, which he found out would take six months for an outside firm to assemble. We had no solution other than waiting. We simply waited. When the data came back, Chen blanched. In some instances, it had labeled restaurants as coffee shops and coffee shops as hospitals. The data was complete junk he wouldn't say which vendor Facebook had used in 2020. In 2020, he left Twitter to found Surge and picked up some of his first customers, executives from Airbnbs and Neva, a once promising AI search engine startup. As only as only a founder in San Francisco might, bumping into them at rock climbing gyms in the city's Dog Patch neighborhood in the Mission District. Talking up his startup to get Serge going, Chen recruited data labeling contractors he knew from his previous roles and funded the startup using his savings. He wouldn't say how much he put in. Fortuitously, Chen focused on language modeling. Scale, by contrast, started out using more visual data for autonomous vehicles. Talked about just as those types of models began to grow in importance. Less than a year later, OpenAI had hired Serge to fine tune its models by teaching them how to avoid producing harmful responses like racially biased language. Biased based on research paper the company published together in. By 2022, anthropic had become a Surge customer.

They're putting out research papers with OpenAI and still managed to stay this under the radar.

Wow. Yeah. So look at this. The label largesse. Data labeling has proved to be a lucrative niche in AI. Surge, founded in 2020, has over a billion in revenue. Zero Funding Scale, founded in 2016, has 870 million in 2024 raised. Oh the. This is. This says funding raised, but this is clearly valuation or something because it says 17.4 billion, which is not what they raised. Touring has 300 million annualized. Raised 225 million. Invisible. Interesting.

Turing too initially was like a marketplace to just hire developers and I think they pivoted into data labeling.

Interesting. It's the same thing when I work with a cloud provider. The enterprise tech customer said, I don't know the internal expectations for why their services work so well. I push a button and I'm glad for the internal work to make that happen. Data labeling companies typically use various techniques to make sure contractors aren't just dilating it in or phoning it in. I guess when answering questions, for instance, the companies randomly insert questions that have no correct answers or make sure labelers agree on the right answer to a question. So obviously you scaffold up these responses so that everything's double checked and then you can kind of see if people are messing around. But wow, what a beast of a business. I had no idea how big this thing is. Amazing. Over in defense tech world, Anduril has partnered with Rheinmetall, the German the German defense tech company the prime really to manufacture Barracuda Barracuda and Fury over there. That's very exciting. And then we also touched on Spotify founder Daniel Ack Guess when Rheinmetall was founded. The way you're saying that makes me think it's like 1650.

I'm putting you on the. I'm putting on the spot like Tucker put.

How can you possibly report on the news if you don't know when it was founded?

This is, this is the best bit earlier to read it out.

Yeah.

Tucker, do you know the Muffin Man? The muff Ted goes the Muffin Man.

The Muffin Man.

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 man? John, this is a post from Zach Stewart.

He's a real gotcha.

Really, really good. Anyways, you can still. I give you permission to comment on. Even though you don't know 1889.

I knew it was really old. 1889.

Dusseldorf.

Okay. I was pretty far off, but over 100 years. I mean, yeah, that's the same. It's general. Well, General Atomic is part of like this roll up and it came out of like I think General Dynamics at some point. And the company that, the founder of, the company that competes with Fury for that autonomous program that they're competing for right now was like the designer of a submarine in, in the Civil War or something like that. Like I'm pretty sure that he's, he died more than 100 years before Palmer Luckey was born. 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 how legacy they are. Like it's not just like if 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 and then they'll have to grow up a little bit, they'll have to learn the game and then they're going to come for you wild.

So yeah. Spotify founder Daniel Ek is leading a $600 million funding round into German defense tech startup Helsing. This is the, this is kind of more of an Andrew equivalent over in Europe, valuing that four year old company at 12 billion. The business makes battlefield AI, drones, submarines and robo fighter pilots. It's now one of Europe's most valuable startups.

And they're using some renders here. John renders this image. They're render.

Maxing, they're rendermaxing.

It is A cool render. Yeah. Look at the water there. It's definitely a render.

Who knows? It's hard to tell these days. It's so we're beyond the uncanny valley. And so Hellsing 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 owned defense products for European countries and really companies all over the world.

Crazy. It was founded in 2021 by Torsten Ryle, a video game entrepreneur, Gunbert Scherf, a former German Defense Ministry official, and Nicholas Kohler, an AI researcher. And they have partnerships with Saab already.

Yeah, and tons of American venture capitalists. In the deal, you got Lightspeed, Accel and General Catalyst, Connor's Cooking. They've raised over 1.37 billion. Daniel X said, the world is being tested in more ways than ever before. That has sped up the timeline for Helsink'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. Next we have Katherine Hahn from Han Ventures coming in the studio to talk about the stablecoin bill. The genius bill is slated past is on the front of the Wall Street.

Journal today and guiding and establishing national innovation for us stablecoins.

We had her on the show and yeah, we're excited to talk to her. So welcome to the show. How you doing, Catherine?

What's going on?

Hi. Hi. How are you guys?

We are great.

Big 24 hours.

Congratulations I think are in order, but please get us up to speed on what's actually happening and where things are in Washington.

And I love that you called me Catherine. That was my Washington name. I haven't been called that since I used to appear in court.

But Katie, let's update the chiron. Katie Hahn.

Thanks for having me on, guys. Actually, I literally just walked off a plane. I was down at the CO2 conference where I was talking to a lot of founders, crypto and non. And everyone loves your show, so I'm happy to be here.

Well, thanks for making your time.

Yeah, thanks. I think congratulations are in order. I don't know if I would say that yet. I mean, first of all, the 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 D.C. circuit, that Article 3, that other branch of our government, left the SEC no choice. 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 in this case. You have the Senate passing this, introducing this legislation. Pass 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 going to slap a percentage on and say which bill is more important, but that's the market structure bill. And to me that's really the transformational bill for the crypto industry.

Okay, so break that down for us.

Yeah, so there's one bill, 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 pre political. And I think I don't want it to be the case that this industry is too political on one side or the other. 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 bill and the market structure bill. And the stablecoin bill obviously paves the way for a regulatory framework for stablecoins in this country. So that's that. But then there's another bill, 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 big question is, well, what's the security and what's not? And I think the market structure really goes a long way in answering that question. And that's why I think it's so fundamental. And we've seen courts across the country weigh in on that question, and that's because we don't have legislation. Gary Gensler said it was also clear, and of course, it wasn't all so clear.

Yeah. So what's the timeline there? What are the different players? What do people want out of it? What is the core kind of crypto industry, both on the investor side and company side, want out of it? And who would not want it to go through, at least how the crypto side has it in mind?

Look, I think everyone in the crypto industry wants the stablecoin bill to go through and become law. I don't think there's really any question about that. The question is, do you go for both? Someone just described it to me as in a sports analogy, and I'll probably fumble that one, but it was like, for the field goal or do you go for the touchdown? And the thing about after a field, you know, after a field goal, the other side gets the ball back. And I think Congress really operates in kind of six to ten year windows, and, you know, it's on their mind. Reform, regulatory clarity for crypto right now. And I think the transformational bill for crypto right now is very much that market structure bill. We also want that 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, 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. And that takes power kind of away at a high level, away from regulatory agencies, and puts it back more in the hands of the courts. And do we want to have another 10 years of litigation percolating up from the district to the appellate court to the Supreme Court on what's the security or what's a commodity? And a patchwork of different answers throughout the country, or do we want Congress to answer that question for us now. And I think it's incumbent for Congress to answer that question now. You asked who, what does the industry want? I think, people, this is a big industry. We say crypto's not a monolith. It's a broad new asset class. And stablecoins are a very big, important piece. Piece of that asset class and a growing piece, as you guys saw. I shared with you the stats. You know, almost a quarter of a trillion dollars. I think you 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? So this bill that was passed yesterday on the Senate, the Genius act, 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.

