US vs. China: Why Trust Will Win the AI Race | GPT-5.2 & Anthropic IPO w/ Emad Mostaque, Salim Ismail, Dave Blundin & Alexander Wissner-Gross | EP #214

28:39Normally, memory comes down at a rate of almost half a year in cost. And so to see it go the other direction is the first bellwether that, hey, there's going to be a huge shortage of compute. and if you don't go public and raise the capital and lock up the supply you're going to be left compute starved yeah i mean the same thing is going on in fundamentals right i didn't put it in the deck but there's a copper crisis right now the price of copper is going through the roof because of wiring these data centers um all right let's move on to our next story here uh wait quick point yeah please if they're next year revenue projections are 26 and the valuation is 30 300 billion.

29:19That's only 10 times revenues. Palantir is trading at 111 times revenues. So that's cheap in that sense. It's a good point. It's a good point. No, it is reasonable. It's crazy big numbers, but it's perfectly reasonable. I think Slim is saying it's overly reasonable. It should be at a higher valuation, and it will be. It'll probably spike after an IPO. All right, here's our story. OpenAI finds confessions can keep language models honest. So a new confessions method trains models to openly admit when they're hallucinating or when they've broke instructions. The method encourages models to self-report mistakes instead of hiding them.

29:58So I am completely curious here. It's like, okay, so you use this methodology. Do you actually get two reports? Here's my answer and here's my confessions. Emad, what's going on here? Yeah, I mean, this whole thing with next token prediction, right, is that the models kind of go along and then they can't have the self-reflection and more things like that. I think that what you find is when you've actually got the right prompts, the right planning, and the right loops, you get very interesting things occurring, particularly as the hallucination rates are dropping now as well. Because models used to jump a lot and skip these behaviors because they didn't have the self-reflection.

30:43They didn't have some of these other things. So I'm not very surprised by this. And again, I think what we'll eventually see is what we saw with the DeepSeq v3.2 math paper, a concept called a meta-verifier where models learn from their mistakes. So rather than just checking against a very small baseline, are you being honest? Where have you made mistakes? Having that as a verification loop is very similar to how humans learn. And that's what causes big leaps in some of these more frontier areas of thought as well. You know what I found shocking? I asked one of the models, you know, how often are you hallucinating or providing wrong answers on average?

31:25And I found a couple of studies. And one of them was that 25 % wrong answers on everyday user questions. another one said gpt40 and claude 3.7 sonnet hallucinate on an average of 15 to 16 percent of the time and i never expect that when i'm when i'm asking my questions i'm assuming and i think the majority of all of everyone perhaps not you imad and alex i'm assuming that they're correct If it's really, you know, 10 to 25 % hallucination, that's scary. It's basically the same as a human doctor, right? And the interesting thing, though, is that it's dropped. So GPT-5 dropped it from 18 % down to 3%.

32:12So it's a last generation of models. Yes, go ahead. Can I give you a dramatic example of this? I think it's worse than a human doctor because they're actually trying to please you, the model. So therefore, they're saying whatever. I had a TV where the power went bad. And Chachapiti said, oh, if it's this model here and it's making a buzzing sound. Yeah, you mentioned that in the last pod. So I asked it then, okay, who do you know that can fix this? And it gave me names of three local TV repair shops that were completely hallucinated with phone numbers, with phone numbers, websites, names, addresses.

32:51And I started calling them. All the phone numbers didn't work. And then I went and looked up. None of them existed. So this is a big problem. If I lift up a level for this confession thing, I think it goes back to the earlier point that it's great to have a feedback loop. It gave me somewhat chills because I went to Catholic high school and the idea of confessions is somewhat chilling. Who's the priest is my question when you do this type of model. But I think the feedback loop is very powerful to have. Wow. Wow. I think it's also worth mentioning the 50-year-old notion from economics of Goodhart's law, which is that when a measure becomes a target, it ceases to be a good measure.

33:29And the way that these models are trained certainly and superficially rewards various sorts of behaviors that might be construed as dishonesty. And being able to avoid Goodhart's law, clever ways to avoid Goodhart, I think are admirable on the part of OpenAI. And maybe the final solution looks a little bit less like naively optimizing just next token prediction objectives or reward maxing on RL objectives to solve math problems or programming problems. looks a little bit more like some sort of multi-objective optimization problem where maybe there's some blend of a good heart avoiding honesty reward and an accuracy award and an ethics reward that maybe almost start to look a little bit like separation of powers in what we see in government systems.

34:26There's an executive in some systems, a legislative, judiciary, etc. I'm going to have to bookmark that comment, Alex, because you lost me at multi-objective optimization problem on that on that note i'm gonna move us forward but you have a good heart salim all right so again it's like the next release google releases gemini 3 deep think which uses parallel reasoning testing multiple solution paths at once that makes sense to me right an upgrade from 2.5 deep think and it's excelled once again humanities last exam and GPQA Diamond, ARK, AGI2. Going to our benchmark expert, Alex. This is a template for how revenue is going to scale to justify the trillions of dollars of CapEx.

35:14It won't just be faster models or better models or stronger models. It's going to be lots of agents, fleets of agents, millions of agents, many millions, billions of agents, all running in parallel to solve problems. That is, in my mind, and certainly based on the architecture of Gemini 3 DeepThink, which isn't just a faster, better, singular model, but it's also scaffolding to have fleets of agents, fleets of Gemini 3 agents that are all running in parallel to solve a given problem. That's the DeepThink part of Gemini 3. Sounds like quantum computing to me. Not at all. No, I know that, but there's the concept I'm going to run this problem in multiple parallel universes and bring back the answer.

35:59I'm going to run this problem in a billion or a trillion agents and bring back the best answer. Parallel, yes, but quantum computing wishes that it has the economic utility of Gemini 3, deep think. I'm with Peter on this one. Go ahead, Salim. I'm with Peter on this one. It feels like that kind of parallelism. But I think the broader point you're making, Alex, is that when you have millions of agents, each specialized, if you take something like the Manhattan Project, you have thousands of people each with a deep specialty connecting together, and the hive mind then solved the problem. And we're going to see the same with agents.

36:34Is that a metaphor that works? Yeah. When Dario speaks of countries of geniuses in a data center, this is what it looks like. We're going to have billions of agents that are all going to be independently probably pretty expensive, even though the cost of intelligence is going to zero. But collectively, yes, this is going to generate trillions of revenue if we have so many agents. And this is how we pay for all those data centers. Well, yeah, I think that's a really important point, Alex, is, you know, everybody talks about the cost of intelligence going to zero, but it's not actually going to zero.

37:04It's going down to a low number. But concurrently, the fleets of agents are getting so much bigger so quickly. And, you know, we saw earlier in this pod, too, the process of expand the context window to entire, you know, hundreds of millions of tokens and run many, many iterations to get rid of the hallucinations, those forces are going in the other direction. And it's working far better than anyone thought it would. And so it's very unlikely that the cost of intelligence is going to go to anywhere near zero. Everybody's going to want more intelligence and more intelligence and more. So there's going to be an acute shortage.

37:44And I only mention that because many business leaders are out there saying, let me just wait and see what happens. And you're going to be starved of access. And you can see this already when the new models come out of Gemini and they add another level of deep thinking. It works incredibly well, but you wait three, four, five minutes to get your answer. And very often it says, we're experiencing unexpected loads right now. Sorry, we're offline. How's that possible if the cost of intelligence is going to zero? Well, it's not. The cost per token is going way, way down, but the use cases are expanding on at least three different dimensions on this ridiculous curve the other direction.

38:22And everybody's going to want it because it works so well. So what does this actually mean other than we have yet another faster model able to hit the benchmarks a little bit better and next week we'll be announcing the next better model? Imad? i think the models are getting to the point now where again ensembles of these models doing different things are just genuinely useful for real world advanced complicated tasks i'm really looking forward to using a gemini 3 deep think 2.5 deep think was pretty good but right now i think the only one usable for real frontier stuff is gpt 5.1 pro which again does something similar ultimately what you want is you don't want a task that's really complicated to be done in seconds nor minutes.

