SpaceX’s $2T Case, Nvidia’s Shock Selloff, America Turns on AI, Trump Pulls AI Order, Bond Crisis?

All right, everybody. Welcome back to. the number one podcast in the world. It's the All-In podcast episode 274. Sacks is out today, but we're very lucky. to have Gavin Baker from a Treaties. Management joining us. The spicy takes. must flow. Welcome back to the program, bestie. Gavin. >> Thanks for having me. Always love it. >> It's been a huge week in tech. We can. start with the SpaceX and OpenAI IPOs. We've got Andrej Karpathy joining. Anthropic, Nvidia crushing it. So many.

different to go, but I think we'll start. with Andrej Karpathy joining Anthropic. Karpathy is only 39 years old. He's. already a legend in the tech industry, if you don't know him. I believe he's. also coming to Liquidity, Chamath. >> He's going to keynote on Monday morning. >> Oh, fantastic. >> I did not know. Tuesday, Tuesday, Tuesday, day two. I think he's. keynoting. Okay. >> As is Gavin. Gavin will be there. Founding member. >> Gavin anchoring day two. >> Excellent. Yeah, and this is Gavin's. second appearance at the event. >> I look at those two bookmarks, Andrej. Karpathy and Gavin Baker. >> Yeah, you know.

>> Liquidity pulls in the stars. >> Obviously, Andrej was a founding member. of OpenAI. He led the self-driving team. >> Also, hold on. Gavin is going to help us. judge the best ideas section as well. >> Excellent. I don't know if you know. that, Gavin, but you're a judge. You're. going to be a judge. >> I'm a pretty thing, man. I'm easy. >> Yes. Karpathy also coined the term vibe. coding. He recently built Auto Research. I think we talked about that here a bit. That's an open-source training tool. It. helps AI models improve themselves by. running 5-minute experiments. That got. over 82,000 stars on GitHub. He did that.

like as a weekend experiment, and all. these civilians started building their. own uh recursive LLMs. Really inspiring. And the Andrej Karpathy skills is a tool. based on his set of principles for. Claude code, and somebody just released. that. And so, it's just pretty crazy. when you think about it. He's going to. be in charge of a new pre-training team. at Anthropic. The focus obviously being. recursive self-improvement. In other. words, they're going to have Claude improve.

itself and they've already talked a. little bit about AI improving AI over at. Anthropic. Chamath, what's your take on. this? Is. this super important in 2026? Obviously, Karpathy is super well respected. He's. obviously, you know, one of the true. talents in the space, but hey, we're in. a we're in a different inning than we. were say 10 years ago when he was at. Tesla or 5 years ago when he co-founded. OpenAI. >> You know what's interesting? If you go. back to like Google, the culture of Google which they got.

right was. the singular technical talents there. They were singled out and they were. called Google fellows. I don't know if. you guys remember this like Amit. Singhal, Shreedhar Ramaswamy, Jeff Dean. These guys are stars. And what's. interesting is if you track what folks, particularly Jeff Dean I guess now. because the other two aren't there. anymore, but. what they did inside of Google, it's. like wave upon wave, they were at the. foot of those waves. What's interesting. about Andrej, he's been at the wave upon.

wave of AI. He was probably the first. person that really commercialized the. Richard Sutton bitter lesson essay. when he was leading FSD at Tesla, which was really about the brute force. computation. And I remember him telling. me the story. I don't know if he said. this publicly or not, but where he spent. a portion of his time, I want to say a. quarter of his time labeling data. Could. you imagine like 2016, 17 like hand. labeling video data from Teslas?

So he did that, then he's co-founder of. OpenAI. He's a star. And he's an exceptional human being and. he's super curious. And. then what he's done as a kind of a free. agent. is also quite impressive. So I think. that this is a really important deal. I. think he's one of these. really curious people that can be sent. off and they'll just go and. invent new things. And I think this idea. of recursive self-learning puts these. models on. a combination of overdrive and.

autopilot. And so if you put those two. things together, I think that you start. to. you can potentially live out this idea. that there's an order of magnitude. improvement on a yearly basis. So like. this new form of Moore's law. Well, so then the model quality just. goes absolutely parabolic. Just like. this. Straight up. >> And I think that a bunch of compute at. the problem and these things learn. really quick. I think is the high-order bit there. Gavin, what do you What's your take on.

Anthropic's recent success and their. massive hiring binge? >> The success is extraordinary. It's. undeniable. I think the fact that they. are now they were even positive per the. Wall Street Journal in the most recent. quarter. is a really important fact for kind of. the whole AI narrative. Because now. there's. you know, you could talk about circular. funding, you could talk about ROI, and. we could go look at the ROIC of the. hyperscalers. But if OpenAI and Anthropic are at call.

it $100 billion of ARR now with 80%ish. gross margins on inference, like the. returns are there. And then if we add in. and they're growing really fast, if we. add in Gemini, we add in Cursor, we add. in xAI, we add in open source, you know, it's it's not hard to see 200, 300, 400 billion dollars of ARR at the. end of this year at high [clears throat]. market. >> Across all of the Across all of the.

language models. And you're talking. specifically about the private language. model companies, maybe not Google, which. is obviously public. You're including. Google. Okay. >> but I was excluding, you know, a lot of. the returns to this GPU spend have come. from you know, better recommender. systems at Facebook and Google, Amazon, better ad targeting, better ad. measurement. >> Sure. >> So, excluding that and just narrowing it. to LLMs, which I think. is the. possible definition, and it seems like there's going to be a.

really strong ROI this year, even. excluding what are still some of the. most economically important and. profitable use cases for GPUs and AI. infrastructure. I do think what Karpathy is working on, recursive. self-improvement, is really important. and unlocking that and continual. learning, you know, maybe the two final frontiers. for for AI. And just the idea of recursive. self-improvement that the model,

while it is training, you know, during a. forward pass, has input into its training, or another. model has input into the training, I think that could be really powerful. and I think. Chamath's statistics of. of, you know, 10Xing every year, you know, might seem conservative if. that comes to pass. And then, of course, continual learning is the holy grail, where the model learns from experiences.

the way humans do. Yeah. And that's. something we haven't unlocked yet. And those those those two combined, I. think would um. they might pull the future forward in a. very real way. >> Yeah, and we have right now Anthropic. has a decent lead on everybody else, whether it's 3 months or 6 months. Obviously, they're probably 6-12 months. ahead of open source. Maybe they're. 3-6-9 months ahead of their. contemporaries, but they have a lead. You put Karpathy in there, Friedberg, now you have Karpathy, he does recursive.

and at some point, and it may have even. occurred at Anthropic, the AI is going. to be improving. the language model more. than. the humans in the loop are doing it. Obviously, they're orchestrating it, Friedberg, but at what point do we think. this, let's call it, super recursiveness. occurs? When will we cross the recursive. valley. and AI is doing more to build a language. model than humans are?

>> I'm not sure when this idea that you. feed the whole model into a context. window to train itself and build a new. model is going to happen, but I think. there's probably a lot of different. architectural paths that could be walked. here. One of which is this idea that you could. make much smaller models and then create. networks of smaller models that work. together where you ultimately have. less energy or less cost per token. produced out of a. aggregation of models than you did with. one single large model. I've said this.

probably three or four times now. There's a lot of work and a lot of. opportunity ahead. in kind of re-architecting models and. re-architecting how models work together. to solve problems. My guess is a lot of. leadership that that he can bring. to exploring those paths. And all it. takes is a minor breakthrough and your. cost per token drops in half. That's a. tremendous efficiency gain. that is seems very much on the horizon. because some of the early papers, I. think I shared one from MIT a few weeks. ago, indicate that there's a lot of room.

to run here. >> In terms of re-architecting models and. deployment of models. >> These very small models, uh, small language models and then. verticalized ones are the future. We've. got a company Abacus that's doing it for. corporations. Crushing it. Everybody's. got an interest in doing this. And I. don't know if you saw the news this. week, uh, Chamath, it happened about 2. weeks ago very quietly. Chrome included. Gemini or Google included in their. Chrome browser the Gemini Nano model.

without telling anybody. 4 GB on your. computer. And that's the one that does. like proof reading, spelling, auto. complete, all that. So, now we have. Google. covertly installing this on everybody's. operating system. >> on. Hold on. Covert is a strong word, so. let's not use that word. >> Without telling people, without giving. people a heads-up. Let's say it in a way. that we can both agree. >> We're in the phase now where. I think breathlessly talking about every.

model improvement is a waste of time. There's no ROI in it. We are on a path of accelerated. learning, and we're going to start to. see end user achievements that were. heretofore impossible. That should be. the focus. So, for example, we were able to solve, I'm just. collectively saying we, in this case it. was specifically. OpenAI. By the use of a human, and this is. important, you know, a math problem that stood. outstanding, not been solved for decades.

and decades. I can tell you in a different example, there are drug candidates that. are about to enter clinical trials and. INDs that were sitting on the shelf and. people didn't think were very viable at. all. So, we're at the phase now where these. things are front and center, they're. useful to people, they're increasingly. valuable. I think what we should do now is focus. on these end user. use cases. because the way that you say it, in my.

opinion, is part of the problem because. it starts to create this boogeyman us. versus them thing, and I'm not saying. you're doing it on purpose, but I'm. saying this is exactly why I think. so many people are becoming sort of like. it's a four-letter word now when you. mention AI because it's presented as. this thing, and I think we have to. present the other side of it, at least. so that people have the data. So, I. don't think Google's in the business of. doing shady or shady things. I don't. They're not that company. There are. other companies that would. >> Meta.

>> [laughter]. >> You're referring to your alma mater? >> I'm not going to say which ones, okay? But Google is not that company. So, I I. think that the reason they did it was. probably because there's user utility. And my point is we should focus on the. user utility because I think that's the. story we're telling from now on because. I think we, collectively, the four of. us, can responsibly tell both sides of the. story in a well-balanced way because I. think nobody wins if we become Luddites. and go back in time. >> Yeah. >> And I think that if we don't if we're. not careful with our words, that's what. will happen. >> Yeah, and by the way,

obviously not a Luddite, but this is. what. you know, has been reported by a lot of. folks that people were. surprised, shocked when they saw the. size of the model being done in the. background, and it has triggered some. people looking at it around privacy, and. I do agree that Google is not a bad. actor in the space. So, probably a speed. hour more than anything, I would say. >> May I just add two things?

Um. there's attorney maxing, and then. there's attorney maxed. And Google is probably. >> [laughter]. >> attorney maxed. >> Yes. >> Yeah. >> It happened for a long time. And the. second second thing I would say is I do. think it's incumbent on all of us as. Americans who are involved in the. technology industry in one way or. another. to be advocates for a the positive, optimistic possibilities. that AI introduces to to everyone in. this world. because it it is starting to feel or.

seem. like there may be a CCP-funded. campaign against AI and data centers in. America. And that's very logical for China, but. it is not good for America. And so, I just I think it's. it we all have responsibility, is what I. would say. >> Yeah. Who do you think's doing. a poor job at that and responsible for. this? Is it Dario with his constant hey, everybody's going to lose their job?