How do you think about big companies getting excited about stablecoins and thinking or institutions and being like, there's a lot of potential here. We should create our own stable coin versus we should just figure out how to lend leverage this technology. Where do you see the kind of line and opportunities?

Well, look, we already have two very dominant stablecoins right? Already today, tether, USDT and then we have usdc. So clearly it's not winner take all. I mean, those two are both growing and they both have market share. So we think there will be 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 just so important and if they launch their own stablecoin, we could also see that too. I don't think we see a world where everyone. I think we get asked this question all the time, is there going to be a world where every company has their own stablecoins? We don't think so. We could be wrong, but that's not the view of how we see this evolving. We do see this.

Yeah. We had Aaron Frank from Lightspeed on earlier and he was comparing certain companies would launch a stablecoin and it maybe would feel like Kohl's Cash where it's like, yeah, good point.

I don't have any of that. Nor do I. I, I don't have any. And, and that's the thing. If I did, would you want to use it on other platforms?

Right?

I mean, every bank could launch a Visa network competitor, theoretically, but that doesn't necessarily make sense.

Yeah, so. So in your mind, is the, is the broader market structure, Bill, the kind of thing that could catalyze a massive amount of new activity? And from my view, you know, stablecoins have been getting adoption. There are a bunch of exciting use cases. We have a public American and stablecoin issuer and circle. Now it feels like yes, regulatory clarity is important there, but having broader clarity around how tokens are treated by how the government actually views tokens feels like it could catalyze much more of an explosion in investment activity and new company formation and new use cases for tokens. Is that the right framework?

I think that is the right framework. Because, because like I said, stablecoin is a big important piece of the pie and very low hanging fruit by the way, to my mind. But crypto as an asset class is much broader. So when you say where do the industry players, where do the crypto investors, where do we want to see it? I don't think it's a monolith. I think crypto as it grows to a multi trillion dollar asset class, like any multi trillion dollar asset class, you have different factions. And I think some fairly and some really smart, smart people think just take this, take this win and move on and don't worry about the rest. And I think that's a little, I see why they might think that if they think that it's this or nothing. But I think that's a false choice. I think that we can have both. And this is a really opportune moment to have both. And I think the question that has beleaguered the industry really has been the question over securities, commodities, which agencies are going to have jurisdiction? I think that's a bigger question and I think it would be a real shame if we let this moment go to waste. You know, the irony too. So you have some stablecoins or only stablecoin companies who are like, yep, genius, act and move on. They don't want to get dragged into this broader kind of a more omnibus package. Right. With the market structure legislation. But I think that's a missed opportunity and I think we'll be sorry as an industry if we don't go for both. Now again, go for the touchdown. And I think all of the, like I told you, all of the fundamentals are kind of working all at once together now when I last talked to you guys, and this is very much part of it. 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, slow Congress operates. They've been trying to update the money laundering laws for two decades. And it's like out of sight, out of mind sometimes. And I think we have a really unique moment to press for both here. And the irony is, some Democrats who are opposed to market structure because of potential abuses, who are opposed to the crypto industry, they cite abuses, they cite fraud, they cite speculation, they cite Trump coin, and I get all of those criticisms. But I'll tell you what, had the market structure bill been passed, that would have answered a lot of those questions totally. The irony is if you would have had the market structure belt, you wouldn't have had a lot of the blowups that you had in the past several years in this industry.

Is crypto truly coming home to 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 you seeing more and more momentum there with some of this positive regulatory movement, or are you still seeing momentum around, around places offshore, Singapore, etc.

I think, look, everywhere that you're going to want to develop does is going to have some rules that you're going to have to follow. When I hear founders who say there is no regulatory, it's often not that there is no regulatory regime whatsoever. Sorry, Balaji, if you're watching, but I am seeing that on shoring a bit. We were kind of seeing the offshoring in an unfortunate way. But it's not 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 So we're still very optimistic. And I don't think it. But we were getting to a very dangerous point with the crypto industry. Had the likes of Gensler and others like him been left kind of to just do this now? Fortunately, the courts were pushing back. So it wasn't a partisan issue. It was just the courts were starting to say, no, you've gone too far. I mean, I lost track now. I literally lost track of how many federal courts of all political persuasions and appointments ruled against Gensler's regime. And not just Gensler, but others like it, where you had very activist regulators who were really far out of their Lane and, and you saw courts curbing back on that. So I think that was already, we're in a dangerous spot, but the courts were maybe going to save us. But you don't only want to rely on litigation to save you, of course, because then you've already lost. But I think hiring and talent is important. 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, and we've talked a little bit at the early stage about some of the synergies between AI and crypto because of course AI creates digital abundance and blockchains are good at enforcing digital scarcity. And I think you're going to see more and more synergies emerge and use cases over time. And I'm not going to say what they are because we've seen that before in crypto a lot of over promising under delivering on use cases. 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. In addition to regulatory clarity, if you're a founder, you want access to great talent, you want your visa situations sorted out for your employees, you want access to other founders, depending on what type of company you are, you want access to capital. So I am optimistic about the state of crypto in the US but also elsewhere. And we invest in companies, we invested in squads, we've announced that. 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 U.S. awesome.

Awesome.

I want to talk about the longer tail of, of regulation because it seems like the stablecoin bill is very straightforward, like the least, the least ambiguity there. Then you have the market structure act and there's a lot more to do there. But I'm sure that there's like riders getting pitched and all sorts of long 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 theory 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. 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.

My view on that is, is no, because we can't just. But we can't have an NFT bell, a bill for bank contracts or we can't have specific bills. And if you saw, if you think back to the advent of Internet, that's not what we had. You know, we had section 230. It applied broadly to platforms. And I think we need something similar here. So on the one hand, I would say it can't be so specific that it's like, okay, if you're a, 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 really at the end of the day. We've seen some early use cases with Product market Fitness. 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. It would have just been for bitcoin, and that would have been a mistake because then a couple of years later on the scene we have eth and a few years later we have Solana. So I think what we need to do. So you don't wait for the end state have any regulation, right? You don't do regulation by enforcement. I can tell you what we don't do. We don't do regulation by enforcement. You don't wait till the end state of things, but nor do you want to get so with such specificity today and do the current state of regulation by the end state of regulation that you can't do either. And so I think what you have are some guiding principles, some generic rules of the road. And really that's all the market structure bill is. And there's enough clarity that you had Democrats vote for it last time it came up. So it's not like it's so specific. It talks about. And I think, look, I think you have people like Hester Purse, who is SEC commissioner, has written and given speeches on this of what that ought to look like, what is a decentralization test. And those are some guiding principles that you can kind of look at and apply as you think through this legislation. You know, what body ought to regulate it. And sure, you're gonna have some outliers and new technologies emerge that you're like, okay, does this fit neatly in the bill. No, but we have laws for everything in this country with technologies that develop that don't fit neatly in a particular bill. And that's why we have, that's why we actually have. We don't do regulation by enforcement. We do notice and comment. We do things like advisory opinions. Certain bodies, by the way, do do advisory opinions, not judges. And then 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 and we were only getting unfair regulation by enforcement. And I say unfair because Gary Gensler basically picked what should have been the best companies, encrypted a poster children for compliance and brought enforcement actions against them. And then the complete spectacular disasters didn't bring anything. So until after the fact. And so I think regulation binds.