39:09You want to be iterating on a task for a period of time, giving it input and feedback, and the model just not making mistakes. Like Gemini 3 Pro still makes mistakes in math when I'm using it, you know? And so Gemini 5.0, GPT 5.1 Pro doesn't. The model usage, again, I think the DeepSeek math paper is fascinating for this. It's the first open source model that gets a gold on the IMO. And to each of the problems, they use 2 billion tokens. So about 2 billion words. Yeah. That gives you an idea of how many more tokens you can use. Yes. And it works. It works. And it works. I mean, if you want to experience this firsthand, just go to GPT 5.1, soon to be 5.2.

39:54Ask it to do something complicated for you that it can't quite do. And they just keep asking it to try harder about a thousand times back to back and it will eventually get it right you're like why does that work what's an example of a hard thing to do oh i do this like all day long in fact right after this pod i'm back i have a fleet of uh kimmy k2 agents scouring the the world right now working on hard problems but i'm you know if i ask it to translate legacy c code into python and then it's you know it comes back slow make it faster improve the algorithm um or Or, you know, more down to earth.

40:26Do you do that with your students? Do you do that with your students too? Work harder. Try it again. Well, that's the difference. That's where everybody's analogy breaks because there are a limited number of humans and students, but there are an unlimited number of AI agents. And so deploying a billion in parallel to work on something is out of your normal range of intuition, but it just flat out works. You need to expand your intuition to this new world we're moving into. I think that's one of the most important things that we can say coming out of this, which is we're about to enter a new world where there is a near infinite amount of intelligence to be thrown at things by anyone.

41:06So then the interlude. One of the really interesting things. Sorry, please. Go ahead, Iman. Yeah, I think one of the super interesting things in the context when just realizing it is, again, the stuff that we get wrong. When we're trying to solve problems, usually the only stuff that survives is the stuff that we get right. Like at NeurIPS, it's papers full of all the stuff people got right. Being able to actually have scientific methods, strategy, and things like that, where the context window includes everything you got wrong for all the different models. Fascinating. We know that will do better because often it's what we got wrong that actually guides the following solution.

41:39Learn from your mistakes. Yeah, sure. I mean, if you had asked everybody in the community three years ago, is that going to work? 90 % of people probably would have said, yeah, I really doubt it. But it does. Now everybody agrees, everybody at NeurIPS, I'm sure, it just flat out works. But that means you need massive, massive numbers of parallel agents. And even any given agent needs many iterations. It's just a huge amount of compute, but it just solves problems. It's incredible. All right. Our next story here is the reasoning AI became so efficient. So AI got more efficient mostly for huge LLMs, with training becoming 22 ,000 times more efficient, while smaller LLMs only improved by 10x to 100x.

42:24So what's the story here, Alex? Yeah, this is sort of a finger in the eye to those armchair theorists who say that the small guys, that the small labs are going to benefit from algorithmic advances. So this is a study that found that 91%, this is a study out of MIT, 91 % of algorithmic efficiency gains between 2012 and 2023 were the result of only two things. One, the switch from LSTMs to transformers, and two, the switch from Kaplan scaling, named after my former office mate in the Harvard Physics Department, Jared Kaplan at Anthropic, and the switch from Kaplan scaling to chinchilla scaling.

43:09Those two things. So LSTMs to transform LSTMs were recurrent to transformers. What are LSTMs? Long short-term memory. So LSTMs were, prior to the transformer revolution, LSTMs were the favored language model. I remember the old days prior to Transformer, prior to GPT, when Andre Karpathy had his char RNN language model that stunned people by being able to generate code. There was a life prior to GPT. But just those two algorithmic transitions, LSDMs to Transformers and Kaplan scaling to Chinchilla scaling, those two were 91 % of the efficiency gains. And what that says is that this story that, well, we're just stacking small wins on top of each other and that eventually somehow algorithmic efficiency gains are going to enable smaller labs to have some sort of advantage relative to larger labs.

44:10This suggests that's just not true and that most of the algorithmic efficiency gains are actually accruing to the large labs that are able to scale out the most. There's one other thing in this paper that's noteworthy. And please don't read it. Alex summarized it perfectly. That's everything you need to know. It's way longer than it needs to be, classic MIT work. But it's a very, very good summary at the beginning of the document of why this work is so important. Because we're putting an immense amount of societal energy into scaling the hardware. And Elon Musk talks about Tennessee all the time and Stargate and a huge amount of thought and research and discussion on our podcast about these massive data centers because they're so visual and they're so expensive.

44:51But the software side of it is very under-researched and very under-analyzed. So they're taking a first shot at trying to give us better insight into the future rate of improvement of the software side of it because that's where it's not as expensive, but the lift could be enormous. And so I think this is a really, really good focus area, and I'm really glad MIT is on top of it. But Alex's summary is all you need to know about the work so far. Amazing. So the inner loop here then is energy going to GPU to agents going to intelligence. And therefore, all of that scales. And the demand is so infinite in terms of adding intelligence to everything that it'll be a long time before we run out of that.

45:35That's why I'm telling the world with data centers. so i i think there's some youtube viewers somewhere with a uh a drinking game or a bingo game for how many times we can say tile the earth with compute or disassemble the moon or whatever it is so so so drink your whatever or cross incredible game to this one i know that's another one so robots are part of the loop we're robots in the loop here we go This next article here I find really important. This is about visual chain of thought. And it's the notion that chain of visual thought methods are now able to give us a better understanding of images.

46:20And this visual thought delivers 3 % to 6 % in gains in continuous reasoning performance. the image here on this on this is asking question is the wall behind the bed empty or is there a painting hanging on the wall and what you see then is the analysis the ability for an AI to understand what it's seeing right at the same time that we're bringing about augmented reality glasses and we have humanoid robots coming in coming online is is going to be fundamental I want my AI and understand what I'm seeing. I want it to be able to remember during the course of the day where I left the keys or who I ran into or recognize a face and give me their name.

47:06How fast is this accelerating? I think this is, if I may, even more profound than just garden variety acceleration. If I ask all of you or I request, don't think about pink elephants. What's the first thing that happens? You start thinking about pink elephants, not in terms of text tokens in your mind. You're not probably thinking in terms of language. You're using your visual cortex probably to create a mental image of pink elephants. And the ability to visually reason is something we've talked about on the pod in the past. We're finally, a few weeks later, a few weeks after this was predicted to happen, we're starting to see major gains in reasoning performance by models that can include visual tokens in their chain of thought, not just text tokens.

47:53And we're going to see a lot more of this. You mind how excited about this are you? Yeah, I'm not surprised at all by this. It's very exciting. I think it's actually something fundamental to reality. Models are the things with the best math that approximates reality. And we've seen some interesting things before. Like originally we built stable diffusion. And then from stable diffusion we extended it to 3D using the same knowledge. We found out actually Harvard did a study that an image model understood 3D. then we extended that out to video and the same thing it's somewhere actually had a concept of physics in there and in fact if you look at the latest image model that's top of the charts now flux by the black forest lab team my former colleagues it started with a language model that then got a video model that then became the best image model in the world and you see now for example luma recently raised 900 million from humane and others to build world models where you input all this data, image, video, text, et cetera, because text is low dimensionality.

48:54If you actually want to understand and reason, you need to have all the different types of data, but the latent spaces are actually very, very similar to them all in terms of your understanding of the universe. So you can go from a text model to a video model, actually, just by adding the right types of data, but the underlying structure doesn't change, which I think has big implications for, again, the actual nature of reality itself, because each of those is modeling a different part of reality. Can you imagine going back to AlexNet when they were putting this together and showing them this capability?

49:29We're trying to recognize the number seven. That was a conversation we had yesterday. I mean, truly extraordinary. It is, and to experience it firsthand, take a screenshot of something you're doing on your computer, dump it right into Gemini and say, help, what's going on here? It's incredible that that works. It would have shocked anyone 10 years ago. Nobody would have believed you at all. And here it is. Go ahead, go ahead, Imad. Well, the crazy thing, I think it was always worth coming back to this, is that if you told someone 10, 20 years ago, they would have thought it'd be like this massive logic tree, right?

50:06We have to remember these models. Is it this or is it that, right? They're just ones and zeros. They're literally like a movie file. And you push words in or images in one side, and it squeezes out this stuff from the other side. The reasoning isn't actually reasoning at all in the way that we think about it. And again, I think that says something profound about the way our brains work and the universe works. The static group of ones and zeros can do that. I think what's important to realize here is where we're going. All of us are going to have an AI with visual capability always on helping you, supporting you, right?