Who's responsible for this? Is it the. CEOs blaming AI for their layoffs? What's your take on this, Gavin? Look at. Hold on a second. Everybody is. trading their own book. It makes enormous sense for Dario to try. to create the boundary conditions for a. regulatory moat because he will be. inside of the tent pissing out. He's big enough now. And if you notice that. a lot of the breathlessness has ramped. up. And Jason, we've talked about this. You.

can annotate successive rounds of. fundraising and successive scale with. the volume. So, I think that it's a reasonable. business strategy and I think that he's. quite clever. And I think that look, if. you actually and I and I do this, if you. actually just have an ash bot, an ash. agent inside of Quad and you ask it what. it would do, it would come up with this. strategy. And meanwhile, there are other. versions of other counter strategies and. counter exploitative strategies. The. point is that each CEO has a clear. incentive. They're operating at such a.

level of scale. that they're they're just reading their. own book. So, it's it's up to us to take. a step back and actually see the forest. from the trees. I think Nick, can you. find this? There was a clip of Shyam. Sankar, friend of the pod, fabulous guy, the CTO of Palantir and he was I think. he was on Fox News. and he said, "Stop breathlessly asking. these model makers what they think. Go to the end user and ask the person in. the factory that's using the model and.

ask him what he or she thinks. Ask what. the doctor thinks. Ask what the. scientist think and start to tell those. stories. That's what we should be. talking about.". >> Yeah, and Gavin, you were. I was sort of asking you your opinion on. what's what's who's causing this and. then what's the solution? Like do you do. you have folks you think in the industry. who are representing it particularly. well we can point out, "Hey, Elon has. said we're going to move to a world of. incredible abundance and working will be. optional." I think that's on the margin.

a little scary for people to hear. because they hear no job. But, he does say, "Hey, universal basic. income is probably going to have to come. into, you know, place." And he said that. multiple times. You have Chamath, according to Chamath, talking his own. book, scaring the bejesus out of people. in order to get regulatory capture. What do you think is going on here? And. how can we do better as an industry? >> I think Chamath outlined like a very. viable and positive path forward. We're. just, you know, real people who are not,

you know, at the tip of the spear. These are the positive impacts AI's had. on my life. I was at a. I was at I was at an event maybe 10 days. ago. and someone who runs a hedge fund, his. daughter was born with a very rare. genetic mutation. that effectively would have. normally condemned her to a life devoid. of joy, meaning everything. The neurons in her brain were not. firing. So, she wouldn't.

you know, who knows what her life. expectancy would have been or what the. quality of her life would would have. been. And it's it's a tragic disease. He said he didn't accept that as an. answer. He found He did an enormous. amount of research with LLMs and found. an existing safe drug on the market that. they thought would have a meaningful. impact on his daughter's condition. And it did. It took I think the percentage of times. the neurons were firing was 30 or 40%. And it took it up to 80 or 90%. And that.

means that she can live a normal life. She may not be as smart as she would. have been, but she will live a normal. life. And he's now figured out how to use AI, how to to further tailor that drug. And. you know, there've been all sorts of. advances in. in protein design, etc., etc. And he's reasonably confident he's going. to have a drug in months. that is a complete cure. And that's just one person.

one dad who was unwilling to accept. defeat for his daughter. and who changed her life and the life of. everyone else with that disease. And we. tell those stories. So, I think Elon's. doing a good job. A future where work is. optional, I think that sounds great to. some people and. you know, scary to others. You know, four-day workweek, you know, I think. it's is probably something that sounds. sounds good to a lot of people. I think. Jensen is doing a good job of being an. effective advocate. And I do think. anyone who's trying to drive reg-.

I just we need to stay focused on the. positives. That's what I'd say. >> Yeah. Freeberg, what's your take here on the AI. PR crisis, if we'll call it that. Uh we. had three different. commencement speeches that were booed. Eric Schmidt being one of them, two. other ones by maybe less notable folks. When you hear young people booing AI. vociferously, why are they doing that, Freeberg, and what's your take on the.

overall PR problem and how to turn it. around? >> Uh that's a. There's a long answer to that question. Um. It relates in some ways to your concerns. about socialism and polarization. >> answer? >> Yeah. What's the long answer? >> I mean, that's like. like why do people hate technology? The greatest technological. >> Why do they hate this technology? They. love their phones. They love the. internet. This technology they hate.

>> Mhm. I think that there's like an underlying. view that technology creates leverage. for a small group of people. which creates power imbalances and. nothing represents that more than AI. That a small number of people that. control and profit from and benefit from. AI. are going to end up getting outsized. returns. relative to the broader population. That.

the time to diffusion of the technology. cuz ultimately all technologies like. commoditize and diffuse. But the time to diffusion here is such. that it's going to be like extremely. asymmetric for society. And I think that. there is something fundamental about. that. It's like, you know, nuclear bombs I. think really created this this moment in. people's minds. in the mid-20th century that by the back. half of the 20th century gave everyone a. high degree of skepticism about. technology and science generally.

That those who have the knowledge and. those who engineer solutions with the. knowledge can create outsized advantages. for themselves and it puts the rest of. us at risk, the rest of the world, the. rest of the population at risk. And because those questions about when. does this benefit me, how does it. benefit me can't be answered today. the economic benefit that's accruing to. the few today becomes the narrative, it. becomes the story and it becomes this. like power system. that a few people take from the many.

And so there's something deeply. disturbing for the average person about. that. They don't understand how it. works, why it works, what it'll do for. them, when it will do it, and all that. they're being told is that some people. are making trillions of dollars. So, I think that it's pretty obvious why. this has got such a backlash. Secondly, I think that there's a deep amount of. external energy that's fueling this. anti-technology sentiment in the United. States and has been for decades. I think to Gavin's point, I don't think. it's just China with NGOs today. I think.

that there is a long history. of. state actors intervening in media. activities in foreign nations to try and. create the sentiment. and fuel a sentiment that reduces. progress in that competitive state. I think this goes all the way back to. KGB design. during the Cold War and it's been. refined and honed and improved over. time. This is not just some conspiracy. theory. There are plenty of great books. about this. The techniques of what's.

going on specifically today, I don't. know enough. I don't have any great. details on that. But I don't think that. there's no foreign interest in seeing. technology advancement slow. in competitive nations. The United. States probably does similar things to. other nations and I think that that's. probably a key part of this. And then I think this this like third. piece is like when. the Copernican revolution happened, it. was a mind, you know, like. heliocentricity was a totally new way of.

thinking for humans and it was uh deeply. disruptive to the church. And it was deeply disruptive to the. power centers, which were. the centers that could tell people Earth. is at the center of the universe, we're. in control, we're the direct channel to. God. And the idea that the sun is at the. center of the solar system and we spin. around it and we're a tiny speck in the. universe was very hard for people to. grasp. There's something about AI that's. very like not human-centric and it kind. of shifts. and with the ego of the human. It.

it's it's almost anti-humanist. And I think that that's like a deep. psychological current for a lot of. people and their disdain for this. technology. It fuels it. It's not the. cause, but I think it fuels it. So I. think there's a lot of complicated. aspects to this, J Cal. You know, I. don't think there's like a simple put. put Cham on on a podcast and he'll solve. the the problems of AI right now. I. think that there's a real set of shifts. happening and there's a real set of. global competition underway. where, you know, various state and. actors and interests are competing with.

each other. >> Yeah. Cham, do you think that we should. slow down? >> I don't think you can. >> No, no, no. Do you think we should slow. down? >> No, I I think I was just talking to some. people on a Zoom right before this, but. I think after the Manhattan Project, the. research labs were stood up to maintain. our scientists that worked on the the. Manhattan Project from uh effectively. leaching back or leaking back to. Russia and Germany and and and other. places that that were adversary to the. United States.

And they all were against the nuclear. bomb. They worked on it because it was. necessary for the United States. security, but then when Russia got a. hold of the secrets, they were leaked. because people were worried that if the. US had all the power, there would be no counterbalance to the. power. And so the the nuclear secrets were. leaked to Russia for that purpose. Then. when Russia had the nuclear secrets and. they began developing hydrogen. fusion bombs, and it it was clear that. they were going to race ahead. The. United States raced ahead with. developing nuclear bombs as a.

counterbalance to Russia. When the. proliferation began, there was no. stopping it. It began and you had to. have this balance in the world, otherwise you have effectively an. asymmetric power that can do whatever it. wants globally. I think there's that moment in the world. right now where. if the United States does not. advance its AI technology, the. availability of it, TBD, industry, taxation, all these all these things. that we're talking about doing, there. will be someone else that will. And if someone else does, we can go.

through what would happen. There's a. There's a complicated game theory on. this, but what would happen if China had. sufficiently advanced models and. sufficiently advanced scaled deployment. of those models relative to the United. States, as you do that analysis, you. realize, wait a second, that's probably. not a healthy place for the world to be. It's also probably not a healthy place. for the United States to be the only one. with AI. And so I I think what we end up seeing. is if we do try and slow down AI,

we kind of lose this moment of balance. that's necessary when you have a. technology proliferation like we saw. with the arms race after World War II. that, you know, we're going to see again. here. >> Chamath, you. I think bring up a good point. You know, should we slow it down or could we slow. it down? There actually have been some. discussions about ways to do this. One. of them would be, hey, with. self-driving, people are scared that all. these cab drivers are going to lose. their jobs, Uber drivers, cab drivers, bus drivers, truck drivers. This is, you.

know, over 10 million people in the. United States driving things for a. living. Would you be in favor of some of the. announcements that. that will be. a paced rollout, it won't happen all at. once. In other words, those people will. be given some amount of job security to. stay behind the wheel with it. Another. example that's been given is if you put. Optimus into Amazon factories or the. Figure robot just did like a week of. just sorting packages. I'm sure. everybody saw that video, we'll insert. it here.

That Figure robot sorting these, hey, if. Amazon deploys those, there'll be a tax. on those per hour and we'll tax humanoid. robots in some ways and then use that. for, say, retraining people. Those are. two very specific conditions and. approaches that people have been. promoting. Do either of those resonate. with you in any way? >> I think it's. interesting that in all of those. discussions. I've yet to see an actual survey of only. the truck drivers and only the package. sorters. >> [clears throat].