We gotta have you.

We gotta have you and Gary on the show to hash it out. I'm sure you guys have had some funny conversations.

Thank you so much for popping out.

Thank you for joining, for having me.

Great having you.

Have a good rest of you.

Cheers.

Okay, bye. Bye.

Up next, we have Justine Moore from Andreessen Horowitz. Incredible map knowledge. Dropped a fantastic map alert all around AI image, AI video models. We're going to have her take us through it. Welcome to the show.

Welcome.

How you doing? Can you hear us?

Can you hear us?

Hello?

Oh, I can hear you guys now.

Sorry.

There we go. Hey, I was saying to John, when you dropped your new market map, I was saying, you know, it's a great sign of respect in our culture to drop a new market map and come on the show.

I'm 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.

We are strongly pro market map.

Yes.

The people love market maps. It's like you can guarantee a popular tweet if it has a market map in it.

Absolutely. And I think people got kind of sick of like, oh, we know the playbook, we've seen it. But there's a playbook for a reason. It works. So, yeah, take us through the latest market map. What are you tracking? How did you decide what to divide it up into and what kind of inspired this moment specifically.

Yes.

So I mostly do AI creative tools here at a16z. So I spend all My time testing all of the image, video, audio, et cetera. And obviously the past few months in particular, video has been like the thing. There's been like VO3, obviously, which was a massive moment with adding the audio for the generations hydra around the talking characters. The new Minimax model, the new ByteDance model, Seed Dance, which is in the arena, already outperforming VO3. So it just felt like a good time to refresh sort of what's going on in the video space. And I kind of formatted this market map just thinking about more from the perspective of a creator, like less in terms of the go to market of the company, more. Just like if you're a person trying to create a video with AI, where would you go for these different use cases? So there's first sort of the model, like the foundation model. Companies 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 vos, the clings, the runways, the picas. 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 like, if you want to take a single prompt or a single image and see what it looks like in five different models, super easily, you can do it somewhere like that. And then the other side of this market map is sort of like what happens when you add speech and talking characters. And so some folks do that by like generating a talking avatar from an image where you can eventually have the person move. And other folks do that by taking like a video of a person and then applying lip sync over it and then syncing the audio. So that's sort of the distinction between talking avatars and lip sync.

Yeah. It's interesting that you're in the consumer group because I can imagine that a lot of the talking avatar companies wind up selling to corporations that want to vend in talking avatars, 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 and it might land as a consumer product, but it also might land as a B2B play.

Most people are not at all rigorous and often don't even know at the beginning. So what we actually saw with the first generation of AI video was it was only researchers making these Magical models and they had no idea what the use cases were going to be. They all just put like a text prompt box in front of the model and then you got an output and a big company and an individual were using the exact same interface. Now I think we're starting to see more at what we call the app layer, which is essentially how do you productize this, how do you create work workflow and therefore how do you go into specific verticals? Maybe an example of that is all of the standalone video ad creation products. So things like Creatify or Captions or Heygen has a product for this too where you can literally just 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. And that's something that like a VO3 or cling the general video model companies won't do today.

Yeah. Where are you seeing the strongest like low churn adoption of these tools? Because just personally like vo3 was the thing that got me to subscribe to Google Pro Max 25 which we can go into the names and how difficult this actually access these. But, but other than that there, there haven't, I haven't seen that many where like we've seen the ASMR Stormtroopers or something 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 Mr. Beast and they're like I'm building a studio. This is a business. I have ad integrations and I have a content schedule. It's very much in like the testing phase. We see the studio Ghibli moments go viral. So where, where, where is the true long term value playing out right now?

Okay, on the content creation side, where we are at right now is actually there's a bunch of content agencies. Like you know, there's a bunch of wonder studios, dream studios. There's probably like 20 of them now. One called 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 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. 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 Brainrot characters. I don't know if you guys.

No, I don't know this. I haven't seen this.

The Italian Brainrot characters are huge. So I can't even say the names here because they will sound ridiculous. But it's people basically making images of, like, an animated talking baseball bat and like, a ballerina whose head is like a cup of cappuccino.

Okay, okay.

And a shark who wears sneakers.

Okay. But they're starting to build, like, a cinematic universe.

Oh, it's massive. Yeah. Accounts have, like, millions of followers.

World isn't ready for Italian Brain.

So is it. Is it. Is it, like, decentralized in the sense that, like, I could just go and participate in this, like, broader trend?

So, yes and no. I would say there were a couple accounts that originated the first few characters, and then other people started participating using the hashtags, remixing.

Okay.

And then the good. The characters. Characters that were good, that came out of that sort of bubbled up to become part of the cinematic universe.

They have Bombardieri, Bombardiero, Crocodillo, which is a bomb.

He's a crocodile plane that shoots bombs.

This sounds like. Yeah, yeah. Super, super viral.

Yes.

Your kids probably love it. It's wild. Before we go into more of the contest consumer side, talk to me about some of the. The more like, niche, like, B2B use cases. Because I remember when, like, GPT 3.5 and we got 4.4GPT 4 dropped. There were still like, a lot of hallucinations, but you saw companies that were just like, yeah, like, sure, it's not incredible at writing poetry, but it's amazing at just like, converting this messy text to JSON. And they were all of a sudden just writing, 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 stuff that, like, artists aren't going to really get upset about because it just feels like a better, more advanced tool. Are a lot of these companies building tools like that or is all the focus just on, like, let's one shot the next Oscar film?

Yeah, it's a great question. There's a Decent amount of a vertical focus I think also like it's very hard for this for startups like if you're not a Google to or an open AI or whoever to play in the game of like let's train the largest one shot best video model. So a lot of them are focusing on verticals. Like Luma, which is a company we've invested in, did this really cool tool where you can upload like a, a 9 by 16 like iPhone style video and you can just say extend and it just basically like out paints around the existing video and makes it look like. So you can just change the dimensions of your video really fast.

Yeah. Or there's companies more of just like a practical tool but super useful for a bunch of creators that are filming vertical content probably and they want to distribute in a horizontal format. So they just do that.

Yes, exactly.

That makes a ton of sense.

Or something like Higgs Field that has all these really special effect like motion loras essentially. So you can take like, like an image of a car and just say like this is like here's a template of what a car explosion looks like. Make this specific car explode. And then on the B2B side we've seen a lot around like how do you scale marketing or L and D or like executive presence type content. So like, you know, tools like Descript now allow you to take a video of someone talking and then change the word that they're saying by changing like cloning their voice, having the voice say the new word and then doing a new lip dub.

Lip sync. Yeah.

So you could have your CEO sending what looks like a personalized holiday message to like every single customer or something like that.

Yep. Or maybe something worse with a phishing scam. But I'm sure we'll get into Stacey at some point.

What do you, what do you think the long term ambitions of companies like Google with Veo and bytedance with their model? What do you think they want out of this category? They obviously have a massive edge. I saw Aneesh was posting about Google's Edge or YouTube's Edge around IP. With Veo you can generate what was going on there.

That is crazy Disney thing.

Is that like a real deal or is that just a beneficiary of like some sort of relationship?

Yeah. Then I want to get a sense of do Google and 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 going to all be verticalized out Where I want to generate ads, I maybe want to generate, you know, customized messages. But I want to understand like this is a good overview of all the, of the ways you can generate content. But like how does the market structure evolve?

Yes. Okay. On the IP question, I have not talked to Google's IP lawyers and I'm not an IP lawyer, but my understanding is Google.

But this is legal advice, right?

Yeah, exactly. This is financial advice.

All the advice.

Our compliance team is going to love this.

