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

Sourced by podcast-ingest on 2026-08-19. Auto-transcribed via AssemblyAI (universal-2, en). Speakers identified by AssemblyAI Speaker Identification using the per-podcast host/regulars hints; the resulting label→name mapping is in the frontmatter. Duration: 2h24m. Episode page: (not provided). Audio: https://traffic.megaphone.fm/DVVTS8448084358.mp3.

Show notes (from RSS)

The mates sit down with Alvin Graylin to discuss China’s AI strategy, the escalating US-China AI race, realistic timelines for ASI, and whether the industry is heading toward a $1.7 trillion AI bubble.

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Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360

Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader.

Dave Blundin is the founder & GP of Link Ventures

Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified

Alvin Wang Graylin is a technology pioneer, entrepreneur, executive, and thought leader with 30+ years of experience delivering innovative products in the AI, XR, cybersecurity, and semiconductor industries. He is the co-author of Our Next Reality: How the AI-powered Metaverse will Reshape the World.

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*Recorded on August 17th, 2026

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Transcript

Peter Diamandis - 1: There seems to be prevailing view around the campuses that ASI is, you know, five to 10 years out, maybe even 20 years. And so I'm really curious what the prevailing view is in China.

Alvin Graylin: They are not behaving like they believe ASI is around the corner.

Peter Diamandis - 2: Why do you believe getting clarity and some resolution on the us, China, AI race is so important right now.

Alvin Graylin: Having a race condition forces people to make irrational decisions. At some point, we will get to a superintelligence type of a scenario. If and when we do, the concept of nations will probably become a lot less important than they are today. 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 a economic correction is due.

Alex: What I hear you saying in your war game is sometime in the next two years, there's a private credit bubble that the US is using to finance its data center buildout. The bubble pop and then the US asks China to help financially in return for what? A quid pro quo regarding Taiwan, I

Alvin Graylin: will tell you this

Peter Diamandis - 2: now that's a moonshot.

Peter Diamandis - 1: Ladies and gentlemen,

Peter Diamandis - 2: welcome to Moonshots, everyone, your number one podcast in all things AI and technology. Your front row seat to the accelerating singularity. I'm here with my magnificent moonshot mates, the original four, including me, AWG, DB2 and Saleem, my brilliant colleagues who every week help me, hopefully you understand what's happening at this incredible rate of speed. I'm Peter Dmanandis, your host and abundance, entrepreneur and evangelist. Welcome to a very special episode of Moonshots Today. Today, our mission is to go deep on China and AI and discuss it with someone who's lived and operated inside both the Chinese and US ecosystems for over 35 years. Alvin, welcome.

Alvin Graylin: Yes, it's great to be here. I watch your show all the time, so I'm glad to be able to chat with all of you.

Peter Diamandis - 1: We're going to quiz you, then I'll ask you trivia as we go.

Peter Diamandis - 2: When do we say drink? What's Alex's favorite term?

Alvin Graylin: His Dyson Swarm. Dyson Swarm.

Peter Diamandis - 2: You gotta build the Dyson Swarm. Drink, Drink, drink. Let me do a proper introduction of Alvin. So, Alvin Wang Graylin is both a friend and someone who's held senior executive roles at HTC, Intel, IBM, Trend Micro, and WatchGuard Tech. He's worked in all five layers of the AI stack. The data centers, chips, PCs, phones, XR glasses and apps. And he's built and founded over four startups two years ago on this channel we were discussing his recent book Our Next Reality. He's now a digital Fellow at the Stanford Institute for Human Centered AI, a Senior Fellow at the Asia Society Policy institute, professor of AI policy at University of Washington. He's currently supporting the U.S. government and for the coming U. S. China AI safety dialogues that's going to be happening on September 24th in D.C. the very next day on the 25th, we have our Moonshots live event. He's lived and operated extensively in the U.S. china and Taiwan with dual master's degrees from MIT in computer science and business. Love having another MIT grad on the show here and an electrical engineering degree from University of Washington. This is a conversation, guys I've been waiting for, for a long time to really go deep and understand what's going on. And Alvin, you're gonna bring a unique perspective on the US and the China AI race. You've argued that the game isn't a prisoner's dilemma, it's a stag hunt. A game theory model about coordination and trust. Alvin is the author of two key papers we're going to link to in the show. Notes below. Beyond Rivalry and Misdiagnosing the US AI The US China AI Race. Last week he just released a new paper around AI security. The biggest AI models are not the biggest threats, where he proposes that it's the smaller AI Models we need to be more worried about and cooperation is the only path towards safety. Alvin just returned from speaking at the World AI Conference in Shanghai where President Xi did the opening keynote. He's had a chance to meet with leadership across all of the Chinese AI labs, discuss AI governance issues with the senior Chinese regulators and policymakers. We'll hear about how they're thinking directly from Alvin. Today's pod is going to be far ranging. We'll be covering topics from China's open weight models, using AI for diplomacy, as well as robots and AI regulation. So very importantly, we'll be discussing the coming U. S. China AI safety dialogues. Want to understand what the objectives are, Alvin, and you know, what you think might be accomplished, so. And we'll close with Alvin's recent substack essay called Great Reckoning before the Reconnecting. Love that you and Alex both have wonderful terminologies and your essay on abundanceism. All right, so let's dive in. There's a lot to cover. Alvin, you know, one of the things that we pride ourselves on the show is disclosing all of our connections. And since we're talking about a sensitive topic here on US China and you've spent two decades operating in China and your bio lists roles like Vice Chairman of Avra, the VR Industry alliance endorsed by the Chinese Ministry of Industry and Information Tech, and a three year professorships at Beihang, which is a defense linked university on the US Entities list. I want our audience to understand the full picture. So if you wouldn't mind so folks can understand where you're coming from, if you'd walk us through those relationships past and present with any Chinese government bodies or government linked institutions, what was your involvement? Anything going on now? Were you compensated? Want to understand your connection to the Chinese government so people understand you are a US citizen. People should know that. But I guess from perspective, point of view, since we're going to be talking about a lot of very sensitive topics, give us your background there, if you would.

