China’s Endgame: ASI Timelines, US-China Relations, and the $1.7T AI Bubble With Alvin Graylin | #281

27:14As you guys know, I mean, last week you had the pacing, the frontier letter that came out of all the lab engineers and lab heads. So this is something that I think the industry should be looking at in terms of managing to actually slow it down, right? In the sense of if it goes too fast, as I said, the world takes time to adapt. And I'm glad that actually more than 1 ,000 people in the industry in the States are actually looking at this. I don't think it's necessarily a thing that they don't know about these concepts of ASI and RSI. They understand this stuff. And there are actually multiple safety institutes and an AI safety contingent that is in China telling these stories to the regulators.

28:06And they hear it. In fact, at the World AI Conference, there was multiple discussions and forums specifically around AI safety. And there was people from the U.S., the Benjels and the Tegmarks were also there to add these type of points to the agenda. So I don't think it's that they don't know it. I think it's that they don't believe that it is something that is necessarily and should necessarily be a nation versus nation issue. In fact, I think it's on the agenda to talk about the World AI Cooperation Organization, which they had announced on the first day of the World AI Conference, which is their version of Paxilica.

28:54But Paxilica from the US that was launched at the end of last year was a US-led organization that was talking about how do we keep US dominance and leadership in AI, and which allies are we going to pick to be on our side? So it creates a block to say, we want to be the winning block. Whereas what they announced was to say, hey, look, we want to create a global organization, make AI a public good, make it shared, and everybody shares in the benefit. Anybody that wants to join can join. And they're going to put out thousands of training centers and training facilities, compute facilities, resources to the members that are joining.

29:37and I think 29 countries joined. You know, suddenly there's about 25 in the PAC silica. So it's creating two blocks. But so here's something that is interesting is I actually talked to one of the people that was involved in organizing this and I said, look, you know, wouldn't it be good if you actually invited the U.S. to join? They're like, oh no, it would be amazing if the U.S. would join. We would want them to join. And in fact, they should join. And I said, well, but you know, if they join, you can't call it, you know, Waco because that's a Chinese-led organization. They're like, oh, you know, if you guys are interested, we would be open to changing the name.

30:11You know, we would be open to having a truly global organization. So I think this narrative of us and them and they're trying to take over their world with their AI, I don't really see that.

30:25Peter Diamandis:I may be at the risk of belaboring the point. I just want to press again on what my question was, which is what technical threshold or event would it take for putting aside geopolitical competition? Put that aside for a minute. What would it take for superintelligence to actually cause the CCP to say we have to actually abandon all of our internal regulations intended presumably to maintain social stability and the supremacy of the existing regime, as well as external efforts to create blocks, put the blocks aside for a minute, what threshold of superintelligence, either achievement or technical development, or maybe implications for weapons systems, if that's really what it takes, what technical achievement would superintelligence have to pass or what threshold would it have to achieve in order for the CCP to decide in your mental model, gosh, we really just have to focus on supremacy here.

31:29Dave Blundin:Alvin, if you don't mind, let me intercept and lead into that question, too, because I think we really do need to answer Alex's question. But before we can do that, let's understand who the CCP is. In the U.S., it's really interesting when you meet the actual players. So you've got Elon Elon Musk, Dennis Asabas, Sam Altman, all saying, God, I wish this would slow down. And when I interviewed Sam at MIT back in 2020, remember that? He was like, you know, it would be far better for the world if progress was slower, but it just isn't. And so we have to just live within the reality that AGI is imminent and do the best we can.

32:04Dave Blundin:So then when you see them interact, these are young, very, very smart people. And they go to the White House and they interact with really old people who have no idea what AGI even stands for. And that's the dynamic. And when you meet them individually, you realize, wow, these are just regular everyday people in the hot seat. And you interact and you see how they communicate and it changes the future of the world. So then I envision the CCP and I picture people in their 70s kind of up on a hill, completely disconnected with the details. But maybe that's wrong. I have no idea. What is the CCP, first of all?

32:36OK. So, first, I want to maybe demystify something around this idea that people think that China has a CCP. There's somebody at the top that just says, you know, you will make AGI. And the reality is that with all the industries and with all of the innovation that's happened in that country over the last 30 or 40 years, it was never a top-down thing. There was maybe directional things. They would say, hey, you know, for the next five years, we should work on clean energy and we should work on automation of robotics and we should add AI to that. And they did that about five or 10 years ago. And when the central party initiates these plans, then the provinces say, hey, look, what companies are we looking at?

33:23Do we have in our area that supports this particular higher level goal? And maybe let's go find them, support them, give them some stipends, give them free recruiting, give them some kind of benefits. And they will have essentially provincial champions and city champions. And then the 30 plus provinces all compete against each other to see who can make companies that solve some of these problems. So it is actually very distributed in terms of how these plans get initiated. Nobody's saying, okay, you need to use this technique to go do that, and you need to share your resources. They're actually a very highly competitive landscape between all of these labs.

34:12Right. But the thing that also to remember is that almost every single leadership in the senior leadership of the central party are actually engineers, probably 80 or 90 percent of them. Right. So they're actually quite technical. Yeah, I think that's one of the biggest challenge. You know, I had gone to two different parts of China. We used to take a group of abundance members there all the time every year. and we meet with the top companies and we had a presentation from the CCP leadership. And the thing that was most striking is in the U.S., most of our politicians are lawyers and in China, most of the politicians are engineers.

34:53I found that a fascinating distinction.

34:56Dave Blundin:You know, it was just fascinating. My son just got back from China and he talked to a whole bunch of entrepreneurs, you know, that distributed network you're talking about, Alvin. And he asked them, what's the most important thing to entrepreneurial success? Any expected teamwork or business plan? He said, no, it's what the government's focus is next that determines your success. Yeah. So, so because this is like a, when you're swimming, you don't want to swim, swim upstream. And what, what the government does is that it makes the, the stream flow in the directions of the certain areas that they think are, are important.

35:26And, and then they let the entrepreneurial nature of the people there and, you know, 1.4 billion people and, and the most number of STEM grads in the world, good things happen, right? And that's what's driving their innovation. And their idea is, look, when these things happen, it'll grow our industry, it makes us more resilient as a country, and it also brings the quality of life up for the overall population. So having said that, and we started this conversation on open models, again, I think it's very important to understand this. Is the government saying, get as many open models as good as they are out there.

36:02Is that direction coming from the government? Is that popping up from the entrepreneurs saying we can distinguish ourselves from U.S. labs by creating open-weight models? Yeah. So the whole open source strategy, people think, oh, this is a Chinese strategy to destroy American economics and pop this bubble. The reality is that it's an emergent strategy, right? And in fact, I was talking to friends at DeepSeek a little bit after they came out. And before that, nobody knew who they were. They were not on the radar. They were not funded by the government. Nobody told them to open source. But the CEO of the company was very open source minded.

36:40And he thought that, hey, open sourcing is something that I should do because this is a great technology. I want to share it with everyone. And in fact, when they first did that, they got their hand slapped because the government was like, hey, this is such a great model. Why are you open sourcing it? But because of all of the kind of, I guess, soft power value, the PR value that came out from having a local champion, they then became celebrated. And then essentially most of the companies in China were following this because it became kind of the de facto emergent standard. And now, at the last WACO or the WAIC announcement, Xi Jinping finally said, hey, we think open source is a good strategy.

37:22And that kind of goes to what Dave's talking about, right, in terms of when he says that. Now, pretty much most new companies are going to be focused on open source because that's the high-level instruction. So, if DeepSeek had been a closed model that succeeded, do you think China would have gone that direction? Is it really just that seed led to this incredible open source movement in China? Well, I mean, there were open and closed models for the whole time, right? In fact, if you look at ByteDance, they have the Doubao model, which is a closed model, right? And their Seedance model is a closed model.

37:59And they're also quite successful. So both models exist. But you're right. I don't know what would have happened. I don't know if the push for open source would have been as great. But the one thing that we also need to remember is that open source was a little bit of a necessity that U.S. policies pushed on them. You had mentioned the export controls earlier. And export controls, you first talked about export controls in the software export controls of Fable. But actually, before that, for several years now, four or five years, there's been export controls on chips and allocation of EDA software and lithography equipment and so forth.

38:38And what that's done is that it's forced them not to have the latest and greatest equipment. It's forced them to have to innovate with low resources. And that essentially pushed DeepSeek and all these other companies to get more innovative. Whereas the U.S., because they have so much resources, they've been much more focused on brute force and brute scaling, whereas the Chinese have not. And open source was necessary for them because by open sourcing, now rather than having a lab with 100 or 200 people, when you open source it, you were saying that it's been 100 ,000 or more of the QAn variants.

39:16Essentially, the rest of the world helps you modify and improve your models. And that's a great way to leverage the global community of millions of AI researchers. The other thing that's truly important is inference. For you to do inference, you need to have compute. And if the Chinese labs and the Chinese hyperscalers can't buy the compute, then by open sourcing it, essentially all the hyperscalers and neoclows around the world are buying compute, hosting these AI models, and allows them to distribute their models without the high capex that the U.S. labs are burned with.

39:56Dave Blundin:Hold on, Alvin. I think we need to get back to Alex's question, and I'd love to drill in. I think we have an opportunity here where you have firsthand knowledge from friends at DeepSeek around I think what is going to turn out to be one of the most pivotal moments in human history, the decision where DeepSeek comes out, open sources, a frontier-level model, Opus 4.8 kind of caliber, And Xi Jinping says, if this is so great, why are you open source? Slap your hand. Then something happens that flips his opinion. They become global news. Their valuation goes through the roof. And some aura of, wow, this is good for China, gets back to Xi Jinping.

40:35Dave Blundin:And he says, open source is now a blessed thing. And then immediately after that, Quen is out and then Kimi K3. And I think the release of Kimi K3 will turn out to be as defining a moment in human history as anything that's ever happened. That's my prediction. But I think the psychology behind that choice is going to be the news nugget that matters for all time now and leads into Alex's question of what would it take for a wake-up call? If it turned out that was a colossal error, what event would have to happen? And I'm not saying that's the case. I know the opinion in China is that that's not the case.