Yeah, they're going to love it.

Sarcasm.

You can. I think my sense is basically when YouTube came about, it was suddenly like all this IP content is on the Internet and Google cut deals with, 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. And so that's sort of the, the, the working theory right now about like why VO3 can generate IP content and not get sued when a lot of other people are struggling with that in terms of the market dynamics. It's so fascinating the question around like Google and ByteDance and, and eventually I think Facebook I hear is going to do more in video soon as well. Like why they're doing it and what their strategy is. I think first of all, like, if I'm one of those huge consumer giants, AI is such a massive shift in consumer behavior that like you want, if you want to own the interface to consumers, you probably want to own text, image and video generation as well. And they have the resources in terms of data. Like YouTube, for example, is a perfect example of this. They have a ton of compute, they have a ton of money and they can hire the best researchers to build the best models. I think the question as you sort of alluded to is like, do they, do they sell those models via API and let other people build the consumer experience on top of them or do they own the end to end consumer experience? 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 going to figure out if they can catch up with some kind of cool new consumer app later.

Yeah, yeah.

I mean, yeah, 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 chat GPT because maybe they already have a subscription or they're fine with the free tier and it does. There ends up being a bunch of different applications on the Enterprise B2B side, but then not so many core consumer subscriptions on just cool videos, pictures, et cetera.

I mean it seems like it's a killer moat for Google cloud platform to have VO3 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 want to get into, into that about YouTube is obviously an incredible training data resource. You mentioned that there was another company that just surpassed them. Was it Tencent you said?

Bytedance.

Bytedance, that's right. So I have a question about that because obviously with Codegen, GitHub has a lot of public repos that people can probably just scrape. It's also just not that much data. You can probably fit it on a couple hard drives, maybe maybe sneak it out the back and go head a flight and train somewhere in Malaysia or something. You can't do that with YouTube. Like it's just too much data. And so my question is how durable, how much should we be thinking about a durable data 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. But, but I don't know, there's so many other, there's so many other ways to attack any of these model developments that there's a lot of different options.

So there's a couple parts of the data question. The first part is like what do you own versus what do you scrape? I mean we've seen companies like OpenAI will scrape YouTube as well to train their models. I think ByteDance also like, you know, here we think of YouTube and Facebook and whatever here in the U.S. i mean as being the big host of content. But like, 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 and I'm sure there's reposts of American videos over there. So it's not like even has a unique flavor. Probably can generalize pretty well, right?

Totally though. Yeah. Like I was one of the very early users of all the Chinese video models when you still had to access them on Chinese apps with Chinese phone numbers and, and they were definitely very good at things that were more China oriented than the US models.

That makes a ton of sense.

Oh okay. The other thing that's important to mention on data is in video in particular, it's not just the volume of data, it's also the quality of data and the quality of data labeling because essentially you can't just feed a video into a video model and assume it can understand what's going on and pull out the relevant data info. You have to have really sort of dense labels is what we call them or super detailed captions about like this is this style shot shot from this sort of camera. The camera is coming from this angle. This is the sort of character, this is how the character is interacting with the background. And that quality data is what drives quality in the video models. And China has really benefited there because there are so many more PhDs than there are here. And it's much cheaper, cheaper for these companies to hire them to do these. These dense labels for the video data.

Yeah. Well, how does Mid Journey fit into all of this now? It's such an interesting company because no venture dollars this like behemoth kind of quietly hiding in a discord server. Still. I saw some examples of video. It looks fantastic. Seemed like they hadn't added audio yet. But how do they fit into the whole. The whole piece? Because. Because it seemed like early on they developed a really great feedback loop for the data that maybe wasn't happening with some of the other model providers.

Yeah. So the Mid Journey model came out this morning really conveniently like 10 minutes after I put out my market map without midjourney video because it's not yet available. I was just playing around with it too. It's really cool. They do image to video. 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 like a low motion and a high motion setting. 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. And it's not as good at like what I call physics heavy world model type things like two cars running into each other and exploding. That sort of thing requires a very, very large and costly usually like text to video model that is more difficult to train. Whereas midjourney, I mean I have no idea how they did it. It's a great model. They could have taken one of the open source image to video models and fine tune it on all their own data.

Yeah, yeah. I've noticed VO3 is really, really good with some of that physics stuff, but it still gets confused. Like if a car is driving away, all of a sudden you'll be looking at the front of the car and then the back of the car and it'll get kind of mixed up. But yeah.

Are you. As all these different models have progressed, I always remember brud and Trevor McFedries and just how early he was to what I think will be this like new wave.

Is that little Michaela?

Yeah, little Michaela, which was like basically cg, a CGI influencer. So very early. I think we're going to see a lot more of this and we've seen some of this to date. But do you expect that to be kind of like a new. A new. Like, how bullish are you on sort of like entirely. AI creators getting real adoption following turn followings turning into real businesses. I'm sure you. You follow a bunch of them already.

Yeah, I'm personally super excited about it because it kind of separates the content from the character. Like now, before AI, if you were on Instagram, you were both the character and the person coming out with the content. And so you had to look in a way and present yourself in a way and talk in a way that was interesting to the Instagram algorithm. And now it's like anyone with a good idea can create a compelling character. And so I think some of those are human characters. I've already seen way too many examples in my reels feed of OnlyFans models who promote themselves with AI avatars of themselves now, which works shockingly well. There's some photorealistic human influencers, but honestly, some of the more interesting ones are things that could never be influencers before AI. So there's one called like, Raccoon stole my iPhone and it's an AI Raccoon influencer. There's like AI Capybara influencers. There's like mystical creatures. Like all of these things that just come out of people's imagination.

Competing for mindshare with Instagram pet pages, you know, dog pages, things like that. Did you have a reaction to Fountainhead? It was the. Or, sorry, Mountainhead, not Fountainhead. Oh yeah, Mountainhead the movie. The. The core overarching theme was that basically deepfakes or AI generated content had gotten so good that it was causing global unrest. Did it resonate at all? It does feel Like, I now have. 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 getting community noted. It's. One person says it's not real. Look at this link. It was this image. They redid it. Another person says it's real. Look at this. So it's like I just assume that everything's fake and made up unless I see it, you know, with my own eyes. But I'm curious if you. If you. If it resonated at all with you.

So I've not. I largely consume AI slop, so I have not seen. I should watch it.

You should watch the movie, the Motion Picture on Slop.

Yeah. Once they have that, I will watch the full film. But it's so interesting. We talked about this a lot, actually, with audio models with the last, like, election cycle, because video, I think, wasn't there yet to have convincing deepfakes, 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 for program where, like, you have sort of citizen watchdogs on various platforms saying, this is real, this isn't real, running them through various sort of AI detectors. But I also think, like, people are starting to develop more skepticism around everything they see online and whether or not it is real, which is probably not a terrible thing.

Yeah, I had this take that After Effects would be more impactful on the election than AI video because, like, you can just show a clip of a burning building from 2020 and it's real video, but you recontextualize it and say, oh, you know, the capital's burning or something, and it's from years ago. Or just, you know, speed up a video, slow it down, edit it out. 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.

Yeah, it even, you know, we're here in LA and when all the imagery was coming out of the protests from a couple weeks ago, it was like burning waymos kind of looks like something you generate with VO3 totally. 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 car that's on fire. And it's like, that looks like.

And even just the way that was photographed there was like, it looked like all of Los Angeles was engulfed in flames, but it was really like one crazy block with a bunch of different angles and then a bunch of different posts and. And you drive around and you'd be like, oh, there's not that much.

See, that's the other interesting thing is, like, even wheel footage can be manipulated. Like any kind of story can be manipulated in a way. Like AI.