50:44And I think that's a vision of the future. People say, well, I don't want to lose my privacy and so forth, but it's going to be watching what you eat. If you want to turn on health mode, it'll tell you, you know, eat more of that, don't eat that, or there's a staircase over there, go take the stairs instead of taking the elevator. I mean, the ability for an AI to be your always on, you know, visual Jarvis assistant is going to be profound throughout our lives, increasing our efficiency of what we do and what our objectives are. Yeah. Salim, do you want to add on that? Just to build on that point, Peter, I'm expecting in a year or 18 months, some sensor that's in your stomach saying, hey, you're about to eat that donut, wait 10 minutes because I'm still metabolizing the coffee, right?

51:27Okay. And creating radical efficiency and all these very little things that we never thought about much is going to be one of those areas that we're going to have a ton of compute against. So I took a screenshot of our podcast as we're speaking and gave it to Gemini just to prove the point. And I said, hey, are these guys having fun? And it completely interprets the scene. It knows exactly what we're talking about. And it says, yeah, it looks like it's fun if you're a tech enthusiast, you like futurism, or you enjoy brain food. It's probably not fun if you dislike technical jargon or you want casual entertainment.

52:00Okay, that's probably true. The point is it completely knows what we're doing from just that screenshot. And, you know, this is going two different directions, too. It's making the AI more in touch with humans and the way we live. But the data is not specific to that. It can also go the other direction where you feed in genetics data, you feed in satellite image data, and it can then get intuition in those domains where nobody that you know has intuition. So it's going in both directions at the same time. So if you kind of study what's going on with vision on this slide, you can develop some intuition about what it's very soon going to be capable of with medical imaging, with satellite imaging, with other types of sensors that we're not familiar with.

52:40I'm still reeling over last week's comment from Alex that we're taking brain scans and running them through AI. I mean, that's going to just generate some unreal insights. Imad has thrown some cycles at that previously. I know, Imad, I was catching up with some of your former colleagues from the MedArc days at Erips. fMRI wants to be its own modality it does indeed i think all the modalities again we just tell the world for some reason right all right we're going we're going back to when the stories we opened up with which is uh the response china is having or the leadership it's providing so china is accelerating its push to become independent of nvidia with uh cambra con planning to triple output to a half a million accelerators in 2026.

53:27So this is a response to US policy. It's always that way. As soon as we restrict a country from buying a product or service that we're providing, especially if it's fundamental to the lifeblood, they will develop competition. And without question, I think the competition will, you know, there's a huge amount of intelligence resident in China. Don't forget the Chinese sort of educational system excels at math and compute. So I would not expect that they would deliver anything sub-NVIDIA. Ima, do you want to kick us off here? Yeah, I think necessity is the mother of invention, right? We also saw more threads IPO this week in China.

54:16They raised just over a billion dollars. They're again another the competitor's GPU, it was 4 ,000 times oversubscribed. So$4 trillion of demand. Now, obviously, that's a bit much. But again, you're going to see more and more of this stuff ramping, particularly for the specific Chinese models. Because having an open source model that you can test as you're developing it really closes the feedback loop a lot more aggressively here. So you don't need just to build for one vendor. You can build for everyone. And most of the Chinese models are optimizing around this very sparse MOE type structure with deep seek and similar arches with Miu-Wan kind of acceleration.

54:54So you're getting towards one architecture that they can just engineer and output industrially. And who's the best industrial manufacturer? Yep. China has been. It's important to remember, NVIDIA used to supply 95 % of China's advanced AI chips. And when that supply got cut, there was a red alert going on in China. And I'm sure the government orchestrates and supports and says, OK, we need our own NVIDIA or multiple NVIDIA companies in China. Alex, your thoughts? Yeah, we don't have a slide for this, but I would definitely encourage the audience to read the national security strategy that was just released in the past 48 hours.

55:37It's most certainly eye-opening and I think spells out a pathway for tech decoupling between the U.S. AI tech stack and the Chinese tech stack. I'm reminded during the Cold War, the Soviet Union had what for those years would have amounted to an independent tech stack and was experimenting with all sorts of crazy architectures like ternary computing and other to westernize unconventional choices. I think we're going to see a Cambrian explosion, no pun intended, of architectures coming out of China now that China has been effectively decoupled from the U.S. tech stack. And maybe many of those innovations will end up one way or another benefiting the overall world, benefiting the U.S.

56:23tech stack. I think we'll see a lot more experimentation coming out of China post decoupling. So what's the implication of this? I'd like to spend an extra couple minutes on this because China is going to be going as rapidly as possible, developing its models, it's developed fully its energy ecosystem, you know, 10x further than the US has. we're going to talk a little bit about China's desire to put data centers in space. I mean, any thoughts on the long-term implications of this complete parallel development between the U.S. and China? I think we see an intelligence race and that will lead to diversity.

57:02We're going to see so many different architectures that are all competing in the U.S., in the West. We have a whole handful at this point of Frontier Labs that are all vertically integrating with their own chip architectures, many of them in partnership with Broadcom or other lower-level infra providers. Now we're starting to see the same happen in China. I think in the end, this heterogeneity that we're seeing in terms of tech stacks is only going to further accelerate the race that we're already in to the finish line. And again, I would pose the question, what is the finish line that we're racing toward?

57:35Because we're going to go much more quickly with this level of integration. So stepping up a level, is this good for humanity or not? I think all other things being equal, more experimentation can probably be better for humanity. Query whether it's good for the US or not. Query whether it's good for interoperability or not. But all other things being equal, more experimentation is probably better. Imad and Salim, I'd love to hear your thoughts here. I think the good news is that more technology development is generally better for the world. If I think about the counterposition between the U.S.

58:09and China, I think a lot of the future will depend on where you end up with trust. And the challenge with China is people don't trust it. Now, people are losing trust in the U.S. on a week-by-week basis. So there's that to be considered. But I think over time, the concept of do you trust Google or do you trust ChatGPT in terms of what the future of AI is going to be, a lot of it is going to come down to where do we place our trust. Really important. If you're an African nation over time, where will you put your trust, right? Salim, really important. I saw a tweet today to entrepreneurs saying, if you're building something that increases trust, double down.

58:53If you're not, then stop doing it. I think trust as a scarce asset is a really important thing to optimize. And I got a shout out to Jerry Mikulski here. He made that phenomenal comment that scarcity equals abundance minus trust. It's just like amazing. Yeah. Yeah. I think that you'll see just like China flooded Africa with smartphones, with TCL and others. You know, these chips will be very aggressively priced. So let's put Cambric on in context. They raised about$2 billion. Their market cap is$100 billion right now. And the 5090 is equivalent to an NVIDIA A100. The 6090 about an H100. But it's about half the cost.

59:37And it's much more power efficient as well. Does this hit NVIDIA's bottom line? Not for a while. For a while, they'll all be used locally. But as they ramp from 500 ,000 accelerators to 5 million, to more, and again, China has the full end-to-end supply chain as well, then you'll see it flooding in a few years' time. Again, this is in the acceleration phase here. To put the 500 ,000 in context, I think there were about 4 million hoppers sold and about 10 million blackwells coming. So in a few years, you can expect even just Cambricon, someone that no one's really heard about, they're already at 80 % of a generation back NVIDIA chips.

1:00:18In a few years, you'd probably expect them just like tesla and byd to actually be fully competitive and now you're seeing byd displacing tesla and over again yeah it also comes down to the engineering versus legalistic thing right the u.s is lawyers managing immigrant and engineers um and china is all engineers with kind of an authoritarian state and where will this play out this episode is brought to you by Blitzy, Autonomous Software Development with Infinite Code Context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise-scale code bases with millions of lines of code.

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1:01:49Iman, you're kind of in Europe, or you're in a previous European nation. And we've had this conversation on this pod over and over again about Europe has been in sort of an AI winter, or ice age as the case might be. So here we see EU to open bidding for an AI gigafactory in early 2026. Europe is finally making a serious move to close its compute gap with the US and China by greenlighting an AI gigafactory bidding in early 2026. Imad, what does this mean? I mean, every nation needs sovereign compute because their intelligence of their nation will be dependent on the number of GPUs, right? The EU with their regulatory acts has kind of held AI behind.

