All-In Podcast: SpaceX's $2T Case, Nvidia's Shock Selloff, America Turns on AI, Trump Pulls AI Order, Bond Crisis?
(0:00) Gavin Baker joins the show! (0:30) Andrej Karpathy joins Anthropic; hypergrowth and profitability (12:42) Why Americans have turned on AI, anti-human perception (27:22) Trump pulls AI EO,
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All-In Podcast: SpaceX's $2T Case, Nvidia's Shock Selloff, America Turns on AI, Trump Pulls AI Order, Bond Crisis?
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podcast-ingeston 2026-05-23. Auto-transcribed via AssemblyAI (universal-2,en). Speakers identified by AssemblyAI Speaker Identification using the per-podcasthost/regularshints; the resulting label→name mapping is in the frontmatter. Duration: 1h42m. Episode page: https://allinchamathjason.libsyn.com/spacexs-2t-case-nvidias-shock-selloff-america-turns-on-ai-trump-pulls-ai-order-bond-crisis. Audio: https://dts.podtrac.com/redirect.mp3/traffic.libsyn.com/secure/allinchamathjason/ALLIN-E274_Ch.mp3?dest-id=1928300.
Show notes (from RSS)
(0:00) Gavin Baker joins the show!
(0:30) Andrej Karpathy joins Anthropic; hypergrowth and profitability
(12:42) Why Americans have turned on AI, anti-human perception
(27:22) Trump pulls AI EO, US-China AI relationship, dystopian AI layoffs
(45:19) SpaceX S-1 tear down! Breaking down the three major businesses and the case for a $2T valuation
(1:11:22) Nvidia smashes earnings but stock falls, why people are shorting chips
(1:22:25) Market update: Flashing red signals, oil, inflation, yields up
(1:32:45) China trip flops, or was progress made behind the scenes?
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Referenced in the show:
https://github.com/karpathy/autoresearch
https://github.com/multica-ai/andrej-karpathy-skills/stargazers
https://x.com/i/broadcasts/1dxYljYVREYJX
https://apnews.com/article/trump-ai-executive-order-ee318f35acc8a2c43e47f3ebf26cb459
https://x.com/wallstengine/status/2057378437485216031
https://x.com/MorePerfectUS/status/2056842597117636890
https://x.com/lulumeservey/status/2057239284487201043
https://polymarket.com/event/spacex-ipo-closing-market-cap-above
https://x.com/elonmusk/status/2057228707606196434
https://www.sec.gov/Archives/edgar/data/1181412/000162828026036936/spaceexplorationtechnologi.htm
https://www.ibtimes.co.uk/leopold-aschenbrenner-investment-shift-agi-over-ai-chips-1797606
https://polymarket.com/event/may-inflation-us-annual
https://polymarket.com/event/fed-rate-hike-in-2026
https://www.cnbc.com/2026/05/18/treasury-yields-inflation-bond-rout-oil.html
https://www.cnbc.com/quotes/US10Y
Transcript
Jason Calacanis: 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 Atreides Management joining us. The spicy takes must flow. Welcome back to the program, bestie Gavin.
Gavin Baker: Thanks for having me. Always love it.
Jason Calacanis: It's been a huge week in tech. We can start with the SpaceX and OpenAI IPOs. We've got Andre Karpathy joining Anthropic Nvidia crushing it. So many different places to go. But I think we'll start with Andrej Karpathy joining Anthropic. Carpathy 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 Palihapitiya: Yeah, Chama, he's going to keynote on Monday morning.
Jason Calacanis: Oh fantastic.
Chamath Palihapitiya: No, Tuesday, Tuesday, Tuesday, Day two. I think he's keynote.
Jason Calacanis: Okay. As is Gavin. Gavin will be there.
Chamath Palihapitiya: Founding member Gavin anchoring day two as well. Excellent.
Jason Calacanis: Yeah. This is Gavin's second appearance.
Chamath Palihapitiya: Look at those two bookmarks. Andre Carpathy and Gavin Baker.
Jason Calacanis: Yeah, you know, liquidity pulls in the stars. Obviously. Andre was a founding member of OpenAI. He led the self driving team also.
Chamath Palihapitiya: Hold on. Gavin is going to help us judge the best ideas section as well.
Jason Calacanis: Excellent.
Chamath Palihapitiya: I don't know if you know that Gavin, but you're a judge, you're going to be judged.
Gavin Baker: I'm up for anything, man. I'm easy.
Jason Calacanis: Yes. Kirkpathy 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 five 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 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 that'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, we're in a different inning than we were say 10 years ago when he was at Tesla or five years ago when he co founded OpenAI.
Chamath Palihapitiya: 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 Ahmed Singhal, Sridhar 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 in 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 Andre is 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 this 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. So then the model quality just goes absolutely parabolically just like this, straight up.
Jason Calacanis: Throw a whole bunch of compute at the problem and these things learn really quick. I think is the high order bit there. Gavin, what are you. What's your take on Anthropic's recent success and their massive hiring binge?
Gavin Baker: The success is extraordinary. It's undeniable. I think the fact that they are now they were ebit 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 an open source, you know, it's, it's not hard to see 200, 300, $400 billion of ARR the end of this year at high margin across all of that, across
Jason Calacanis: all of language models. And you're talking specifically about the private language model companies, maybe not Google, which is including Google.