Yeah. 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 anything on content verification side and trying to create some sort of mechanism to prove whether something was actually shot on an iPhone. Right. Proving through the metadata and some type of public setting. Is there any pitches from that side?

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 VO3 generations has little VO3 11 labs, which shows the audio. They actually have a site where you can upload any audio and it will tell you if it was generated with 11 labs or not.

That's cool.

Which is pretty cool. The other place we've seen development there is for, like, prominent individuals, like, you know, celebrities or someone who's. There's, like value behind their brands and who potentially even might want to monetize it in the age of AI. Like, if you're an actor and you suddenly don't have to, you know, film, go fly back to LA when you're filming a movie in Australia to tape like 5 ads for some cell phone brand and you can have your AI avatar generated to do it instead. And it looks just as good. Like you might actually want to, you know, have some licensing company that owns your AI licensing rights, whether it's your traditional talent agency or not, who can manage that for you?

Yeah, totally.

Very cool. Well, thank you so much for. We can talk for another hour. I have so many more questions in the. In our doc, but we'll have to have you back. So thank you so much for stopping by.

Thanks, guys.

Thanks, Justine.

We'll talk to you soon.

Great chatting. Have a good one. More breaking news. Nvidia to drop humanoid robots that will produce Nvidia GB300 chips in Q1 of 2026. Nick says, Holy based. That is so Nvidia Foxconn in talks to deploy humanoid robots at Houston AI server making plant.

Wow, that is extremely.

I don't totally understand this.

What does that mean?

I guess Fox Foxconn has been training the robots to pick and place objects and insert cables.

Yeah.

I don't know if this is marketing. It feels like we've had, we've, we've asked a bunch of robotics experts about humanoids and so far I haven't got a. I, I don't have the confidence that, that this is actually a super great use case for them.

It's just the definition of like, what is humanoid? Because you go to a, you go to like a Ford F150 F150 factory and they have like massive robotic arms, like moving windshields around. Right. Like, it's like you could anthropomorphize that by like spray painting it pink and putting some hair on the, on the hand and being like, it's a humanoid now. But you could retrofit bicep definition totally. Amazon has tons of robots sliding around. You could put googly eyes on them and be like, they're humanoids now. And you maybe get a stock bump. But 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 the three axis pick in place, 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 just a grabber? Will it have legs or will it have wheels? It could just be sitting there. Because for a lot of these pick and place jobs, you 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, it feels like it's a little bit wrapped in marketing lingo, but still cool that more companies are making humanoids because it does seem like a cool form factor that hopefully people will break through and get there. And this seems like, you know, a step in the right direction in the sense that it's a very defined task. I think when people think humanoids, they think some. Like my new Turing test is, is humanoid robotics will, will be here. And when they can put up a six minute nurburgring time. In a manual.

Yeah, gated manual.

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 wheel and the stick shift so efficiently and so quickly that they are truly performing.

Yeah. And a manual can be weirdly like probabilistic. Right. And that like you're like, you know.

You can move the, synthesize a lot of data.

Yeah. It's not, it's not like, you know, perfect system. Right.

You're not gonna, you're not gonna put up a sub 7 minute nurburgring time with a Joe Biden walk.

That's right.

You're gonna have to be moving fast. Those actuators are going to have to be.

That's right.

High speed. So, yeah, I don't know where all this goes, but I mean, exciting to see that they're at least doing work on it because it seems like an important, it's clearly an important path in the tech tree. We don't know how relevant it is to other formats, but cool to see a lot of money pouring into the sector from very big companies.

So Foxconn will be announcing their robots in November and then deploying them shortly after in our year 2026.

I mean Foxconn seems like the right builder for this. Unitree feels like it's scaling up to the point where like Unitree robots should be usable in certain locations. 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, ten fingers, ten toes? Is that, is that really like the right form factor or, or should we do be just doing things that are more specified? Because if you're, if you're, 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 will be cool to see. I'm sure we'll see a lot of viral videos about it. It'll be very cool.

I invested in a company making robots for data centers and they intentionally chose not to make it humanoid format, which, and I think a lot of those. The reason behind that decision would also transfer to manufacturing setting.

Right.

Which is like, do you need legs if you can use wheels?

I mean, data centers have the most perfectly polished floors with like no dust at all. Like it's 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. Right?

Yeah.

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 racks 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 Hotz. How you doing, George? Good to hear from you.

What's going on? Welcome.

Can we hear you?

Oh, can you hear me?

Yes, I can hear you.

Gotcha.

Let's kick it off with something simple. I want to take your temperature on AGI timelines, P. Doom, the easy and fun stuff.

I don't know what AGI means and I don't know what you mean by doom.

No. Are these terms just like, entirely irrelevant? I mean, now we've shifted to, like, super intelligence. They're all buzzwords, but at the same time, like, there is, there is an idea of like the, like, I don't know, the conversations may be shifting to, like, the AI generating more economic value than humans. Is that a relevant metric to track?

Machines have been generated more economic value than humans since the Industrial Revolution.

Is there some other metric that we should be tracking or is it just, like, irrelevant?

You're just talking about, like, hype. Like, I don't know, I mean, I. Like, I don't know what you mean. Like, you can talk about concrete things. 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. It's a. Linear aggression. Intelligent. What if it's big enough? The Chinese does know Chinese.

Yeah. I mean, what about your, your decision to get on a spaceship traveling at 0.9 C away from the. Yeah, 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, it was maybe going to happen within your lifetime. Hasn't moved at all.

Yeah, I don't know. I don't know if I'm actually going to get that spaceship, but it's kind of like in an ideal world, what I would want to do, you know?

Yep.

Just, just, just back away and chill. Don't look back. Actually, you can't look back.

You can't.

Like, they're all there.

You need the, you need the blast shield, right?

You need the information shield.

Information shield. What do you mean?

Oh, that's how they're going to get you.

Okay.

Right. I mean, okay, so here's a way you can think about AI, right?

Yeah.

Imagine there were 10 CIA agents assigned to you and they're running at 1000x real time. So they're like hyper fast CIA agents that devote their entire lifespan to your day and they're trying to manipulate you, maybe to get you to buy things, maybe to get you to vote for a certain guy, whatever. But like that's what you're going to be up against with AI what we're currently building. What, what, what if you think about the biggest companies in AI, what they do is advertising. What advertising is, is just manipulation of humans. So you're going to have a team of CIA agents thinking about you and trying to manipulate you at all times. And now you see why you want to head away at the speed of light, Right. Even CIA agents can't beat that.

Is there, is there some world where there's like a capital war and I'm paying for a more powerful ad blocker?

Yeah, I mean that sounds good. Like another question is kind of to say like, okay, if you think that you either think that current like capital accumulation dynamics are going to continue and that the rich are going to continue to get richer and if you believe that, the question is kind of, well, how many people are going to survive in the future? How many people are going to have any modicum of independence? Right. Like you have some far AI people who think that there's going to be a singleton. Right. There's going to be literally one. Right. You know, some people maybe think it's 10. Some people. Thousand. 10,000. Some people think that all the humans will get to continue to exist as independent entities. Are they already independent entities? That's a question, right? I don't know.

Question. I mean, if you were trying to put it in like the form of a bag, that human population above or below 8 billion in 20, 30.

Above. I think I would just be a normal trend. Isn't that what the trend says? Yeah, just go with the trend says. I don't think there's going to be any discontinuities to any trends. Really?

Well, yeah, I mean, I mean at some point, but the question is like how far out do you have to go until you start seeing these effects?