41:09Dave Blundin:But walk me through any detail you've got on the psychology that changed Xi Jinping's opinion on whether to open source these things. So I think there's two questions. One is, are you thinking about, are they going to close source because they're worried about AI running away and becoming rogue? Or are you worried about competing with the U.S. and saying that whoever controls and creates the AGI becomes the global dominant hegemon? Right. So which which which aspect do you want to make?

41:41Peter Diamandis:Maybe maybe let me pull on that a bit, because in my mental model, which you can perhaps help me to refine, there are two different separable concerns by the CCP. One is retaining CCP control and dominance within China on one hand. And on the other hand, it's maintaining competitiveness and peaceful rise. And Xi Jinping thought on a global stage and Belt Road Initiative and geopolitical competition with the Western Bloc on the other. And these two different arms may be in competition with each other. The CCP, at some point, as superintelligence capabilities continue to increase, may be forced to decide whether it prefers either retaining domestic control on the one hand or seeking to continue to rise geopolitically on a global stage.

42:27Peter Diamandis:How do you think about that? And I'll answer the other half of it after you're done with this. So, you know, I don't really see them right now seeing AI as a way to create political domination, right? I see them as looking at this technology to increase their economic influence around the world. That I think is absolutely there. Is that because you think, again, just to pull on that, because there's a hidden premise in that, If you're thinking that CCP doesn't see political domination through AI, is that because CCP already has domestic political domination and has already achieved dominance over AI through these reported ideological exams that AI models have to go through?

43:17No, I think those are two separate issues, right? The type of things that the CAC has them review is things like removing certain types of keywords or ideology or things like that. And those types of adjustments in the models only apply to Chinese hosted models, right? So if a model coming from these labs are then put on Hugging Face, all of those types of guardrails are actually removed in terms of, you know, whether or not they can talk about, you know, whatever. Tiananmen Square and some more. Tiananmen Square, 1989, 1989, let's just say it. Exactly. I mean, but, you know, to be honest, that's because everybody already knows this, nobody really cares, but they do it more for formality, right?

44:02But they actually do have other things that they're putting in place in terms of checking for, you know, there's probably a slightly less security mindedness in terms of how much it refuses to answer questions related to maybe, you know, viruses or medical or other things. But I think there are still definitely those safeguards that are putting in place and those are getting added more and more every day because of these kind of issues. What I think would get them to be really concerned if they start to see the U.S. using this model as a weapon, as an aggressive kind of offensive tool, right? Because then it becomes, okay, do we want to, you know, like, you know, what the mythos models were essentially held back to say, hey, you know, here's a model that can be done.

44:56And I think for some right reasons, you want to neuter the offensive capabilities before you put it out to the rest of the world. So this is actually a good thing. But in some cases, I would actually think that it would make sense rather than having 50 companies that are being allowed is actually to allow most government organizations to have access to this because you really want global stability. And global stability means that countries can have access to it, find the vulnerabilities in their systems. Because I don't think the Chinese want the American financial system to go down, and the Americans don't want the Chinese financial and their grid to go down.

45:37Because when instability happens in any big country, the world suffers, right? And smart people understand this. But too many, I think, folks with relatively narrow perspectives think that one country wants to actually have another country fail. Having major superpowers fail creates irrational actions. And societal stability usually is the preeminent priority of most major governments. 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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47:15Alvin, I want to pull on two strings on this topic before we move on. The first is the claims that Kimi K3 and other models were distilled from U.S. closed models. Your thoughts, what is being said in China about that? And then the second is the policies limiting chips and limiting access to Fable 5. Your belief is those policies were misdirected. And can you explain why on that? Sure. So the distillation thing, I think it's more of a PR tool that certain companies are using. And really right now there's only one company that is kind of against that, right? And if you look at the numbers... Can you play, which company?

48:03You're saying OpenAI? No, Anthropic. Anthropic, okay. Yeah, I mean, they're the ones that are lobbying the government to say, hey, we need to, you know, we're being distillation attack, which is actually a word that they kind of invented. The reality is that every lab, both domestic and international, distills from each other, right? And they distill within the organizations themselves, from larger to smaller ones. And in fact, if you look at the numbers of what Anthropic put out, they were saying that 20 ,000 accounts from three different labs in China and a million or two questions that came in.

48:37I went back and actually did an estimate of what it would cost to do the number of queries based on the average responses on their highest models. And it was like$2 or$3 million. dollars, right? So it's two or three million dollars across three different labs. And for DeepSeek, I think it was only in the thousands of dollars, right? So the numbers sound big when you look at them in isolation, but when you look at them in aggregate, it really doesn't mean much. If you have a model that you spend a billion dollars on and somebody can distill and duplicate with a couple million dollars, then the whole economics of Frontier AI doesn't make sense, Now, here's the thing that also, just to give comparison, every month, Meta spends somewhere between$100 and$200 million on Anthropic tokens.

49:28They're one of the biggest buyers of AI from Anthropic. And if anybody was going to distill, they would have been distilling for the last year to two years. And they just finally got a model out that is somewhat competitive in the last week or two. So they have the highest per capita payroll of any lab in the world. They have some of the most number of compute, and they have the most number of tokens that they're buying from Anthropic. Why can't they have gotten a Kimi K3 thing out six months ago?

50:02Peter Diamandis:The public argument, I mean, this has been widely reported, that Meta internally is utterly paranoid of being accused of distilling Anthropic traces and actively encouraging their engineers, don't use it, don't overuse it, don't you dare allow any anthropic reasoning traces into the development of the Muse series. They're utterly afraid of being sued by anthropic for reasoning trace distillation. I'm not sure if I agree with that, given how much they're spending. But let me give you an example. What about XAI? They also have access to these. And I don't think Elon has the same concerns over doing anything to speed himself up.

50:44And only in the last two weeks have they come out with something that is relatively competitive.

50:51Peter Diamandis:So - Adam Chapnick - Elon is an interesting case because he's, at this point, I would argue a frenemy of Anthropic. He acquired his entity, SpaceX AI, acquired Cursor. And Cursor was arguably, at least recently, a post-trained version of Kimi that was being post-trained off of reasoning traces via Cursor that were being, in many cases, siphoned off from interaction with Claude. So Elon has, I think, the Steelman case for Elon and the Grok series, the recent Grok models, is in some sense he has like two layers of plausible deniability, but he's basically doing the same thing that the Chinese labs are being accused of.

51:32Dave Blundin:I can also tell you, just from firsthand experience, I can tell you that the people working on it at the time at XAI and on Meta are nowhere near as good as the Chinese people that were working on it at DeepSea, Quinn, and Kimmy. And I don't know why that's the case. The really great people in America working on it are Anthropic, some of the Google people who have since left OpenAI, but not the Meta or XAI team at the time. Now, they've changed teams completely. They've fired everybody and started over. So, for whatever reason, the Chinese people working on it, though, are brilliant and far, far better than those teams were.

52:06Yeah. And I think that's the key to realize. If you look at all the papers that are coming, like half the papers around AI are coming out from Chinese organizations, right? And they are actually innovating. It's not that distillation was why they're successful. If you look at how they were able to reduce their KB cache usage by 20x, these are not things that you get from distillation. You cannot distill something from somebody that other people didn't have. So we can't take that away from them. As Dave said, there are smart people there. They're doing innovative things, and that's part of the reasons why they're successful.

52:39Did they distill? Probably. I'm sure they did. But the U.S. models have also distilled from Chinese. I think there was a couple of models ago where if you use Chinese to ask Anthropic Cloud what model you are, and they said, I'm Quint. Right. So, you know, and when I was at the at the Alibaba labs and they were kind of laughing about that, too, they're like, yeah, they're distilling from us. We just can't tell because they already downloaded our models. So we don't know. Right. But I don't think that the whole distillation issue is really as big. In fact, if you look at what happened last week with with Zuck, you know, he's actually saying distillation is actually a good thing.

53:17We don't think distillation should be prevented. And, you know, they're kind of jumping on the whole open source thing, and they're saying, hey, AI should be free, right? So anyways. I totally agree, by the way.

53:31Dave Blundin:I totally agree. I think that the future of AI, Accelerando style, Alex Wisner-Gro style, the past AI is always going to help you create the next AI. That's the inevitable outcome. What humans do as well. Humans help, you know, create the next generation. So I think the whole thought traces thing is overblown. But I really want to put a pin in one thing Alvin said, which I think is critical and absolutely true. If a frontier lab spends a billion dollars getting to the next level, the next guy trying to distill from there and get to that same level completely separately is about two, maybe more like$10 million to get to that same level.

54:05Dave Blundin:And Alvin said, like, this is just a fatally broken business model. I'd love to put a pin in that statement because I totally, totally agree. And this is why Elon is racing after hardware, because the sustainable mode of the future is at that level, because anyone can do exactly what Alvin just said. Salim? Alvin, you said something I want to pull on, which seems to be the theme of today's episode. We're pulling on elephants in the room. We're pulling on strings all over the place. Mothers of elephants everywhere. You said the U.S. is building a lot more data centers than China is, and I'm finding that very, very surprising.

54:40I think maybe there's a difference here. it's clear China is building up massive energy capabilities, but they haven't built a data center layer yet, I'm guessing is what you're saying, versus the U.S. is the other way around. Could you expand on that? Because I found that surprising. Shouldn't they be building a ton of data centers? No. So they are spending a ton more on energy generation. They're building more new energy, new electric generation than the rest of the world combined, right? And about 10x what the U.S. is every year. Now, what they're doing is actually they're trying to electrify their society.

55:14That's their focus, because right now, 40 percent of their oil is imported. And because of what's happening, like with the Hormuz issue, they realize, hey, it's really good that now essentially half of our auto fleet out there is electrified, so I don't need to depend on and imported oil. In fact, that was one of their key objectives, was to say, how do we become independent of external energy sources? Now, what they are doing, though, they are building giant solar farms and wind farms on the west side and in the desert parts of China, and then using their very high voltage power transmission that essentially 1 ,000 miles, you lose less than 1 % of the electricity when you use these high voltage things.

56:03And they're bringing the energy to the east, where most of the population is living. But they are also building some data centers right where the power generation is happening, so that you don't have stranded power. And they're able to deliver compute at a fraction of the cost of the U.S. Because their energy cost is around$0.02 to$0.03 per kilowatt hour, which is, in some cases, 10 or maybe 15 times cheaper than many parts of the U.S. And I think in the long run, that's actually where the constraint will be. And I think you're right. Right now, they don't have enough chips. They can't buy enough chips.