Alvin Graylin: Sure, absolutely. And you're right, I'm a US citizen for over 45 years. So I moved here when I was very young. I was born in China, but having worked and lived in China, you have to deal with the government on a daily basis because that's an important part of being functional there. The IVRA industry of VR alliance was an industry association that was endorsed by the government. And if you want it to be a functional organization, it has to be endorsed. And there was 300 plus members. About a third of them were international companies, companies like Nvidia and Samsung and Qualcomm and AMD and Google and so forth. So these are the kind of companies that they're trying to get into to accelerate the industry. When I was working there for htc, who at the time was the head, the leading virtual reality, augmented reality company in the world and I was kind of the head of the organization, the head of the company in China, by the way, HTC is Taiwanese company, so at the time I was working for a Taiwanese company, but we were given a lot of, I guess a lot of influence because we were such an important party and important player in the industry. The Beihai University is a very large university. It's a university of aeronautics and aerospace, but it also was a leading university for virtual reality, augmented reality, and they've been teaching that for over 30 years. And in my role as head of HTC, which was a virtual reality company, they wanted me to teach there on a part time basis and neither of these positions were compensated. After I've Left China in 2024, I've not had any involvement with either of them as well. So just to hopefully clarify where things are, but I think the thing to remember is Is that for you to understand and work with any industry, with any government, you have to understand both sides. And I think this is why having actually close discussions with them, having worked with them at the city level, province level and some national level leadership there, you understand their mindset. And I think that's very important to actually have proper dialogue.

Peter Diamandis - 2: Alex, do you have any other question you wanted to ask?

Alex: Now we'll get into it as we get into it, but this should certainly be an interesting discussion.

Peter Diamandis - 1: We got Alvin's professional bio, but his growing up bio is really interesting too. Why don't you tell us just about your childhood and growing up and then how you got to the States.

Alvin Graylin: It's a super cool story that is a little bit strange, but I was born during the Cultural Revolution. So both my parents were artists and my mother sent a letter to Xi Jin, not to Xi, to Mao Zedong's wife because she had closed the ballet school that my mother had helped co found and was sent to be reeducated. And this is why I was actually born on a Chinese reeducation farm during the Cultural Revolution. So Alex, I do understand some of the downsides of what happens in improperly organized or governed states, but I was able to move here in 1980 when my uncle, my actually grand uncle, helped to sponsor me. My grandmother was a reporter for the New York Tribune back during the Sino Japanese War and she was there reporting, but had to leave my mom behind when the Japanese bombed Pearl harbor. And it took her eight months to get over from Shanghai to Chongqing where the Flying Tigers were. And so, you know, so this is why I was born there and this is why, you know, I'm actually part Ashkenazi, part Scottish and part Chinese. So it's a little bit strange for my generation actually.

Peter Diamandis - 2: Yeah, amazing. And it's worth noting your brother is I guess the first nuclear sub commander in the U.S. navy.

Alvin Graylin: Yeah, yeah, so he was a senior officer in a nuclear submarine actually. So one of the big boomer ones that actually has the capability to destroy nations and in fact three of his four children are now active officers in the US Navy and went to the Navy Academy Annapolis.

Peter Diamandis - 2: This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup Technical Guide for Generative Media gives you a complete blueprint for deploying Google DeepMind's models in production. Images, video, audio, all of it. Real architecture, real results. Find the link in the show notes below. Yeah, we talk on this pod a lot about the fact that the US China AI race is driving a lot of what's going on. This is a lot of important policy happening, and it's in the same way that the U.S. soviet moon race drove the Apollo program. We keep on falling back to the reason for racing in the US on the AI model development is to make sure that we've got, you know, we get to ASI before anybody else. And that's been coloring everything. So I want to get into that on this program. It's important for everyone listening to understand the backdrop of this. So let's kick it off. We've talked a lot about open weight models over the last few weeks on this pod. And Alvin, in your essay Misdiagnosing the US China AI Race, you lay out a staggering shift, right? Chinese open weight models climbed from 2% to 61% of open router traffic in the last two years. Alibaba's Quinn model alone has over 700 million downloads. I'm sure the numbers surpassed since I looked.

Alvin Graylin: It's up to a billion now.

Peter Diamandis - 2: So, yeah, there we go with 180,000 derivative models. And one of the things again we talk about is, you know, when you have an open weight model, it's very easy to fork it and develop it and retrain it yourself. You see that the US export controls on Anthropics Fable 5 backfired spectacularly. Specifically that within 24 hours, China's Z AI released GLM 5.2 under MIT license. In fact, that was the model used to deal with the hugging face debacle. Brazil's Rio built on Quinn. Japanese Sakana released Fugu Ultra. You say that the US denial strategy didn't slow China at all. It accelerated the innovation and alternative ecosystems. And you call this sort of a denial keeps us ahead fallacy. So let me throw out the first question. Why do you believe getting clarity and some resolution on the US China AI race is so important right now?

Alvin Graylin: Yeah, so in fact, this is probably one of the most critical questions that we need to get resolved. Because having a race condition forces people to make irrational decisions. And right now there is a perceived race condition, and it's based on some assumptions that I think are actually misguided or maybe misunderstood, is that there is a perception that there is a finish line. There's a perception that the world is zero sum. There is a perception that whoever gets to AI first or AGI first can somehow rule the world forever. This is a certain segment of the Policy making circles have this belief and a certain portion of Silicon Valley elites have this type of belief. I think that narrative forces the whole discussion into a national security issue when the reality is right now, none of those assumptions are really based on real data. Today we don't know. Well, first of all, we do know that the world is not zero sum as you guys talk about every day, every episode. The world's getting better, we're getting more resources, we're getting more. So it is not a zero sum game. And there is no clear finish line in the sense of as these technologies get better, they're progressing. And as you mentioned, with all of these open source models, when the difference is gap is moving from a year and a half to now, probably two or three months gap between the open source and the closed source models,

E: there

Alvin Graylin: is no finish line where you say, okay, we've won. It's not like the space race, the space race, you say, hey, we've landed on the moon, we've won. There is an end. Whereas an arms race type model that we are in today is a constant spend and a constant pursuit without clear value being returned. But I don't want to take too much of this, but I think this will help set up the conversation that we're having.

Alex: Yeah, maybe just to pull on the thesis, Alvin, I think that's latent that there isn't an end game. I'd love to understand how you think about this. From my perspective, there's an obvious end game. There's space, there's development of the solar system, there's interstellar exploration, all of which I expect to be fulsomely and holistically supported by superintelligence. Surely somewhere among the various scenarios that I assume you're analyzing, there are scientific and engine engineering endgames, quote unquote, that are intrinsically valuable to pursue. Is it your thinking that science and engineering and solving everything as it were, is not the end game? Is there some other non endgame that you have in mind? Do you think that this is sort of a red queen type scenario where intelligence is just sort of endlessly racing as an end to itself? Or, or is there is there an honest to goodness afterwards after the singularity in your mind as it pertains to US v China?