1:02:34but I mean recently we saw Jan Lecun is now hiring for teams in Paris you know we see teams in Germany we had the stable diffusion team there's a lot of talent there it's just they've got to cut the red tape and we're seeing I think a change in that and now the UK, Europe and others are like well this is the future we have to cut the red tape but the US is still far far ahead can they move fast enough I saw you know they're going to relax GDPR to give access to data finally I mean GDPR was just a chokehold on entrepreneurs. I mean, how are you feeling in the UK right now? So I think, again, you've seen a step change just in the last few months.

1:03:13And as the agents hit next year, proper agents, not these stochastic parity agents, everyone has to change. No country has an option but to change and to go all in on this. Because if you don't, then you're going to be left behind. You'll be outcompeted by your peers. Well, I'll tell you, just observing without judging, there's a square mile in Palo Alto, a square mile in San Francisco, and a square mile in Cambridge. And the gap between those three places on earth, Cambridge Mass, yeah. Yeah, not the original Cambridge. The gap between those three square miles and the rest of the world is getting wider and wider at an incredible rate.

1:03:56And I have always the same observations that Ahmad has. There's amazing talent all over Europe and all over the world. And shouldn't this proliferate out to all that talent? But when I observe, you know, Peter, that meeting we had with Richard Socher, I heard you go, holy shit, like 12 times during that meeting. Yeah, yeah. And there is nothing on the planet. And we'll talk about that soon. Not that we can say anything about it, but hey. We can't. We can't right now. But the gap between what's going on in those three square miles of the Earth and the rest of the world is mind-blowingly big and accelerating very, very quickly.

1:04:29So I think building data centers around Europe is way too little, way too late, unless it's done in combination with some other force that I don't know about yet. But just observing it, that gap is accelerating very quickly. Europe is best at public-private partnerships. The problem is that in this world, speed is the ultimate high-order bit, and speed is not the strength there. I mean, you and I have had these so many meetings throughout many of the European nations, Salim, and the energy isn't there, right? The drive, the absolute, you know, my favorite Joseph Campbell quote is, like a man whose hair is on fire seeks water, right?

1:05:16I mean, that's what we're seeing right now in the hyperscalers here. It's like, you know, this code red. It's like, you know, everybody jumping in. It's 24-7. It's not, what was it, it's not 996. It's, I don't know where it is. It's 6-12-7. It really is that way. That's just that. You know, I tried to make a point of this with Mustafa, you know, yesterday. And that'll be on our next podcast. You'll see it. But, you know, he just name-dropped. Well, you know, when I was talking to Sam the other day and then I saw Demas last night and then Sam and I were thinking about Dario, it's all first names.

1:05:54All of these are just first names to him. And so it's not corporate. It's not data center investments made by the government. It's this very small group of people that are on a first name basis that have now, no joke,$50 billion budgets to build this out. So that's what's really happening. We saw the same thing in the space industry, right? In the United States, we gave birth to Blue Origin and SpaceX and Virgin Galactic and a whole bunch of entrepreneurial space companies. And in Europe, it's the industrial military complex creating Ariane 5 and a few other smaller rockets. But they can't compete with the current entrepreneurial space industry.

1:06:41The only way to compete is because the government buys local. And that simply makes the entire space-based services that are launched out of Europe more expensive. It just can't be supported. Well, and it's changing so quickly. You know, it has to be on a first name, informal basis at the rate of change. You know, in Massachusetts, this will drive Alex crazy. But in Massachusetts, you know, we have a very good relationship with our amazing governor. And she said, you know what I need to do? Put together an AI task force. and so the timeline on that kind of action is is like three orders of magnitude slower than the evolution of so in europe in europe they would say sometime in q3 of 2026 we'll start the discussion to create that task force actually there's a very interesting thing there's an initiative called next frontier.ai to build frontier ai labs and again it's well-intentioned It's like they'll give 12 teams 25 million euros over the next two years to see if they can accelerate up and get there.

1:07:4225 million euros per second? Yeah. Can I double down on this just for a second? We are working with one of the biggest companies in Europe. I have to apologize to our European listeners. We don't want to make fun of the situation there. It's serious. Just spend two years in the middle of it and then go back home. That's the way to solve the problem. Look, I spent all the 90s living all across Europe, right, in like five different countries. So I've got some kind of personal thing here. In terms of the ability to live and have a great life, Europe is amazing. But in terms of technological progress, it's not really the place to be.

1:08:23You have to move to the West Coast and others. We are working with one of the biggest European companies. It's one of the biggest global companies on transforming their metabolism. And we finished one of our major sprints with them. And they said, well, we need to start another one right away. And this was back in February. And they said, let's have the first meeting about it in October. And this is the problem. The people aren't seeing that the metabolism of everything that is happening needs to accelerate by 100 times across Europe for them to jump. And it's culturally blocked. You know, there's an old adage in Europe, you work to live.

1:09:03In the US, you live to work. Yeah. Yeah. Which may not be the very best thing for your health. Now we're going to live to compute. Yes. All right. Let's jump into jobs and economy. A few interesting articles this week. The first one is Michael Dell's$6.25 billion investment in America's kids. So it's called Invest America and it will give every child born after January 1st of 2025 an investment account of$1 ,000. It will be deposited to build financial security. Let's take a listen to Michael and Susan Dell describe what they're doing. We're making a$6.25 billion investment in America's kids through our charitable funds.

1:09:47Next year, every American child will be able to get an investment account powered by Invest America. We've seen what happens when a child gets even a small financial head start. Their world expands. The real power of these accounts is that anyone can contribute. Parents, relatives, friends, everyone can help shape a child's future. To philanthropists, companies, community leaders, if you want to be part of something truly meaningful for our kids, for our communities, for our country, join us. So I, you know, celebrate them for that effort. There's been a number of players who have talked about similar situation.

1:10:28Of course, being able to invest versus just save is a part of what's made America great. Now the question becomes, is this too little too late? Right? Or we're just flat out irrelevant, given that all education is moving to AI. You know this better than anyone, Peter. I mean, one of the questions became, you know, maybe what's going to happen is every single kid will have an AI agent that is out there generating revenue for them. All right. This was a, where was the conversation we had about this? No, it was, it was the conversation that Ilya had on his recent pod saying, you know, one of the problems is if you've got an AI agent that's doing all this work for you, generating revenue, supporting you, representing you.

1:11:14the question is does the human fall out of the loop and becomes irrelevant and is it important instead then to ultimately merge with ai but that's a different conversation i thought it's a different conversation but i think i think i'm 100 sure of this topic you know teaching at mit harvard and a little bit at stanford uh there was a huge push to move all educational materials online when the internet exploded and it kind of worked and kind of didn't work you know It made all the material available. I mean, surprising. Surprising, I'm 100 % sure that now that there's an AI face and voice that matches your personality on top of that, that it's going to absolutely take off.

1:11:52Sure. And traditional education will be completely irrelevant imminently because it can match your, it matches your accent, your favorite voice, your favorite star, your self-image. Well, I think this is more than just for education, right? I think this is more about how do you provide a financial stability? We've talked about this in the pod before that, you know, this was a few episodes ago on the data from FI9 that the majority of the world is absolutely concerned about not being able to be employed and the cost of living. And if you have a, you know, a seed kernel of capital when you're born that is growing by the time you're 18, does that give you some additional stability?

1:12:36Salim, you were going to say? I have two thoughts about this. One is I really, really love the fact that it has every child born and it's kind of essentially universal. It's creating a wealth floor for every kid, which means every kid from day one will be thinking about how investment and how do I think about it, et cetera. I didn't come across the concept of investment until I was like 16 or 17. If I'd had that way earlier, I'd be a way richer person today than anything else. And I think that by adding the employer add-ons and encouraging people to contribute, you're creating a community effort here.

1:13:08So I think that it may be late to be doing this, but at least it's being done. And I got to applaud them completely for doing it. Well, I think also it's just money. So it'll be pivoted over to access to compute and say, look, education. Oh, it doesn't have to be tuition. You can also get, you know, your GPUs. Yeah. Ultimately, that's the currency that matters. Ultimately, it's just hard for folks to. acknowledge that and understand it. Imad? Well, yeah. I mean, it used to be that capital is what compounded, right? You give people money earlier, that$1 ,000 has become$20 ,000. Now it's computing cognition that compounds as you move to self-learning systems.