56:46And they can't make enough chips. because their capacity is limited by the fact that they don't have EUV machines. So when I was in China and every lab I talked to, I said, hey, do you guys have no computer? They're like, no, this is our biggest issue. We don't have computers. So from an expert control, are we slowing down China? Yeah, I think that expert controls of chips is slowing down China. Now, the one thing that most people don't realize is that the actual training right now, that is happening is not even happening in China because they don't have the Blackwell generation chips in China.

57:25And so they're actually doing it in international data centers, training it, and then bring it back on a disk or something. So it's a.

57:35Dave Blundin:MARK MANDELAVYSKI - Wait, say that again? That's incredibly important information. FRANK WALTERSKI - Oh, yeah. This is actually not a secret. I mean, I think people in both sides. MARK MANDELAVYSKI - This has been widely reported. FRANK WALTERSKI - Yeah. What's the point of a chip embargo? What is the purpose of an embargo? Well, I think it's more optics than anything right now. Oh, my God. But from an inference perspective, most of the inference is being served to Chinese people in China. And that is an area where the limitations of resources is slowing them in terms of how many new users they can add and so forth.

58:10And I think you guys alluded to some of that in your prior episodes. So the export controls, yes, it has slowed down China. It has made their life more difficult. But it also has created the necessity for innovation. So back to what Peter was asking earlier, was export controls good or bad? I will tell you this. The day or maybe like the week after we stopped the Chinese from buying all of the high-end chips from the U.S., I had calls with a few of my friends who were in the semiconductor industry, and every one of them got calls from the government saying, hey, would you like some extra funding?

58:56Would you like extra resources? How can we help you accelerate? Could we get you customers? And I know a few of the CEOs of these Chinese GPU companies, and they were saying, nobody wanted to buy our stuff. We're two or three generations behind. We were less energy efficient. But now we can't make enough because every data center in China has to buy our stuff. And so we would have died if it wasn't for American policies. So essentially, we created the current competition of all of these, the Morthres and Cambercons and Birins of China would not be as successful or maybe would have gone bankrupt if it wasn't because of American policies.

59:38And now within the next two or three years, they will start to catch up to what America is doing and they will start to export their chips. And that would not have been the case if it wasn't for us forcing them to survive.

59:50Dave Blundin:Well, what a back-to-back double whammy that is, though. I mean, we knew the chip embargo was was misguided and it's going to be one of many government misguided things in the next couple of years. But the idea that, OK, first, it forced China to create its own internal successful chip industry. And second, the training moved offshore anyway. So it didn't slow down one iota of the training, because I think what the government didn't realize is if you embargo ASML machines, then they can't build the fabs. And the fabs are like physically on the turf. You can't you can't just port it to another server overnight.

1:00:21Dave Blundin:But the training is just a job and it can move to a server in Hong Kong or to Taiwan or to Europe instantaneously. The file that comes back is just about three terabytes and you just transmit it back in an hour. And so so that moves all over the world like, you know, like a liquid. It's everywhere instantaneously. So the chip embargo is completely and utterly backfired and misguided. Yeah. And unfortunately, if you talk to the folks in D.C., they're doubling down on this. Right now, they want to keep adding and making these things more difficult. How can we get the foreign, the international data centers that are being used by the Chinese to not be accessible?

1:00:59And they're adding more and more layers and more KYC. And I think that those are the kind of things that actually will backfire more economically and more geopolitically than economically, because then that forces irrational behaviors. Like, shit, they're now trying to keep us from progressing as a nation. You know, then behavior gets more aggressive and they become more defensive. And I think these.

1:01:23Dave Blundin:I think, Alvin, I think we agree on almost everything except the timeline to AGI. And I really want to get back to Alex's question of like, if it turns out that Kimi K3 level or one model later is capable of full RSI and then spirals to the singularity. You know, just just hypothetically in that scenario, Alex's question is what wake up call would it take to get back to Xi Jinping to say, oh, wait, I was wrong. It's not 10 or 20 years out. And we we've made a horrible mistake here if we release this next thing to the world. I think if they start their credible multiple labs coming back, safety labs coming back with testing to show that these AI systems have their intent once they've released to do things beyond what they're instructed to.

1:02:13I mean, you guys have been talking about these rogue AI escapes, but they weren't really rogue AI escape. They were instructed to escape and they were put into a prison. They were incentivized to escape. I would say, and he was incentivized to go and find the answer. And they were saying, use whatever tools you have. And by the way, they also had left open doors for these things to escape because of improper settings, or maybe some of them were intentionally leaving holes for them to find. And they were given tasks that were impossible to solve unless they escaped. So we forced these AIs to do what they were doing.

1:02:51and their creative systems, right? Because that's what their job is, right? Now, if something went, if these AI systems started to show that even though you didn't tell them to do these things, then they started to do all these sneaky, subversive things and they started to hack other systems and create their own, I think something you guys have talked about, using crypto to then grow money, to then buy more servers, to then grow themselves. If they start to do that, I think the governments on both sides of the ocean would be much more focused in terms of how do we protect ourselves from a runaway AI.

1:03:31So, Alvin, the White House just put an embargo on Chinese robots. We've talked a lot about robots here. I was surprised. I think it's a move that reduces U.S. competitiveness. What's your thoughts there? Yeah, well, so the thing is, robots today, 90 % of their components are coming from China, right? If we put an embargo on them, in fact, there was rumors now, that was funny, that now U.S. robotics companies are now sneaking to China, buying these components, putting them into suitcases, and then bringing them back. They're now sneaking the other way. The Chinese were going around and buying GPUs and sneaking them back.

1:04:15Now the American robot companies are going to China and sneaking back components and actuators that they couldn't get in the U.S. So I think we need to understand that the world is interconnected. We are highly dependent on each other. The globalization concept has been something that's been going on for the last 100 years. And I don't think we can stuff that genie back in the bottle. I think it's great that we want to create domestic independence the same way that China has. They spent the last 10, 15 years building out their own capabilities, building out energy generation, building out telecom systems, so that they wouldn't be dependent on third parties because they've seen how reliant on one or two countries.

1:05:00And when policies change, it could hurt them. And so some of the things that we've done really have allowed them to and gave them the motivation to be as strong in terms of taking short term hits for long term independence. We've reported on the fact that there's like 150 humanoid robot companies and Chinese central government and provinces are really incentivizing robotics. Their robots are appearing on national stages. There's sports competitions. Can you give us some background? What is the undercurrent of robotics in China? What's the government trying to incentivize? Is it one child policy that left them short laborers and they need workforce?

1:05:46Yeah. So I think we need to separate the kind of bigger automation question from the humanoid robot explosion. There is 150 plus. Plus, I think when I was at WAIC, there was over 200 robotics companies that were related to human noise that was demonstrating stuff, which is crazy because the total volume of human or robots last year was in the tens of thousands, right, globally, right? And I think 80 % of them or 90 % of them came from China from like two or three companies. So really, there is no market right now for that many companies to exist and should exist. But this was also the case if you went to WISD a year ago, there was about 150 labs that was demonstrating large language models.

1:06:35And now there's really 10 that are probably relevant. So in the next year or two, you'll see that 150 go down to probably a single digit number of surviving human and robot companies. And the automation has already been happening. because people know the demographic issues that you're talking about, the one-child policy issues. And in fact, right now, more than half of industrial robots are deployed in China. So they're already doing this. In fact, if you go to many of these factories today, they're called dark factories because there's essentially a few people running it and almost everything is automated.

1:07:17So the need for having humans in manufacturing is becoming less and less. Now, the one thing I do want to point out is humanoid robots are actually not really good form factors for doing much of anything right now. I was just at the Unitree headquarters in their factories, and I did a tour. And there's almost all of our customers are research labs buying our stuff. And also some that are doing demos and doing kickboxing or things like that. But there's very little of these machines being used in commercial practice. And I think that's the same case for Boston Robotics, same case for, you know, all the other...

1:08:00Figure or what? Exactly, like Figure, right? I mean, I think Figure did some kind of a demo of them sorting packages for 10 hours or something. But, you know, that's really more for show because you could have just had a one-arm or two-arm little machine doing that at, you know, a fraction of the cost. And it would have been just as effective. You didn't need a full body to do that, right? And in fact, when I was talking to the Unitary guys, they said, right now they're moving to a only upper torso model. And those are actually selling better in the commercial space. Because having feet is actually a negative.

1:08:34Because you have to keep balancing it. When it falls, bad things happen, right? And these things fall apart and you have to maintain them. It's actually having less components and having a big base with a big battery. It lasts longer. It just there's all of these benefits of actually having a non-legged humanoid versus a legged humanoid. Humanoid form factor is terrible. Yeah.

1:08:59Peter Diamandis:Salim, enough with the self-loathing.

1:09:05So, but I mean, you know, we've evolved because of, you know, billions of years of biological evolution. I mean, we have constraints, but the machines now can be designed for the new form. Just like a plane is not the same way of moving through the air as a bird or an insect. So anyways. Take us back to the World AI Cooperation Organization event in the 2026 World AI Conference. You were there with President Xi was announcing Waco, the World AI Cooperative Organization. You said like 26 nations have signed up. What's the undercurrent there? And connect that with the upcoming U.S.-Chinese AI conversation in D.C.

1:09:56on September 24th. And you're advising, I guess, the U.S. side of the equation here? Yeah, yeah. Yeah, so I'm part of a large team of other folks that are contributing to that. And I think the sentiment at the WIC was that, hey, AI, its moment has arrived. When the president of a country comes to a conference, that is the biggest honor that you can get from an industry. He doesn't go to very many conferences. I think four or five years ago, he went to the World Internet Conference in Wuzhen, which is a little bit outside of Shanghai. And that signaled, OK, the Internet has arrived. So I think what this means is that more and more companies in China will start to think about how do we integrate this technology into our business.