What do you mean by human? Right. What about someone who lies in bed all day, watches TikTok, Are they human?

Yeah, that is odd. They kind of drop out of society.

I think, I think question that popped up for me is is this all this debate about AI safety and what should labs Be doing what should labs not be doing? It feels like your angle is it should be each individual's responsibility look to look after their own safety. In the context of AI, is that at all?

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.

Yeah, but I mean people still look to you as like an example of like someone who might have answers.

No, I don't have any answers.

Not, not necessarily answers, just like.

But you can buy my shitcoin here. Did I shill a shitcoin? Here you go. Just click the QR code and you can buy a George Hots coin. And that will give you answers. You will find satisfaction and fulfillment in your life after purchasing a George Hots coin.

Is that the end state? We all have our own coins.

No, no, no, no, I don't mean it like that. I mean like I think that a lot of people are like, they don't really know what they're looking for and that vacuum you, is, is very, you know, it's very dangerous and it's going to 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.

Yeah, I mean do you think that there's a chance that someone is able to take a stand 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 start all. There was a stagnation in real world build out of nuclear capability on the energy side.

Yeah, I mean there's a few things about nuclear that make it different. So nuclear even as a weapon is incredibly hard to deploy tactically. Right. So, so if a country has, has nuclear weapons, they're aside from like a mutually assured destruction 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.

Yeah, right.

Russia has some tactical objectives they might want to accomplish, but nukes aren't really going to do it. Right. I mean from a pure real politic perspective, not even from a like oh like a taboo moral perspective. Like what do you want? An irradiated pile of rubble? Like that's what you're going to get. No, what you want is drones that are hyper specific and can take out exactly who you want, can control areas. Right. So like as A military technology. Nukes are not that good. AI is way better.

Yeah, but what about it as an energy technology? It feels like, it feels like the fear, like the mimetic 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 the AI doom scenario, whether it's real or not, becomes so memetically powerful that someone's able to harness that and actually say it's. If you try and build a big data center, we will shoot you, then maybe it stagnates.

No, really think that's the reason for nuclear? I think it has more to do 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?

Yeah.

And if you look like that is the thing, if people think that there's some weird taboo around nuclear. Right. But then, okay, look at Hydroelectric, right? There's no taboo around Hydroelectric. But China leads in installation of both nuclear and hydroelectric and everything. It's almost like they're correlated, right?

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 going to develop anymore because we're already developed. You see the D on the end, right?

Like, interesting. Yeah.

So is that just cultural then? When you are like, the malaise sets in. Would you expect that to happen to China when they catch up?

I don't know. I. Yeah, I mean, maybe it's just like this normal story arc of, like, you know, it's, it's. I don't know. I don't know. I think that, like, you have a real problem when the kids can't live better than their parents.

Yeah.

So. But I don't have anything more to speculate on that.

Did you have more context on, on China and, and specifically in the AI context, US Electricity looks like this and.

China electricity looks like this.

Is that all that matters?

Pretty much, yeah. I mean, that's a pretty good proxy for everything, right?

Yeah.

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. With any administration, I'm looking at two things. Did you decrease government spending and did you increase total electricity production of America? America. Those are the only two numbers I care about. Those will capture everything.

Why does government spending matter? We were joking that, you know, Trump must be extremely AGI pilled if he's running up a massive budget deficit.

What the hell is AGI? I don't know what this is.

Like in this formulation.

Never seen it. Never seen it.

In this formulation, it's that. It's numbers. Yes, yes, yes. But it is an extra lever on labor and capital and it creates more GDP that then can be taxed to pay down the increasing amount of debt.

Super. Super Excel.

Yeah, Super Excel.

What does Super Excel do that normal Excel doesn't?

Let's give it up for better Excel.

Yeah.

Yes.

We need Excel 2.0, right?

Yes.

The thing is, Excel was the final piece of software, but in order to add another $100 trillion to global GDP, we needed to, like, like, kind of rebrand it. And so now we get AGI.

GDP is the complete. It's the biggest thing ever. Right. Like, I always joke with my friend and I that we're going to start companies and be billionaires. And I'll tell you how we're going to do it.

Okay?

Right. I start a company, he starts a company, we both write contracts to each other.

Yep.

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. Whoa, look at our revenue. Wow. That all contributes to gdp. Wow. We made. We're billionaires overnight, right?

Yep.

Like, like, and that's my argument is the economy is just that with a lot of extra steps, right? You can't use services. It's not part of gdp. This is complete nonsense. You can't have services. Like, literally, literally, you take the steel out of the ground, you grow the corn. Okay? That's gdp.

But is, I mean, if that GDP is fake, is not the. Is the deficit not fake? Like, is government spending less fake?

We owe that shit to people. It's not fake.

But can't you just tax the fake money? Like, if you tax your scenario where you're generating a billion million dollars in fake money, you can't tax the fake.

Money because we're passing the same dollars back and forth. The minute you tax it, that falls off so fast.

Yeah, yeah, yeah.

You can only tax productive work.

Is AMD doing productive work right now?

AMD is doing all right. Yeah. Either Nvidia is really overvalued or AMD is really undervalued. It has to be one or the other.

How does it all play out? Like, what does AMD actually need to do to get back on track or realize their potential, Nvidia needs to stumble.

I mean, it worked for AMD 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.

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.

Okay.

They're being a better second place than they were a few years ago.

Yeah.

And then when Nvidia stumbles, AMD is like, oh, hey, we're here.

Is DGX lepton like their cloud offering a potential stumbling block or is it the right move for them?

I don't know what that is. What's an Nvidia cloud chip?

Yeah, exactly.

You can break AI down basically into like, there's like five tiers, right? Like at the base level, you have like, electricity and data centers and land and like, things like that. Tier 2 or like TSMC, ASML, Samsung, Intel. Right. Fabs, Nvidia, AMD, OpenAI, Anthropic. And then on top, you have, like, completely worthless things like Turner and Windsurf. You know, these character AI, all these people who think, oh, we're the app. We're gonna. We're gonna get the ARR. No, that worked. To the web. It won't work for AI. And I can go into why, but it's kind of boring.

I want to keep going, keep going, keep going, basically.

Okay, so like, here's the difference between AI and. And web. When you want to run a service like Gmail, one server can serve 10,000 people easily. Right. And there's no demand for, like, better Gmail. Right. It's not like, it's not like I can click and get like, yeah, you can buy Gmail Pro. It'll have a few things, but most people don't really care. Right. There's no limit to the ceiling of how good you want your AI to be or how fast you want your AI to be. Maybe there's a limit to the speed, but like, when you're at like a thousand tokens per second, I want the biggest model in the world. Right. Like, so there's very little limit on that. But suddenly you can't serve 10,000 users from one server anymore. 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 wind service. They aggregated to the OpenAI and the Andropics. Right. Nobody who built like an email client survived. They all got eaten up by the tier fours of the web. Right? The Googles, the Facebooks, all of these like app providers, right? Where's a Zynga today? You know, like this already happened, right? People just don't. Where's Zynga? Oh, Zynga's gonna be the next thing, man. Like, no, it's not. Facebook ate all of that value, right? Google ate all of the value from all the people building on top of Google. So the tier fours ate all that value.

Yeah.

So OpenAI anthropic will eat all the value from the cursors in the windserfs of the world. They'll acquire some of them. They'll compete with some of them. Right. Same as you saw on the web by argument that the tier fours aren't even going to have value. Because the tier fours, 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 03. I'm running. You know how much I cost open AI every month? I pay the $200 a month and I cost him a lot more than that. You can now click on Codex.

Yeah.