Alvin Graylin: Yeah, so. So I think what you're describing in terms of at some point we will get to a, A, you know, superintelligence type of a scenario. That may be. But if, if, if and when we do, the concept of nations will probably become a lot less important than they are today. The reason that we've created nations, it's actually started with city states, is because we wanted to protect a certain level of resources and we wanted to defend and gain additional resources In a world where we actually do achieve ASI and we get the kind of abundance that Peter and all of you have been talking about for ages, then the need to have separate nations with these type of competition really would not exist. If it still existed, then we would probably have destroyed ourselves

Alex: to make sure then. I understand your thinking on this. Am I understanding correctly that your worldview is basically fulsomely developed? Superintelligence naturally yields to world government on the one hand and everything else, post superintelligence as it were, being solved. And those two, world government and post superintelligence are inextricably linked.

Alvin Graylin: I think that at the point, if we can get a aligned, peaceful superintelligence, then we will naturally move to a more world government, maybe a galaxy government type of a model. But it is not something that I think is imminent and it is, it is not something that will happen without some level of turmoil. Right, so. So I think the important part is about how do we get there.

Salim Ismail: Right?

Alvin Graylin: I agree with you in terms of where the long term goal is going. But right now I don't think in the next two or three or five years, which is what we're really racing against. We're trying to build, well, we're building 10 times more data centers than China is, you know, and to be one or two or three months ahead, it's not clear that the value is actually there.

Alex: And what is just a quick follow up question. What is your perceived timeline for world government and post superintelligence you mentioned it's not 2 to 5 years, is it 10 years? What's the timeline?

Alvin Graylin: I mean, I think the whole evolution of this is going to take probably on the order of decades. Maybe by the end of this now century I think we will get to a point and in fact I think we need to move at a pace that the world can adapt. And trying to move too quickly actually creates a lot of instability in the world. If you look at the prior industrial revolution, it was 80, 60 and 40 years respectively in playing out. And you know, we're talking about this revolution going from, you know, where we are today to the singularity in five years. And according to some folks, that is not a speed that the world can adapt to. Even though Digest. Digest, yeah, because. And when that happens, turmoil happens and you know, it creates instability and they may actually move the civilization backwards.

Salim Ismail: Look, I think a couple of comments here. One is, I think one endpoint that has turned this into an arms race is the idea we may achieve asi. And then you have one party is uncatchable because they've got so much recursive self improvement going on. And that has turned this into an arms race. Whereas in reality this whole thing is a platform race. Right. And so I think this is the point that Alvin makes very appropriately in his commentary. I think the second mother, the elephant in the room that we've just touched

Peter Diamandis - 1: on here is a mother, the mother of the elephant

Salim Ismail: is the fact that we're running the world on an architecture of 17th century nation states and we're trying to run 21st century applications on that 17th century operating system. And it's simply not going to work. A huge chunk of the issues that we see in the world are that fundamental problem.

Peter Diamandis - 2: I mean, I would put forward the notion, the biggest concern is whether a Chinese authoritarian level of AI enablement drives other nations to have to take on that political structure. The US prides itself on freedom, on privacy. If we have privacy, that's a different subject. And, and the question, you know, I think the battle here is US wants to continue its form of government, its form of, of democracy, and not be challenged by an ASI out of China. I think that, I think that's the, ultimately the bottom line.

Salim Ismail: I think that's a good way of putting it.

Alvin Graylin: Yeah. But from that perspective, I think, you know, US and China are actually very aligned, that neither one wants to have a ASI that comes out of nowhere and destroys the system that is available today. Right. So I think there is a common shared interest. And that usually shared interest is how cooperation, dialogue begins.

Peter Diamandis - 1: So, so it's going to come out

Salim Ismail: of Zimbabwe and it's going to be really ugly.

Peter Diamandis - 1: It's a possibility now, actually. The RSI is popping up everywhere. You know, curious though, Alvin, if you said, look there, there seems to be a prevailing view around the campuses that ASI is, you know, five to 10 years out, maybe even 20 years. And then around San Francisco and around the big labs, it's like, look, one, two years maybe. And every year that goes by, they reel it in. For 30 or 40 years that I've been working in AI, every year it goes back a year now it's getting reeled in every single year. And so I'm really curious what the prevailing view is in China. Does the bulk of China, either the population or the government, really believe it's 10 years, 15 years in the future and we have time to just twiddle our thumbs and think about it.

Alvin Graylin: Yeah. So I think the timeline issue is probably one of the biggest disagreements between both these countries as well as between, I think, the average person and maybe some of the folks that are in Silicon Valley. But if you look at the behavior of how the Chinese government is operating, they are not behaving like they believe that ASI is around the corner. If they did, they would not be telling their labs, don't buy the H2 hundreds that the Americans are giving them. They would not be putting out regulation that is slowing them down, which they've had regulations around AI, privacy, data provenance, marking, transparency and marking in public child addiction, anthropomorphism, compromising AI. All these regulations have been around and every single model that is released in China has to be reviewed by the cact, the Cyberspace Administration of China, which again, delays it by weeks or months. So they're seeing this as something that is akin to other technologies that has happened and they understand that general purpose technology usually takes, even when it's invaded and mature, it takes years if not decades to actually diffuse into society. And they're behaving like that. So I think there's definitely a difference between Maybe Beijing and D.C. in terms of how they're looking at it. One thing I will say that there are probably two or three labs in China that are a little bit AGI pilled, not maybe to the level of the Silicon Valley folks, but their goal is very idealistic and aspirational to say, hey, we also want to create AGI. But in general, the majority of China, Chinese labs, as well as Chinese regulators, see this as a technology that is not. Dislike other technologies, maybe.

Alex: Let me pull on that a little bit, Alvin. So what I think I hear you saying is the Chinese Communist Party leadership has not yet perhaps woken up. Assuming you believe the premise that we're in the middle of a singularity and that recursive self improvement is already here, perhaps the CCP has not yet fully woken up to that possibility. What do you think it would take? What technical development, what geopolitical development would it take, assuming that premise is correct, for the CCP to wake up and say, oh my goodness, we need to treat this as a national emergency in order to compete for recursive self improvement? Throw all of these regulatory speed bumps. We've talked about it on the pod in the past. You alluded to reeducation camps. It's been widely reported that China makes all of their own labs, frontier models pass certain ideological tests before they can be released. What would it take for the Chinese government to say, throw caution to the wind in order to compete, we have to just pick whatever cliche you want. We have to go at the speed of light to compete with American recursive self improvement. What would it take?

Alvin Graylin: Well, first of all, maybe I'm probably on a slightly different timeline as you

Alex: in terms of when most of the

Alvin Graylin: world is in a different timeline from Alex. As you guys know, last week you had the pacing, the frontier letter that came out of all the lab engineers and lab heads. This is something that I think think the industry should be looking at in terms of managing to actually slow it down in the sense of if it goes too fast. As I said, the world takes time to adapt. I'm glad that actually more than 1,000 people in the industry and 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 AI safety contingent that is in China telling these stories to the regulators and 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 us The Benguels and the techmarks 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 the World AI Conference, which is their version of pacsilica. But pacsilica from the US that was launched at the end 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 bloc. 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 a 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. And I think 29 countries joined, there's about 25 in the PAX, 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, wouldn't it be good if you actually invited the US to join? They're like, oh, no, it would be amazing if the US would join. We would want them to join and in fact they should join. And I said, well, but if they join, you can't call it Waco because that's a Chinese led organization. They're like, oh, if you guys are interested, we would be open to changing the name. 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.