>> The question that I would have is do the. people that do these jobs want these. jobs? And if they do, then there's a. reasonable claim to make to keep those. jobs the way that they are. If you're saying this is the job that I. do, I love it, I'm able to provide for. my family, great. That's a very. different argument than well, you know. what? Amazon has 35 or 40% churn inside. of their warehouses. and we should probably ask the question, why is that? Because if it was such a. great job, I suspect the churn would be. 3% or 4%. So, what exactly is it that we.

want to protect? And have you asked. them? And I think that this is just a again, a. bunch of. people in the peanut gallery who want to. take a moral high ground and try to make. some other group of people feel guilty. or feel bad. At no point are we actually. asking the conversation that. that we should be having, which is. it's interesting to me that the there. was supposed to be an EO, an. presidential executive order that was. announced today. And then it was pulled. It was scrubbed.

at the last minute. >> Mhm. >> Did you guys notice that? >> Yeah. >> And yesterday, what was leaked was. everybody that was attending. It was all. the big neo labs CEOs, and it was all. the big hyperscaler CEOs. Including friend of the pod, Nikesh. Arora. Shout out to Nikesh. And then it was scrubbed an hour ago. Why was it scrubbed? And the president said that there were. aspects of the bill that he didn't agree. with. And as far as we can tell, the. aspects would have required some amount. of. supervision, insight, review from the.

federal government. >> Of language models specifically. Of. these frontier models is what I read. >> Not language models, cuz I think just of. AI, because there's going to be many. different kinds. They're not always. going to be language models, but of AI. So, look, I think Freeburg is is right. We are in a proliferation. with China. I think it's actually good. that China is less than 9 months behind. us. I think it allows us to find a detente. where we have a certain magnitude of. capability that they also have. And that allows all of us to then seek.

peace and abundance. And the fact that. we are orthogonal societies, we are. organized differently, increases the. probability of finding peace using the. René Girard kind of framework of mimetic. theory, than if if it was like us and. another country that was exactly similar. to us. So, I think what we need to do. we probably need KYC. I think that that. should be something that us and China. get together and say, "You don't want it. to get into the hands of people you. can't control." You probably already KYC.

those models anyway inside of China. You. already review those training runs. before you allow these models to get. released. We already know that that's. happening. >> Yes. >> So, we should probably do some sort of. KYC so some crazy person doesn't create. some biological weapon. I think that. those are like some reasonable ground. rules, but otherwise Freeburg is right. You have to take a a little bit of a. deterministic view here, which is that. we are in this existential race. and we need to get to the place where. each of us, meaning us and China, can. look each other in the eye and say, "All. right, weapons down." So to speak.

>> Kevin, I'm going to hold you to answer. two questions. One, should we. run frontier models cuz that's. specifically what was mentioned in the. leak about the EO frontier models, the. powerful ones. Should they be run. through some sort of testing before. they're released and should there be. some regulatory framework for that? That's my first question to you. Yes or. no question and then you can explain. your answer. >> Jeez, like I just think it's such a. complicated topic. It feels.

we're a little early for that. I don't love the idea of the United. States. um doing it and no one else doing it. I. like I think in a world where we hold. hands with China. like I think that's that's much more. palatable and we are aligned and we. trust each other and have kind of. verification. uh capabilities. I do think. >> Right. Yeah. Let Let me then rephrase. it. Should China and the US come up with.

a simple battery of things that have to. be. tested before these go out including. bioweapons, terrorism, and in genre of. and that vertical of just really known. dangerous things just like the FDA might. test for poisons or contaminants in a. food or a drug. Would you be in favor of. that? I'm curious. >> So, a few things like the one one thing. that's great about America is there is. one thing that's. just.

we have other forms of regulation. >> Self-regulation, sure. >> We have self one we have self-regulation. also we have the courts. And if an AI model company. behaves responsibly. they know that there are. ways that people who have been harmed. can seek recourse. And so we already have a system that. encourages responsible behavior on the. part of the model makers. >> That's a great point because OpenAI is. being sued right now by a kid who who.

killed themselves after talking to. OpenAI's model. So, you're you're. correct in that. Yes, after the fact. Yeah. >> And we will see we'll see we'll see more. of that. I just. you know, to me once you give something. give a power to the government. it's almost never taken back and it. seems to grow. And it's kind of a one-way a one-way. path. >> One-way ratchet. Yeah. And then the. one-way second yeah, second question. then. Chamath is saying hey nobody listens to. the you know, these cab drivers or maybe. the.

people sorting the packages do they want. their jobs or not. Actually the UK. there was just a 60-minute special in UK. and also Boston and New York are pretty. adamant that they want humans to stay. and they want to ban self-driving in. those locations or severely limit it or. maybe limit it in some way to let those. people keep their jobs. How do you feel. about that possibility? Is that. something you think society should be. open to some gradual licensing. >> They're going to get sued for wrongful. death. When somebody runs over somebody.

else and you could have implemented a. solution that has a zero death rate, that's very different from package. sorting. >> Okay. >> Go talk to the package sorters is what I. say. Go talk to the people inside the. Amazon warehouse. Ask them what they. would rather do at Amazon. Ask them. >> Yeah, sure. But Gavin, what are your. what are your thoughts here on either. one of those examples here? >> I think going to a city where you can't. get in a Waymo or a cyber cab is going. to feel barbaric and unsafe until you. >> Agree. I strongly agree. >> I don't know if you remember like but. the early days of Uber, sometimes you go.

to a city where there was no Uber. >> Yeah, that'd be incredibly frustrating. >> What I'm not going to come back until. they have Uber. It's so inconvenient. And I think so whatever individual. municipalities decide, I do think one, Chamath's point is really powerful. There's 50,000 automotive deaths per. year in the United States if I recall. correctly and a million globally. And you know, that's not tolerable and. there will be for sure be wrongful death. lawsuits and then just from a. convenience and quality of life.

perspective, I just don't think it's. going to persist. And that's another great thing about. America is you know, you have this. patchwork of different states and. municipalities and. each one doing things in a different way. and I'm not suggesting that's good for. AI, but it does tend to, you know, as historically the Curley effect aside, led to, you know, I think more positive. outcomes where cities and states. compete. You know, the Curley effect. being that. >> Yeah, that yeah. That this is a really.

important point you're making, Gavin. With Flock Safety as but one example, we. had a an AI there's an AI tool called. Flock Safety. It's cameras that use AI, monitor people who are committing. crimes. There's a privacy issue around. it. It is bottom-up. You just do it by. town. It's not top-down and states can. regulate it. Same thing will probably. happen with self-driving and states will. probably have some say in how AI is. deployed even if maybe some centralized. governments don't want to do that. I really think this It comes down to.

>> The Flock. >> thing I think it's so good, Jason. Crime. is now a choice. >> Yeah. >> You know, I think the the Cambridge City. Council voted. to turn off gunshot detectors 2 days. ago. And. >> which city did that? Which municipality? >> Cambridge. Cambridge, Cambridge, Mass. >> That's the place where Harvard is. >> That's the place where Harvard is. >> So, the geniuses coming out of Harvard. in that town decided. gunshot detection. shouldn't occur. >> We don't want gunshot detection. Just so. we're clear.

>> It's wild because, you know, there's. there's a theory that it disadvantages, you know, that it might lead to an. illegal migrant. who's shooting a gun being apprehended, and we don't want that. >> Got it. >> And A16Z had a great essay on Flock. We can really, really solve crime, and it's just a choice. And different. states and municipalities will make. different choices to be pro-crime or. anti-crime. And I'm sure they don't cast. it as pro-crime. There's. an, you know, some sort of, you know,

moral or ethical reason they may make. that choice, but people will vote with. their feet over time, and then voters. will vote with their votes, and we'll. see what works. >> Have you guys been to Vegas recently? My. wife and I went to visit Vegas, and we. spent the. the afternoon with Ben Horowitz and his. wife, Felicia. She has done this. incredible job with the Las Vegas Police. Department. It is one of the most impressive things. I've ever seen, and to your point, crime is an option, and they've said no. So, what happens there is they have.

gunshot they have drones that get. deployed off the roof of the police. building. We were sitting inside of. mission control where you see it. happening, Jason. If something happens, they have eyes on site within minutes. They can track offenders and bad guys. all the way to wherever they're hiding. And you walk out of it, and you feel. incredibly safe, like they're really on. top of it. And when you understand the. level of investment, it's not it doesn't. take billions of dollars compared to the. cost of the crimes. It's de minimis.

It's de minimis. Especially when. compared to the cost of the crime. occurring. >> Exactly. If you gave the Las Vegas. Police Department. 30, 40 million dollars a year, it would. be the safest city in America and that's. all it would take. >> Yeah, exactly. And the for the privacy. concerns Freiberg, there are very simple. solutions to this. I I am a privacy. advocate myself, of course. We all want. some level of privacy. I had the Flock CEO on This Week in. Startups twice in the past 10 years. He's very considered. And the way they. do it with Flock is they allow you to. have a rolling database and I think.

there's a maximum you can save the. license plates for and they don't do. facial recognition. I I don't see why. not, but let's put that aside. You can. only keep it for two or three years. And. then they insist on having an audit. trail on it. So there are all little. things you can do on the back end to. protect privacy with audit trails, etc. We got a lot more to get to in the. docket. I just want to just give my. final thoughts on. what we're talking about here in terms. of the AI problem. and the PR problem. I think we have to. recognize that the layoffs that are. occurring in Big Tech and in a lot of.

these places are not just the bloating. issue anymore. And I'm just going to. point to two factors that I think are. scaring the bejeezus out of people and. we just have to admit that this is. occurring as opposed to we've been. debating it here. Is it occurring? Is. this just cover? And are we AI washing? The first one I want to give you an. example of is Matthew Prince. who's the CEO of Cloudflare, incredible. company, public company. Two weeks ago I. laid off more than 20% of my workforce. I didn't do it because Cloudflare is. struggling. We posted record revenue.

growth, have strong free cash flow, and. are adding an unprecedented number of. customers, yada yada yada. And he says basically he's getting rid. of measurers. Measurers are the people. who manage people and who measure data. And he just says we're getting rid of. all those people. They're unnecessary. because of AI and we'll be adding to. people in other positions. At the same. time Zuckerberg did another round of. layoffs, and they were done in a way. that people felt was not considered. and a bit.

um. What's the word? Dystopian. Dystopian, thank you, sir. Uh. he did him in a in a pretty dystopian. way. Here's Zuckerberg for 30 seconds. >> In general, the average intelligence of. the people who are at this company is. significantly higher than the average. set of people that you can get to do. tasks if you're working through the. contract um. through through these contractors. So, if we're trying to teach the models. coding, for example, then having people.

internally uh build tools that or or. solve tasks that um that help teach the. model how to code, we think it's going. to dramatically increase our models'. coding ability faster than what others. in the industry have the capability to. do who don't have thousands and. thousands of extremely strong engineers. at their company. >> [clears throat]. >> Okay, so what Zuckerberg did at the same. time, concurrently, he told everybody, "We're laying off these 8,000 people." A. lot of those people are incredibly. talented. Some of them are on H-1B visas, creates. all kinds of chaos for them in their.

personal lives, and obviously they're. having record profits there as well. At the same time, he was laying off. those 8,000 people. This is after tens. of thousands of layoffs before, which. were obviously because of bloating. He. said, "We're putting recording software. on every single person in the company's. computer to study and train our model.". And people were like, "Oh." And previous. people said, "I built during the AI. hackathons they had months ago. I. built all these AI tools to make my job. uh more efficient." And then Zuckerberg. laid me off. So, the now per- the.

perception people have now, and it's. quite correct, I think, is the most you. can hope for here is you keep this job. for some amount of time and train your. way out of it, and hopefully there's. some more work for you, but they're. studying you, and Zuckerberg just said. it plainly there, "Hey, we're going to. study everybody here, and that's going. to lead to more replacements. This is. scaring the bejesus out of people and we. need to have an answer for it. Yeah. >> I thought the Matthew Prince note was. horrible. >> Okay, explain. >> This was like from the.