Gavin Baker: 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.
Jason Calacanis: Sure.
Gavin Baker: So I was excluding that and just narrowing it to LLMs, which I think is the strictest 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 Karpathi 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 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. And that's something we haven't unlocked yet. And those two combined, I think they might pull the future forward in a very real way.
Jason Calacanis: Yeah, and we have right now, Anthropic has a decent lead on everybody else, whether it's three months or six months. Obviously they're probably six 12 months ahead of open source. Maybe they're three, six, nine months ahead of their contemporaries, but they have a lead. You put carpathy 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 at 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?
David Friedberg: 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 rearchitecting models and rearchitecting how models work together to solve problems. My guess is a lot of leadership 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 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 rearchitecting models and deployment of models.
Jason Calacanis: These very small models, 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, Chamath, it happened about two weeks ago, very quietly. Chrome included, Gemini or Google included in their Chrome browser the Gemini Nano model without telling anybody. Four gigabytes on your computer, and that's the one that does like proofreading, spelling, autocomplete, all that. So now we have Google covertly installing this on everybody's operating system.
Chamath Palihapitiya: Hold on, hold on. Covert's a strong word. So let's not use that word without
Jason Calacanis: telling people, without giving people a heads up.
Chamath Palihapitiya: 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, 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. 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 or shady things. I don't. They're not that company. There are other companies that would.
Jason Calacanis: You're referring to your alma mater.
Chamath Palihapitiya: I'm not going to say which ones. Okay. But Google is not that company. So 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 worth telling from now on. Because I think we collectively, the four of us collectively 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.
Jason Calacanis: Yeah.
Chamath Palihapitiya: And I think that if we don't, if we're not careful with our words, that's what will happen.
Jason Calacanis: Yeah. And by the way, obviously not a Luddite, but this is what 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 arrow more than anything.
Gavin Baker: I would say maybe just add two things. There's attorney maxing and then there's attorney maxed and Google is probably attorney Maxed.
Jason Calacanis: Yes.
Chamath Palihapitiya: Yeah.
Gavin Baker: And have been for a long time. And the second thing I would say is I do think it's incumbent on all of us, has Americans who are involved in the technology industry in one way or another to be advocates for the positive, optimistic possibilities that AI introduces to everyone in this world. Because 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.
Jason Calacanis: 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 CEO is blaming AI for their layoffs. What's your take on this, Gavin?
Chamath Palihapitiya: Look, and 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 up. 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, 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 do this, if you actually just have a Nash bot, a Nash 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. They're operating at such a level of scale that they're just reading their own book. So 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 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, asks what the scientists think and start to tell those stories. That's what we should be talking about.
Jason Calacanis: 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 place. He said that multiple times. You have Dario, 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 do we do better as an industry?
Gavin Baker: I think Chamath outlined like a very viable and positive path forward where just, you know, real people who are not, you know, at the tip of the spear. These are the positive impacts AIs had on my life. 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 can live a normal life. And he's now figured out how to use AI, how to further tailor that drug. And there have been all sorts of advances in protein design, et cetera, et cetera. 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 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, you know, scary to others. You know, a four day work week, you know, I think is, 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 is trying to drive re. I just. We need to stay focused on the
Jason Calacanis: positives is what I. Freeberg, what's your take here on the AI PR crisis, if we'll call it that. 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?
David Friedberg: That's a. There's a long answer to that question.
Jason Calacanis: It relates in some ways to your concerns about socialism and polarization.
Chamath Palihapitiya: What is the long answer? What's the long answer?
David Friedberg: I mean, that's like. Like, why do people hate technology? The technological.
Jason Calacanis: Why do they hate this technology? They love their phones, they love the Internet, this technology they hate.
David Friedberg: 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, because 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 nuclear bombs, I think, really created 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 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 advancements 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 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 f s with the ego of the human. It's almost anti humanist. And I think that that's like a deep psychological current. 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 JCal. You know, I don't think there's like a simple. Put Shyam on a podcast and he'll solve the problems with 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 various state actors and interests are competing with each other.
Chamath Palihapitiya: Friedberg, do you think that we should slow down?
David Friedberg: I don't think you can.
Chamath Palihapitiya: No, no, no. Do you think we should slow down?
David Friedberg: No, I think I was just talking to some people on 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 Manhattan Project from effectively leeching back or leaking back to Russia and Germany and other places 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 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 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 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 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 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 we're going to see again here.
Jason Calacanis: 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 giving 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 things, hey, if Amazon deploys those, there'll be attacks 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?
Chamath Palihapitiya: 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. 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, 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 we should be having, which is, it's interesting to me that there was supposed to be an eo, a Presidential Executive order that was announced today and then it was pulled. It was scrubbed at the last minute. Did you guys notice that? And yesterday what was leaked was everybody that was attending, it was all the big NeoLabs 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
Jason Calacanis: language models, specifically of these frontier models is what I read.
Chamath Palihapitiya: Not language models, because 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 Friedberg is. Is right. We are in a proliferation with China. I think it's actually good that China is less than nine 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 Rene Girard kind of framework of mimetic theory than if it was like us in 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 in 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 some reasonable ground rules. But otherwise, Friedberg is right. You have to take a little bit of a deterministic view here, which is that we. We are in this existential race, and we need to get to the place where each of us, meaning us in China, can look each other in the eye and say, all right, weapons down, so to speak.