Alex: Maybe. 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.

Peter Diamandis - 1: 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 us. It's really interesting when you meet the actual players. You've got Elon Musk, Demis Hassabis, 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. Is imminent and do the best we can. 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?

Alvin Graylin: Okay, 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 will make AGI. And it just happens. 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, 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. They did that about five or 10 years ago. When the Central Party initiates these plans, then the provinces say, hey, look what companies are we looking at? Do 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. 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. It is actually very distributed in terms of how their, 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. 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% of the them. Right. So they're actually quite technical.

Peter Diamandis - 2: Yeah, I think that's one of the biggest challenges I had gone to different parts of China, 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. I found that a fascinating distinction.

Peter Diamandis - 1: You know, it also is 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 and expected teamwork or business plan, he said, no, it's what the government's focus is next that determines your success.

Alvin Graylin: Yeah, so. So because this is like a, when you're swimming, you don't want to swim upstream. And what the government does is that it makes the stream flow in the directions of the certain areas that they think are important. And then they let the entrepreneurial nature of the people there and 1.4 billion people and the most number of STEM grads in the world, good things happen. 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.

Peter Diamandis - 2: 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. Is that direction coming from the government? Is that popping up from the entrepreneurs saying, we can distinguish ourselves from US Labs by creating open weight models?

Alvin Graylin: Yeah. So the whole open source strategy, people think, oh, this is Chinese strategy to destroy American economics and politics. The reality is that it's an emergent strategy. In fact, I was talking to friends at Deepseek a little bit after they came out. 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 is very open source minded and 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. In fact, when they first did that, they got their hand slapped because the government's 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 emergence standard. And now at the last Waco or the WAIC announcement, Xi Jinping finally said, hey, we think open source is a good strategy. And 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.

Peter Diamandis - 2: If Deep SEQ 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.

Alvin Graylin: 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, and their Cdance model is a closed model, and 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 US 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. 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 US 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 Kwan variants. Essentially the rest of the world helps you modify and improve your models. That's a great way to leverage the global community of millions of AI researchers. The other thing that's truly important is inference. Right? 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 neo clouds around the world are buying compute hosting these AI models and allows them to distribute their models without the high capex that that the US labs are burdened with.

Peter Diamandis - 1: Hold on, Alvin. I think we need to get back to Alex's question and I 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 deepsea comes out open source as a frontier level model, Opus 4.8 kind of caliber. And Xi Jinping says, if this is so great, why are you open source slightly 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 and he says, open source is now a blessed thing. And then immediately after that, Quinn 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, but walk me through any detail you've got on the psychology that changed Xi Jinping's opinion and on whether to open source these things.

Alvin Graylin: 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 US and saying that whoever controls and creates the AGI becomes the global dominant hegemon? Which aspect do you want to maybe.

Alex: 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 a Western bloc on the other, and these two different arms may be in competition with each other. The ccp, at some point, as superintelligence intelligence 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. How do you think about that?

Peter Diamandis - 1: And I'll answer the other half of it after you're done with this.

Alvin Graylin: So I don't really see them right now seeing AI as a way to create political domination. I see them as looking at this technology to increase their economic influence around the world. That I think is absolutely there.

Alex: 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, it has already achieved dominance over AI through these reported ideological exams that AI models have to go through?

Alvin Graylin: No, 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, those types of adjustments in the models only apply to Chinese hosted models. 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 whether or not they can talk about Tiananmen Square and so forth.

Alex: Tiananmen Square, 1989. 1989, let's just say it exactly.

Alvin Graylin: But to be honest, because everybody already knows this, nobody really cares, but they do it more for formality. But they actually do have other things that they're putting in place in terms of checking for. There's probably a slightly less security mindedness in terms of how much it refuses to answer questions related to maybe viruses or medical other things. But I think there are still definitely those safeguards that are putting in place and those are getting added it 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 US using this model as a weapon, as an aggressive kind of offensive tool. Right? Because then it becomes okay, do we want to like what the Mythos models were essentially held back to say, hey, here's a model that can be done. I think for some right reasons you want to neutered the offensive capabilities before you put it out to the rest of the world. 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 Americans don't want the Chinese financial and their grid to go down. Because when instability happens in any big country, the world suffers. 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.

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Peter Diamandis - 2: Alvin I want to pull on two strings on this topic before we move on. The first is the claims that Kimik 3 and other models were distilled from US 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?

Salim Ismail: Sure.

Alvin Graylin: 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,

Peter Diamandis - 2: which company you're saying OpenAI.

Alvin Graylin: No, anthropic.

Peter Diamandis - 2: Anthropic. Okay.

Alvin Graylin: Yeah. I mean they're the ones that are that are lobbying the government to say hey, we need to, you know, we're being distillation attacked, 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 it distilled within the organizations themselves from larger to smaller. 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. I 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 two or three million dollars. So it's two or three million dollars across three different labs. And for Deep Seq, I think it was only in the thousands of dollars. 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 sense right now. Here's the thing that also just to give comparison, every month Meta spends somewhere between 100 and 200 million dollars on anthropic tokens. They'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 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 Kimmy K3 thing out six months ago?

Alex: The public argument, I mean this has been widely reported that Meta internally is utterly paranoid of being accused of 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.

Alvin Graylin: 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 that same same concerns over doing anything to speed himself up. And only in the last two weeks have they come out with something that is relatively competitive.

Alex: Elon is an interesting case because 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 Kimmy 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.

Peter Diamandis - 1: I can also tell you just from firsthand experience, yeah, 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.

Alvin Graylin: Yeah. 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 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 KV cash usage by 20x, these are not things that you get from distillation. You cannot distill something from somebody that, that other people didn't have. So we can't take that away from them. As Dave said, they're smart people there. They're doing innovative things and that's part of the reasons why they're successful. Probably. I'm sure they have. But same the US models have also distilled from Chinese. I think there was a couple models ago where if you use Chinese to ask anthropic Claude what model you are, and they said, I'm Quinn, when I was at the, at the Alibaba labs. And they were kind of laughing about that too. They're like, yeah, they're just stealing 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 Zuck, he's actually saying distillation is actually a good thing. We don't think distillation should be prevented. And they're kind of jumping on the whole open source thing and they're saying, hey, AI should be free. Right. So, so anyways, I totally agree, by the way.