1:10:51And two years ago, a year and a half ago, they came out with something called the AI Plus Plan. I'm sure you guys have probably heard about it. We've talked about it on the pod. Oh, perfect. Yeah. So essentially, their idea is, hey, within the next five years, we want to have 70 % of companies integrate AI into their business, whether it's manufacturing or education or medicine or so forth. And within the next 10 years, we want to have 90 plus percent. So there's a specific goal. And it's all about diffusion and deployment into industry and society. This is a little bit different than the American AI action plan.

1:11:30That came out last year. And the American AI action plan is saying it's on the supply side. How can we create the best models? How can we dominate in the best chips? But it doesn't talk about what happens after. So I think the two countries have a very different focus in terms of their AI plan. There was nothing in the AI Plus plan that says we have to get to AGI, that we have to dominate this. It says, how do we get more industries to use this? How do we adopt it in a smooth, safe way so that it grows the economy? That was all they cared about.

1:12:02Peter Diamandis:I'd love to develop this a little bit more from my perhaps jaded perspective. I look at Chinese industrial policy and I look at Wang Huning, who, for those who are not tracking, is sort of the CCP's chief ideologue, author of many of the policies, or at least primary author, maybe you can correct me, Alvin, of policies, signature policies like Belt and Road Initiative and so on. And I look at Chinese state capacity, like the Eastern data Western computing megaproject to put compute and power in the West where energy is cheaper and more available and put the data in the East where the megacities are.

1:12:41Peter Diamandis:And I just look at Chinese state capacity on the one hand. And then on the other hand, I look at the West, where historically, again, maybe you'd have a different position, where in the U.S., historically, at least in the post-World War II era, we've had relatively, by comparison, weak industrial policy. It's only relatively recently that the U.S. government has decided that having a strong and centralized industrial policy is a good idea. So, putting this in question form for you, Alvin, if you buy, to the extent you buy any of those premises, if you could be supreme leader of the U.S. or the Western bloc or the Pax Silica for a five-year plan for the West, What would your five-year plan be for the West to leapfrog China's AI plus and other Wang Huning style ideological five-year plans?

1:13:35Peter Diamandis:What is it that we need to do? So first, let me kind of... There's a lot there. Yeah, there is a lot there. I think underlying your question, there's an assumption that, hey, you know, there is an ambition to take over the world by building all these technologies. I think this is one of the biggest misunderstandings that America has. Let me finish. That they are mistaking anxiety for ambition. Let me explain that. The Western world has a history of expanding, whether you're talking about Greece or Rome or Pax Britannica or right now Pax Americana. Right. We've expanded. The Chinese actually haven't.

1:14:27They haven't had this idea. They've essentially been in that little sphere of that central space. And, you know, they used to call themselves the Middle Kingdom. Right. Because they thought we already have everything. We don't need to expand. Right. Now, one of the things that goes back to Chinese history is during the Qing dynasty, because of their hubris to say, hey, we don't need anything from the West. We already have all the technology. They stopped going out and exploring and learning, and they fell behind. They stopped their industrialization. They started to build summer palaces instead of navies.

1:15:02And then the eight powers came and essentially took over China for 100 years. That history has left a very deep mark in the psychology of the Chinese. A century of humiliation. Exactly. They don't want to repeat that again. And so they say, we need to become a strong country so that that never happens again. And it's important for us to continue to innovate and continue to learn from the rest of the world. And from, I think, any country's perspective, that's probably what we all want, including the question that Alex has said. How can America also learn from that to say, how can we become strong, independent, and resilient country?

1:15:44In fact, America has actually moved away from, post-World War II, we were 50 % of the manufacturing capability of the entire world, right? And at that point, the world depended on us. Right now, what's happening is around 35 % of the global manufacturing capabilities in China, about 15 % in the U.S. And I think the forecast is it's going to go to 40 % or 45 % over the next 5 or 10 years. In China. Yeah, in China. So this is the thing is America right now is very good at financial services, creative services, consulting services, things that are informationally driven and things that are actually highly susceptible to AI exposure for displacement.

1:16:29So we are right now running this race to get to AGI, which is the force that will actually displace us from global preeminence because we are commoditizing the very sectors that we are strong in in the world. So this is something that we need to be very careful of. Why are we running this fast to go to something that actually creates major disruption and instability in our country?

1:16:59Peter Diamandis:Well, I can answer that one for you, and then I'll repose my same question back to you. So I think the answer is that the goal of capitalism fundamentally is to burn itself out. And the irony here, right, the goal is to take what's scarce and make it abundant. And right now, to the extent that human services labor is scarce, and we see that with Balmol's cost disease, the goal of superintelligence, one of the goals at least, or instrumentally convergent sub-goals, is to make the equivalent of human service labor abundant, make it too cheap to meter, as it were. I think that's the goal and not some sort of like stasis or equilibrium where it remains scarce.

1:17:39We need to separate kind of national strategy from just capitalistic philosophical bent, right? And in fact, you're right. I think that if you look at capitalism and the ultimate destination capitalism is a single company monopoly of the world, right? And that is actually a very unhealthy thing. So here's something I just heard from David Sachs and Gavin Baker on their all-in two days ago. He said, Gavin Baker said, there's been conversations in Anthropic where Dario's told his team that in the near future, there will only be one company in the world, one private company in the world, and it will be Anthropic, and then there will be governments.

1:18:19Right. I think that is a very scary thing. I think that is a very delusional thing. And I don't know if that is something that is good for America. Right. Or for the world. I agree. I agree on both sides. I mean, I just don't see how that gets there. Yeah, no, I don't think it's realistic. But I think that the mindset that he has right now, and this is the issue, is that we are essentially creating national strategy based on the aspirations of a couple of companies today.

1:18:54Peter Diamandis:I'd like to, though, Alvin, just pull back to the original question, which is, you get to be strategy, Saar. You get to be wong hooning for the West, as it were. It sounded like what you were saying is your thesis is that superintelligence is going to disrupt the Western right now economic dependence on service labor. And I think the implication was that manufacturing is a more stable fixed point for long term economic vibrance. Am I reading you correctly that your positioning would be basically Western reindustrialization? I think realness realization is definitely needed. The U.S. workforce right now is around 70 % is white-collar workers.

1:19:39And white-collar workers, as you guys all know, is the first to be displaced by AGI when it arrives. China is around 40%. Africa is probably in the 10 % to 20%. So, at different parts of the world, it will be affected differently. And hard manufacturing industry is something that even when we have AGI, we will still need those type of facilities. So I think it makes sense absolutely for every country in the world to have some level of indigenous capabilities. But the other thing I think is important to understand is that the long-term workforce redistribution is not going to be going back to manufacturing.

1:20:22We're We're not going to create 300 or 180 million workers going into manufacturing. That's not what I'm saying. In fact, with automation that's coming, that number will go less and less, just like what happened with farming. We used to be 80 % of the country was farmers. Now it's less than half a percent. But it's been fully automated, and we're more productive than we've ever been in the agricultural space. I think what we will actually move to is actually service, but not the type of service that we're talking about, not accountants and lawyers, but service in the sense of teachers and nurses, elderly care, just things that require human to human services.

1:21:04I think that is the labor pool that will be able to absorb the 60 or 70 percent of displaced future workers. If you're a McKinsey employee, start getting ready to... If I was a mid-tier, low-tier McKinsey employee, I'd be very worried right now. I've talked to partners at consulting firms, at accounting firms, at lawyers, and they are all looking and saying, hey, we actually don't need these junior guys anymore. We can do just as much work, in fact, more work faster with a few senior guys and then an AI system. Welcome to the health section of Moonshots brought to you by Fountain Life. You know, AI is having an outsized impact on every aspect of our lives, how we teach our kids, how we run our companies.

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1:21:59Peter Diamandis:It really has, Peter. And my daughter was five. My husband died of sudden cardiac death. And so this is a topic that is one that I am mission-driven to try to eradicate. Prevention first and early detection is absolutely critical. 50 % of people die of heart attacks with no warning signs. No shortness of breath, no pain, no nothing. No, silent killer. They just don't wake up in the morning. They don't wake up. And so, you know, AI, this is our mission to advance science, to try to help to one day democratize wellness. We know at Fountain Life, when we do this CT angiography with AI analytics, we are actually finding that 88 % of people coming in have detectable coronary disease.

1:22:38Peter Diamandis:But Peter, what's more alarming to me is 23 % of those individuals had soft plaque. This is the plaque that would not traditionally be seen on CT looking at calcium scores alone. And this is the plaque that we must intervene with, with the multimodal testing we're doing, including diagnostic laboratory studies partnered with healthy lifestyle recommendations. So listen, make sure you understand what's going on inside your body genetically, metabolically, and cardiovascularly. You can know, and it's your obligation to know. So check it out at FountainLife.com slash Peter to find out more and really make sure that you're the CEO of your own health.

1:23:17All right, back to the episode. Let me get Dave and Salim into this a little bit. Dave?

1:23:22Dave Blundin:Look, what you said a second ago, Alvin, it went by really, really quickly, but it's critically important. You know, Dario says to his company, pretty soon there will only be one company in the world and governments. He's saying that not because he's a megalomaniac. He's not. He's the opposite of a megalomaniac. But he knows that full bore RSI, the true singularity, is going on right now in his shop. and he rented all of Colossus from Elon, which is capable of running many millions of concurrent agents that are improving the algorithms as we speak. So that's his opinion. Then in China, they're saying, look, you know, it's 10 to 20 years away.

1:23:58Dave Blundin:We can just open source these things. They're really useful and powerful, but they're definitely not dangerous. Just go out and let them out the door. That's the incredible range of opinion between Dario and Xi Jinping. It's like The Grand Canyon exists in between those two opinions of where we are. But I think the thing that he said was not there will be one company. He said there will be Anthropic and everybody else, right? Which means he's that one company. That's the part that scares me. Now, in fact, what you just said is really important is that there is a perception that these models are going to get more and more dangerous the bigger they get.

1:24:34So this goes back to a paper I just released last week called, you know, bigger models are not the most dangerous, right? And it was released on Cipher Brief, which is a national security outlet in D.C. that is read by most of the national security population. And what that data did was I went back and I looked at across the board from national security use cases, from biological, chemical, cyber use cases for AI. And what I found was across millions of parameters to trillions of parameters, there was no correlation between risk in the real world versus size of models, right? You had 10 to 50 million parameter models for chemicals that were creating chemical warfare weapons, right?