PR school of retards. >> Okay, here we go. >> You could not have written a worse memo. It's like you reduce humans to a label. called the measurer. and then you're like I'm going to lay. off all the measurers. I mean. I just think that part of this again, I'll go back to the. maybe the Sham Sankar quote that I'm. thinking about should be extended beyond. the model makers. Can you just play this. for 1 second and I'll tell you why I. think this is just so.

>> And then we'll go on to the S1 from. SpaceX. >> We're listening too much to the. inventors of AI. I know that's. appealing. They're geniuses, they're. smart. We need to be listening to the. frontline factory workers who are using. AI saying, "Wow, I was able to add a. third shift. I was able to hire more. workers." Or the ICU nurse who says, "I. have more time to spend with my. patients. I'm able to ensure they don't. code during a shift change down.". >> so look, my my point is like the first. part of what he said applies here, which. is who cares what Matthew Prince thinks? Because the reality is that if this is. the way that you're going to message.

something as critical as this, I think. you did a horrible job. And now you. label these people and you put a scarlet. letter on their back. So now when they. try to get a different job, they're. like, "Oh, you're one of the Cloudflare. measurers?" How does that help anybody? It didn't needed to be done this way. There's enough of these tech. CEOs that are now public. You can hear. them, you can understand them. And I think what we're learning is men, they're really good at one thing and. they're not necessarily as good at all. the other things. >> Yeah. Uh okay. >> And so I would say shut the up.

Get behind the keyboard, just do your. job. And if you need to manage. something, just manage it, but don't. write these missives. You're terrible at. it. All of you. You're all terrible. You. suck at this. >> All right. >> End of my TED Talk. Thank you for coming. to my TED Talk. >> Thanks for coming to Chamath's 18-minute. TED Talk. And we'll we'll we'll uh keep. moving on. >> Sorry. And sorry. When everybody gets. upset, this will be why. >> Yes. I mean I I do think the Zuckerberg. this and Jack saying, you know, "Hey, we're going to have half as many people.

everybody reports directly to me." This. is all building this fear in society and. I think people are right rightfully. scared. If the people building it tell. you be scared, your job's going away. >> Wait till the next. regulatory filing comes out from these. companies and they authorize a massive. share buyback and an increase in their. dividend. >> Yeah, and their cash pile grows. >> All I'm saying is there's a right way to. do this, make these decisions, and then. there's a wrong way to do it, which is. to message it in the way that they're. doing it. So, whoever is running PR and.

comms and approves and reviews these. things are really at their job. >> Mhm. >> They don't understand the moment. >> Oh, some breaking news here. It looks. like Anthropic has hired three more. people. Here we go. Oh, here we go. Personal job news from. Sam Altman. He'll be joining Anthropic. I say that's pretty good. Okay. Who else. is joining Anthropic? Let's see if we. checked everybody's socials. Oh, Tucker. Tucker Carlson is also joining. Anthropic. He'll be doing their PR and. podcast from Anthropic headquarters. And.

who else? Oh, Chamath. Looking good. [laughter] Well, you look like you put 5. lb on. And using the pants. >> First of all, this is not This is not. what I look like. And. >> Did you gain 5 lb? Looks like the same. guy. Are you not wearing Are you not. wearing underwear? He's not wearing underwear and he's. wearing his khakis, but I think it's. just he's trying to not show off those. scrawny those scrawny splints those. those little slats he calls legs. He's. covering them up now. >> Uh hold on. I'm going to send Nick. I I I knew that this was going to come.

up. I'm going to send Nick an updated. picture of my legs, and you you can deal. with this. >> You can Photoshop your legs all you. want. >> I didn't Photoshop. >> look like ostrich, brother. >> He's better than you today. I'M WORKING. ON. IT. >> [laughter]. >> HE MAY NOT BE PHOTOSHOPPING. He may have. been leg maxing. >> He could be leg maxing. >> Are you leg maxing? Are you BP 157 your. legs? What are you doing here? >> of all, first of all, I'm 6'2, you. goons. Okay, so. >> Ostrich legs. >> All you little people, you know, Jason, you're 5' tall, so you know, your.

ability to have legs. >> I'm on a good day with my platforms. >> to have legs is is different cuz like my. muscle mass won't show on my legs the. way it shows on your leg. >> Oh, I don't think you're help but I look. at You know what he's doing there? Freeberg, you see it, right? Look at how. skinny the calves are and then look at. how he's wearing a. >> Oh my god, Jason. >> bra for your quads. >> Oh my god, stop. >> equivalent of a push-up bra. He has. those Bosu balls. He put Bosu balls. under his hammies to You did it. You're. using filets to pump those up.

>> my legs and I flat Okay, you know what? Move on. >> You know, I was just saying I think we. should give credit where credit is due. >> Yeah. Jamath's legs. >> better. >> Jamath has been doing a lot of work on. his legs. >> Thanks, man. >> It's better. >> Thank you. >> It's better. >> Thank you. I'll I'll give him better, but I do think that he's pumping them up. here. Okay, let's keep going here. All. right, topic two is SpaceX just filed. their S-1 on Wednesday. They are aiming. to raise 75 billy at a 1.75 trillion. with a T valuation. This would be the. largest IPO ever by more than double.

Saudi's Aramco $29 billion IPO a couple. years ago. Listing is expected mid-June, likely. June 12th. Ticker will be SPCX. We got a lot of interesting information. in the S-1 teardown. Obviously, SpaceX. has three main business units. Starlink is the money printer right now, but there's a second one that's. emerging. Starlink did 11.4 billion in. revenue last year on 50% growth with 4.4.

billion in operating income. Over 10 million people are now. subscribing to Starlink. That business. could easily be hundreds of millions of. paying subscribers. So, that that's a. lot of growth potentially there. The. space business is but 4 billion in. revenue. It's growing 17% growth, which. would still be strong growth. Uh but had 650 million in operating. losses. AI did 3.2 billion in revenue. That's more than double year-over-year. growth, but it had 6.4 billion in. operating losses. SpaceX had 20 billion in capex spend.

last year. Over 60% was for the AI. compute buildout. And obviously they were trailing. Anthropic and OpenAI and Gemini in terms. of XAI, uh playing catch-up. And he did. a big reboot of that as we saw on the. Twitter. But here's the big one. EWS, Elon Web. Services, as we call it here on the. All-In Pod, has exploded. Anthropic is. paying SpaceX, wait for it, 1.25 billion. a month to rent out Colossus 1 and parts.

of Colossus 2. It's a $45 billion deal. over 3 years, 15 billion a year. In. other words, they added a Starlink in. terms of revenue to the party. Plus, if. they buy Cursor, that's going to add. another 2 or 3 billion. Not. >> Not if. I already told you they already. bought it. >> Okay. I'm just trying to, you know, dot. the i's and t's here. But when they buy. Cursor, that adds 2 or 3 billion. That's. not in the S1. >> That's also growing and doubling. >> Yeah, that's probably growing 2x.

year-over-year. And who knows how much. faster it'll grow. Polymarket, 71%. chance SpaceX closes its first day of. trading with a market cap above 2. trillion. Thank you to our partner, Polymarket. I'll stop here. Gavin, you've been. involved in the company for a long time. Chamath, you I think were a big investor. in the satellite company that became. part of Starlink, which is the revenue. driver there. So, you both have a lot to. say about this. Gavin, your take on the. S1 and I think specifically Elon web.

services. >> Well, I think what's important about. Elon web services does make me laugh. But 15 billion, that means the AI. business right there is going to. quadruple. It has already effectively. quadrupled. I think what's important about that is. there's a stat in it that for I think. the the first data center was 122 days. With the second one, it took them 91. days. The third one was I think 66 days. They build data centers dramatically.

faster than anyone else at a lower cost. And now that you have a. clear off-take partner and I would. expect partner to become partners, there is no reason they can't start. stamping these data centers out really. fast. And having watched Jensen for a long. time, it is important to Jensen that his. GPUs be used. And so GPUs will be allocated to who can.

plug them in, turn them on, and start. converting electrons into tokens. And so I think this business can grow. dramatically faster than I think. you know, maybe what anyone could have. contemplated three, you know, three. three months ago. But 15 billion dollars. from Anthropic. is is extraordinary. >> Important note, it can be canceled by. either party with 90 days notice. Just. want to make sure we also have that in. there. So that means Elon might want his. compute back or Anthropic may find.

another solution. So they do both have. an out. >> And I think that's that's a. you know, I think that's that's that's. probably an important provision. >> Yeah. >> for everyone. But I think the other. thing that came out this week, which was. not in the S1. Nick, can you throw up. the parade of frontier and maybe don't, you know, include the email and the. names and everything, but the composer. 2.5 stat. I think this is really. extraordinary. So, Cursor's Composer 2.5 model came out. this week. And I mean, this is Pareto dominant.