Peter Diamandis - 1: I totally agree. I think that the future of AI accelerando style Alex, was the past AI is always going to help you create the next AI. That's the inevitable outcome.

Peter Diamandis - 2: It's the way humans do as well. Humans help, you know, create the next generation.

Peter Diamandis - 1: So I think the whole thought traces thing is over. Bloom. I really want to put a pin in one thing Alvin said, which I think 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 2, maybe more like $10 million to get to that same level. 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, not at the. Because anyone can do exactly what Alvin just said.

Peter Diamandis - 2: Salim.

Salim Ismail: Alvin, you said something I want to pull on, which seems to be the

Alex: theme of today's we're pulling on elephants

Salim Ismail: in the world, strings all over the place. You said the US is building a lot more data centers than China is. And I'm finding that very, very surprising. I think maybe there's a difference here. It's clear China is building a massive energy capabilities, but they haven't built a data center layer yet, I'm guessing is what you're saying versus the US 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?

Alvin Graylin: No. So, so they, they are spending a ton more on energy generation. They're, you know, they're building more new energy, new electric generation than the rest of the world combined, right about 10x what the, the US is every year. Now what they're doing is actually they're trying to electrify their society. That's their focus because right now 40% 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 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. And they bring 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 2 cents to 3 cents 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 and 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? No. This is our biggest issue. We don't have compute. So from export control, are we slowing down China? Yeah, I think that export 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. They're actually doing it in international data centers, training it, it and then bring back on a disk or something, you know, so it's, it's. Wait, say that again.

Peter Diamandis - 1: That's, that's incredibly important information.

Alvin Graylin: Oh yeah. I mean, well, this, this is actually not a secret. I mean, I think people in the, in both.

Alex: This has been widely reported.

Alvin Graylin: Yeah. And both sides.

Peter Diamandis - 1: What's the point of a chip embargo? What is the purpose of an embargo?

Alvin Graylin: Well, I, I think it's, it's, it's more, you know, optics than anything right now.

Peter Diamandis - 1: Oh my God.

Alvin Graylin: 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. I think you guys alluded to some of that in your prior episodes. The export controls. Yes, it has slowed down. China 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 would 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 US I had calls with a few of my friends who were in the semiconductor industry and every one of them got got calls saying, hey, would you like calls from the government saying, hey, would you like some extra funding? Would 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 more threads and Camerons and Birens of China would not be as successful or maybe would have gone bankrupt if it wasn't because of American policies. And 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.

Peter Diamandis - 1: Well, what a back to back double whammy that is though. I mean, we knew the chip embargo was misguided and it's going to be one of many government misguided things in the next couple of years. But the idea that, okay, 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 the training because. 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 just port it to another server overnight. 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 that moves all over the world like a liquid. It's everywhere instantaneously. So the chip embargo is completely and utterly backfired and misguided.

Alvin Graylin: Yeah. And unfortunately right now if you talk to the folks in dc, they're doubling down on this. Right. 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 these Chinese to not be accessible? And 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, more geopolitically than economically because then that forces irrational behaviors like shit, they're now trying to keep us from progressing as a nation. Then behavior gets more aggressive and they become more defensive. And I think these.

Peter Diamandis - 1: 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 if it turns out the Kimi K3 level or one model later is capable of full RSI and then spirals to the singularity, 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've made a horrible mistake here. If we release this next thing to

Alvin Graylin: the world, I think if they start, there are 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 were instructed to. 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. How can you escape?

Peter Diamandis - 2: They were incentivized to escape. I would say they were incentivized to go and find the answer.

Alvin Graylin: And they were saying, use whatever tools you have. And by the way, they also let you. That 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. And they're creative systems because that's what their job is. Now, if something went. If these AI systems started to show that even though you didn't tell them to do 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 are on both sides of the ocean, would be much more focused in terms of how do we protect ourselves from a runaway AI.

Peter Diamandis - 2: So, 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?

Alvin Graylin: Yeah, well, the thing is, robots today, 90% of their components are coming from China if we put an embargo on them. In fact, there was rumors now that was funny, that now US 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. Now the American robot companies are going to China and sneaking back components and actuators that they couldn't get in the U.S. i think we need to understand that the world is interconnected. We are highly dependent on each other. This has been a. The globalization concept has been something that's been going on for the last hundred 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, 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 and when policies change it could hurt them. 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, of taking short term hits for long term independence.

Peter Diamandis - 2: We've reported on the fact that there's like 150 humanoid robot companies and Chinese central government and provinces are really incentivizing robotics. 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?

Alvin Graylin: Yeah. So I think we need to separate the kind of bigger automation question from the humanoid robot explosion. Right. There is 150 plus. I think when I was at WAIC there was over 200 robotics companies that were related to humanoids that was demonstrated stuff, which is crazy because the total volume of humanoid robots last year was in the tens of thousands globally. 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 WSE a year ago. There was about 150 labs that was demonstrating large language models. Now there's really 10 that are probably relevant. 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. The automation has already been happening because people know the demographic issues that you're talking about, the one child policy issues. 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. The need for having humans in manufacturing is becoming less and less now. The one thing I do want to point out is, 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. There's very little of these machines being used used in commercial practice. And I think that's the same case for Boston Robotics. Same case for all the. 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 that's really more for show because you could have just had a one arm or two arm little machine doing that at a fraction of the cost and it would have been just as effective. You didn't need a full body to do that. And in fact, when I was talking to the unitry 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 because you have to keep balancing it. When it falls, bad things happen 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. There's all them of of these benefits of actually having a non legged humanoid versus a legged humanoid.

Salim Ismail: Humanoid form factor is terrible.

Alvin Graylin: Yeah,

Alex: Salim, enough with the self loathing.

Alvin Graylin: But I mean, we've evolved because of billions of years of biological evolution. The 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. Right.

Peter Diamandis - 2: 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. on September 24th. And you're advising, I guess the U.S. side of the equation here.

Alvin Graylin: Yeah, yeah. So I mean, I'm part of a large team of other folks that are contributing to that. And I think that the sentiment at the WAC was that, hey, AI has its moment has arrived. When the president of a country comes to a conference, that is the biggest honor that you can get for 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 was that signaled. Okay, 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? And two years ago, a year and a half ago, they came out with something called the AI Plan. I'm sure you guys have probably heard about it, but we've talked about it on the podcast. Oh, perfect.

Salim Ismail: Yeah.

Alvin Graylin: So essentially, I mean, 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. Right. 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, the American AI Action Plan that 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. I think the two countries have a very different focus in terms of their AI plan. There was nothing in the AI plan that says we have to get to AGI, that we have to dominate. 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.