1:13:45Your capital almost becomes irrelevant as the compute can get capital quicker than anyone. It's all about, again, how do you build that whole cognition architecture around you? So I think this is great. And then the other thing is we've got to give people access to frontier compute as young as possible as well in a way that makes them able to compound the benefits from that i would just add this to my eye looks like the beginning of universal basic equity we've spoken on the pod about ubi ube ubs this looks like universal basic equity where every person in the economy will have an equity stake in the economy and if we do see hyper growth, macro hyper growth over the next few years than$1 ,000 in a 530A account, which is, again, what this Invest America, thank you, Brad Gerstner, for helping to conceive this idea.

1:14:39What$1 ,000 in an account now in a 530A account, a few years from now, if we experience hyper, hyper growth, could be quite material to a person's living circumstances. Yeah. And Brad's brilliant. And he's agreed to come on the pod and talk about his moonshot. So we'll make that happen probably in early 2026. Along these lines, our next story here, college students flock to a new major, AI. Okay. Not very new for us, but AI majors are exploding with popularity with schools like MIT and UC San Diego and launching AI branded degrees. So Dave, I'm going to go to you first. Everything is AI at MIT these days, right?

1:15:16It sure is. Yeah. So this is at MIT lingo. This is course six, four, which was only added just a minute ago, basically. And it's already almost caught up to 6.3, which is core computer science in terms of people who are majoring in it. And I'll tell you, when you talk to the students, they say the curriculum sucks. There are two or three great classes. Well, because you're trying to build an entire major and there's only two or three classes so far. You know, it takes the school too long to build, you know, the material because they're used to this much slower timescale. So I'm sure it'll fill in because the demand is so high.

1:15:49But as of right now, there's just a couple of classes and then a whole bunch of garbage, which is frustrating the heck out of the students, by the way. Everybody wants to move to this, and for good reason. No matter what you're trying to achieve in life, whether it's biotechnology or space travel or whatever, the way to achieve it is via AI. So if you get a good grounding in AI, you're actually then empowered to do virtually anything. So it's the perfect thing to study anyway, especially when you're young and you have time on your hands and you can really grind through these complexities. So I'm really glad this is happening.

1:16:21I just want the curriculum to move much faster to catch up. The interesting note here to add is that AI-related job postings in the U.S. was up 50 % year over year from 2024. So continue that. That's going to continue. Any other thoughts on this one? I mean, it feels kind of obvious. And I think the biggest challenge I've got is it shouldn't just be in college. I mean, we should be seeing this in high school as well. We're going to see a lot of people that are going to skip college, I think. That's a debate that we've had. So if we can get you started in high school to think about AI, think about the world you're going to be inhabiting and inheriting, and how do you use this technology to create your vision and your passion?

1:17:05Emad? Well, I'll tell you, if there's one actionable thing to talking to every school administrator, every high school principal, every college administrator, approve the applications. When the students say, I want to study this on my own. I don't want to study that. Just say yes. Just approve it. Let them carry themselves forward. Don't hold them back. Intrinsic motivation. Unleash them. My favorite Joseph Campbell quote is, follow your bliss. Let them follow their bliss. Yeah, that's a good one too. I think it's fascinating because the fundamentals of AI are not actually that hard. It's not easy math, but it's not that hard mathematics.

1:17:47My take is if you have a semi-vocational course where you do fast.ai, which is a fantastic intro into the math and the basics for programmers, Andre Carpathy's video series on YouTube, and then you just vibe code and build, and the entire class implements some latest research every month, that will put you way ahead of everyone. And I think that CVs and qualifications move to show me what you have built and done with AI. Yeah, so if you're listening to what Ahmad just said and you're a student, take exactly what he said. Take the Carpathie material. Carpathie is the one guy from that OpenAI original crew who is not a self-made billionaire because he's building education for the world right now.

1:18:34He's given up. He could be a billionaire tomorrow if he just signed some documents. He probably is anyway, actually, from his OpenAI stock. But putting that aside, he's building out the best educational platform you could ever imagine. Just go find him online. Then tell your high school teacher or your college professor, I want to study this instead. Can you allow me to do that in replacement for this class I would have taken? Brilliant. That's the solution. But what you just said is antithetical to the concept of a university structure. Or a high school program. Yeah. I think just quickly, I think that if you implement the stuff together and discuss it, and again, that fits with it, it's way better than doing it by yourself.

1:19:18For sure. But I'm just saying you have to literally hijack a high school curriculum or university curriculum to do that because it's not going to offer today. To Dave's point earlier, Peter, literally my wife has been pressured by all the local parents to have a day of just AI mind shift for all the teenagers. So we're going to do that and pilot that out and see how it goes. I heard that you've stolen Max Song, my Strikeforce member, to join me. Yeah. I should also point out, Peter, I mean, just want to look at this for a minute from the perspective of economics. Right now, AI engineers are complementary good or complementary service to AI compute.

1:19:57The cost of intelligence is going to zero. And so right now, pursuing careers and majors in AI, highly complementary. But recursive self-improvement is also potentially imminent. And to the extent that recursive self-improvement gives us soon AI engineers, we might start to see AI itself become a substitute for AI engineering labor, in which case maybe this rush to major in AI at MIT and UCSD maybe reverse itself, unwind itself, and everyone goes back to majoring in the humanities like they used to. And we had the conversation in the past about, you know, should you learn to code? And there comes vibe coding.

1:20:37One of the conversations we had yesterday up in Redmond, we'll hear about it later this week was the importance of studying philosophy. All right, let's talk about the next job boom, which are in data centers where the gold rush is for construction workers. So AI data center construction boom is making welders, electricians, and supervisors earn between$100 ,000 and$225 ,000. And these AI companies need that kind of labor. There's a national shortage of 450 ,000 skilled trade workers. And it's significant. This is a alternate career path where you don't come out with hundreds of thousand dollars in debt.

1:21:23You come out with the ability to earn immediately. How long will this opportunity last before Optimus 4 or 5 or figure 6 comes in and does this work for us? I don't know. Maybe it's five years, 10 years, something in that realm. Thoughts? Agreed. I think that is the multi-trillion dollar elephant in the room. As with college majors flocking to AI in this case, right now, if you can pursue a career in the so-called skilled trades to facilitate tiling the earth with compute, drink your whatever again, I think that That's potentially a very promising local strategy. But, of course, five to ten years out, and I agree, Peter, with your timelines, we're going to see humanoid robot substitution effects.

1:22:17All right, let's jump in. Yeah, go ahead. The economics and dynamics of AI data centers are really similar to fracking, actually, when you think about it. Even the financial structures and these booms in these industrial kind of areas. So I think it'll last longer, but let's see. I find this next article. So Amazon Eye is expanding its network after talks with USPS Stahl. So you may not know this, but the U.S. Post Office is one of Amazon's main delivery carriers. So the U.S. Post Office is delivering Amazon packages last miles in rural areas. It's been a significant, about a$6 billion per year contract between the two.

1:23:00And that contract is breaking down. Um, my prediction is the U.S. post office will be put out of its own misery and Amazon will get a contract from the government. Today, the U.S. post office has about an 80 billion per year operating budget and it's losing seven to ten billion dollars per year annually. Um, thoughts, comments, gents. What happens when we have last mile robotic delivery services? I think we have to prepare for that imminent future here. And that is probably best done by the private sector. Drones. You know, we saw an article probably about a month ago that Amazon is giving its drivers now augmented reality glasses, right?

1:23:46And it's saying to the drivers, okay, wear these glasses. We'll warn you about if there's a dog in that apartment building or that house, they will show you where to drop the package and so forth. And I think what's really going on here is that Amazon is collecting all of the last mile or the last hundred meter data and being able to train its future robots, right? Autonomous trucks, autonomous robots doing that last hundred, I keep wanting to say hundred feet. I hate the fact that we use feet and pounds in the United States. It really drives me up the wall. And it drives me up the wall that science fiction writers are using that as well.

1:24:23Damn it. We need to switch over to metric back in the 60s. Pain in the ass. Anyway, yeah, this is going to be an interesting battle. What's your under over and how long the post office lasts? Anybody? This is an interesting bellwether because it should have been privatized probably 30, 40 years ago. Everybody knows that, but it's written in the Constitution. And, you know, nobody wants to mess with the Constitution. But it's so obvious. Like space travel is getting or space launches are getting privatized. It's not in the Constitution because space didn't exist when the Constitution was written.