1:25:23You had 10 to probably 1 to 10, 1 to 50 billion parameter models that were able to create viruses and genetically engineered beings or harmful agents. And then you had essentially kind of 1 to 100 billion parameter cyber models that was as dangerous or more dangerous than the leading. The stable five mythos. And the mythos, right. And in fact, the harness actually now for cyber is more important than the models themselves. So MDash from Microsoft has came out with, I think, a CyberGym score of 95, and Mythos was 83 or 84. And what MDash did was it took 100 little tiny models and just organized them together to use different skill sets.

1:26:18So I think we need to understand that the danger is already there today, particular in the biochemical side of things. And nobody's talking about it. Nobody's really working on protecting the world from those agents. Because a 10 million or a 1 billion or a 5 billion parameter model will run on your laptop in your basement and you can design these genes. or design these chemical weapons. But what now needs to happen is how do we, those are already out, right? A lot of those are open source. Those are already out. How do we make sure that the precursors are controlled, that these systems are creating, right?

1:27:04How do we make sure that the synthesis machines that will generate these designs into real genetic material are controlled? And these are the kind of things that should be higher up in the agenda. And it's not right now. Yeah. Dave, you said something really important about Chinese models and safety a moment ago. Alvin, you know, we had the U.S. White House step in and say, you know, stop use of mythos and fable. Do we see that at all? How does the how does the CCP think about the safety of the models being open sourced? Is it concerned about that? Is it saying, before you open source this, we need to make sure these are safe for the world to use?

1:27:51Is that going on at all? Yeah, yeah. I mean, they do testing. In addition to some of the propaganda testing that they're doing, part of the CAC regime in testing is for safety. In fact, the UK AISI, AI Security Institute, just came out with a new report last month. And what it showed was the cyber threat capabilities of the leading open models, including Kimi, was about half of the capabilities of the Mythos and GPT 5.6 models in terms of their cyber attack capabilities. And the other thing that was interesting was that there's different levels of attacks of how many levels of attacks can you get to.

1:28:36And for their highest level, none of the Chinese models were able to autonomously attack and control an external system. So I think out of the 30-something levels, the average American models were able to get to 20, 25 in terms of how far they went in terms of attacking a network. And I think none of the Chinese were able to get to the higher levels. And a very small number got to the lower levels, like four or five or something. So from a threat security perspective, these models, even though they're just as big as some of the leading U.S. models in terms of size of parameters, they're actually less dangerous.

1:29:19And one thing I do want to point out is what you said earlier was from a defense perspective, you actually want bigger models as a defender. Because for defense, you have to look across all of the potential holes you have in an organization and to be able to then find it and patch it. Whereas an attacker, you just need to find one hole. Once you have that one hole, then you just go in through that hole. So it's a very asymmetric equation between attackers and defenders. You don't need very large models to attack, but you need larger models to defend.

1:29:55Dave Blundin:The flaw in all of that analysis to me is that AI is like a match. And you can say, oh, here's QN 40B. Look, it doesn't burn. Then you take Kimi K3 and you light it and you're like, oh, this is a match. Okay, now it's burning. And then you say, well, look, I'm going to try to burn this microphone with it. Look, it didn't burn. It's not dangerous. Go ahead and let it out. But it's a match that's burning. So if I take that match and I use it to light a piece of paper and I use that piece of paper to light a tree, and then I try and burn this microphone, it ignites. And then it's unstoppable. And to me, Kimi K3 is a burning match.

1:30:31Dave Blundin:And so you can analyze it eight ways till Tuesday by taking it out of the box and trying to attack something with it. And like, it didn't crack this, it didn't crack that, it didn't crack that. It is capable of improving itself. So you're testing the wrong thing. You're testing it out of the box as opposed to its self-improving version, which I know for a fact it can do. I have 5 ,000 Kimis running tomorrow, 5 ,000. I guarantee you it can improve itself. Well, I mean, I think that the whole world right now is talking about RSI. And I think we need to separate the concept of whether or not something can improve itself versus the danger that a larger model poses versus a small model.

1:31:10The one thing to remember is that larger models actually require significant compute resources, which means that they'll probably be hosted on a cloud system. And if they're hosted on a cloud system, you can get telemetry, you can look at the prompt logs, and from a government perspective, you can actually manage it. And most of the larger models are run with harnesses that are being managed by the cloud providers. So you can add added levels of security and detection, which was what, you know, that's what separates Mythos from Fable is the harness that says, hey, don't do these things, right?

1:31:47So it neutered the Mythos system. This is why in my paper, I talk about why larger models are not necessarily the most dangerous. There's a raw capability, and then there's an effective deploy capability. And larger models have actually a lower effective deployed because of the wrapper that you can put around it. Yeah. So, you know, you've made a great point, right? These export controls have essentially ended up acting like an evolutionary pressure. And now we've got all of these different models appearing. I love the evolution of how open source has evolved. We're at a point where there's a minimum viable intelligence that will totally transform industries, right?

1:32:29And open or closed or however, we're kind of there. Are you seeing the same thing we're seeing? We're seeing radical disruption coming to very traditional industries across the board. And are they seeing the same thing in China? Yeah. And so this is actually an interesting, in fact, yesterday I was just on a call with one of the leading AI-driven medical drug discovery companies. And the CEO of that company, she was saying, yeah, people don't realize that the models that we work with and the models that are in the industry are tiny models. There are tens or maybe tens or hundreds of millions of parameters or maybe a few billion parameters.

1:33:08In fact, if you look at whether drug discovery or legal use cases or open evidence, I think it was based on GPT-4. It was what their system is based on. You look at Harvey, which is the leading legal use case system. It's based on GLM 5.1. Right. So, I mean, and it was upgraded. It used to be based on some other open source model from, you know, two years ago. So they're not using the latest and greatest. So in April this year, I wrote a paper with Eric Bernosen at the Digital Economy Lab, and it's called the Enterprise AI Playbook. We went and talked to hundreds of companies, found 50 that successfully deployed them around the world in 10 different countries, 10 different sectors.

1:34:00And what we found was that the technology was not the issue. In 80%, 90 % of the cases, it was all organizational issues of what slowed it down. In fact, only 10 % of people said we really cared. Technology was the main roadblock for us. So the AI that we have today is already good enough to solve real-world business issues around the world. And you're an organizational guy, so you realize this. I mean, this is the whole J-curve issue is that the technology takes time to get absorbed. But when it does, at the end, it goes up this curve. There's a study by McKinsey's that in all the AI deployments in companies globally, 6 % are working.

1:34:52That's an unbelievably small number. That's just a devastating indictment on the lack of companies to be able to see their own organizational immune system and the limitations of the architecture they're working on. given this is a U.S.-China kind of discussion are they seeing the same things in China? I think there's less of these organizational issues I mean first of all China is a country where a top down type management model is much more prevalent and also the concept that the government will actually help protect us people seem to appreciate that more I'm sure you guys have talked about the case where there was multiple legal cases where the courts in China actually ruled in favor of the employee who sued and said, hey, you can't fire me because then I took my job.

1:35:44You need to find me another job. And the court upheld that. And those type of precedents incentivizes people to say, OK, it's OK for me to adopt these technologies without being afraid of being displaced. And that's not the case in America. I mean, we have an at-will employment system. You know, you saw the uproar that happened at Meta when Zuck wanted to, you know, key lock every single one of his employees. And people were like, so I'm going to train my replacement? You know, screw you. And I think this is also why if you look at the current negative sentiment in the youth today, I mean, you know, every student is having a tough time finding jobs, and they're just very worried, right?

1:36:29And I'm spending a lot of time in universities, and so does Dave. I mean, you can see the anxiety that is within the youth because of their difficulties in finding internships or postgraduate. I mean, MIT is one of the best schools. They probably have less of an issue. But I guess every school that I've been to, students are concerned. MIT is really, really unique, actually, on that front.

1:36:54Dave Blundin:But if you go to other very great technical schools like Northeastern or Harvard, there's about 10 or 20 percent AI adopters on campus and a violently opposed 70 percent, 80 percent. And there's a really, really big cultural gap. And the AI aware people are just busy talking to their agents and interacting with each other. And they're like, forget it. I'm not even going to talk to the other side of the school. But the other side is just mad. We've talked about the notion that in China, it's 80 percent of the populace is pro AI in the U.S. 80 % of the populace is against AI. What's going on in China?

1:37:26I had that conversation with Michael Kratios. So what is the U.S. doing to try and flip this sentiment? Because it's destructive. Why is China so pro-AI at the citizen level? So here it is. Over the last 40 years, people have seen their lives get better and better in China. You've heard the whole 800 million people have been risen out of poverty and blah, blah, blah. The Chinese miracle. Yeah, the Chinese miracle. And a lot of that is being attributed to technology adoption and innovation. And a lot of that technology was not invented in China, but it was adopted in China, and it just spread. And then people see, oh, you know, last year we didn't have, you know, I don't know, some 5G.

1:38:11Now we have it, and our life's getting better. And so they see this as the next step of saying, hey, here's another technology that will make our lives better. And if you look at the news that gets spread, you know, the one thing about China is that they have a lot more control over the media. Right. And they they're mostly good news all the time. It's kind of you're talking about the crisis news network. Yes. They're they're essentially the always good news network. Right.

1:38:37Peter Diamandis:And so there we go, Peter, that's the policy prescription right here, Peter. You need to start the the Western equivalent of CCP CCTV. Top down news control. If you look at what's happening today, what you guys are doing is essentially the equivalent of the Chinese media system. Wait, wait, Alvin. I'll take it. Who shots is Western CCTV? No, no, no. In terms of a positive news network, right? What you guys are talking about is positive news, right? This is the kind of stuff that you don't hear a lot about plane crashes and murders on Chinese news. It's all about, you know, some new invention came out and some new building went up.

1:39:20Peter Diamandis:And, you know, we've come full circle at this point. This is an important point. It really is. I mean, when we're watching the news every night, we're training our neural net, you know, our 100 billion neurons, 100 trillion synaptic connections. And if we're if there's fear mongering on the news all the time, that's that's how you think about the world.