Alex: 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, least a 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 mega cities are. And I just look at Chinese state capacity on the one hand and then on the other hand, and I look at the west, where historically, again, maybe you'd have a different position. Where in the US 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 US 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 US 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 and other Wang Huning style ideological five year plans? What is it that we need to do?

Alvin Graylin: So first let me kind of.

Alex: There's a lot there.

Alvin Graylin: There is a lot there. I think underlying your question, there's an assumption that, hey, there is an ambition to take over the world by building all these technologies. I think this is one of the, I think biggest misunderstandings that America has that. 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, we've expanded. The Chinese actually haven't. They haven't had this idea. They've essentially been in that little sphere of that central space. And they used to call themselves the Middle Kingdom because they thought we already have everything. We don't need to expand 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. And 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

Alex: to say a century of humiliation.

Alvin Graylin: 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 enter, 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? In fact, America has actually moved away from post World War II. We were 50% of the manufacturing capability of the entire world world. 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 going to go to 40 or 45% over the next five or ten years.

Peter Diamandis - 2: In China.

Alvin Graylin: Yeah, in China. This is the thing is, America right now is very good at financial services, creative services, consumer consulting services, things that are informationally driven and things that are Actually highly susceptible to AI exposure for displacement. 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?

Alex: Well, I can answer that one for you and then I'll repose my same question back to you, Alvin. 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 Balmal'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.

Alvin Graylin: We need to separate kind of national strategy from just capitalistic philosophical bent. 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. And that is actually a very unhealthy thing. So here's something I just heard from David Sacks and Gavin Baker on their all in two days ago. He said, Gavin Baker said there's been conversations in Anthropic where Dario 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. 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 or for the world.

Peter Diamandis - 1: It's also greedy out there.

Salim Ismail: I just don't see how that guess there.

Alvin Graylin: Yeah, no, I agree. 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.

Alex: I'd like to though, Alvin, just pull back to the original question, which is you get to be strategy sar. You get to be wang huning 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?

Alvin Graylin: I think re industrialization is definitely needed. The US workforce right now is around 70% is white collar workers. And 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. 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. We're not going to create 300 or 180 million workers going into manufacturing. That's not what I'm seeing. 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, 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. I think that is the labor pool that will be able to absorb the 60 or 70% of displaced future workers.

Peter Diamandis - 2: If you're a McKinsey employee, start getting ready.

Alvin Graylin: If I was a mid tier, low tier McKinsey employee, I'd be very wary 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 an AI system.

Peter Diamandis - 2: 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. It also is having a huge impact on health. Helping you prevent heart disease, one of the key things. I'm here with Dr. Dawn Musailam, our chief medical officer at Fountain. Heart disease has been personal for you as well, hasn't it?

E: It really has, Peter. When 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. Silent killer.

Peter Diamandis - 2: No shortness of breath, no pain, no nothing.

E: No silent killer.

Peter Diamandis - 2: They just don't wake up in the morning.

E: 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 artery disease. 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.

Peter Diamandis - 2: 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@fortunlife.com Peter to find out more and really make sure that you're the CEO of your own health. All right, back to the episode. Let me get Dave and Salim into this a little bit.

Peter Diamandis - 1: Dave, look, what you said a second ago, Alvin, it went by really, really quickly. But it's critically important. 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, it's 10 to 20 years away. We can just open source these things. They're really useful and powerful, but there's 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.

Peter Diamandis - 2: Right.

Alvin Graylin: I think that 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. This goes back to a paper I just released last week called Bigger Models Are not the Most Dangerous. It was released on Cypher Brief, which is a national security outlet in D.C. that is read by most of the national security population. 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. 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. You had 10 to 50 million parameter models for chemicals that were creating

Salim Ismail: kind

Alvin Graylin: of chemical warfare weapons.

Salim Ismail: Right.

Alvin Graylin: You 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 1 to 100 billion parameter cyber models that was as dangerous or more dangerous than the leading Fable five Mythos. And in fact, the harness actually now for cyber is more important than the models themselves. So M. Dash from Microsoft has came out with, I think, a Cybergem score of 95, and Mythos was 83 or 84. What M. Dash did was it took 100 little tiny models and just organize them together to use different skill sets. So 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. 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? How do we make sure that the synthesis machines that will generate these designs into real genetic material are controlled? These are the kind of things that should be higher up in the agenda, and it's not right now.

Peter Diamandis - 2: Yeah, Dave, you said something really important about Chinese models and safety a moment ago, Alvin. We had the US White House step in and say, stop use of Mythos and Fable. Do we see that at all? How does the CCP think about the safety of the models being open source? Is it concerned about that? Is it saying, before you open source this, we need to Put, you know, we need to make sure these are safe for the world to use. Is that going on at all?

Alvin Graylin: Yeah, yeah. I mean, they do testing in addition to some of the propaganda testing that they're doing. You know, part of the CAC regime in testing is for safety. In fact, the UK AISI Security Institute just came out with a new report last month 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. The other thing that was interesting was that there's different levels of attacks, of how many levels of taxing you get to. And for their highest level, none of the Chinese models were able to autonomously attack and control an external system. 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 level and a very small number got to the lower levels, like four or five or something. From a threat security perspective, these models, even though they're just as big as some of the leading US models in terms of size of parameters, they're actually less dangerous. 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, 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.

Peter Diamandis - 1: The flaw in all of that analysis to me is that AI is like a map match. And you know, you can say, okay, here's quin 40B. Look, it doesn't burn. Then you take Qemi K3 and you light it and you're like, oh, this is a match. Okay, now it's burning. And you say, well look, I'm gonna 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, Kimik 3 is a burning match. You can analyze it eight ways till Tuesday by taking it out of the box and trying to attack something with it. And it didn't crack this, it didn't crack that, it didn't crack that. It is capable of improving itself. 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 Kimmies running tomorrow. 5,000. I guarantee you it can improve itself.

Alvin Graylin: 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. The 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. 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? That's what separates Mythos from fable is the harness that says, hey, don't do these things. Things. Right. So 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 effective deploy capability. And larger models have actually a lower effective deployed because of the wrapper that you can put around it.

Salim Ismail: Yeah. So 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. And 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?

Alvin Graylin: Yeah, 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 industry are tiny models. They're tens or Maybe be tens of or hundreds of millions of parameters or maybe a few billion parameters. In fact, if you look at whether drug discovery or legal use cases or open evidence, I think is based on GPT4 was what their system is based on. You look at Harvey, which is the leading legal use case system, it's based on GLM 5.01, right? So I mean, and it was, it was upgraded. It used to be based on some other open source model from, you know, two years ago. So, so they're, they're not, they're not using the latest and greatest. So in, in April this year, I wrote a paper with Eric Brynoson at the Digital Economy Lab and it's called the Enterprise AI Playbook. Right. We went and talked to hundreds of companies, found 50 that successfully deployed them around the world in 10 different countries, 10 different sectors. And 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. You're an organizational guy, so you realize this, 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.