Jason Calacanis: Gavin, I'm going to hold you to answer two questions. One, should we run frontier models? Because 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.
Gavin Baker: Geez, 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 doing it and no one else doing it. I like, I think in a world where we hold hands with China, look, I think that's. That's much more palatable and we are aligned and we trust each other and have kind of verification capabilities. I do think.
Jason Calacanis: Great, yeah. 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 that genre of. In 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.
Gavin Baker: 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.
Jason Calacanis: Self regulation. Sure.
Gavin Baker: We have self one we have self regulation also we have the courts. And if an AI model company behaves irresponsibly, they know that they're 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.
Jason Calacanis: That's a great point because OpenAI is being sued right now by a kid who killed themselves after talking to OpenAI's model. So you're correct in that. Yes, after the fact.
Gavin Baker: And we will see, we'll soon, 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
Chamath Palihapitiya: way path, one way ratchet.
Gavin Baker: Yeah.
Jason Calacanis: And then, yeah, second question then Chamath was saying, hey, nobody listens to the, you know, these cab drivers or maybe the people sorting the packages, do they want the jobs or not? Actually the UK there was just a 60 minute special and 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?
Chamath Palihapitiya: 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.
Jason Calacanis: Yeah, sure. But Gavin, what are your thoughts here on either one of those examples here?
Gavin Baker: I think going to a city where you can't get an awaymo or a cyber cab is going to feel barbaric and unsafe until you agree.
Jason Calacanis: Strongly agree.
Gavin Baker: I don't know if you remember, but the early days of Uber, sometimes you go to a city where there was no Uber.
Jason Calacanis: Yeah, incredibly frustrating.
Gavin Baker: Well, 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 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, has historically, the curly effect aside, led to, you know, I think more positive outcomes where cities and states compete. The curly effect being.
Chamath Palihapitiya: It is.
Gavin Baker: Yeah.
Jason Calacanis: 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 flak 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 only comes down
Gavin Baker: to the block safety thing. I think it's so good. Jason. Crime is now a choice.
Jason Calacanis: Yeah.
Gavin Baker: You know, I think the Cambridge city council voted to turn off gunshot detectors two days ago.
Jason Calacanis: Wait, which city did that? Which we're not talking about.
Gavin Baker: Howard. Cambridge.
Chamath Palihapitiya: Cambridge.
Jason Calacanis: Cambridge. That's the place where Harvard is.
Gavin Baker: That's the place where Harvard is.
Jason Calacanis: So the geniuses coming out of Harvard in that town decided gunshot detection. We don't want to occur. You don't want gun type detection.
Gavin Baker: It's wild because, you know, there's a theory that it disadvantages, you know, that it might lead to an illegal migrant shooting a gun being apprehended, and we don't want that.
Jason Calacanis: Got it.
Gavin Baker: And a 16Z had a great essay on flock. We can really, really solve crime, and it's just your 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 some sort of moral or ethical reason they're making 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.
Chamath Palihapitiya: 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 detection, 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 people.
Jason Calacanis: It's de minimis compared to the cost of crimes.
Chamath Palihapitiya: It's de minimis. It's de minimis, especially when compared to
Jason Calacanis: the cost of the crime occurring.
Chamath Palihapitiya: Exactly. If you gave the Las Vegas Police Department 30, $40 million a year, it would be the safest city in America, and that's all it would take.
Jason Calacanis: Yep, exactly. And for the privacy concerns, Freeberg, there are very simple solutions to this. 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 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 in it. So there are all little things you can do on the back end to protect privacy with auto trails, et cetera. 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 bejesus 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 is 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. What's the word?
Chamath Palihapitiya: Dystopian.
David Friedberg: Dystopian.
Jason Calacanis: Thank you, sir. He did him in a pretty dystopian way. Here's Zuckerberg for 36.
Gavin Baker: 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, through these contractors. So if we're trying to teach the models coding, for example, then having people internally build tools that. Or solve tasks that help teach the model how to code, we think is going to dramatically increase our model's coding ability faster than what others in the industry have the capability to do who don't have thousands and thousands of extreme, extremely strong engineers at their company.
Jason Calacanis: 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 H1B 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 computers 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 this AI tools to make my job more efficient. And then Zuckerberg laid me off. So the now, 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.
Chamath Palihapitiya: I thought the Matthew Prince note was horrible.
Jason Calacanis: Okay, explain.
Chamath Palihapitiya: This was like, from the PR school of retards.
Jason Calacanis: Okay, here we go.
Chamath Palihapitiya: 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 one second and I'll tell you why I think this is just so.
Jason Calacanis: And then we'll go on to the S1 from SpaceX.
Chamath Palihapitiya: We're listening too much to the inventors of AI.
Jason Calacanis: I know that's appealing. They're geniuses, they're smart, they're.
Gavin Baker: We need to be listening to the
Jason Calacanis: frontline factory workers who are using AI
Chamath Palihapitiya: saying, wow, I was able to add a third shift.
Jason Calacanis: 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.