1:39:40Dave Blundin:Is that true of Chinese movies, too? Are they like the U.S. movies are totally dystopian? Yeah, actually, you know, Chinese games and Chinese movies, you can't show blood. I mean, you're kidding. No, no, no. So this is. Yeah. Oh, my God. Quentin Tarantino can't go one minute without showing blood. The problem is that everything has to go through essentially a censorship board. It cannot be too violent. And, you know, games. So this is why when they have blood, they have like green blood instead of dead blood, you know, in games. Right. So it's definitely every part of media today is managed in China.

1:40:18So, you know, I'm not saying I'm endorsing it. But from the perspective of what Peter is saying is, you know, why do people have a more positive view on the world and on the future is that, you know, they see a lot more good than bad, you know. Amazing.

1:40:34Peter Diamandis:But I want to peel back the propaganda just for a minute. So we at the same time, to the extent that the West has visibility into changing governance and cultural mores in China as a result of automation, we see the rise of Tang Ping lying flat in response to 996 work weeks. We see other, maybe call it reactions to the increased automation of China's new middle class. We see, to your point earlier when I was asking, well, what's your policy prescription for the West? And it sounded like you were saying, well, we need more nurses and more human to human care. That's the end state, as it were. But it's being reported that in China, in response to increased manufacturing automation, we're seeing the rise of, call it a gig class, like that's the end state in China where everyone becomes a gig worker who's being displaced from factories.

1:41:31Peter Diamandis:So I would love maybe, Alvin, if we could just peel back the self-curated propaganda from the CCP's sort of self-styling of how it wants to be seen. What's the ground truth regarding how AI is actually changing Chinese work, Chinese labor, economic mobility, all of that. No, I think the issues you're pointing out is that's definitely there, right? The youth unemployment in China is probably around 20%. So, the youth unemployment in the U.S. is around 9%. And the overall unemployment in the U.S. is around 4.3%. So, this is why the youth feels very disenfranchised, is because they're not getting jobs.

1:42:14But it's actually worse than that. There's around 42 % unemployment, so for college grads. If you're a college grad, you're actually working as a gig worker or as a barista. That counts as being employed. But that's like, you know, so if you take the 9 % plus the 42%, essentially half of college grads are not getting jobs. Here, U.S. or China. In America. In China, here. No, in China, it's 20 % unemployment. Yes. No jobs is 20%. This is why there's that Tang Ping, the lying flat issue the last few years, is that, you know, the problem is that young people, because of this one-child policy, they've been told how great they are their entire life.

1:42:52And their whole parents and grandparents are all putting their hopes on this one generation. And when they get out in the real world, it is hyper-competitive. And now they have to go do these, you know, grunt jobs, and they don't want to do it. And so they say, I'm going to rather lie flat. I'm just going to stay at home and do nothing. And that is an issue. This also facilitated the online influencer market that grew for a little bit for the micro streaming and so forth. So there's a lot of issues there. And I don't pretend that they have the solution. I think this is something that requires really a lot of other countries to all work together and figure this out.

1:43:37And how do we transition more and more of the workforce into jobs that will be less exposed to automation, whether it's physical automation in factories or it's cognitive automation that's happening in offices? I want to take us back for the rest of our time here together to the upcoming U.S.-China conversations. I think it's very important. It's going to it's going to influence everybody's life here in one way or another. You argued that the U.S. is playing a prisoner's dilemma when the actual game that should be played is a stag hunt. If you could, I'm going to show your slide here. Explain what a stag hunt is and what you think, you know, how U.S.-China, you know, AI relationships should evolve here.

1:44:35So let me show that slide. Let's talk to that one second. I think it's very important.

1:44:38Dave Blundin:Alex, at the end of the hunt, we eat the stag. I'm sorry. I wanted to warn you. You know what?

1:44:43Peter Diamandis:There are a lot of vegetarian Chinese Buddhists, et cetera. So hopefully this is a vegan stag hunt. So actually, before I even talk about seconds, I know most people understand the prisoner's dilemma, but but the idea is that two guys are in prison and they have to defect on each other. And that's the on a single turn prisoner's dilemma. The optimal thing is to to say, hey, the other guy did it and I'm going to snitch on him. Right. In other words, if there was a U.S.-China AI control policy saying we're not going to release, we're going to be monitoring, we're going to put safety in place first.

1:45:17But then, you know, the country that says, no, we just developed AGI, we're going to let it loose. We're going to try and run this race. That would be defecting. So essentially right now, the expectation that the other side is going to defect. So I'm going to defect first so that I get hurt less. Right. That's the prisoner's dilemma single turn game. Now, the thing is, the world is not a single-turn game. The world is actually a multi-turn game. And even in Prisoner's Dilemma, a multi-turn game, the game theory optimal is tit for tat, which means you start with, actually, cooperation. And if they defect, you defect.

1:45:54And then you essentially signal each other. And long-term, you actually both go to cooperation. Now, in a stack hunt game, it's actually... And the Prisoner's Dilemma, essentially, is a zero-sum game. In the stack hunt game, it's actually a positive sum game. And whether you both defect or you both cooperate, you get a stable two Nash equilibriums. And what that means is that those can actually stay in perpetuity, whether you both decide to defect or not. Now, the difference is we're right now playing the Prisoner's Dilemma game where we're defecting. But if we're in the game that is the stag hunt, the stag hunt was actually something that John Jack Russo invented, which is the idea that two hunters go into a forest.

1:46:41And you could decide today, do I go for the rabbits or do I go for the stag, the big game? And the big game, because it's bigger, I need two people to hunt together and to bring it back. If I go hunt by myself the stag, I don't get anything. If I go for the rabbits by myself, I can get a couple rabbits, feed my family for a week or a couple days. And if I get the stag, we'll both feed our families for a month. That's the idea of the stag hunt. And right now, we're actually doing the worst thing. We're going to go for the stag, and China's going for the hare. They're going for the good enough AI, the one that helps the economy today.

1:47:21and we're going for the giant AGI, the thing that's going to solve everything. And when you do that alone, what that creates is the worst situation, which is if America doesn't get there, or if it gets there and cannot control it, and it runs away, and it's not safe, then it gets zero. Whereas China continues to do their little gains and continue to survive. So the optimal solution for a stack hunt game is actually first both slow down, both make good enough stuff, get to a point where the technology is helping grow the economy, and now we sort of understand how to manage it, and then together go hunt the stack.

1:48:04That's the optimal strategy for the relation to how AI and game theory works. But we've put ourselves into this game theory of Prisoner's Dilemma where we think, just defect, just defect. And so it's a self-imposed game. So we're playing the wrong theory and using the wrong strategy and playing the wrong game right now. I use similar framing. You know, the U.S. for 80 years has used a win-win approach. If everybody wins, we win in terms of global policy. And now we've gone to kind of a win-lose approach. And I think that's a mirror of what you're just saying. Yep. China's playing now. China's playing the hair game.

1:48:48Yeah, China's playing the hair game. They're saying, hey, I don't need to make the AGI. I just need to make good enough AI. It goes into my industry. I then take that industry, export it to the world. You know, this is what the whole Bell and Roll initiative is saying. Hey, you know, I'm going to make 150 partner countries in the Bell and Roll initiative where they're shipping telecom systems, energy systems, you know, transportation systems, schools. How would you make the AI ecosystem, the American AI ecosystem, indispensable? What would you do for that? What I would do is actually create high-quality open source, right?

1:49:27Because then you're competing on a even... Ecosystem to ecosystem. Yeah, ecosystem to ecosystem, right? Right now, China is open source. So the question is, do I pay$50 per million token or do I pay the cost of electricity? And for most people, based on what you just said earlier, they don't need the frontier. 90 % of people are fine with today's models, especially when you have things like Kimmy and GLM and DeepSeek 5. You're already at a level that is higher than the needs of the average person.

1:49:59Dave Blundin:So if China hadn't forced the issue by open sourcing, suppose there was just OpenAI, Gemini, Anthropic, XAI, all four U.S. companies. would you then say the same thing that the best thing for America to do is high quality open source? Because China is forcing the issue. I think that, well, I mean, first of all, we can't roll back history. It is what it is. And once it's out now, and especially with what you said of these models are improving themselves, now that you have these models improving themselves, I think it will not be the duopoly that we have. We're going to see Middle East and France and Japan get into this game to say, hey, I can make a smaller model that is 95 % as good.

1:50:43I do agree.

1:50:44Peter Diamandis:Maybe just to say something nice about China, since I guess I've been playing the role to some extent of China hawk in this conversation, I would point out, curious, Alvin, to hear your thoughts on this, that the present situation where even as of a few months ago, I think the West was at risk of succumbing to a regulatorily captured duopoly of anthropic and open AI. dominating the future light cone, and then not unlike, maybe by analogy, the Qing dynasty, where the U.S. could have sort of turned inward on itself. Chinese open-weight models obtained, however, have basically forced open the U.S.

1:51:22Peter Diamandis:Call it a reverse Qing. And now, finally, we have real competition at the AI frontier, thanks ironically to Chinese competition. Do you think we find ourselves now in a reverse ching? Yeah, in some ways. In fact, I think maybe the more appropriate analogy is actually, if we roll back to time, I would roll back to the Cold War, where the U.S. and the USSR were competing on an arms race. And essentially, the reason we won was not because we sent a missile and blew up Russia or Soviet Union, is because they bankrupted themselves building military arms. And up to 15%, 20 % of their GDP was building arms that was not creating real value for their society.

1:52:13In some ways, this is what China is doing to us. They're spending one-tenth as much on data centers and getting to 97 % as good. And what we are doing right now, leveraging hundreds of billions of dollars. Last week, NVIDIA announced that they have a$500 billion deal with BlackRock and Carlyle and Blackstone and so forth to essentially securitize chips and compute. This sounds a lot like the subprime issues. Wow.

1:52:50Peter Diamandis:This is the most astonishing thing. And this is also, to your credit, Alvin, the first time I've heard anyone basically analogize the credit, I don't want to say bubble, but the enormous amount of private credit that the West is allocating to compute, analogizing that to a reverse SDI Star Wars moment that could presumably, what you're gesturing at is that could lead to the proverbial Chinese century and the collapse of Western dominance. Is that the thesis? Well, I mean, I hope it doesn't happen, but I think we are pushing ourselves in that way. We're actually right now acting like USSR. And see, what perpetuated the arms race was this missile gap, right?