Spin up four nodes. Yeah. Why would I not click four? It's not my computer. You gave me the button. Hey, I'm just using it.

George Hotz single handedly bankrupts $300 billion.

There's no value in just being the front end to AI applications to be like the front door, just the default button. Because we see these models kind of go back and forth in terms of benchmarks or what's hot. And there isn't as much customer churn as you would expect because people are just kind of like defaulted into the app that they installed whenever. And so even if Gemini gets better in terms of the actual performance metrics, people don't switch from OpenAI to Google.

Because it's so negligible. You got to make something 10x better.

Okay.

You got to make something 10x better. So like this whole game is open AIs. Unless they stumble.

Sure.

I'm not switching to gemini because it's 20% better. Download the new app and think about a whole new thing. Right?

No one's going to switch. Is there, is there a chance for a company to kind of come out with something that's 10x better with an algorithmic improvement? Or is it just a race for scale? Like what could actually be that next. It felt like GPT 3.5 when they really broke through with DaVinci and then 4o or and then 4 like it felt like this kind of like binary moment when a lot of people realized that this was, was usable for their daily life. Even if it's just a Google search replacement or whatever. Write a poem or whatever. Like a 10x what you're describing, like a 10x improvement feels like that kind of like qualitative binary shift. Is that possible with just scale or is this something that we need a different model for?

I don't know. I don't know. I would bet majority still on. Like these big labs are also attracted tracking the talents. But it is also like it's pretty commoditized. A lot more so than like Google search. Right. Like you can look at people track how far open source is behind. It's not that far behind.

Yep.

So no, I don't know. I think this game is mostly going to be chatgpt. I think Elon's aware of this too. That's why he's trying to go 10x bigger with the data center. Yep, we'll see. Maybe it'll work. You know there's someone to bet on anthropic. I'm not that bullish on but maybe.

You kind of predicted the pre training wall. But that's not a refutation of the bitter lesson. And we're going to see similar scale play out and reinforcement learning or is there going to be something else that we're building the big data centers for?

There's something that we don't understand in terms of terms of data efficiency. So like when you think of how long it takes a GPT to learn to talk, like how much data it takes. It takes like terabytes of data in order to make a GPT talk like a normal person. It takes terabytes of data.

Okay.

Whereas a human trains on megabytes. Yeah, 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, you transcribe it, it's going to be a couple megabytes. 10 megabytes, maybe 100 megabytes.

Yeah.

So humans have this thousand X data efficiency advantage and we're going to have to fix that if we want like reinforcement learning to work. Especially like reinforcement learning that you want to do in the real world. Humans could do. Humans can learn from very few samples. And yeah, I think that like it might be okay if these foundation models train unsupervised on lots and lots of stuff.

But yeah, is that, is that something that somebody's working on just like a new, more data efficient algorithm to drop into the pipeline or do we have any leads there? Because it feels like right now we're going down the path of reinforcement learning with verifiable rewards and we're going after individual business use cases that are increasingly long tail and that could be kind of of like valuable. But it doesn't feel like the breakthrough that you're talking about.

Like, has there ever been a breakthrough? Right? Like people think GPTs were a breakthrough. No, they weren't. Like you just, if you watch the world, it was just, it was all just smooth curve. But what I will say about AI scaling laws. 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. You can put in exponentially more money to get linear returns.

Exactly. Do you believe that the real value is investing in, in humanoid robotics then? Have you heard this theory? So, so it, so I mean if you, if you put exponential more money into humanoid robotics, assuming that they work, and assuming you can, you can make 10 times as many robots, you get 10 times as much output.

Anyone, anyone who wants a humanoid robot has never worked in a factory in their life.

Okay, right, break it down.

No one wants a humanoid. Oh, yo, yo. It's gonna walk around this thing. It has legs, right? No, here's what I want. Yeah, yeah, we got a laugh track. Can you show me a robot arm that's capable of putting a screw in something?

Probably, yeah.

Put the screw in the thing.

Yeah.

No, no, no, no.

Not like you carefully jigged up the screw dispenser, like the way a normal human does it with a screw sitting there in a little bucket on the thing. And it picks up one screw and it puts it in. It takes a screwdriver.

No, no, no, we're, we're not close. But also it feels like we're not far. It feels like. That's what I feel like.

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 like why we shouldn't build them. But then, and so much capital and so many different teams are trying to make them work that they very well might work for some things. And like they just, humanity might brute force it because we saw it in a sci fi movie, you know, 30 years ago.

Why, why, why are we cooked on humanity?

This is as dumb as self driving cars. Was right. And nobody learns their lesson. And people like Kyle Boat should be ashamed of themselves like they really should. These people who go and raise large amounts of money for another thing that like they should know, they should know better. Right. Here's basically like, remember in 2012 and Google said that, you know, my, my 12 year old daughter would never have to get her driver's license.

Yeah.

Come on, that's nonsense. Right. And like now, okay, they shipped Waymo, it's in a few cities. They're teleopped. Right.

How, how teleoperated are they in your opinion? Is it effectively one to one?

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 an autonomous system that they're probably doing some higher level inputs on. They're definitely like saying when you can be aggressive, when you should slow down, whether you can turn to the stop sign or not. Again, here's the simple reason to know that it's like that. Right. There's definitely some teleop of the waymos, right?

Yeah.

Have you ever seen a picture of that room?

No.

Yeah. Why not?

I've always thought it was like an ace up their sleeve because like if there's a lot of pressure on them to say these waymos aren't safe, they can pull the sheet off of the ghost and say there's actually a human in the loop. Don't worry, it's safer than you thought.

Yeah, yeah. Like the fact that you've never seen that room tells you that it's way worse than you think it is.

Right.

Okay.

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 the place.

Yes, yes.

You don't see any pictures. There's so cruise that actually came out, the lawsuit. I think it was like 1.5 or 1.7 humans per car. Right.

Or, or vice versa. Like. Right. 1.5 cars per person. Right.

No, no, wait.

More people than cars.

Yeah. That's what he's saying.

It's still that.

Because an Uber only requires one person.

Yeah, 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 you know. Exactly.

I'll pay more for that. I'll pay more for that. Yeah.

But I mean, is there any hope that we drive this down and we get to two cars per person, then four cars per person, it starts doubling exponentially and eventually like we are there.

I mean, yeah, like it's obviously going to happen, right? It's obviously eventually going to happen. If you want to see where the real state of the art of unsupervised self driving is to that there's no person with fsd. When you get your Tesla, that's not teleop, you can go press FSD and that's real AI and well, you can see how good it is, right? Would I take a nap in there? Even for five minutes away in hell, you'd be super tech.

Right?

How are things going on the comma side? Give us the update there.

Pretty good. We're on track too, who are on track to be two years behind Tesla.

So there you go.

So two years behind Tesla. 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, right? Or Airbnb. When you roll out something like that, you're trying to roll out a two sided marketplace. You got to spend tons of money on customer acquisition costs. You've got to make sure that you've perfectly matched that marketplace right away. Because if drivers aren't getting rides, they're going to leave the platform. If riders have to wait too long for drivers, they're going to leave the platform. So it's this careful balancing act. But once you get this marketplace, you got, you got a moat, right? Switching costs are real high. Try to get everybody to switch at the same time. It's a challenging point. Never do it. Self driving cars don't look anything like that. Self driving cars look like scooters. The only thing that it's going to take to roll out big fleets of self driving cars is capital. It's just strictly a capital market. You could just. If I look at a city, I can calculate how many waymos there are. If I want to build my own network and deploy that network and run at a lower cost, it's straight up capital. Easiest thing for investors to calculate, very little risk. So self driving cars are going to be this awesome race to the bottom. It's going to be like scooters where there's going to be like 10 providers of these things for a while and then they're going to consolidate like one's going to do it. But yeah, people are really going to win.