Salim Ismail: There's a study by McKinsey's that in all the AI deployments and companies globally, 6% are working. That'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 off. Given this is a US China kind of discussion, are they seeing the same things in China?

Alvin Graylin: 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, you can't fire me because the AI took my job, you need to find me another job. And the court upheld that. Those type of precedents incentivizes people to say, okay, it's okay for me to adopt these technologies without being afraid of being displaced. And that's not the case in America. We have an at will employment system. You saw the uproar that happened at Meta when Zuck wanted to key lock every single one of his employees. And people are like, so I'm going to train my replacement. Screw you. I think this is also why if you look at the current negative sentiment in the youth today, I mean, every student is having tough time finding jobs and they're just very worried. I'm spending a lot of time in universities and so does Dave. 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.

Peter Diamandis - 1: This is really, really unique actually on that front. But if you go to other very great technical schools like Northeastern or Harvard, there's about 10 or 20% AI adopters on campus and a violently adopted, opposed 70%, 80%. It's just 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.

Peter Diamandis - 2: We've talked about the notion that In China it's 80% of the populace is pro AI in the US, 80% is. The populace is against AI. What's going on in China? I had that conversation with Michael K. So what is the US doing to try and flip this sentiment? Because it's destructive. Why is China so pro AI at the citizen level?

Alvin Graylin: So here it is. Over the last 40 years, people have seen their lives get better and better in China. Right? You've heard the whole 70 or 800 million people have been risen out of poverty and blah, blah, blah.

Alex: The Chinese miracle.

Alvin Graylin: Yeah, yeah, the Chinese miracle. And a lot of that is being attributed to technology, 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, I don't know, some taichi. Now we have it and our lives 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, the one thing about China is that they have a lot more control over the media and they're mostly good news all the time. You're talking about the Crisis News Network, they're essentially the always good news network.

Alex: There we go, Peter. That's the policy prescription, right? Peter, you need to start the Western equivalent of ccp, cctv, top down news control.

Alvin Graylin: No, I mean if you look at what's happening today, what you guys are doing is these essentially the equivalent of the Chinese media system in terms of.

Alex: Moonshots as Western cctv.

Alvin Graylin: No, no, no, in terms of, 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 some new invention came out and some new building went up

Alex: and you know, we've come full circle at this point.

Peter Diamandis - 2: 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, our 100 trillion synaptic connections. And if we're, if there's fear mongering on the news all the time, that's how you think about the world.

Peter Diamandis - 1: Is that true of Chinese movies too? Are they like the US movies are totally dystopian.

Alvin Graylin: Yeah, actually, you know, Chinese games and Chinese movies, you can't show people blood. I mean, are you kidding? No, no, no. So, so this, yeah.

Peter Diamandis - 1: Oh my God. Quentin Tarantino can't go one minute without showing blood.

Alvin Graylin: Well, this is the problem is that every, everything has to go through a, essentially a censorship board so it cannot be too violent and you know, you know, games, you know, so this is why they, when they have blood, they have like green blood instead of red blood, you know, so in games, right, so it's, it's, you know, it definitely every part the of media today is managed in China. So I'm not saying, I mean I'm endorsing it, but from the perspective of what Peter's saying is why do people have a more positive view on the world and on the future is that they see a lot more good than bad.

Peter Diamandis - 2: Amazing.

Alex: 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, to changing governance and cultural mores in China as a result of automation, we see the rise of tongping lying flat in response to 9, 96 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, 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. So I would love maybe Alvin, if we could just peel back the, 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?

Alvin Graylin: No, I think the issues you're pointing out is definitely there, right? The youth unemployment in China is probably around 20%, right? So the youth unemployment in the US is around 9% and the overall unemployment in the US is around 4.3%. So this is why the youth feels very disenfranchised, is because they're not getting jobs. But it's actually worse than that. There's around 42% underemployment. 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. So if you take the 9% plus the 42%, essentially half of college grads are not getting jobs, US or China.

Alex: They're in China here. Yeah.

Alvin Graylin: No, In China it's 20% unemployment in the sense that the actual no jobs is 20%. This is why there's that tangping. The lying flat issue the last few years is that the problem is that young people, because of this one child policy, they've been told how great they are their entire life and 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 grant 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. That is an issue. This also kind of 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. 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.

Peter Diamandis - 2: I want to take us back, you know, 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 influence everybody's life here in one way or another. You argue that the US 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 US China, you know, AI relationships should evolve here. So let me show that slide. Let's talk to that one second. I think it's very important, Alex, at

Peter Diamandis - 1: the end of the hunt we eat the stag. I'm sorry, I wanted to warn you in advance.

Alex: You know what, there are a lot of vegetarian Chinese Buddhists, et cetera. So hopefully this is a vegan stag hunt.

Alvin Graylin: So actually, before I even talk about seconds, I know most people understand the prisoner's dilemma, 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 dilemma, the optimal thing is to say, hey, the other guy did it and I'm going to snitch on him. Right?

Peter Diamandis - 2: In other words, if there was a US 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 for first. But then 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

Alvin Graylin: that would be defecting. So essentially right now the expectation is the other side is going to defect. So I'm going to defect first so that I get hurt less. 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 and then you essentially signal each other. And long term you actually both go to cooperation. Right now in a stag hunt game it's actually, and the prisoner's dilemma essentially is a zero sum game. In the stag hunt game, it's actually a positive sum game. And whether you both defect or you both cooperate, you get a stable 2 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 Jean Jacques Rousseau invented, which is the idea that, that two hunters go into a forest and you could decide today do I go for the rabbits or do I go for the stag? You know, 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 few a month. That's the idea of the stag hunt. 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. And we're going for the giant AGI, the thing that's going to solve everything. When you do that alone, what that creates is the worst situation where it's 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 static 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 stag. That'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 effect, just defect. So it's a self imposed game. So we're playing the wrong theory and you know, using the wrong strategy and playing the wrong game.

Salim Ismail: Right now I use similar framing. You know, the US 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 is playing now. China's playing the hair game.

Alvin Graylin: Yeah, China's playing the hair game. They're saying, hey, I don't need to make the AGI, I just need to make, make good enough AI goes into my industry, I then take that industry, export it to the world. This is what the whole Bell and Row initiative is saying, hey, I'm going to make 150 partner countries in the Bell and Row initiative where they're shipping telecom systems, energy systems, transportation systems, schools.

Salim Ismail: How would you make the AI ecosystem, the American AI AI ecosystem indispensable? What would you do for that?

Alvin Graylin: What I would do is actually create high quality open source. Right, because then you're competing on a

Salim Ismail: even ecosystem to ecosystem.