And this is just. you know, three, four weeks of doing. reinforcement learning. on Colossus 2. with Cursor's data. And Cursor has We will never know, but. but Cursor allegedly has more tokens of. coding data than exist on the public. internet. And that is a stat from I think more. than a year ago, so I'd imagine it's. grown significantly. And I think Cursor and Anthropic.

probably have the most proprietary. tokens of coding data. And what this. this jump from Composer 2 to Composer. 2.5 showed us. is that when you do an appropriate. amount of reinforcement learning using. that data, let alone injecting it into. the pre-training of a new base model. Cuz Composer 2.5 is the same base model. as Composer 2, which is Kimmy K K.25. Like this is amazing. This is three or.

four weeks, and it is Pareto dominant. The Pareto frontier, if you draw a curve. of the blue dots, you can see. Composer 2.5 is literally. well outside the Pareto frontier. And. that's after three weeks. And what's going to happen next is. you're going to have a. new base model. with a Cursor model in it. >> Yep. >> Then the Cursor model. RL'd. using the biggest coherent.

compute cluster in the world. And I think. this is. I I think this may. >> It's significant, yeah. >> It's extremely significant for XAI and. Cursor. >> And Cursor was dead in the water in. terms of access to compute and they were. falling very far behind Kodaks, Google, Anthropic, and then Elon let. them on Colossus and boom, instantly. their models are.

growing faster and this could be we. could be sitting here a year from now. and they're the dominant player. And. could we be sitting here Gavin in a year. and Elon is selling compute to Google. and Open AI? Is that a possibility or. not? >> Well, I think it's much easier to see. him selling compute to Google and I. think that's going to happen. There've already been posts about that. >> Yeah. >> And for sure Google is going to want to. be part of orbital compute.

You know, it's it's a very funny. The. only people who are skeptical of orbital. compute are those people who are not. involved. in data centers or space. Google, Anthropic, Amazon, Nvidia. They are all very convinced that orbital. compute is going to be reality and. obviously SpaceX is extraordinarily well. positioned for that. But I do think that composer 2.5 data. point is really powerful. >> Keep an eye on it. Yeah. >> And then the other thing that's come out. is Grok builds. So, what Grok lacked.

that a lot of other models had and I do. think it's important to. remember that the newest version of Grok. 4.3 is on the Pareto frontier for all. frontier models. And you're either on the frontier or. you're not. And the the companies on the frontier. are xAI. with one build of Grok 4.3, which is a. 500 billion parameter model, Google 3.1 Pro, and then Open AI and. Anthropic. And that's it. Those are the. companies on the frontier. >> And then the four horsemen, yeah. >> Google today each have one dot on the.

Pareto frontier. And obviously you want as many dots as. possible, but Grok lacked a harness. So, Claude had Claude code, OpenAI had. Codex, and now with Grok build, there is. a harness that is available to to Grok, and you know, as I'm as I'm sure. >> a downloadable app to translate into. English that has integrations to all. your favorite stuff, whether it's. Notion, Gmail, Slack, etc. And if you.

don't have that, it's just like using a. basic chatbot from a year ago. So now. they have their downloadable, it's in. market, and they are cooking with oil on. it, and they're playing catch-up, but. they're moving fast. >> And and it's it's more than just an app. It's it's a runtime, it's an. environment. It manages state, it. manages memory. It makes these models dramatically. more useful to the extent that I think. the people at the frontier all agree. that the harness is essentially as. important as the model, especially in an. energetic world, and the harness and the.

model need to be developed together. So. the release of Grok build and the pace. at which they're iterating. is I think also really encouraging. So. now you have cursor, you have the cursor. data, you have a clear existence proof. that the cursor data is really. important. Composer 2.5 is now Pareto dominant and. the most selected model on cursor, and. that's also important because, you know, these evals don't capture everything. You know, this is why people on X talk. about the vibes, and the vibes on cursor.

2.5 are also really good. >> They're immaculate, yeah. >> That together. >> Yeah. >> with Grok build, I think these are. really important developments. >> Yeah, I think they're There was Elon was. incredibly frustrated by the state of. affairs at xAI. He was very public about. that, and he's less frustrated now, and. he's shipping a lot faster. And so I. think that says something, and he has. been very focused on it. Freeberg, your thoughts on the SpaceX. IPO and what this collection of.

companies might look like a year or two. from now, especially if, like many. people believe. Tesla and. SpaceX merge, what do you think of. dollar sign E L O. E L O N as an entity and what impact it. might have as if those two were put. together the market cap would put them. in the fourth largest company in the. world. We can revisit our earlier. conversation about an anti-tech, anti-AI, anti-.

progress. world and society ahead. And if there is. an effort a concerted effort and. organized effort by governments to stop. or block access to information, restrict freedom of speech, restrict. freedom of purchasing or buying things. to. control more things. And I think there's. a trend line in this direction right now. globally. The internet has always been. lauded as this kind of. system that provides an open alternative. to physical commerce that you could.

create digital commerce, digital. uh. information, digital media that you. could share. And um it's almost this. digital representation of society, but. the internet has to sit physically. somewhere. And the assault on data center builds. out in the United States right now, I think. may indicate the importance of having an. alternative internet from the ground. layer up. If you have a communication. network that isn't restricted and. controlled.

by a government. on Earth, it's almost like a backup. for civilization, but it's a backup for. progress. And I don't own any SpaceX shares, and. I'm not trying to sell the book of. SpaceX, but I think that there's like an. important aspect of. can you create a system that's not under. the control of governments. as a way to ensure humanity's progress, to ensure civilizational continuity if. things go south, if things aren't good,

if things are restricted, and if you. know, fundamental forms of tyranny start. to restrict speech, restrict commerce, restrict information flow and whatnot. And I think having like a space-based. communication network, space-based data. centers, and space-based communication back down. to Earth wireless, I think it's generally a good thing. It's good to have a backup. >> Yeah. >> So, put all the economics aside and the. multiples and the valuations and whatnot. and whether it's SpaceX or not,

I think the idea that you could have. data centers, store information, transmit information, route information, and access information through. space-based systems that can't be. controlled, manipulated, or destroyed by. governments is is important. And I I. just I like that. Yeah, if you. >> Most people don't remember this, but. when Elon was starting SpaceX, the. original idea. when he was running around with the DAO. and they were. looking at some rockets and getting. carriage from Russian rockets was to.

back up the biosphere. And he came back. from that trip, and I remember talking. to him about it, and he said, "I think I. just have to make my own rockets because. that's actually where the problem is, and it would be easier just to make my. own rocket to back up the biosphere.". And he wanted to put geodomes, like geodesic domes in space. with all the plants and wildlife and and. creatures. Uh and what incredible vision, and then. it you know, there was the necessity of. actually getting that up into space, and. that's that's the the unknown origin. story. I will say this, Chamath, the.

idea of putting. uh data centers in space seems. completely doable, even though there are. a bunch of people who are saying it's. not, when you compare it to what happened. with SpaceX um with Starlink, which. people said also wouldn't work. And now. he's got 10,000 Starlinks up there. The. difference between a Starlink satellite. and a data center satellite is really. not that different. And. >> No, they're they're pretty different. >> Well, conceptually, yeah, of course. they're physically different, but.

conceptually Elon put 10,000 Starlinks. up. Is he capable of putting 10,000. >> No, look, the size is much the size the. size is much bigger, Jason. The foils. are much bigger, the wings are much. bigger. >> but it's it's yeah. My point is it's not. different if he has the new Starship. Cuz that's 10 times bigger, yeah. >> You can't just scale like this. That. being said, it's technically possible. I. think he will be the first one to figure. it out. But I'll just take a much more. pedestrian take, which is okay, you're.

sitting here. and if I'm asking myself, Chamath, how. do I underwrite SpaceX at $2 trillion? Here's the basic math that I would do. Well, last year it did 18 19 billion. dollars. It'll probably do 25 to 30 this year. Okay. So, I'm buying this thing. at a fairly. costly premium, right? So, what am I buying? Well, I'm buying probably the most. important internet infrastructure.

project that's happened since the. internet itself. That's going to scale to hundreds of. millions of users. And the reason that's. going to scale to hundreds of millions. of users is. it's just very useful and it's just. going to become cheaper and cheaper and. cheaper. So, that's number one. I'm buying a delivery infrastructure. But I think over time. GDP plus 10, GDP plus 15 kind of a. grower. So, good business, valuable business, but it's the. underlying platform that allows. everything else to happen. And then I'm buying an AI business which. will be at the top level the apps, but.

at the bottom layer all the compute. capability. And I think when you scale that out, like why is Colossus so valuable to. Anthropic? Maybe that's like a good. question to ask. It's because if you look at who's. actually capable of delivering a. gigawatt data center, these guys are the closest. Like an actual gigawatt. And And the. reason is is that this stuff is very. complicated and very, very hard. I think.

you've probably heard this famous story. where Jensen was like, "Yeah, he was the. one that figured out this one thing that. we that nobody else could figure out so. that you could strip a bunch of racks. and drive a bunch of east-west traffic. and make the whole thing work together.". So, I suspect what happens is next year. it's probably 40, 45 billion. And then. the year after that it probably doubles. again. So, now I'm buying it at 20 times. revenue. And you would say, "Well, why. can you buy a company like this on. revenue versus earnings and cash flow?".

And I think the reason is because what. the revenue does is it gives him the. operating leverage to go and invest in. all of these other businesses. that ultimately consolidate. his differentiation and his competitive. moat. Because what he creates is a. capital moat that then accelerates a. technology moat that then accelerates an. execution and a learning moat. And that's flywheel when it starts to. spin very quickly. And you would say, "Hey, hold on a second. It's probably. spinning quickly now.". I would say we're at the beginning of.

the beginning. Because he's Again, he still has all. these disparate assets. I still don't. like the fact that Tesla's over here. And as I've told you, that will get. merged in. And now you have this. incredible corpus of. physical capability, movement of all kinds, X, Y, and Z, right? You have learning capability. You have. infrastructure. You have all the. connectivity. That thing will look very cheap, I. think, in a few years.