1:24:57So it can just move over to SpaceX and Blue Origin. By the way, look at the FedEx line, right? I mean, FedEx had such an amazing lead. Fred Smith was such an extraordinary entrepreneur. And it's been just slowly on a decline. All right. My guess is U.S. post office has at max five years left. I don't know if anybody wants to go. Yeah, that's how it would have got about the same. Yeah. It'll take an act of Congress. Yeah. And two third ratification of the states. It's a structure. Like this is a good case study. It's not that big a deal, but it's a great chance to learn. Like, what are we going to do that's blatantly stupid because of legacy structure?

1:25:37And how is that going to get fixed? So, yeah. All right. Let's move on to space. A fun subject. There are four space stations under development in the U.S. today. VAST, which is being launched by SpaceX, Axiom Space, Starlab, and Blue Origin Orbital Leaf. Just throwing this out because it shows finally we're going from government to truly commercial inhabitation. Alex, do you want to add anything here? Yeah, it's not a coincidence that there are four separate private space stations that are about to launch. These are actually all causally related to a NASA program. When we speak of privatizing the government, NASA in 2021 started the commercial LEO, low Earth orbit destinations program with ultimately one and a half billion dollars in funding.

1:26:31And the SpaceX surge to space that we saw was in part the result of another analogous NASA program to try to commercialize space launch capabilities. Yeah, the Commercial Crew Program. That's correct. In fact, the Commercial Crew Program was what saved SpaceX, right? SpaceX had three launch failures of their Falcon 1. They got the fourth one finally to orbit after Elon literally borrowed money to be able to put that together. And in Christmas, was it 2008, he won a billion-dollar-plus contract from NASA to go forward with Falcon 9, which is today the most successful launch vehicle on the planet by, like, an order of magnitude.

1:27:15That's right. So the commercial LEO destinations program was spun up in part because the International Space Station is going to need to be deorbited sometime soon. And there was a desire for private U.S. space presence to succeed the ISS. So I'm very optimistic about all of these and other private space stations. I think we're going to see an exponential rise of humans in low Earth orbit. You know what I'm excited about as well, Alex? Jared Isaacman. I cannot wait. So Jared Isaacman is back on the docket to be our NASA administrator. I'm not sure when the congressional hearings finalized. Do you know?

1:27:51Several days ago. Oh, is he in finally? Well, there has to be a vote. but the hearing was several days ago. Okay. So I've been texting with Jared, and he's agreed to come on the pod as soon as the confirmation is done. So excited about that. He is brilliant. Absolutely brilliant. I've known him for a long time. I took him to Russia to watch the Soyuz flights from some of our commercial launches there. All right, continuing on. Wait, I have a quick comment. Yeah. This space station thing reminds me of a date put out by, I remember one of our NASA astronauts telling us the most interesting date in the world for him was October 31st, 2000.

1:28:32And it was on that date that the first human being lifted off of the International Space Station. And since that date, we've always had at least one human being off planet. And so the first molecules are kind of drifting off this thing. So this next article is a bit of a surprise that SpaceX is considering a 2026 IPO. I mean, I've had this conversation with Elon. He was always resistant to take SpaceX public for a number of reasons. When you're a public company, you have to disclose all the details. He doesn't want to disclose all of his details and how he operates to his competition. But the other thing in particular was, you know, if you're a public company and you're spending a whole bunch of money to build Mars vehicles to go and colonize the Martian surface, is that something which your shareholders are going to support?

1:29:24Um, so, uh, uh, listen, I'm a SpaceX investor. I've held it from the very beginning. I, I would love to see it public. I always thought that what Elon was going to do was spin out Starlink and take that public and keep the launch capability. That was the conventional wisdom. Yeah. I do think. Okay. The amount, sorry. Yeah. No, I mean like Elon's a smart guy and he's got a million GPUs. and so they'll have more AI lawyers than anyone to attack the stupid people that come after them. But I mean, serious, this is like SpaceX, XAI, Tesla, all will basically have full AI teams top to bottom. Like you can criticize their strategy.

1:30:07The AI will just clap back at you. You can sue them for the silly stuff and the AI will just clap back. It's a big difference in the way that you can actually run public companies. Yeah, you take SpaceX public and you take X public and Elon leaps over the trillion-dollar mark in terms of personal net worth. Okay. Also, maybe just to comment quickly, I'm also not sure the historic story that Starlink would spin out and do its own IPO. I think with the rise of orbital data centers, I think that muddies the water somewhat in terms of Starlink as pure communication service versus Starlink as a predecessor to orbital data centers and putting compute up there.

1:30:46Good point. And not just comms capabilities. So in that sense, I think I could imagine a scenario where orbital data centers are actually pulling all of SpaceX to go public, not just spin off Starlink. Yeah. And that's a relatively new part of the conversation. That's right. It's very recent. I love this competition. You know, it's fun. My mission has always been to open up space. And I, you know, built so many companies on the space theme. and it does the nine-year-old in me so, so proud and gives me such contentment that two of the wealthiest humans on the planet are battling it out to open the space frontier.

1:31:25So Blue Origin plans to start flying cargo to the moon in early 2026 using its Glenn Heavy Lift rocket, which by the way, recently did a launch and full recovery of its first stage and it's backed by a multi-billion dollar NASA contract for targeted human landings in 2028. The government has always wanted dual suppliers. So for most of the America spaceflight industry for the 70s, 80s, 90s, it was Boeing and Lockheed Martin competing for this. Here comes SpaceX, which becomes the dominant player. and now the government wants a number two and it looks like it's going to be Blue Origin, which is super exciting.

1:32:13Alex, thoughts on this? This was basically the plot of season three of the television show For All Mankind. I love that show. It's a wonderful, wonderful show. The three-way race, in the case of season three, it was a three-way race to Mars. In this case, it's a three-way race between SpaceX, Blue Origin, and China to land humans again on the surface of Mars by 2028 or earlier. And I think this resumption of a space race, which was dormant for 50 plus years and maybe also had collateral downsides for the rest of the economy in terms of overall innovation, it's coming back to life. We're back in the space race again.

1:32:51And one might hope we'll see a lot of growth and innovation come out of it. So the nine-year-old in me is so happy. Just to put some numbers and size against it. So NASA's 2025 Artemis budget. Artemis is their lunar program. Their human lunar program is$7.8 billion. Let's look at that compared to the Apollo program. So in 1966, NASA's budget was about, well, actually, the Apollo budget was about$3 billion of NASA's 5.9 budget. So Apollo was half of NASA's budget. And if you adjusted the Apollo budget to today's dollars, it would be about 35 to$40 billion. So compare that to the 7.8 billion that we're spending in Artemis.

1:33:40We were spending about a half a percent of the US GDP on the Apollo program back in the 60s. Pretty impressive. And the reason we don't have to do that anymore, of course, is commercialization and technology. We brought the price down, orders of magnitude. I find this article hilarious. Sam Altman enters rocket business to compete with Elon and SpaceX. What's fascinating is Elon goes for BCI and Sam goes for BCI. Elon goes for space and Sam goes for space. There's probably a few other areas. Any particular thoughts on this one, gentlemen? Well, I'm really curious to see how the code red interacts with, Sam has cut a deal in every single dimension related to AI, including Johnny Ive with the wearable device and Stargate with the data center and Broadcom with the chips, the TB.

1:34:33So he's cast it out in every direction. But I think that's Sam personally versus open AI, right? It's a mix. It's a mix. The bigger deals are open AI and then there's about 300, 400 personal deals that are all the use cases and components. But it's a massive metric in this Samoverse, a massive network of connected parts. But now you've got this code red where, hey, wait, the thing that matters at the middle of it is these AI benchmarks. And we're now off the chart on Polymarket. Code red, code red. So I'd be very curious to see what that means. Because, you know, he has a lot of talent, but there's still a limited supply.

1:35:13It's not infinite. And so if that all gets drawn back into the middle, that's going to cut some of the things on the edges. To give some more detail here, the company he's in discussions with is a company called Stoke Space. And it's founded by two former Blue Origin propulsion engineers. It's, as with every launch company, needs to be fully reusable. It's a two-stage, fully reusable rocket. It's never flown, right? They're using something called a ring-shaped aerospike engine, which also has never flown. So it's a little bit of a risky bet. But if Sam wants to enter the orbital data capabilities, I think having space launch capability.