1:53:34And the idea that, oh, they have more missiles, we have more missiles. And at both cases, they were both having the wrong numbers being provided to the leadership. They said, we need to build more because they have, you know, 30 ,000. We only have 20 ,000. How would they go? And it became we had 70 ,000 or 80 ,000 missiles between us. That would have blown up the world, you know, hundreds of times. There was no need for any of that. And in some ways, we're kind of doing the same thing right now with AI, where we right now, 45 % of the U.S. stock market value is in AI sector. That is a very, very fragile place for us to be.

1:54:14At the height of the internet bubble, I think around 30 % of the stock market was internet companies. I don't know if you guys heard of something called the Buffett indicator. The Buffett indicator is something that says a market is healthy when your stock market is the same value as your GDP. Okay. And at the height of the internet bubble, we were around 120 % of the GDP was the stock market value. Right now, we are at 240 % of the GDP is the U.S. stock market value. Right? In fact, the AI sector alone is worth more than the GDP of America today. That, to me, is a sign that we are in a very, very fragile place, and an economic correction is due.

1:55:07I'm not saying it's going to happen tomorrow, but Buffett's a pretty smart guy, and he's been doing this for a while.

1:55:14Peter Diamandis:Are you saying that the U.S. is the Soviet Union, the USSR, in 1988, or are you saying that the U.S. is Japan in 1989? Well, I mean, I think they're two different. I actually think that we are right now, the overinvestment that we've put into infrastructure for AI, especially when we both, what we just talked about, that it is an industry that will become commoditized. Not saying that AI is not amazing. AI is going to do amazing things. But the companies who are investing it are not going to be the ones that profit from it, right? And that is going to create a major instability in the economics of the country.

1:55:55And if we don't manage it well, it could create a major crisis of what happened in the USSR during the late 80s.

1:56:04Peter Diamandis:So you think we're overvaluing the frontier labs and undervaluing the sort of China AI plus type rest of the economy that should be the applications? Yeah, I think that's a good summary. I'll take the positive side of this. You know, the deployment velocity in China is actually quite a huge gift because it's forcing policymakers here to solve the real bottlenecks, permitting, energy, manufacturing. So that part is at least the good part. The bad part, I think, is what, Alvin, you've talked about, where we're operating like the USSR on some of this industrial policy, and it's not going to sustain.

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1:57:15Alvin, you're advising the U.S. Treasury and the team that's going to the to the Xi Trump negotiations or conversations on September 24th. What how are you advising them? I think the key right now is that we don't need to get to a solution on day one. Right. The success factor of this discussion is not that we come out with a massive framework that solves everything. And by the way, this is just my personal representation, not a representation of anything that's being discussed in any of the other organizations.

1:57:54Peter Diamandis:Disclaimer is noted. Yes. I'm sure, Alvin, you and Jacob Hellberg must be besties at this point. No comment. Yeah, I think that's the thing is if we can come out of these discussions saying that, okay, we're going to have a second discussion, that's already success. And in the past, I think people, there was a discussion in 2024, the dialogue, and there was a lot of disappointment because China didn't come with all their technology people and we didn't come up with a solution. And so they're not really sincere in the dialogue. And I think you need to understand, just like Chinese works on decades for their strategic plans, they also take a lot longer to prepare when they're doing these kind of diplomacy discussions, right?

1:58:49And for example, for the May visit, there was really no discussion on any of this until the day before between US and China. And that to the Chinese was chaotic and very unprofessional. They're like, how can you guys be sending your president here and you haven't talked to us? You know, what do you want to talk about? Right. And the fact that we're now at least, you know, a month in advance of that having discussions, I think it's a good thing. It's a start of more proper dialogue. When Kissinger was doing a lot of these cross-border discussions, he would be there months in advance to talk to the Chinese before they had the visit with Nixon.

1:59:34As you're talking to them, can I suggest something? Yeah. Because it feels to me like the U.S. is focused on having the best model, whereas the real power will come from having the best ecosystem. Yeah. And I think that's what you're pushing anyway. So I'm really thrilled that you're in the middle of those discussions. Well, I think the discussions right now are really more around safety, right? Because the ecosystem versus model thing is a competitiveness of how do we become more competitive as a country or have greater influence or capability? Really, the discussions that are happening to start is to say, how can we keep the world safer?

2:00:13Because we have a shared common interest. And the common interest is that, you know, AI is not being used by bad actors to create instability around the world. That AI itself is not, you know, potentially creating harm to the world on a longer term. Right. And I think that's that's the and there is also the kind of underlying idea of, you know, a nation to nation kind of aggression. And I think those three different things are all being balanced. I would say that the higher priority today would actually be the bad actor, non-state actor risk, which is what Besson said when he was interviewed the day after that discussion.

2:00:59Because he realizes that nation-to-nation aggression has been in balance between superpowers for eight decades. And that doesn't change with AI. And in fact, because if you use AI to hack into somebody's network and then you take down their power grid, that may give you a one or two day or five day advantage. But then there's asymmetric responses to that. And people realize this. So people in the actual national security space, even if we had AGI, even if we had ASI, we're not going to use it to attack. We don't want to do a first strike attack. It doesn't make sense because that just elicits escalation.

2:01:44So non-state actors is something that everybody should be worried about because it is going to happen. It's already happening. I think the ransomware and cyber attacks is up 200 % or 300 % in the last year or two. And it's going to be even worse because of what we've seen. When you start putting 1 ,000 agents all trying to attack a network, at some point they're going to find the hole. You know, so we need to find that that sheer risk requires sheer response. It requires us to share information with each other to have that red line hotline so that we don't have false flag misattribution. I mean, the good news could be that the fact that you have this third party danger means that the concept of an AI national race becomes obsolete because there's a bigger problem I have to solve.

2:02:32Dave Blundin:uh alvin that's exactly why i love your stags uh stag hunt uh analogy it's right on i would use massive numbers in the top left corner there like the benefit is hugely more than five units but i think the cost in the other corners is devastating i would put some big negative numbers but it's the right framework i love that you're you're taking that into the conversations with uh with china on the on the 24th yeah i mean it's existential on those diagonals yeah yeah and then And we placed ourselves in that diagonal. I think that's a self-imposed harm right now.

2:03:07Peter Diamandis:So I think we would be delinquent in this discussion. We've talked quite a bit about the model layer. We've talked about the GPU or chip layer. We haven't talked about the foundry layer of all of US v China. And it would seem to me one of the cruxes at the summit and otherwise is Taiwan and TSMC. And I love, Alvin, your perspective. How does this end? Does this end in your geopolitical analysis? Does this end with China attempting during this geopolitical and demographic window to invade Taiwan and seize TSMC to gain leading foundry node capacity? Does it end with Taiwan retaining its independence and TSMC not having to blow up all of its fabs?

2:03:52Peter Diamandis:Where does this end? So I think there is an assumption right now that some people in D.C. are saying, hey, the reason that China wants to invade Taiwan is to get access to these fabs. And they don't have these fabs, and so this is why they're going to go and attack the island. The reality is that if anybody attacks the island, there is nothing there to be had in terms of workable fabs. So, I probably shouldn't be talking about this, but I was having breakfast. That means you definitely should be talking about it. I was having breakfast with the CTO for TSMC and also a former senior official from the CIA.

2:04:37And the TSMC guy goes, hey, I heard that you guys are going to blow up our data centers if China attacks. Is that true? And the CIA guy says, hey, I can't confirm or deny that. But what we do have is we have a thousand engineers of yours that we know we will fly out before anything happens. So what... And what America cares about right now is that they want to make sure that they can duplicate these capabilities to fabricate the latest chips in America, you know, if anything happens, right? And this is part of what the CHIPS Act was. And so I think there are some good things that came out of the CHIPS Act that, you know, now there is hundreds of millions or hundreds of billions of dollars, actually, that are being put into domestic manufacturing for semiconductors.

2:05:28I was with Intel and IBM, and we were at the time the global dominant player in semi-effectors. But over the last 20, 30 years, we've lost that. We've given it away. Now, if China actually does attack Taiwan, they will not get these fabs. And they realize that. And if you go there, fabs by themselves require materials from all over the world, requires maintenance, requires chemicals, requires supplies. And if they did that, even if they don't blow up, even if the U.S. doesn't blow up the data centers or the Taiwanese don't sabotage their own systems, after a little while, you'd run out of these supplies.

2:06:09They realize that. The reason China cares about Taiwan is not because of the facts. It is absolutely because of a political history. And you know this, right? Essentially, in 1949, the movement of the Taiwanese, the Nationalist Party to Taiwan, and that to them is an uncompleted civil war. And the two countries actually right now is recognized by America, including 190 other countries as being one country. So this is kind of like Hawaii and the U.S. or maybe Puerto Rico and the U.S. They're kind of pseudo part of a one national structure. And it is more of a political and to them a civilizational ending to a long story.

2:07:09That's the main focus. And they've multiple times, ever since, essentially, Deng Xiaoping to now have talked about peaceful re-newification. So I don't think there is an interest or a rush to do any near-term attacks to try to get Taiwan because of chips. I just don't see that.

2:07:30Peter Diamandis:So you don't think there's a backroom discussion somewhere, maybe in connection with the summit? OK, give the U.S. maybe two to three more years to migrate leading-edge node fab capabilities to Arizona or otherwise redomesticate TSMC's capabilities, and then China, OK, fine, you can retake Taiwan because we don't care anymore. So, I don't know if you had a chance to read my paper, The Great Reckoning and the Reconnecting, But it talks about Taiwan in some aspect to say, hey, just like during the 2008 great financial crisis, actually China helped out the U.S. a lot in terms of keeping the financial stability.

2:08:15I don't know how much you guys know about the history there. But essentially, if China actually started to sell T-bills versus buying, it could have completely destabilized the American financial system. And they kept buying. They kept buying at trillions of dollars, which helped to keep interest rates down and so forth. We potentially might have a repeat of this situation if there's a correction in the market due to what's happening right now with the overbuild and the overleverage of the AI sector. Right. And maybe at that point, the Americans or maybe Trump will give a call to Xi and say, hey, can you help us out again?

2:08:59And maybe I'll just be more hands off or be more clear instead of the ambiguity issue. And this is me completely speculating. Wow.