And he has this one thing that nobody. else, if you look at the big CEOs, who steps on stage where you're always. curious, "Okay, what does he got up his. sleeve?" You know, the Steve Jobs, "Oh, and one more thing.". This is the only guy at the scale of. civilizational. out of left fields. He's he's the guy. Whether you like him. or you hate him, he's the guy. And. there's a premium that is well-deserved. that comes with that. So, if you had to pick an underwriting.

case, Jason, I would flex the revenue. and realize that terrestrial data. centers alone. are 100 or 200 billion dollars of. revenue by 2030, 2032. Just And that. means just building it. So, already. you're buying it at 20 times revenue. just for that business. Everything else. is gravy. >> on the ground earth-based. >> it'll be Colossus three. No, no, forget. space for a second. It's a Colossus. three, Colossus four. >> It pencils out with that, yes. >> Getting a nameplate 1 gigawatt Look, it. is freaking hard, man. Getting a.

gigawatt nameplate working. is almost And then, by the way, there's. all the stuff that he can do on land. that he's the best positioned to do. I'll give you one example. There's a. great push that Jensen's making, which. he needs a partner, and I think Elon. becomes a natural partner, to do DC to. DC. Forget all this DC to AC to DC. nonsense that goes inside of a data. center. All the lossiness, all the. lossiness. >> that is in English, yeah, for everybody. >> Just like, look, you go through a bunch. of power transformations to to actually. deliver the electrons into the rack so.

that, as Gavin said, you can generate. the token on the other end. Today, it's it's very inefficient, it's. very costly, it requires a lot more. power, it requires a lot of cooling, it. requires complexity. And what people. have said is, "Wow, if we could just do. DC to DC like it comes in as DC, direct. current, it goes right to the rack as. DC." But it requires a fundamental. rearchitecture. Jensen needs a design partner and a. thought partner to get that done. He's probably the only one. So, I just. think there's a lot of reasons where you. can underwrite this to a multiple of.

revenue plus the X factor, which is just. the creativity and the the one more. thing. >> Love it. And then here's two charts, and. I'll have you comment on these, Gavin, after it. Here's the rocket sizes. Just in terms of scale, and I most. people have not actually seen a Starship. in person. When you see this thing in. person, and I I've been inside that. rocket. I think you were we were together, Gavin, when we were in the first build. And like inside of that, you can fit 300.

people. It's basically like. a giant. If you thought of a commercial air. aircraft, that's what it feels like when. you're inside, right? Like a 747 in. terms of the amount of space in it. Especially when you compare the Falcon. Heavy, which is their workhorse, correct, Gavin? >> Yeah, and Starship's going to get. bigger. Based on their road map, it's. going to get a lot bigger. >> A lot bigger. And then this one is the. most interesting that this started. trending this week. This is cumulative. payloads launched 1957 to today. SpaceX.

is basically about to in just that and. and this is really what exponential. growth is about, and this is what. disruptive technologies are about. Just from 2012. to today, SpaceX is about to dwarf. the rest of the world's cumulative. payloads into space. So, Gavin, maybe. take the other side of it. When do these data centers in space. happen? What has to happen for those to.

be a reality? When does that hit. SpaceX's bottom line? We've heard from. Chamath, "Hey, here's all the things. that hit the bottom line in the short. term and mid term." But I think data. centers in space would be a mid term to. long term play. 3 years is what I'm. hearing. So, tell us about that business in relation. to the two charts I just shared. >> Well, the one thing I would just say, well, first, all those charts about. launch are before Starship was. operational, and most most of that mass. to orbit was done by Falcon. >> Yes. >> And Starship.

the Falcon is reusable. Starship is. designed to be rapidly reusable. And. this is a critical difference. Like, let's say Blue Origin successfully. solves reusability. They're where SpaceX was 10 years ago. Let's say China solves it 10 years ago. Rapid re- The reusability means that you. extensively refurbish the rocket, you know, the engines, everything, the. fairing. It takes a lot of time. You know, maybe you can fly that rocket.

again in. 30 days, 60 days. Rapid reusability means that you can fly. the same flying land the same rocket. multiple times per day. So, if SpaceX and and it's really hard. to do rapid reusability. I think it would have been It would have. been not trivial, but much easier to. have Starships working if it was just. designed to be reusable. >> Mhm. [clears throat]. >> That's not enough. for what Elon wants to achieve of, you.

know, a a moon base, a colony on the. moon, a colony on Mars, mass drivers on. the moon. You need rapid reusability, and that is why Starship is such a an. engineering challenge and will be such. an impressive achievement when they have. rapid reusability. But, I do think that. mass to orbit. rapid reusability of Starship means. if they get. >> you When do you predict they'll have. that, rapid reusability to space, you. think? >> I mean, we're going to find out We're. going to find out, you know, we find out.

I'm I'm I'm I'm going to be at Starbase. today for the whole launch. >> Yeah. >> So, you know, we we we turn over cards. and, you know, it's important for. everyone to remember, like, let's just. let's just say it's a fireball. SpaceX. will still learn. from this. >> Yes. >> They They They learn from failure. If. you don't fail, you're not learning. Same way, if you're not wrong, you. didn't learn anything in that day. And this is a brand new rocket, a brand. new booster, a lot of new technology. There's a lot of instrumentation on it.

So, whatever happens today, SpaceX is. going to learn and rapidly iterate. I don't know when. I don't want to make. a prediction. I would guess a year or two. Maybe sooner. >> I think that's most consensus. A year or. two is I think perfect consensus, yeah. >> We'll see. So, like the Even if. everybody else solves reusability, master orbit from everyone else will. quickly. asymptote to a very small number. As far as when will orbital compute be a.

reality, I would say, "Well, it is. important to realize there is a working. H100 and NVIDIA H100 GPU in space today. >> Yeah. >> Andrej Karpathy both trained a model on. and used for inference. So, this is. Yeah. You know, it's it There's a working GPU. in space today. >> And NVIDIA's making a space-designed. version of this, which will be different. because the heat sink has to be. different. There's a bunch of weight. that you put on it when it's in a data.

center that you don't need in space. And. you also have to reinforce it for the. journey to space because these things. are going to shake and break apart. The. data center ones are not made to have. that many Gs put on them. So, you're. going to need an an an an industrial an. industrial-strength one that gets to. space that has a different profile. Yeah, Gavin? >> Well, one of the things that's been so. magical about SpaceX is they're very. good at engineering the rocket and the. payload so that you can use. semiconductors that are not designed.

>> Hm. >> be in space or satellites in space, and. those semiconductors are a lot cheaper. We have a couple My my firm, Seraphim. Space, is an investor in a company. called Excite Labs that. it's a matter of public record is going. to be in essentially every Starlink. And the chips were not designed to go to. space. They're not radiation-hardened. You know, everyone, you know, SpaceX really liked a lot of. the the specifications on the chips. and. then it's like, well, we'll see how they. do with rad testing and they just so.

happen to pass. And so that is one of. like one of something that's very under. appreciated I think about space out. >> One of their specialties. >> One of their specialties. >> Yeah. >> But I think. second half of 28 to first half of 2030. would be my point prediction. >> All right, let's do Nvidia and then the. the market recap since we have you here. Gavin and since Freeberg you wanted to. get in on that. Nvidia blew out its. earnings again. Q1 performance is just mind-boggling. 81.6 billion in revenue up 85%.

year-over-year, 20%. quarter-over-quarter. High growth in the. stock market for those people who don't. participate, 20% would be a high growth. company. Year-over-year. They did that. quarter-over-quarter. 58 billion of net. income and 48 billion in free cash flow. They're doing all this at 75% gross. margins. They're growing massively and. they're obviously the most valuable. company in the world at a 5.3. trillion-dollar market cap. Stock's up. but 16% year this year with all that.

growth. That's a magnitude of that 16%. And. they've announced another 80 billion in. additional buybacks on top of the 100. billion in buybacks they did at the. start of 2023. So they're buying back. about 4% of the company. They raised the quarterly dividend 25x. from 1 cent a share to 25% cents per. share. And their CFO said they're going to. return 50% of the free cash flow to. shareholders. Never been a company like this, huh.

Freeberg? The the scale of this is just. extraordinary. >> Mhm. >> Yep. >> Don't don't seem to. >> They have first there's your market. report from Freeberg. Don't seem so. enthused. >> Yeah, it's a mhm mhm. He's got potatoes. in the oven. >> I have a question for Gavin. He did a. really interesting talk with Patrick. O'Shaughnessy and there was this one. thing that I wanted to ask you about. cuz I thought it was so interesting. You. said when you look at the revenue. multiples of the chip companies and you. look at the revenue multiples of the.

DRAM companies, both cannot be true. In. the context of Nvidia's earnings, can. you just explain maybe in plain language. for folks? I just thought it was so. fascinating cuz it explains it explains, I think, just to set it up where is. value over the next 5 years? Like, I. think if you looked at Leo Ashan. Brenner, his fund has gone from like 0. to 5 billion dollars overnight and it. looks like he's just got massive puts on. the chip sector and he's kind of. rotated. So, just give us context, Gavin. Where Where's the puck going?

>> Well, so maybe take the question in the. reverse orders. For Leopold, who's. clearly a brilliant man, I think he was. a road scholar like 19 and I think my. understanding is he's putting up pretty. extraordinary numbers. I I've yet to. meet him. He actually shares an office in San. Francisco with a friend of mine, so I. think I'll probably meet him sometime. soon. But, it's got to for that 13F that. he filed was at the end of the first. quarter. when, you know, I would say we were in. the, you know, the the thick of. geopolitical fears.

And I think you saw a lot of puts on a. lot of 13Fs and I don't know that those. puts are still there. >> Okay. >> You know, I think a lot of people wanted. to be hedged for on. and, you know, now I think it's a little. more clear. So, I wouldn't read I. wouldn't read Leopold's 13F as being. super negative on on semi. >> Chips, okay. >> On chips. Second thing, I think cross actually, if. you look at the valuations for all these. AI names, they just they can't all be.

accurate. You have memory makers that, you know, three to five times PE, you have Nvidia. at a really low PE. You actually have, um, you know, some. other accelerator companies at. reasonable multiples. And then you have everything else. Everything in power, everything in. cooling. And when I say power, I don't. mean utilities. So IPPs are actually. quite. reasonably valued. But power, cooling, even probably some of some of the. optical names.

These are discounting very different. things. If the multiples on the power, cooling, optical names are correct, Nvidia, memory, they're going up a lot. If the multiples on Nvidia and memory. are are correct, everything else is probably going to. underperform. The AI market is. cross-sectionally inefficient right now, which is what I was trying to say. As. far as the Nvidia quarter, I do they. went to a new reporting structure, data. center and AI, and then with no data.

center and edge, and then within within. AI they have hyperscalers, and then I think they call it AI clouds, >> AI clouds, >> industrial and enterprise. What I. believe is if we were to make a true. apples-to-apples comparison, and Broadcom, you know, there's a. narrative that Nvidia is losing share to. the TPU. And Broadcom guided for 143%. year-over-year growth in their AI. semiconductor revenue in the quarter. that they will report. That's comparable.

to the one Nvidia just reported. I think. if you were to and I just. >> [laughter]. >> I so wish they had reported slightly. differently. I wish they'd done. hyperscalers, AI clouds, and then. industrial and enterprise. Because I. think the segment that is comparable is. the sum of hyperscalers. plus AI clouds, stripping out China, because Broadcom. just did not have the China business. that Nvidia did. And I think on that basis, in other. words, in within the western AI world,

within data centers that are being. built, whether they're being built by. CoreWeave, XAI, Amazon, Google, >> Mhm. >> Nvidia's AI business is growing faster. than Broadcom's. And faster than a lot of other companies. that are, you know, seen as part of this. ASIC share gain story. And, you know, I think Jensen has become. and you could you can hear it. increasingly frustrated, and rightfully.

so, at two things. One is to say, what is the performance. of stock? Uh. two two. >> vocal about that. Like, what is going on. here? You're putting up record numbers, and we're getting no. like, uh credit. >> Yeah, I get it. It It just. how can there be a share loss narrative. if I'm gaining share? And it is. indisputably true that he's growing. faster than hyperscaler CapEx, even. without these adjustments. >> Yeah. >> And I think the other thing that's so. frustrating to him is these other ASICs.