1:35:57And of course, let's not forget Eric Schmidt is also in the rocket business. Yeah, I think this vertical integration by hyperscalers into space is probably an inevitability at this point where we're certainly not going to get our Dyson Swarms drink without that. But I also think, you know, imagine near-term future, are we going to get a meta space station? Are we going to get an anthropic space station? Maybe clusters in space for variables. Fascinating. Just like we're getting hyperscaler fusion plants. That's right. Yeah. Facebook Space Station. Oh, no. I'm not going there. You've got to be full stack to control the likelihood of humanity, eh?

1:36:43Exactly. Love that. At least it's a better place to put a name than a sports stadium. Maybe Instagram Space Station. I'm not sure. Oh, God. You guys can be grovers here. All right. Orbital compute energy will be cheaper than on Earth by 2030. So again, I still find this kind of challenging just because we have so much solar flux on the Earth and don't have to worry about launch. But if we can really get the cost of launch down$100 per kilogram, which is the projection with Starship versus$500 to$1 ,000 per kilogram, perhaps. Who wants to jump in on this one? I'll just comment it could also be even cheaper than this once we get compact fusion online a lot of these orbital compute projections are assuming that solar is the primary power source for orbital compute doesn't have to be what once compact fusion is cheap enough and there's no reason to expect it won't be we can tile low earth orbit at minimum with compute as well and it won't require all of these expensive solar panels so we're going to throw fusion reactors into orbit yes Wait, so the theory there is launching a fusion reactor is cheaper than just a solar panel?

1:37:57The solar panel in space is about 10 times more effective than it is here on Earth. But it's still cheaper to launch a fusion reactor? It's maintenance. I just won the bingo game. We said launching a fusion space reactor. So Liam wins. No, so I mean, solar in space is still fusion-based. It's just using the fusion reactor at the center of our solar system. And so I think the question is, where do we want fusion power to be located for space-based compute? And as fusion reactors, there have been a number of deep space probes that NASA and other organizations have launched that are using fission, for example, ion-based propulsion.

1:38:39It's not like nuclear energy is that foreign for space. Fission thermal has been used by deep space probes for decades. It's not like we don't know how to do it. What's going to be new is compact fusion in particular. We've put fission-based energy in space for decades. You know, Alex, I'm looking at the numbers here and it says current terrestrial average is$12 per watt. And we're talking about$6 to$9 per watt in space. That's not enough of a difference for the level of complexity. Yeah, you're going to need at least a 10x drop in that. Yeah, so maybe it is compact fusion. I think if we're actually mining the moon, lest I say disassembling the moon to build, you know, the beginnings of the ice.

1:39:27Salim already won the drinking game. Yeah, well, hey, maybe that occurs. But, you know, I love the fact that it's now orbital data centers that are driving humanity's expansion to space. That's amazing. would have never thought it. It was going to have to be something. I mean, if you look at all the sci-fi plots, it was either going to be the discovery, again, for all mankind, without spoiling too much, it was either going to be ice on the moon or the discovery of microbial life on Mars or something like that that had to motivate space exploration and development. Who knew that it was going to be data centers?

1:40:07Well, it had to be something. It had to be. I remember when I was in college, I was at MIT and I was running SEDS and I put together this brochure on why open the space frontier. And I used to have to rationalize like better materials there. And I mean, there's like always this like very soft rationalization. But this is real industry, real base. People were trying to like, what can we manufacture in space that has value here on Earth? Guess what? Peter, this is the moment. This is the moment you've been waiting for since you were an undergrad. I mean, you should be like a kid in a candy store on this.

1:40:41But it totally makes sense. And it always drove me nuts when, And, you know, like Roman Cepeda, when he graduated, our buddy, he went to Ford and he was working on wire harnesses and rearview mirror motors for Ford. And I'm like, why do we need like another electric component in a Ford? Why don't you work on space or something foundational that changes humanity? And it's like, well, because, you know, it's kind of like your iPhone now. A new feature for this massive installed base is economically incredibly valuable, even though it's marginal for society. So it sucks up way too much great talent.

1:41:16And something really important like space data centers doesn't get worked on. But you need an economic crack that starts the whole process. And this is it. We finally have it. And it is so much better of a storyline than for all mankind. Actually, it's a lot later in that history. I'm still betting on asteroid mining. I mean, everything we hold of value on Earth, metals, minerals, energy, real estates, and infinite quantities in space. So, you know, those nickel iron asteroids that are worth trillions of dollars in platinum group metal or those carbonaceous chondrites we're going to mine for oxygen and hydrogen for fuel.

1:41:54Can I burst your bubble there, Peter? Oh, don't do it. I think AI transformation of material science will ride around all the scarcities around that. I don't know. Or maybe it'll accelerate it. But I don't know, Peter, when you were founding SEDS, did you, I'm guessing, not foresee the plot twist that the killer app for space would actually be like getting enough compute available to do generative cat videos doing funny things? That I was not able to project that far ahead, to be honest. So who knows what the asteroid belt will actually end up being used for? So, you know, lest we... We'll assemble it for compute, obviously.

1:42:33Lest we leave the Chinese out of this, China, a company called Cosmospace, is planning to build and add AI data centers in space. They're putting up a supercomputing cluster with three modules. One's got 100 megawatt level energy. The other is 10 terabits per second comms. And the third is 10 X operations per second, 10 exaflops, 10 to the 18th level compute module. So, Alex, what do you think about this? I think we're seeing a race to build Dyson swarms. It's as simple as that. It's not just a race to the moon. It's not just a race to tile the Earth. It is a race to put as much AI accelerated compute into low Earth orbit as possible.

1:43:19And Como Space emerged from nowhere. I had never heard from them several months or heard of them several months ago. And I don't think an obscure or otherwise obscure Chinese provider is going to be the last story we hear for Chinese orbital AI compute. We're going to see probably a dozen different vendors from China. We'll see, as just discussed, a dozen hyperscalers in the West. And the concern maybe becomes like overpopulation on Mars, making sure that all of these Dyson swarms remain interoperable. Can we just point out to all of our listeners, if you've been following us on Moonshots, this conversation of orbital data centers did not exist four months ago in any way, shape or form.

1:44:04It was there. I'm sure people were speaking about it. But it's now become a weekly conversation over the last three months. It literally came onto the scene with a vengeance. It's extraordinary. And technology clearly works. It's proven technology now. So it's just a question of launch costs. That's the only missing link, you know, and it looks promising. They figured out the dissipation side of things? I think that was still outstanding. Yeah. No, no, they got it. I mean, I'm shocked. There is still an issue of how you can get efficient energy dissipation on the back end. In fact, that was a subject.

1:44:40It was proposed as an XPRIZE this year at Visioneering. So they'll figure it out. It'll make more sense. But the thing that always gets me with this is it's horribly insecure. Like you had the proposal by Eric Schmidt and others, like how much of things go against data centers. Space data centers think they'll go up and they'll just start disappearing, honestly. Yeah, I'll give you the counterargument. And I totally agree, by the way, so I don't want to. But just to give you the counterargument, the hardware depreciates in three years anyway. So you only need it to be secure for three years. So I think the counterargument is that the U.S.

1:45:16Space Force will basically guarantee enough safety that you can get three years of hard work out of it before something bad happens. And that's all you need to pay it off. So what about solar flares? One of our subscribers asked that question. What happens when you have solar flares hitting these? And what happens when there's an EMP that hits them as well? All of this gets knocked out. Actually, I've got a very interesting thing. So we were training on thousands of A100s a few years back, and we kept getting errors exactly at the time of solar activity because it was basically messing with the EMCC memory.

1:45:54Wow. Yeah. We'll find out how these things sustain in the vacuum. You know this better than anyone, Imad, but a little inside scoop on the million compute clusters that are being built now. They have errors here on Earth, too. And you have to solve that problem in order to have coherent training anyway. So the error rate goes up a lot in space, but you have to have a process for backing off. And you can't, you know, right now everybody does checkpoints and rollbacks, but you can't, you know, invest, you know, an hour of a million GPUs at millions and millions of dollars and say, oh, wait, we have an error.

1:46:28We're going to roll back all of those GPUs for an hour. So you have to do it, you know, unit by unit. And so that work is well underway. So presumably that'll work fine in space, too. And you can tolerate the error rate. All right. The other comment, of course, is that those models just want to learn. So for AI compute workloads, to the extent we're doing training or inference, they can be structured to be fault tolerant. Yeah, Microsoft was actually the leader in that. And now Google's the leader in that. It's just seamless the way that it flips. It'll be interesting once we get out of space.