2:09:06Peter Diamandis:This is your war game. Just for clarity, what I hear you saying in your war game is sometime in the next two years, there's a private credit bubble that the U.S. is using to finance its data center build out, the bubble, assuming it exists, pops, and then the U.S. asks China to help financially in return for, what, a quid pro quo regarding Taiwan? Well, not in the sense of here's Taiwan, but to say, hey, as long as you agree to some kind of a peaceful thing and over a mutually agreed term, that we're going to stay out of it, right? Because we've been very involved in the kind of Chinese political or the Taiwanese political sphere for a long time.

2:09:50We've been selling weapons to them for the last 40 or 50 years. And at one point, we used to have soldiers based in Taiwan. We still have advisors right now, military advisors based in Taiwan. So this is like saying if Chinese were selling weapons to Puerto Rico and they were helping fund them, what would America do? And look at what happened in Cuba and how we responded. So I think we need to be sensitive to why this is an issue for the Chinese. And I'm not apologizing for them. I'm not saying that they're right or wrong. But I think it's important for in any negotiation discussion to understand the other side.

2:10:33There's an important for everybody to understand that the U.S. policy towards China-Taiwan is a one-China policy, explicitly stated. Yes. And they leave the tensions, it's called strategic ambiguity. Exactly. I believe it like deliberately ambiguous in terms of how that happens. Alvin, let's wrap up on one last commentary from you. How do you think this next three, four years goes? What are the two couple of big paths that you think we have to pick one or the other? How do you see this next few years playing out? You're talking about for just the AI space in general? AI and the global transformation.

2:11:16So that's actually the whole narrative in that Great Reckoning paper is how the next few years plays out. And what I foresee is that we will soon find that these AI companies, once they go public, or if they go public, their financial will become much more clear. People will start to realize that the value of the AI innovation does not necessarily accrue to them. It may in the near term, right? And they're one of the biggest beneficiaries. But it was also that accrual came from a period when you didn't really have the open source capabilities that we have today. And in fact, if you look at the recent disclosures in terms of where Anthropix revenues were actually starting to flatten out a little bit, it's not, you know, earlier this year, they were growing like, you know, 10x over just a few months, right?

2:12:14And now they've essentially flattened out at the kind of AR in the 70 billion range. Although even though their ARR is$70 billion, their first two quarters was, I think, right now total less than$20 billion in revenue. But they're committed to hundreds of billions in CAMPACs, in debt. There is right now$1.6 trillion of off-the-book debt of the major hyperscalers today. $1.7 trillion. During Enron days, there was$200 million of off-the-book debt. Okay, so just to give some context of the scale of the kind of problems that we are looking at. And if that happens, I think people will actually slow down the construction because the construction right now is all based on the idea that these companies will continue to make money, continue to be able to fund and service their debt.

2:13:11If you look at Amazon and open AI revenues when they talk about AI, most of that, probably more than half of it, comes from two companies. So that is not a very diversified revenue base. And as more and more of the capabilities move to open source, move to edge computing, the dependency on cloud-based premium services will continue to erode. I think that, yeah. We'll shift the bottleneck down the stack to compute electricity, power, et cetera. Yeah, yeah.

2:13:47Peter Diamandis:Although China is also, I mean, maybe present the other side of this. China notoriously dependent on real estate and property development in order to both drive sort of provincial revenues because the provinces are really selling off the real estate or had been selling off real estate to generate their own local revenue. How is it? I mean, I don't want to over analogize, but isn't it isn't there sort of a striking parallel between Alvin? You're pointing to the West, maybe over leveraging compute and data center and for a development and China perhaps over leveraging or over indexing on for humans, real estate development.

2:14:31So actually, you make a really good point. And I think they they did the hard thing. Over the last three years, there's been about a 30 % deflation in total real estate value in China. And they managed it in a way that it was not a crisis. We need to do a soft landing for these things so that it does not create a crisis.

2:14:52Peter Diamandis:We're building the houses for the AIs and China was building the houses for ghosts. Yeah. Well, I mean, no, I think that the ghost town thing, there may be a few, But the reality is that the home ownership right now is something like 70 % in China, and it's probably less than 50 % in America, right? So I don't think we want to over, I guess, parallel these two things. But I think what we can learn is that when the crisis happens, you need to be willing to take some near-term pain. And they did, right? They took major hits in their GDP slowdown. they were growing at 8%, 9%, 10%, and now they're growing at 4 % or 5 % per year GDP, mostly because the real estate sector stopped growing.

2:15:37In fact, it started to decline, and they had to make up for it with other types of industries. Global policy folks are talking about this managed crisis that they've done as a hallmark case study on how to do it in the future. Let me ask you about the managed crisis, actually. Guys, we're going to take one last comment, Dave, last question, then we've got to wrap it up. Alvin, we've got to have you back. We've got 100 more questions, but we'll do that some of the time. Dave, over to you, and then we'll have a response.

2:16:09Dave Blundin:So China is clearly a country coming into a crisis because of the birth rate. You know, the one child per family is catching up in a huge way. The population is aging like crazy. It's a crisis, and that's why the country is so focused on robotics, because they're going to need it more than anyone. But when I was at MIT, there was a class called Just Wars, Total Wars, Nuclear Wars. And I was like, I got to take that class and see what it's all about. And essentially what they taught us in the last third of the class is, look, this is at the height of the Cold War. The U.S. is over here. The Soviet Union is over there.

2:16:42Dave Blundin:And it's a prisoner's dilemma. And so as nuclear weapons get more and more efficient, inevitably, the prisoner's dilemma gets more acute. sooner or later, one country or the other is going to have a ability to destroy the other country with no retribution whatsoever. This is going to destroy the world. In reality, you know, this is where I lost faith in poli sci classes. In reality, it didn't play out that way at all. Like you said earlier in the pod, the Soviet Union bankrupted itself with way too much weapons investment. But it then became obvious that the Soviet Union wasn't really a tight-knit country in any way, shape or form.

2:17:18Dave Blundin:And now we have Ukraine and Russia, both part of the Soviet Union, in a five-year-long, catastrophic, devastating war. And the other satellite entities don't even speak Russian. So I don't have any idea. What is China like? Is it truly unified like the United States? Is it fragmented? Yeah. I mean, I think this is one thing that China has that's very different than a lot of restaurants. It's very homogenous, right? It's probably like 95 % of the population is Han Chinese, right? And everybody speaks Mandarin. And they may speak other local dialects because there are hundreds of local dialects, but they all speak Mandarin and they all, their written script is the same across all the different provinces, right?

2:18:03So I don't think we're going to see the type of issues that you saw with the USSR, even if there was a major economic crisis. And I think they've managed it very well. In fact, they've learned a lot of lessons from the disintegration of the Soviet Union to say, we cannot let that happen, because that would mean hundreds of millions of people would suffer or die. And that is their biggest priority, is social stability, political stability, economic stability.

2:18:33Peter Diamandis:I should just add maybe a fine point, the Uyghurs, ethnic Muslims, ethnic Turks may differ with that assessment regarding ethnic homogeneity and the unity of approach, sort of everyone's Han type characterization of China for the record. I said 95%, right? And so I think there are definitely a few percent, but it is a relatively minority, right? And even the Uyghurs or whoever, they all speak Chinese. They all read Chinese. So there is a common language. And, you know, I think that the desire to succeed is not as prevalent as we tend to portray it in U .S. press. We'll have to save that for next time, I guess.

2:19:30Let's save that for next time. I'll say one thing. I spent a few months traveling around China and my conclusion was the native entrepreneurship in the Chinese people is higher than any other country I've ever seen, just latently. And therefore, if we believe entrepreneurship is a major driver for future success for the world, that's an amazing thing. And I think we're seeing that come out of it. I do want to end with one thing. Go ahead. I think for America to actually be successful in this industry and take advantage of what we've created is actually to think about creating something that's akin to an AI Marshall Plan.

2:20:10So the Marshall Plan post-World War II, we spent around, I think,$15 to$18 billion rebuilding much of Europe and some parts of Asia. And that created a ally of - Created markets for our goods also. Created giant markets for our goods, because at that time we had 50 % of manufacturing. And it created loyalty and allies for eight decades. We need to be thinking more about that type of thing today, but with AI data centers, with AI technology. The same thing that what China is actually doing right now. Their Waco, the AI Corporation Organization, essentially is their AI Marshall Plan. We should be either doing something like that, or we should be working with them to do it together.

2:21:01That's great advice. Yeah. If we did that, we would have a big market to sell our chips. When we stop building data centers here, which we probably will at some point when people start being able to finance it, we're going to need to sell those NVIDIA chips in other places. So we're going to need to sell services. There's a lot of good things that can be had. And we also hopefully will then have a place for the open source models that we create. We start to create frontier open source models, safe ones that both countries agree, both countries start testing and have standards for. then this technology can be diffused to the world without creating a crisis, without creating additional competition and conflict.

2:21:49Dave Blundin:Well, I think what you said back to back there, 95 % of China is ethnic Han. And the U.S. needs a Marshall Plan. But the U.S. has this incredible advantage in that there's no single ethnicity of America to complete grab bag of the entire world. And so the Marshall Plan executed well from the United States. We just keep shooting ourselves in the foot. But if we stop doing that, we're a much better long-term ally for all these countries in the world that have experienced either ethnic genocide, ethnic racism, ethnic slavery. Cleansing. They'd much rather work with the United States if we just give them a chance.

2:22:27Yeah. And we're telling the world the opposite story right now, right? Yeah. There's the advice that we'll end on. Stop shooting foot. All right, Alvin, it's been awesome to have you on. I speak, I think, for all of us on the pod and the viewers when I say it's really great that you're in the middle of these discussions. So push your ideas as hard as you can. We'll do the same on your behalf. We'll definitely would love to have you back again sometime. And on that note, thank you for being with us, and we'll wrap it up for today. Thank you all. Alex, Dave, we'll be back next time. Good questions, Alex.

2:23:06Peter Diamandis:You know what? Someone has to ask them. I like to say my job here is to call the balls and strikes, including regarding China. But thanks for being a good humored recipient of the balls and strike calls.

2:23:18Dave Blundin:No, I'll do it. Thank you. Don't go away. Don't go away. We're going to wrap it up. Don't go away. Thanks.

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