Chamath Palihapitiya: So, look, 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 clouds flare 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 meant they're really good at one thing and they're not necessarily as good at all the other things.
Jason Calacanis: Yeah, okay.
Chamath Palihapitiya: 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.
Jason Calacanis: All Right.
Chamath Palihapitiya: End of my TED Talk. Thank you for coming to my TED Talk.
Jason Calacanis: Thank you for coming to Chermat's 18 minute Ted talk. And we'll keep moving on.
Chamath Palihapitiya: Sorry. And sorry. When everybody gets upset, this will be
Jason Calacanis: why, yes, I do think the Zuckerberg this and Jack saying, 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 rightfully scared. If the people building it tell you, be scared, your job's going away, wait
Chamath Palihapitiya: till the next regulatory filing comes out from these companies and they authorize a massive share buyback and an increase in their dividend.
Jason Calacanis: Yeah. And their cash pile grows.
Chamath Palihapitiya: 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. They don't understand the moment.
Jason Calacanis: Oh, some breaking news here. It looks like Anthropic has hired three more people. Here we go.
Chamath Palihapitiya: Let's see.
Jason Calacanis: Oh, here we go. Personal job news from Sam Altman. He'll be joining Anthropic. I see. That's pretty good. Who else is joining Anthropic? Let's see, we checked everybody's socials. Oh, Tucker. Tucker Carlson, also joining Anthropic. He'll be doing their PR and podcast from Anthropic headquarters. And who else? Oh, Chamas, looking good. Well, he looks like you put five pounds on.
Chamath Palihapitiya: And this is not how I. First of all, this is not. This is not what I look like.
Jason Calacanis: And did you weigh five pounds? Looks like this.
David Friedberg: Are you not wearing underwear?
Jason Calacanis: He's not underwear and he's wearing his khakis. But I think it's just he's trying to not show off those scrawny, those scrawny skins, those. Those little slats he calls legs. He's covering them up now.
Chamath Palihapitiya: Hold on.
Jason Calacanis: I'm not gonna leg shame you.
Chamath Palihapitiya: I knew that this was gonna come up. I'm gonna send Nick an updated picture of my legs. And you, you can deal with this.
Jason Calacanis: You can Photoshop your legs all you want.
Chamath Palihapitiya: I didn't. I didn't Photoshop.
David Friedberg: You look like ostrich, brother.
Chamath Palihapitiya: Those are ostrich.
David Friedberg: Today.
Gavin Baker: He may not be Photoshopping. He may have been leg maxing.
Chamath Palihapitiya: He could have been.
Jason Calacanis: I've been leg maxing. Are you BP157 in your legs? What Are you?
Chamath Palihapitiya: First of all, first of all, I'm six foot two, you goons.
Jason Calacanis: Okay, so gauge legs.
Chamath Palihapitiya: All you little people, you know, Jason, you're five foot all. So you know your ability to have
Jason Calacanis: a good day with my platforms.
Chamath Palihapitiya: Yeah. Your ability to have legs is, is different because like my muscle mass won't show on my legs the way it shows on your leg.
Jason Calacanis: Oh, I don't think you're helping. I look at, you know, what he's doing there.
Chamath Palihapitiya: Freeberg, you see it, right?
Jason Calacanis: Look at how scrawny the calves are. And then look at how he's doing.
Chamath Palihapitiya: Oh my God.
Jason Calacanis: That's a push up bra for your quads.
Chamath Palihapitiya: Oh my God.
Jason Calacanis: That's the equivalent of a push up bra.
Chamath Palihapitiya: He has those sponsu balls.
Jason Calacanis: He put bosu balls under his hammies to. You did it. You're using fillets to lifted my legs and I flex.
Chamath Palihapitiya: Okay, you know what? Move on.
Gavin Baker: I would just say I think we should give credit where credit is due. Yeah, legs better. Been doing a lot of work on his legs.
Chamath Palihapitiya: Thanks.
Jason Calacanis: It's better.
Chamath Palihapitiya: Thank you.
Jason Calacanis: It's better.
Chamath Palihapitiya: Thank you.
Jason Calacanis: I'll give him better, but I do think that he's pumping him up here. Okay, let's keep going here. All right, topic to SpaceX just filed their S1 on Wednesday. They are aiming to raise 75 billion 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 S1 teardown. Obviously SpaceX has three main business units. Starlink is the money printer right now. But there is 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'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 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 build out and obviously they were trailing anthropic and OpenAI and Gemini in terms of XAI 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 three 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.
Chamath Palihapitiya: Not if I already told you they already bought.
Jason Calacanis: Okay, I'm just trying to dot the I's and T's here. But when they buy cursor, that adds to a 3 billion that's not in the S1.
Chamath Palihapitiya: That's also growing and doubling.
Jason Calacanis: Yeah, that's probably growing 2x year over year. And who knows how much faster it will grow. Poly market 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.
Gavin Baker: 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 their first data center was 122 days. 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 offtake 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 maybe what anyone could have contemplated three months ago. But $15 billion from anthropic is extraordinary important note.
Jason Calacanis: 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.