>> Mhm. >> are not being submitted for benchmarks. They're not in the CV analysis in for. inference max. They're not in MLPerf. And I think the reason they're not being. submitted is they will lose. >> Mhm. >> And you can't fight shadows. And until. we see a clean benchmark. of whether it's GB300s versus TPU. V7s or, you know, versus. >> versus inferentia, yeah. Yeah, yeah. >> versus yeah, versus Tranium. >> Yeah. >> If we're we're not going to know. And. that's why the a lot of these other.

chips. >> I think Tranium's in a great spot. Aren't being submitted. But nonetheless, if Nvidia's doing well, once you become the largest company the. world, you kind of you tend to trade by. observation would be at stairstep. patterns. Where you kind of the multiple. compresses, compresses, compresses, cuz. people are skeptical of the size. >> Then you have a re-rating. Yeah. >> And then you re-rate. >> New floor is established at a higher. rate. Yeah. >> I think there was one other really. important thing in the Nvidia quarter. It's they said that they thought their. CPU business was going to be $20 billion.

this year. >> Yeah, yeah, yeah. >> Put it there. It means overnight you're. one of the world's largest CPU. manufacturers. And I think that is a. testament to Nvidia has a unique. position. They're the only company that. works with every lab. And so that puts. them in the best position to architect. their chips, they call co-designed, for. where the models are going. And I think that $20 CPU figure is. pretty extraordinary.

>> This is the thing like at the end of. this Grok transaction last year, my kind. of prevailing thought on this is we're. going to move to these domain-specific. architectures. I thought that was like a. a fait accompli, we're just now waiting. for which models, but the reality is. that that DSA. market evolution is actually happening. inside of Nvidia. That's what's so. insane to me. That was my takeaway from. the quarter as well, which is like holy. These guys actually have domain-specific. architectures because they're doing. these design programs with every This is. why back to sort of the, you know, when. he does DC to DC with Elon and Colossus.

3 or whatever, it's just this it's. another game-changer for everybody. >> He doesn't get a one-year flip. He makes. nine. And then I don't think the cost at. which you can finance these chips and. these useful lives is really important. >> You had an incredible insight, which is. the amortization schedule for Coreweave. and all these guys, they got saved. You may want to just explain what that. is and what why you said that. I thought. that was a great insight. >> No, thank thank you Chamath, I. appreciate it. So, when Coreweave and. all these neo clouds came public, and by. the way, this goes for the hyperscalers. too, there was a big bear case that hey,

the these guys are amortizing their GPUs. and CPUs over four or five six years, and that's way too short of a lifespan. The true lifespan of a GPU is more like. two years, and therefore, you know, the. profits of all these businesses are. overstated. The reality is. >> This was Michael Bury who put this out. there. >> Yes, to be clear, yeah. Yeah, and you. know, thank you Michael Bury, we need. bears. Thank you. >> Yeah, that's like that's like asking. Gerardo about modern music. >> Well, I don't I don't want to cast.

aspersions on Michael Bury, he's a he's. a brilliant man, but we need Barry. >> Let me Hey, somebody call Vanilla Ice. and ask him what he thinks. >> [laughter]. >> Oh my god. Milli Vanilli, check your. mail. >> waste. What a waste of time. What a. waste of time. >> Oh, poor Michael Come on the program. anytime, Michael Berry. >> [laughter]. >> Go ahead, Gavin. >> Yeah, I know. Keep it on track. >> I'm happy to chat. But now that we've. disaggregated inference, we have these. different domain-specific accelerators. You can mix and match them. And I think. the GPU stays in a lot of ways at the. center of this constellation for a. while. And you can put whether it's a.

Groq accelerator, whether, you know, it's a Cerebras accelerator in front of. old GPUs, use Groq or Cerebras for. decode. And then those older GPUs, they. have a useful life for 10 or 15 years. And this means that you can finance GPUs. I think Corey's lowest financing, I. can't forget if it's 6 or 7%. >> 6%. 6%. >> Yeah. >> And if you can get an asset-backed loan, an asset-backed financing. for GPUs at a lower rate than other. chips. >> No, that That's a profound advantage.

>> That quarter single-handedly saved the. Neo Neo's clouds. This quarter Nvidia. [laughter]. saved I mean, they single-handedly saved. them all. I think they they should all. They should all say an incredible thanks. to Jensen because. I interviewed the CEO of Core Weave, Michael in Trader Michael in Trader, yeah. And he was saying, "Hey, listen, people have no problem. buying and financing these over a 6-year. period." And people are asking for. things that are coming off and that he. thinks they're going to have year 7 8 9,

they'll have some useful life. You know, uh in addition to that. So, Yeah, so he's like, "I I I don't know. what anybody's talking about here.". Like, this is just not informed analysis. was his point. Like, I the game on the. field and people are betting with their. dollars with him. He has them pay in. advance and sign 6-year contracts. If. they didn't think it had 6-year. lifespan, they wouldn't be signing a. 6-year contract. Pretty straightforward. And they can't get enough of them. Okay, let's end on this market update, macro. picture not great. Oil remains elevated,

although there might be a settlement. every week we have there is a settlement. coming. Maybe this time 16 time it's a. charm in the Iran war is going to wrap. up, but we're in week 12 of it. And this. was supposed to be 4 to 6 weeks. So, wars never get resolved quickly. That's. one thing we've learned in our. lifetimes. Oil is driving inflation. massively higher. Polymarket says 99%. chance May inflation comes in at 4.2% or. higher. Survey of professional. forecasters projecting CPI hits 6%. You. heard that right, folks. We weren't just. talking about a 3% handle, which we just.

said. Now people are saying 4, 5, and 6%. in Q2. And obviously, that's a huge. revision. And the narrative was, "Hey, more Fed rate cuts coming." Now we're. talking about Fed. rate increases. Inflation is causing. obviously bond yields to rise. 10-year. hit 4.6%. You remember we've had Bessen. on the. pod multiple times, and his goal was to. get that under 4%. Now it's. significantly above that number. And.

also, if we go around internationally, Japan's 30-year is at a high of 5.1%. Highest ever recorded. UK yields highest. since the great financial crisis. Germany highest since 2011. And in. Korea, retail investors are borrowing. borrowing record amounts of money to. trade in AI chip stocks. They also had. an incredible run in Korea betting on. crypto at the peak. So, that's some sort. of an interesting signal. Friedberg, is your alt personality going.

to come out right now? Are you. concerned? Is Dr. Doom making an appearance here, or do you think this is manageable? How. concerned are you? >> What is the point of being concerned. when you have ridden the roller coaster. to the top and it is beginning. [laughter] its descent? I I don't know. what there is to be concerned about. The. the the force of gravity is inevitable. The roller coaster will roll down. We. will throw our hands in the air and we. will scream, "Whee!" as we go for the. ride. Global debt to GDP is 310%.

Reserve currency status. to the side, the spending problem at the federal, state, local level, the spending problem. at every country to basically keep. economies growing to support existing. leverage, ultimately creates a cascading. effect. It ultimately breaks. And as it. starts to break, you have massive. inflation because the value of your. underlying. currency collapses and then you have. money printing and all this other sort.

of stuff, which inflates the value of. assets, which allows you to keep. servicing your debt. And the spiral takes off. And so we will just enjoy the ride. This. is the moment, you know, 30-year 5.2%. This Japanese yield. Some argue might, you know, you should. talk to more active market participants. than me, but. and probably some economists who trade. the market, but I would think that this. is one of those things that could be a. catalyst for a for a credit crisis.

Because there's a lot of people that are. in this carry trade. And we'll see, you know, this is. >> Okay. >> This is water leaking out of the bucket. There it is. >> he is. Dr. Doom is here. Chamath, your. thoughts on. Dr. Doom's panic attack of the month. Is. this Is this time real? Is this the 17th. prediction of the next six recessions? What do we got here, Chamath? Are you. concerned? How concerned are you about. these signals that are flashing? >> I think I think that's exactly what that. is, Jason. There are signals that are.

flashing. I think there's pockets of the. market that still make sense that you. can underwrite if you. want to buy businesses that represent. the future. And if you can find a few of those and. you can get comfortable with that and. you can own it for 10 years, I think you buy those companies. and generally everything else I think. you should not speculate and you should. generally avoid. Not just because it's. an up market, but in every market. I've. learned this the hard way. We've all. kind of gone through this. As I get. older, I it's just not worth it. The.

vicissitudes of the market. um don't give me. anywhere near the sugar high it used to. on the way up and it makes me feel. horrible on the way down. So, how I. manage myself is I have a few companies. that I really believe in. I have. extremely concentrated large holdings in. those. Large for me doesn't mean large. for everybody else. And then otherwise, I just kind of stick. to my knitting and keep my head down. It's a much more rational way to behave. So, >> How many public stocks can you keep in. your brain and still sleep at night.

holding for the long term, Chamath? What's the Is there a number for you? Is. it five? Is it 10? Is it. >> Seven. It's five It's five or less. >> Five or less? >> Five or less. >> And so, what your largest holding right. now is what percentage of your net. worth, which is a. >> I don't know. >> Or like top two, maybe. >> Yeah. Oh, top two? >> Yeah, like one and two. One is 20, two. is 15, or one is 40, two is 20. >> I don't know. Again, it depends on the. day. But I don't know. But it's it's. >> Just curious. But I think that's I think that's really. important.

>> My point is there's no 30 things that. I'm tracking. I don't I don't have the. time. I'm not smart enough. There's too much information. There's. like four things that I stay on top of. >> Gavin, you you do this for a living. How. many positions do you manage and what's. your take on some of the flashing signs. that are saying, "Hey, slow down." or. maybe there might be a wreck around the. corner here, you know, when they do the. checkered flag in the F1 or whatever the. metaphor you want to use is. >> Well, so what I I manage. more than 100. positions at my firm. Um and I do that.

with a team. We're over 30 people now. So, it's not just me and I work with. some some great people. I then. three things can be true. Rates going up. is very concerning. What is happening with AI right now with. Anthropic growing faster than. any country any company in history at. massive scale. >> And certainly any country. >> Absolutely unprecedented. Yes. They're. actually Yeah, they are they are now the. size of you know, yeah yeah they're we. pull up where they. >> They're bigger than a hundred different.

countries. >> For sure. >> Exactly. >> And compounding really fast. >> And now profitable. >> Yeah. >> Which I think really changes the moment. >> Which is bizarre. >> Yeah. >> Yeah, how did that happen? >> So, those things can both be true and I. think we should all remember the tech. bubble happened with you know, the. 10-year and the 30-year much higher than. they are today. And you know, the the Nvidia of of of the tech bubble. was Cisco and it traded a hundred times. forward earnings. And you know, I think. Nvidia is probably at a low teens. multiple of kind of low to mid teens.

multiple of real earnings, you know, if. you that that'd be a buy side consensus. not the trade number. And then the third. thing that I think is true is a straight. up formula is being closed. While it's terrible for everyone, it is. relatively the best for America because. we are self-sufficient in energy, we are. self-sufficient in food, we've become a. massive exporter of oil, we're now the. world's largest not only oil and gas. producer, but oil and gas exporter. And you know, those three things can be. true. What do they mean? I think it's.

probably hard for me to see. with America being the most advantaged. by what is going on. >> We're still the best currency. >> Yeah. >> the best economy. We still have the best. public companies and we have the best. private market companies. >> Yeah. >> And we are. one of the greatest producers of oil in. the world. So, we're in good shape. despite this international chaos. >> think a dollar crisis is around the. world. Now listen, like if you know, the. Bundesbank.

in was still in charge and you had the. Deutsche Mark and there was a currency. with better fundamentals, we would be at. very high risk, probably. But just cuz. we're the best house in what is globally. a, you know, bad neighborhood of high. debt levels, and we have AI in our. corner, and we have energy. self-sufficiency, and every day the. Strait of Hormuz is closed, I think it's. relatively good for the. reindustrialization of America. Like I think, you know, you have to you. have to all.