What's most valuable in terms of developing the next, like the next better version of full self driving, is it having a lot of data, building a big data center, having a great team to actually design the system. What's most important are they all equal?

Yeah, all those things matter. Right. I think the main thing that matters more than anything else is just time. Like we're figuring things out with research. Infrastructure is getting better. I think a lot of it's just infrastructure. When new companies, AI infrastructure. Right. Like the infrastructure gets better. My coworker has a saying, 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 10 years ago is now one command today. And today, you know what? You, you. Yeah.

What's the current use case for most people with tiny boxes? That's my design. Right. You're not supposed to know.

But I mean, I sell a computer, it has specs, right. So many people want to tell you, and I hate this. I hate this. They're telling you, like, how the product is going to impact your life. Use the product for. Oh, my God, who cares? Here's what it is. I'm going to tell you you what it is. That's your job. Right. I'm not an advertiser, but I mean.

I mean, our intern wants to build something with a tiny box. I want to give him some ideas.

Go buy one.

I don't know.

Why do you want to build some of the tiny box? I mean, is it good?

Yes, just a.

It's a bunch of GPUs in a box. You know, it's a nice little box. GPUs in a box, weight to it.

What, what 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. Are there any other kind of form factors that you're thinking about that you are generally optimistic or excited?

Just too arm. Right. Because I. Look, I run a factory. I run a factory in San Diego. We make all the commas 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, 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.

Yep.

Right. Show me anything that's anywhere near that level today.

Yeah. What would you do if you were trying to build like a truly multipurpose robotic arm?

The arms already good enough. Arms are fine. It's all software again. It's always all software. Autonomous vehicles are all software. Robotics is all software. But everybody loves to bike. Shit.

Yeah.

What color are we gonna paint the human? Yeah, let's have a great conversation about that. Well, you know, we don't want to paint them red because that might scare people in a. This is actually the level of stupidity that I see in those discussions about human hydrobots.

Yeah.

Would you, will you trade in your legs for wheels if you could?

I got that in my legs for wheels.

Yeah. This is a question from Aaron Frank, friend of the show. He's asking us in real time, you're.

A wheel guy then like people had asked me if the wheels are like making a statement. I just don't want to have to have this conversation.

Well, what about the sim to real gap in robotics? Like how is simulated data, you know, you build a bunch of data in Unreal engine, then you try and transfer learn it back. And 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?

Yeah. So I think with a lot of SIM to real stuff, the reason people are excited about it is because of that data efficiency gap. We spoke about current machine learning algorithms like 1000x less data efficient than humans. So yeah, you need 1000x more data. Right. If a human can learn something in, in one example or 10 examples, the computer is going to need 1,000 or 10,000. Now do you really want to reset the stupid state of the physical world 10,000 times? You might do it 10, but you're not going to do it 10,000. Right. So that's where you want a simulator where you can just click reset and everything's back to exactly how it was. So I think this stuff's going to play a role, but I think more fundamentally that data efficiency gap has to be understood.

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 agentix software are you excited about? Do you expect to, you know, what's agentic mean? Yeah, basically bots. It's, it's like what we're calling bots now.

What's a bot.

But, but, but, but anyways, like I just, you know, I don't know.

From Star Trek.

Yeah, yeah, maybe. No, but, but, but I think about a world in the future. You know, do you, do you expect to be, I don't know if you're a, A slack guy, an imessage guy. Discord, maybe no messaging at all, just, you know, you know, telepathy. Telepathy. But, but do you expect a world in the future where you're just, you know, perfect interaction between, you know, human employees and agents? Or is it, you know, going to be more like, you know, you'll do the odd deep research or maybe you send some automated outbound emails or have some Codex bots running.

I don't even follow this.

When do you think you'll be able to book a flight just by saying, I'm trying to get to New York tomorrow.

Oh, see, the worst part about this is like. And that's going to come pretty soon, actually.

Okay, right.

We're going to pretty soon have computer use models that are actually capable of going to delta.com and booking a flight. But then what's actually going to happen is Delta, Delta is going to partner with whatever company does that and they're going to put it behind the stupid thing. And like. Yeah, so that's going to. Yeah, that's going to be here in a few years, right? Not with agentic shit, but just with normal. Hooking the APIs together, right?

Yeah.

What is the bullish on APIs?

What is the mistake about like the agentic buzzword? Like what are people like even describing again?

It's another thing that I really have no idea what it means. You know, I was hanging out with some friends last night and like, like my friends, this VR company and the, you know, the, the CEO is really interested in things being open source, but he's also really interested in making sure that things are protecting our intellectual property and proprietary. And the truth is he has no idea what the word open source means. He has no idea what it means that they can copy his shit.

Right?

Like that someone else could use it. He just, he just heard the word open source in some like buzzword thing and he's like, do we have the open source? Do we have the open source and the thing.

Okay, so check the box.

Check the open source box.

But let's protect our ip. Last question about the age. 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. And so you have like 10 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? And then is it just a matter of like better harnessing to actually get to two hours of work, which is kind of what the agentic people are like advocating for?

No. So I don't think it's better. Harder. But this is definitely a real phenomenon. This is definitely a real phenomenon you can experience. There's papers exploring it which show that if in 10 seconds there's absolutely no way I'll come even close to a modern LLM.

Totally.

Because the first shot from the LLM is great. And then it kind of degrades and it degrades pretty quickly. Whereas humans look a lot more like this. Humans can stay coherent internally for much longer. So. So yeah, I think that that's a real thing. I think that that's mostly going to be fixed by like long context, just more energy. Long context. RL yeah, just like you just got to do it. We'll figure out new ways to make the context better. We'll combine diffusion and auto regression in some clever ways. Yeah, I think that this is just going to be like, there's not going to be a breakthrough here. There's not like one magical thing that we're missing.

Yeah.

I think it will be a continued plot. The same thing with data efficiency. I think people will start to care about it. Some new tricks will come out. Some of them will work, some of them won't work. We'll continue to do graduate student descent until we find that. Anything.

Anything.

Let's wrap it.

Last question for me. Anything that you're particularly optimistic about. Anything. You check the timeline and you think this is awesome. I love this. I love this. I want to see more of this. Maybe a little white pill to kind of cap it off.

Yeah. So here's something I'm optimistic about. That fact that the one server can't run 10,000 users. That is most of the reason that the modern Internet. That is one of the reasons that the modern Internet sucks. That so much of the stuff is a non recurring expense. And then it becomes really, really hard to compete with these people. Right. Like you could run Twitter on one computer. Yeah, and 20 people could do it too. But, like, they don't, because again, these companies have moats and they invest in making sure that their moats can't be broken. With AI, I think there's going to be a much less of a vote, especially when you look at the move from autoregression to diffusion. So auto regression can run in large batch sizes. When you run chat, you're running with a whole bunch of other people on that same computer. Yeah, it's only 100. It's not 10,000, but still it's 100. Diffusion is running the cloud at batch size 1, and once you're in batch size 1 land, running it locally starts to make sense, actually running the models locally, or at least having your own computer in the cloud, not being some shared resource that's really controlled by some else. So, yeah, this was never a thing because you can't put lots of people on a gpu.

That makes sense.

They tried some weird stuff with the licensing.

Yeah, fantastic. Well, thank you so much for stopping by. This is a great conversation.

I wish we had a full hour. This is great.

We'll talk to you soon. Josh, George.

Cool.

Bye.

See you later.

Cheers.