Gavin Baker: And I think that's, that's a, you know, I think that's, that's, that's probably an important provision 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 Pareto 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 three, four weeks of doing reinforcement learning on Colossus 2 with Cursor's data. And Cursor has, we will never know, 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 would 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, because Composer 2.5 is the same base model as Composer 2, which is Kimi K25. 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. Then the Cursor model RL using the biggest coherent compute cluster in the world. And I think this may.
Jason Calacanis: It's significant.
Gavin Baker: Yeah, it's extremely significant for Xai and Cursor.
Jason Calacanis: And Cursor was dead in the water in terms of access to compute. And they were falling very far behind. Codex, 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 computer to Google and OpenAI. Is that a possibility or not?
Gavin Baker: Well, I think it's much easier to see him selling compute to Google and I think there have already been posts about that. And for sure Google is going to want to be part of Orbital Compute. It's 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.
Jason Calacanis: Keep an eye on it. Yep.
Gavin Baker: And then the other thing that's come out is Grok Build. 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 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 OpenAI anthropic, and that's it. Those are the companies on the frontier. And the four horsemen, 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 codecs, and now with Grok Build there is a harness that is available to Grok and as I'm sure a downloadable app to
Jason Calacanis: translate into English that has integrations to all your favorite stuff, whether it's notion, Gmail, Slack, et cetera. 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.
Gavin Baker: It's more than just an app, 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 agentic world. And the harness and the model need to be developed together. 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 because Composer 2.5 is now Pareto dominant and the most selected model on cursor. And that's also important because these evals don't capture everything. This is why people on X talk about the vibes. And the vibes on cursor 2.5 are also really good.
Jason Calacanis: They're immaculate.
Gavin Baker: Together with Grok Build, I think these are really important developments.
Jason Calacanis: Yeah, 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. Friedberg, 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 $sign Elo 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.
David Friedberg: 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, an organized effort by governments to stop or block access to information, restrict freedom of speech restrictions, 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 at this kind of system that provides an open alternative to physical commerce that you could create digital commerce, digital information, digital media that you could share. And it's almost this digital representation of society. But the Internet has to sit physically somewhere. And the assault on data center build outs 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 is generally a good thing. It's good to have a backup.
Gavin Baker: Yeah.
David Friedberg: 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 important. And I just, I like that.
Jason Calacanis: Yeah. If you, most people don't remember this, but when elon was starting SpaceX, the original idea, when he was running around with Adao 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 creatures and what incredible vision. And then it, there was the necessity of actually getting that up into space. And that's the unknown origin story. I will say this Chamath, the idea of putting 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 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, of course, they're physically different, but conceptually. Elon put 10,000 Starlinks up. Is he capable of putting 10,000?
Chamath Palihapitiya: No, look, the size rockets, the size is much bigger, Jason. The foils are much bigger, the wings are much more.
Jason Calacanis: But it's, but it's. Yeah. My point is it's not different if he has the new starship, because that's 10 times bigger. Yeah.
Chamath Palihapitiya: 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, Jamath, 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. 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, 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 the reason 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 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 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 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. 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 has he got up his sleeve? The Steve Jobs. Oh, and one more thing. This is the only guy at the scale of civilizational out of left field. 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 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 and everything else.
Jason Calacanis: Is the colossus on the ground earth based?
Chamath Palihapitiya: It'll be not even in space. No, no, forget space for a second. It's like Colossus 3, Colossus 4.
Jason Calacanis: It pencils out with that. Yes.
Chamath Palihapitiya: Getting a nameplate one 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 position 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 laws seen as.
Jason Calacanis: Explain what that is in English. Yeah, for everybody.
Chamath Palihapitiya: Just like, look, you go through a bunch of power transformations 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 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.
Jason Calacanis: It's.
Chamath Palihapitiya: It goes right to the rack as dc, but it requires a fundamental RE architecture. 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 one more thing.
Jason Calacanis: 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 most people have not actually seen a starship in person. When you see this thing in person, and I've been inside that rocket, I think we were together, Gavin, when we were in the first build. And inside of that you can fit 300 people. It's basically like a giant. If you thought of commercial 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?
Gavin Baker: Yeah. And Starship's going to get bigger. Based on their roadmap, it's going to get a lot bigger.
Jason Calacanis: A lot bigger. And then this one is the most interesting, that this started trending last week. This is cumulative payloads launched 1957 to today. SpaceX is basically about to in just that. 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 midterm. But I think data centers in space would be a midterm to long term play. Three years is what I'm hearing. So tell us about that business in relation to the two charts I just shared.
Gavin Baker: Well, the one thing I would just say. Well, first, all those charts about launch are before Starship was operational. And most of that master orbit was done by Falcon.
Jason Calacanis: Yes.
Gavin Baker: And Starship. 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 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 fly and land the same rocket multiple times per day. So if SpaceX and it's really hard to do rapid reusability, I think it would have been much, it would have been not trivial, but much easier to have starships working if it was just designed to be reusable. That's not enough for what Elon wants to achieve of 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 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 and starship means. If they get.
Jason Calacanis: When do you predict they'll have that rapid reusability to space, you think?
Gavin Baker: I mean we're going to find out. We find out. I'm going to be at Starbase today for the launch.
Jason Calacanis: Yeah.
Gavin Baker: So we turn over cards and it's important for everyone to remember. Let's just say It's a fireball. SpaceX will still learn from this. Yes, 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.