>> You're saying it's a forcing function. It makes us, just like COVID did, be. more resilient and, yeah, more. self-reliant. >> Yes, and. electricity is a base input to every. manufacturing or industrial process, essentially all of them. >> Mhm. >> And what we make electricity with in. America overwhelmingly is natural gas, and you can look it up. NG1, it is down. this year. >> Mhm. >> The input cost for electricity in the. rest of the world, you know, lots of.

different things, but LNG is a very. important one, and it's up 100, 200%. And so, the Strait of Hormuz is. absolutely. bad for everyone, but relatively good. for America, and relatively good for Trump's policy. goals. >> Mhm. >> And that's why I think he's in no hurry. Every day the Strait is closed, and for. whatever he does seem like a relative. thinker. Every day the Strait of Hormuz. is closed is relatively good for. America. It's terrible for Europe. It is.

terrible for Asia. >> Japan and China need that oil. Philippines needs it. India needs it. Yeah. >> Yeah, it's so all these things can be. true, but the one thing I do just want. to say is rates going up. and inflation going up is never good. But we have to hold what's happening. with AI, where the fundamentals are. getting a lot stronger in our mind. And. the the one thing I would just add is. AI has been seasonal, the market's. seasonal. You know, it often, you know, sell in.

May, go away. And AI fundamentals also appear a little. seasonal. In the past that's been cuz you know, cuz college students they they use a lot. less chat GPT. and Claude in the summer. And generally. people maybe work a little less hard. when the weather's nice. Now with the. generative AI, will the fundamentals. still be seasonal? We will see. >> Oh, that's a really interesting point, right? We see that e-commerce, apps, subscriptions as investors in a lot of. these companies, we would always have.

these board meetings Chamath. Oh, uh Q3, uh yeah, people are out gallivanting and. they're not playing Candy Crush or. buying calm or whatever, but oh hey, Uber and DoorDash went up, people are. traveling, etc. Okay, final story of the. week. We had a 48-hour jaunt. by a bunch of tech CEOs and the. president. to hang out with Xi. A lot of high. fives, a lot of handshakes, a lot of great vibes, but coming out of. it we haven't seen anything.

>> definitive Friedberg. in terms of policy. This was supposed to. be some big breakthrough. It would have. downstream effects on tariffs, on us. selling chips to China. We did see a. little movement there uh and the Strait. of Hormuz, we would become, you know, Wonder Twins with Xi and Trump reopening. it, but nothing really definitive other. than some soybeans being sold and some. H100s, A200s getting sold to Baidu and. some of the top folks. So what do and.

maybe some planes got sold, too. So. other than a little BD, a little. business development is. uh Friedberg, what's the outcome here or. was it just a bit performative in your. mind? >> There was a a question. would the administration. leave China with a grand deal that made. everyone feel like there's a long-range. view on a partnership, but I don't think. that that's. what happened. There were a few. announcements obviously around an. intention to continue to work together. in a cooperative way and find a path to.

partnership, an intention to. establish additional trade deals, and. and, you know, there were some purchases. of aircraft and. and some agricultural product. commitments, but fundamentally, the. grand deal, the big deal that I would. say reduces or de-escalates tension. probably didn't manifest as some had. hoped it would. And I don't think it's. any surprise that Putin is with Xi. today. And this is also performative, that. following the US visit, there's now a. relationship bonding moment happening.

between China and Russia. So, the story continues. You know, there. is no happy ending, and there is no. rainbow-colored chapter three in this. book. It's going to continue to be a. dramatic arc. as this rising power continues to. challenge the United States. And I think the story continues. >> Were you expecting a happy ending? >> CAN'T ANSWER THAT QUESTION. >> [laughter]. >> I MEAN, TO THE STORY OF THE CHINA VISIT.

Not not I'm not talking about any other. things going on in your life, but. it seemed like some planes and soybeans. got sold, some H-100s, perhaps, but. >> the. >> it wasn't like there was some grand deal. that occurred, but it's nice to see them. together, right? I mean, that is nice. >> I think it was successful. I think. there's what you see on the surface, and. then there's what happens behind closed. doors, and. without speculating too much, I think. that it was a useful and productive. trip. I think the the biggest thing that. they probably got alignment on is just. geopolitically, the tic-tac-toe of what.

has to happen next. And and I think that. there's some amount of agreement there. I'm just guessing. >> Yeah, and so that guess, if I was going. to unpack it, hey, we got we have. Venezuela, we have Iran, and Taiwan. You have lots of things to. >> here's. geopolitical chessboard, and. here's what I would say, just very. generally. Like it's just. I think that there's a that there's a um. a way to divide up the game board in a.

way that helps them and helps us. >> Mhm. >> [clears throat]. >> Gavin, any thoughts on specifically. Nvidia being able to sell more chips. into China? Material for the company? Good for America? I mean, it's obviously. a pretty debatable issue. >> I think I disagree with Chamath on this. I think selling. depreciated Nvidia GPUs. to China. lowers the odds of them developing their. own alternative ecosystem, which would.

be a lot power hungrier. Um cuz you do. use optical you bring in optical a lot. earlier for scale-up fabrics. I think. there's sound arguments that this. is stabilizing for the world. and is the best highest probability path. for keeping America ahead in AI and kind. of keeping control of AI. And that's almost a shame we've had to. have this debate because now people like. me have said this many times and try to.

If they didn't understand it, they. probably do really understand it. And by. the way, that's not to say we shouldn't. have had the debate. But um. that is what I believe, you know, reasonable minds can disagree. >> No, wait. What Where do you think we. disagree? I'm not sure I agree with you. >> Oh, good. I'm glad we. >> I was going to I was going to jump in. No, no, you start you start with I'm in. agreement on. >> No, no, no. I'm like sell. >> I'm like sell everything to them. No, what I was just saying is that there was. what you see on the surface of what they. can speak to the press, but I think the. most important thing was the negotiation. of hey, listen, like.

we're going to do these things, you do. these other things. And that's never going to get put out in. a multi, you know, memoed press release. That's my point. That's all I'm saying. >> Yeah. And I I would just say, listen, it. like. America and China talking is only good. >> Only good. >> the these trap that is being discussed. And China talks about a lot. They're. very aware of it. And they brought it. up. >> [laughter]. >> She brought it up by name. Yeah. Talking. is a. integral step of avoiding this.

situation. Having a nice resolution. From my. perspective, like the greatest. superpower Trump has is his ability to. bond with dictators, monarchs, royal. families, Gulf monarchies. He's just. great at it. They see eye to eye. They. vibe. He has no problem going to see. them. He has no problem inviting them to. UFC fights. Like this is like if if she. comes to the United States and he's. sitting courtside with Dana White, like. that's when we know things are going to. be okay. I do think he's probably giving.

them the green light on like, "Hey, Taiwan's yours. Just let's not have it. during my administration. Maybe like we. do a 30-year deal or a 20-year handoff. deal." I wouldn't be surprised if. something like that happens. Or a. 100-year deal or a 200-year deal. But. the one thing I would just say that I'm. sure was communicated is, "Hey, wars consume a vast amount of oil. You buy your oil from Iran, Venezuela, and Russia. Russia alone can. supply a fraction of what you need.

And now it should be clear to the world. Two of the three are off the chessboard. Yeah, if you Two of three are off the. chessboard, if you do something we don't. like, Venezuelan oil, gone for you. American. oil, gone. Brazilian oil, gone. And we'll say to all of our good friends. in the GCC, "We're so sorry, but we have. to close the Strait of Hormuz again.". So, Iran, all of Middle Eastern oil, gone for China. Now you just have. Russia, and good luck fighting a war.

with just Russian oil against us, Japan, South Korea, Australia, UK, France, Germany, the world. I mean, who knows. about Europe? But for sure Japan would. be there. For sure Japan would be there. Oh, and Australia for sure, Korea for. sure. Yeah. >> And so I think it's going to be a more. stable world on the other side of Iran. However it resolves, and I think that's. nothing but good. >> Yeah, I think that's a good insight. I.

think it's a great insight. All right, listen. We missed you Sachs. Come back soon. And Gavin. >> Big shout out to bestie Gavin. Thank. you. >> Yeah, you're so great. Thanks for. coming. We appreciate it. Hey, and your. father-in-law, what's his name again? >> Jeff Painter. >> Jeff Painter. We love you. Thank you so much for all. the kind words. We'd love to invite you. to come to Liquidity or the Summit. I. know you're a big fan of the show. Want. to give you a shout out here on the. show. Thanks. I used your fandom of the show.

to leverage Gavin who was like, "I can't. make it today." And I was like, "Tell. your father-in-law. we're going to get him backstage VIP. tickets to the next two events. if you show up today. And if you don't, I'm going to back channel it to him.". And all of the sudden Gavin made it to. the show. Love you boys. A little bit of pressure. That's my way of the That's my hormone. straight. >> Yeah, so I'm always there for my. father-in-law. >> Absolutely. All right, everybody. We'll. see you next time. Bye-bye.

>> [music]. >> You let your winners ride. Rain man David Sacks. We [music] open sourced it to the fans. and they've just gone crazy with. >> [music]. >> Besties [music] are gone.

>> We should all [music] just get a room. and just have a one big huge orgy cuz. they're all just useless. It's like this. like sexual tension that they just need. to release somehow. [music]. >> Wet your bed. Wet your bed Wet your bed. Wet. >> [laughter]. >> We need to get merch. >> Merches are back. >> I'm going all in. >> [music]. >> I'm going all in.