1:46:57Our last topic here, we're going to dive into robotics just for a few stories. Here we are. After an AI push, the Trump administration is now looking to robots. So robotic are the focus for a 2026 executive order to accelerate U.S. robotic development. We're seeing this in China, right? China is crowning its winners. It's got huge investments into the robotic industry. In fact, in our last pod, we talked about the fact that there is a, at least what the The Chinese are calling a robot, what do you call it, a robotic bubble going on today with over 150 Chinese robot companies. I find this one fascinating.

1:47:46After the acceleration, so major national robot strategies are coming online. Robotic firms are likely to have tax credits, subsidies, protection against trade measures. There's something along the CHIPS Act once again. Thoughts, gentlemen? I'll comment that the zeitgeist at NeurIPS this year was that humanoid robotics is the next big thing for AI after agents. I think this is how reindustrialization of the U.S. and the West happens. I think this is probably the best path for radically increasing economic growth and automating the two-thirds of the services sector that relies on physical intervention.

1:48:26that this is instrumentally convergent for the future that we want. Yeah. Just to remind folks from our last pod, we talked about the fact that China installed 54 % of the world's total robots last year. So again, massive, massive push. I want to show a couple of quick videos here just for fun to close us out. we saw in the last week a little bit of optimist versus figure competition. Elon posted this image of optimist walking. Let's take a look. Here it comes running along, jogging. And then we had Brett posting this one of figure running across. I have to say they look pretty natural compared to where they were six months ago.

1:49:22Which one did you like better? Let me play this again. Here comes Optimus. Optimus coming along. I don't know. It kind of looks like Figures doing a better job running than me. What do you guys think? I think they're both incredible. And I'd also throw out maybe a request to the audience for the show. If you're interested in supporting robot athletics in the United States, either as a host or as a vendor or in some other capacity, please reach out to me. I'd like to do what I can to ensure U.S. dominance and Western dominance in general with humanoid robots via robot athletics. Yeah, well, let's take a look at Chinese dominance with this video.

1:50:00Then we can talk about it. So we saw last week the T-800 humanoid robot from Engine AI in China. This is 5 foot 8 inches tall. Incredible capabilities. they put out a new video that i wanted us to take a look at here uh because it's a little bit shocking all right this is we are 100 sure this is real by the way uh yeah this is this is they claim it's real and this is a follow-on um uh but uh so here we are with this t-800 robot basically kickboxing, but check this out when it goes up against a human opponent.

1:50:48Like, wow.

1:50:52Kind of scary. I'll go back to my standard comment that having a robot doing kickboxing is not a great marketing message. Yeah. I think calling it a T-800 is also not a great marketing message. what about all the skulls that they put in there on their can i do a little headline yeah we love your rant salim go for it a human being has evolved for four billion years which is an optimized strategy well 200 200 000 years as a human being whatever for survival we we have the human structure for to survive and being able to quickly pick fruits off trees we have opposable thumbs and whatever. I mean, a wheel is so much more energy efficient than walking.

1:51:34It's ridiculous. I think, for God's sakes, at least put those little wheels in the bottom of the robot like the kids with the wheels in their sneakers so they can be more efficient as battery power seems to be a huge limiting factor in this. So why don't we have a wheel along with the legs so they can do both when it's needed? This having robots copy human beings seems to be the stupidest thing in the world. It feels to me like when we first had tv we're doing radio announcers and we're doing a television reading the same scripts we're going to be doing a podcast we're going to be doing a podcast from figures headquarters uh in palo alto in january you're not invited yeah i don't know i think this is really interesting you guys kickbox the robot this is really interesting so the entire chest cavity of the robot's actually a battery here um but this is really interesting because the 450 max joint torque that's the really interesting part basically this thing can punch harder than a gorilla like four times mike tyson do you really want those to be walking around in the streets like are they going to have to do regulations on the max joint torque also if you actually look at the full video which is real they even show a behind the scenes one and you look at the previous video so there's something called sim to real which can basically model human actions in a robot So we have full, almost real steel, the movie with Hugh Jackman, teleoperation capabilities now in robots, and soon it'll be policy learning.

1:53:02Like, this robot can do freaking kung fu. UFC is coming. UFC is coming. We're going to see Tesla bot, you know, basically Optimus versus T-800. I mean, it's going to be Olympic level sports. It's going to be amazing. Olympics versus robot UFC. I think that'll be exciting. But we have to actually ask, do we actually want to have regulations around the max joint talk of humanoids in the street? Because I'm fine with these being in the fighting arena. I think it's fantastic for an industry. But I don't really feel comfortable with them walking around. Yeah. The challenge comes. No, no, the kitchen.

1:53:38They're going to be in the kitchen. The challenge comes when they enter warfare, right? I mean, this is Terminator in sort of the pure sense of robots on the battlefield. and it's a scary direction for us to take humanity. Yeah, I think it's all of the above. It'll be warfare, it'll be in the kitchen, it'll be on the street and you'll see, I think, governance and governments at different levels, whether it's municipal or national or international regulations for the parameters of what the rules of engagement are making an omelet versus fighting a war. All right. I want to just do a thanks to CJ Trueheart, who gave us our first song on the Moonshot Mates.

1:54:24This is an outro piece called The Exponential. But before I play our outro piece, gentlemen, it's been a blast to spend time with you guys again. I love this. Imad, it was wonderful to have you as a fifth here today. Grateful for you. What's your week ahead look like, Iman? Lots of policy work and more agent stuff. We've got lots of releases coming. Exciting times. And how was Japan? You were there for FII Japan? Fantastic. Huge amounts of corporate and government interest in using AI to help accelerate the way forward. And so again, hopefully some announcements about that soon. yeah and uh and dave and and awg you're about to hop your flights back to boston i gather i think collectively we covered 12 countries in the last week and a half in this group so it'll be nice to be home for at least a week nice and uh and same for you celine chance to stay home yes i'm here for a bit i just got back so i'm gonna be i'm preparing for the big uh online meaning of life session where people are interested come armed with any question you have about life and Any question.

1:55:36Any question. When is it, Salim? It's December 17th, 11 a.m. Eastern. We'll go for several hours on metaphysics, philosophy, and the moon. Yeah, and when Salim says go for several hours, like six to eight hours, get prepared. Well, it's a big topic. It is for sure. This is an example. We start off on a conversation of what is truth and have it broken down to a two-by-two framework that just is sense-making. It allows us to have a decent conversation. What do we mean? Do we mean by that? Well, on Monday, I'm heading up to the Buck in the Bay Area to talk about longevity and AI, my favorite one-two punch.

1:56:14And with that, let's listen to the music of CJ Trueheart as we wrap this episode. Gentlemen, see you on the next episode of Moonshots. thank you to all our subscribers if you haven't subscribed yet please do we're now putting out uh more than one episode a week just because the speed is moving so rapidly so if you want to know when the episodes drop a quick hit subscribe and uh and let's listen to cj

1:56:57Linear thinking held us down, crawling centuries slow

1:57:05But something shifted in the code, now watch the numbers grow One becomes, two becomes four, the double it never ends Deceptively flat at first, then vertically ascends Can you feel it building the pressure in your chest? This is the moment where the future manifests

1:57:32We're rising exponential Straight up to the sky Every second accelerating This the time to be alive Digitize, disrupt, democratize the dream Nothing's ever been this fast We're breaking through the scene On the curve of infinite Rocket boosting now The inflection point is here And we're never coming down All right, if you're a music producer using AI and you want to give us an outro, just go ahead and let us know. And please, next, when you're watching this and you have questions, please post them in the comments. We are going to do more AMA in the next couple of sessions. Gentlemen, Moonshotmates, Dave, AWG, Mr.

1:58:31EXO, Imad, thank you guys. Having a fantastic week. Every week, my team and I study the top 10 technology metatrends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more, there's no fluff. Only the most important stuff that matters, that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important meta trends 10 years before anyone else, this reports for you.

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1:59:43So, you're about to make a trade based on a friend's text. But which you do you listen to? Is it, we could buy a house in Tulum? Get optioning those options. We could lose everything. Or, let's do a little research. Get your head in the trade and make the investment decision that's right for you. Learn more at finra.org slash tradesmart.