Jason Calacanis: I think that's most consensus. A year or two is I think perfect consensus.
Gavin Baker: 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, an Nvidia H100 GPU in space today.
Jason Calacanis: Yeah.
Gavin Baker: Andrej Karpathy both trained a model on and used for inference. So this is, you know, it's. There's a working GPU in space today
Jason Calacanis: and Nvidia is making a space designed version of this which will be different because the heatsink 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 G's put on them. So you're going to need an industry, an industrial strength, one that gets to space, that has a different profile. Yeah, Gavin?
Gavin Baker: 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 be in space or satellites in space. And those semiconductors are a lot cheaper. We have a couple. My firm Atreides 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. SpaceX really liked a lot of the specifications on the chips. And then it's like, well, we'll see how they do with rad testing. And they just happened to pass. And so that is one of like one of something that's very underappreciated I think about SpaceX.
Jason Calacanis: One of their specialities.
Gavin Baker: One of their specialities, yeah.
David Friedberg: But I think.
Gavin Baker: All right, second half of 28 to first half of 2030 would be my point prediction.
Jason Calacanis: All right, let's do Nvidia and then the the market recap since we have 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 market cap. Stocks 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 $0.01 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? Friedberg, the scale of this is just extraordinary.
David Friedberg: Yep.
Chamath Palihapitiya: Don't say it there.
Jason Calacanis: You have FERCs, there's your market report from Freeberg.
Chamath Palihapitiya: Don't seem so enthused.
Jason Calacanis: Yeah, it's a. He's got potatoes in the oven.
Chamath Palihapitiya: 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 because 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 because it explains, I think just to set it up, where is value over the next five years? I think if you looked at Leo Aschenbrenner, his fundamental has gone from like zero to $5 billion 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's the puck going?
Gavin Baker: Well, so maybe take the questions in reverse order for Leopold, who's clearly a brilliant man. I think he's a Rhodes Scholar at 19 and I think my understanding is putting up pretty extraordinary numbers. 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 I would say we were in the thick of geopolitical fears. And I think you saw a lot of puts on a lot of 13 Fs and I don't know that those puts are still there. I think a lot of people wanted to be hedged for Iran and 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 semi chips.
Chamath Palihapitiya: Okay.
Gavin Baker: On chips. Second thing, I think cross sectionally, if you look at the valuations for all these AI names, they can't all be accurate. You have memory makers that three to five times pe, you have Nvidia at a really low pe, you actually have 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. The IPPs are actually quite reasonably valued. But power, cooling, even probably 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 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 a, within AI they have hyperscalers and then I think they call it AI clouds, industrial and enterprise. I believe is if we were to make a true apples to apples comparison and Broadcom, 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. 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, within the western AI world, within data centers that are being built, whether they're being built by Core, Weave, xai, Amazon, Google, Nvidia's AI business is growing faster than Broadcom's and faster than a lot of other companies that are seen as part of this ASIC share gain story. And I think Jitson has become, you can hear it, increasingly frustrated and rightfully so at two things I would say what is the performance of the stock?
Jason Calacanis: He's been vocal about that. Like what is going on here? You're putting up record numbers and we're getting no credit.
Gavin Baker: Yeah, I get it. How could there be a share loss narrative if I am gaining share? And it is indisputably true that he is growing faster than hyperscale or Capex even without these adjustments. I think the other thing that's so frustrating to him is these other ASICs are not being submitted for benchmarks. They're not in the CB analysis inference Max, they're not in MLPerf. And I think the reason they're not being submitted is they will lose and you can't fight shadows. And until we see a clean benchmark of whether it's GB3 hundreds versus TPU V7s are very versus inferentia.
Chamath Palihapitiya: Yeah.
Gavin Baker: Versus tritium, we're not going to know. And that's why a lot of these other chips, I think Trainium's in a great spot. Aren't being submitted. But nonetheless Nvidia is doing well. Once you become the largest company in the world, you tend to trade. My observation would be in stair step patterns where the multiple compresses. Compresses, compresses because people are skeptical of the size.
Chamath Palihapitiya: Then you have a RE rating.
Jason Calacanis: Yeah.
Gavin Baker: And then you re new floor is
Jason Calacanis: established at a higher rate. Yeah.
Gavin Baker: I think there was one other really important thing in the Nvidia quarter. It's they said if they thought their CPU business was going to be $20 billion this year.
Chamath Palihapitiya: Yeah, yeah, yeah.
Gavin Baker: That's extraordinary. It means overnight for 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 it co design for where the models are going. And I think that $20 billion CPU figure is pretty extraordinary.
Chamath Palihapitiya: 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 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, it's another game changer for everybody.
Gavin Baker: He does chip, he makes nine and then I think the cost at which you can finance these chips and these useful lives is really important.
Chamath Palihapitiya: You had an incredible insight, which is the amortization schedule for Core Weave and all these guys, they got saved. You may want to just explain what that is and why you said. I thought that was a great insight.
Gavin Baker: No, thank you, Chamath, I appreciate it. So when Core Weave 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, these guys are amortizing their GPUs and CPUs over four, four, 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.
Jason Calacanis: The reality is this was Michael Burry who put this out there. Yes, to be clear.
Gavin Baker: Yeah, yeah. And you know, thank you, Michael Burry. We need bears. Yeah, thank you.
Chamath Palihapitiya: Yeah, that's like, it's like asking Gerardo about modern music.
Gavin Baker: Well, I don't, I don't want to cast dispersions on Michael Berry. He's a, he's a brilliant man. But we need bears.
Chamath Palihapitiya: Let me. Hey, somebody call Vanilla Ice and ask him what he thinks.
Gavin Baker: Thanks.
Jason Calacanis: Oh my God. Milli Vanilli.
Chamath Palihapitiya: Check the waste. What a waste of time. What a waste of time.
Jason Calacanis: Oh, poor Mark. Come on the program anytime. Michael Murray. Go ahead Gavin, keep us on track.
Gavin Baker: Happy to chat. But now that we've disaggregated infrareds, 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 it's a Cerebras accelerator in front of all 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%.
Chamath Palihapitiya: 6% it's going to come down.
Gavin Baker: And if you can get an asset backed loan and asset backed financing for GPUs at a lower rate than other chips.
Chamath Palihapitiya: No, that's a profound advantage. That quarter single handedly saved the Neo Neil's clouds. This, I mean they single handedly saved the wall. I think they, they should all, they should all say an incredible thanks to
Jason Calacanis: Jensen because I interviewed the CEO of Core Weave, Michael in Trader. Michael and Trader. Yeah. And he was saying hey listen, people have no problem buying and financing these over a six year period and people are asking for things that are coming off and that he thinks they're going to have year seven, eight, nine, they'll have some useful life, you know, in addition to that. So yeah, so he's like, I don't know what anybody's talking about here. Like this is just not informed analysis was his point. Like the game on the field and people are betting with their dollars with him. He has them pay in advance and sign six year contracts. If they didn't think it has six year lifespan, they wouldn't be signing a six 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, 16th time, it's a charm. And the Iran war is going to wrap up, but we're in week 12 of it and this was supposed to be four to six 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 professional forecast is projecting CPI hits 6%. You heard that right folks. We weren't just talking about a 3% handle which we just hit 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 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?
David Friedberg: What is the point of being concerned when you have ridden the roller coaster to the top and it is beginning its descent? I don't know what there is to be concerned about. The force of gravity is inevitable. The roller coaster will roll down, we will throw our hands in the air and we will scream wee 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 in 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 Treasury 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.
Jason Calacanis: There he is. Dr. Doom is here. Jamal, your thoughts on Dr. Doom's panic attack of the month. 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?
Chamath Palihapitiya: 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. It's just not worth it. The vicissitudes of the market 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 of those. Large for me doesn't mean large for everybody else. And then otherwise I just kind of stick to my eating and keep my head down. It's a much more rational way to behave.
Jason Calacanis: 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 ten?
Chamath Palihapitiya: It's five. It's five or less.
Jason Calacanis: Five or less.
Chamath Palihapitiya: Five or less.
Jason Calacanis: So what your largest holding right now is what percentage of your net worth would you say? I don't know, like top two, maybe? Yeah.
Chamath Palihapitiya: Oh, top two, yeah.
Jason Calacanis: Like one and two. One is 20, two is 15 or one is 40, two is 20.
Chamath Palihapitiya: I don't know again, it depends on the day, but I don't know. But it's, it's just curious.
Jason Calacanis: But I think that's, I think that's really important.
Chamath Palihapitiya: 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.
Jason Calacanis: 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.
Gavin Baker: Well, so one, I manage more than 100 positions at my firm and I do that with a team. We're over 30 people now, so it's not just me and I work with some great people. 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
Jason Calacanis: and certainly any country.
Gavin Baker: Absolutely unprecedented. Yes. They're actually. Yeah, they're, they're now the size of, you know. Yeah, they're would pull up where they
Jason Calacanis: rank bigger than 100 different countries for sure.
Gavin Baker: Exactly. And keep really fast and now profitable. Yeah. Which I think really changes the moment.
Chamath Palihapitiya: Which is bizarre.
Jason Calacanis: Yeah. Yeah. How did that happen?
Gavin Baker: 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 the Nvidia of the tech bubble is Cisco and it traded 100 times forward earnings. And I think Nvidia is probably at a low teens multiple of kind of low to mid teens multiple of real earnings. That'd be a buy side consensus, not an Atreides number. And then the third thing that I think is true is a straight up Hormuz 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 have 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 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.
Jason Calacanis: We're still the best currency.
Gavin Baker: Yeah.
Jason Calacanis: So the best economy. We still have the best public companies and we have the best private market companies.
Gavin Baker: Yeah.
Jason Calacanis: And we are one of the greatest producers of oil in the world. So we're in good shape despite this international chaos.
Gavin Baker: I don't think a dollar crisis is around the world now, listen, like, if, you know, the Bundesbank 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 because we're the best house and what is globally a 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 Formos is closed, I think is relatively good for the re industrialization of America. I think
Jason Calacanis: you're saying it's a forcing function, makes us just like Covid did, be more resilient and. Yeah. More self reliant.
Gavin Baker: Yes. And electricity is a base input to every manufacturing or industrial process, essentially all of them. And what we make electricity with in America overwhelmingly is natural gas. And you can look it up NG1 it is down this year, 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 street of Hormuz is absolutely bad for everyone, but relatively good for America and relatively good for Trump's policy goals. 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 homos is closed is relatively good for America. It's terrible for Europe, it is terrible for Asia.
Jason Calacanis: Japan and China need that oil. Philippines, India needs it.
Gavin Baker: Yeah, yeah. And 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 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, you know, because college students, they use a lot less chatgpt and Claude in the summer and generally people maybe work a little less hard when the weather's nice. Now with agentic AI, we will the fundamentals still be seasonal. We will see.
Jason Calacanis: 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, Q3. Yeah, people are out gallivanting and they're not playing Candy Crush or buying. Com or whatever. But oh hey, Uber and DoorDash went up, people are traveling, et cetera. 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, to China. We did see a little movement there and the Strait of Hormuz, we would become wonder twins with Xi and Trump reopening it. But nothing really definitive other than some soybeans being sold and some H1 hundreds, A2 hundreds getting sold to Baidu and some of the top folks. And maybe some planes got sold too. So other than a little bd, a little business development. Yes. Freiburg, what's the outcome here, here, or was it just a bit performative in your mind?
David Friedberg: There was a, a question. Would the administration leave China with a grand deal that made everyone feel like there was a long range view on a partnership? And 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 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 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 is now a relationship bonding moment happening between China and Russia. So the story continues. 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 this story continues.
Jason Calacanis: Were you expecting a happy ending?
Chamath Palihapitiya: I can't answer that question.
Jason Calacanis: I mean to the story of the China visit. I'm not talking about any other things going on in your life, but did seem like some planes and soybeans got sold. Some H1 hundreds perhaps, but 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.
Chamath Palihapitiya: 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 I think that there's some amount of agreement there. I'm just guessing.
Jason Calacanis: Yeah. And so that guess if I was going to unpack it, hey, we get, we have Venezuela, we have Iran and Taiwan.
Chamath Palihapitiya: You have, I would just say, look,
Jason Calacanis: here's this geopolitical chessboard and here's what I would say.
Chamath Palihapitiya: Just very generally like, it's just I think that there's a way to divide up the game board in a way that helps them and helps us.
Jason Calacanis: 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.
Gavin Baker: I think I disagree with Chamath on this. I think selling and deprecated Nvidia GPUs to China lowers the odds of them developing their own alternative ecosystem, which would be a lot power hungrier because you 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 that is what I believe. You know, reasonable minds can disagree.
Chamath Palihapitiya: Where do you think we disagree? I'm not sure I agree with you.
Gavin Baker: Oh, good, I'm glad we.
Jason Calacanis: I was going to you start. You starting agreement on.
Gavin Baker: No, no, no.
Chamath Palihapitiya: I'm like sell. I'm like sell everything to them. No, what I was just saying is that there is 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, memo press release. That's my point. That's all I'm saying.
Gavin Baker: Yeah, I would just say listen it like American China talking is only good. We want to avoid the cities trap that is being discussed. And China talks about a lot. They're very aware of it and they brought it up.
Jason Calacanis: Yes, she brought it up by name. Yeah.
Gavin Baker: Talking is a integral step of avoiding, I have to say, having a nice resolution.
Jason Calacanis: From my perspective, the greatest superpower Trump has is, 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 him 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
Gavin Baker: 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
Chamath Palihapitiya: the world, two out of three are off the chessboard.
Gavin Baker: Yeah, if you two or 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 Formulas 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.
Jason Calacanis: Japan, South Korea, Australia, uk, France, Germany, the world good luck.
Gavin Baker: Who knows about Europe, but for sure Japan would be there. For sure Japan would be there.
Jason Calacanis: Oh, and Australia for sure. Korea for sure. Yeah.
Gavin Baker: 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.
Chamath Palihapitiya: I think that's a good insight.
Jason Calacanis: I think it's a great insight. All right, listen, we missed you, Sacks. Come back soon.
Chamath Palihapitiya: And Gavin Baker, shout out to bestie Gavin. Thank you.
Jason Calacanis: Yeah, you're so great. Thanks for coming. We appreciate it. Hey, and your father in law, what's his name again?
Gavin Baker: Jeff Painter.
Chamath Palihapitiya: Jeff.
Jason Calacanis: 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. Wanted 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 a sudden, Gavin made it to the show.
Chamath Palihapitiya: Love you, boys.
Jason Calacanis: A little bit of pressure. That's my way of the. That's my hormone straight.
Gavin Baker: Yes. I'm always there for my father in law.
Jason Calacanis: Absolutely. All right, everybody, see you next time.
Chamath Palihapitiya: Thanks, guys.
Gavin Baker: We'll let your winners ride.
Jason Calacanis: Rain Man David Sack.
Gavin Baker: And it said we open source it
Jason Calacanis: to the fans and they've just gone crazy with it. Love you. The queen of kin. Besties are gone.
Gavin Baker: That is my dog taking a notice in your driveway. Oh, man.
Chamath Palihapitiya: My habit will meet me at. We should all just get a room
Jason Calacanis: and just have one big huge orgy. Cuz they're all just useless. It's like this I sexual tension, but
Chamath Palihapitiya: they just need to release somehow.
David Friedberg: We need to get merch.