Alvin Graylin: Ecosystem, 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, right? 90% of people are fine with today's models. I mean, especially when you have things like Kimming, GLM and Deep seq5, you're already at a level that is higher than the needs of the average person.

Peter Diamandis - 1: So if China hadn't forced the issue by open sourcing, suppose there was just OpenAI, Gemini, Anthropic, XAI, all four US companies, would you then say the same thing, that the best thing for America to do is high quality open source because China's forcing the issue?

Alvin Graylin: I think that, well, first of all, we can't roll back history. It is what it is once it's out now, 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.

Alex: I do agree, 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 and 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 regulatorily captured duopoly of anthropic and OpenAI dominating the future light cone and then not unlike maybe by analogy, the Qing dynasty, where the US could have sort of turned inward on itself. Chinese open weight models obtained however, have basically forced open the US 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 Qing?

Alvin Graylin: 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 US and the USSR were competing on an arms race. Essentially the reason we won was not because we. 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. In some ways, this is what China is doing to us. They're spending 1/10 as much on data centers and getting to 97% as good. What we are doing right now, leveraging hundreds of billions of dollars you had 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.

Peter Diamandis - 2: Wow.

Alex: Wait. This is the most astonishing thing. And this, 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. Presumably what you're gesturing at is that could lead to the proverbial Chinese century and the collapse of Western dominance. Is. Is that the thesis?

Alvin Graylin: Well, I hope it doesn't happen, but I think we are pushing ourselves in that way. We're actually right now acting like ussr. What perpetuated the arms race was this missile gap, right? And the idea that, oh, they have more missiles, we have more. 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 30,000. We only have 20,000 on. We did go and it became we had 70 or 80,000 missiles between us that would have blown up the world hundreds of times. There was no need for any of that. In some ways, we're kind of doing the same thing right now with AI, where right now 45% of the US stock market value is in AI sector. That is a very, very fragile place for us to be. At 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. And at the height of the Internet bubble, we were around 120. 20% of the GDP was the stock market value. Right now we are at 240% of the GDP is the US stock market value. 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. I'm not saying it's going to happen tomorrow, but Buffett's a pretty smart guy guy and he's been doing this for a while.

Alex: Are you saying that the US is the Soviet Union, the USSR in 1988, or are you saying that the US is Japan in 89?

Alvin Graylin: 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 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. And that is going to create a major instability in the economics of the country. And if we don't manage it well, it could create a major crisis of what happened in the USSR during the late 80s.

Alex: So you think we're overvaluing the frontier labs and undervaluing the sort of China AI type Rest of the economy. That should be the applications.

Alvin Graylin: Yeah, I think that's a good summary.

Salim Ismail: 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, to solve the real bottlenecks, permitting energy, manufacturing. So it's that part of the key, at least the good part. The bad part, I think is what Alvin, you've talked about where we're operating like the USSR in some of this industrial policy and it's not going to sustain.

Peter Diamandis - 2: On behalf of my Moonshot mates and myself, I'm inviting you to join us at our inaugural Moonshots live event on September 25th in downtown LA. Alex Saleem, Dave and I will be hosting 1500 entrepreneurs, builders and creators, and hopefully you, for a full day dedicated to designing and building your moonshot, shaping your mindset and steering humanity towards an abundant future. Get ready to enjoy incredible networking and an awesome party while walking away with the tools to change the future and the confidence that you can. Seats are limited, admission is competitive. Check it out@moonshots.com Alvin, you're advising the U.S. treasury and the team that's going to the Xi Trump negotiations or conversations on September 24th. How are you advising them?

Alvin Graylin: I think the key Right now is that we don't need to get to a solution on day one. The success factor of this discussion is not that we come out with a massive framework that solves everything, by the way. This is just my personal representation, not a representation of anything that's being discussed in any of the other organizations that you disclaimers not.

Alex: Yes, I'm sure Alvin, you and Jacob Helberg must be besties at this point.

Alvin Graylin: 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 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. 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. And for example, for the May visit, there was really no discussion on any of this until the day before between us and China. That to the Chinese was chaotic and very unprofessional. They're like, how can you guys be standing your president here and you haven't talked to us. What do you want to talk about? The fact that we're now at least a month in advance of that, having discussions. I think it's a good thing 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.

Salim Ismail: As you're talking to them, can I suggest something? Because it feels to me like the US is focused on having the best model, whereas the real power will come from having the best ecosystem. And I think that's what you're pushing anyways. So I'm really thrilled that you're in the middle of those discussions.

Alvin Graylin: Well, I think the discussions right now are really more around safety 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 that are happening to start is to say how can we keep the world safer because we have a shared common interest. And the common interest is that AI is not being used by bad actors to create instability around the world. That AI itself is not potentially creating harm to the world on a longer term. I think that's the. And there is also the kind of underlying idea of 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 Bessen said when he was interviewed the day after that discussion. Because he realizes that nation to nation aggression has been in balance between superpowers for eight decades. That doesn't change with AI. In fact, 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. People realize that. 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. So 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 2 or 3, 100% in the, the last year or two.

Salim Ismail: Right.

Alvin Graylin: So then it's going to be even worse because of what we've seen. When you start putting a thousand agents all trying to attack a network, at some point they're going to find the hole, you know, so, so we need to find that. That share risk requires share 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

Salim Ismail: 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.

Peter Diamandis - 1: Alvin, that's exactly why I love your stag hunt 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 taking that into the conversations with China on the 24th.

Salim Ismail: Yeah, I mean it's existential on those diagonals.

Alvin Graylin: Yeah, we placed ourselves in that diagonal. I think that's is a self imposed harm right now.

Alex: 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, 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, in your geopolitical analysis? Does this end with China attempting during this geopolitical and demographic window to invade Taiwan and see 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? Where does this end?

Alvin Graylin: 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, 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. I probably shouldn't be talking about this, but I was having.

Alex: That means you definitely should be talking about it.

Alvin Graylin: I was having breakfast with the CTO for TSMC and also a former, former senior official from the CIA. And the TSMC guy goes, hey, I heard that you guys are going to blow up our data centers if China attacks. Is that true? The CIA guy says, hey, I can't neither confirm nor deny that. But what we do have is we have 1000 engineers of yours that we know we will fly out before anything happens. What America cares about right now is that they want to make sure that they can duplicate these capabilities, these to fabricate the latest chips in America if anything happens. 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 now there is hundreds of millions or hundreds of billions of dollars actually that are being put into domestic manufacturing for semiconductors. I was with intel and IBM and we were at the time the global dominant player in semiconductors. 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 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 US doesn't blow up the data centers or the Taiwanese don't sabotage their own systems, after a little while you run out of these supplies. They realize that the reason China cares about Taiwan is not because of the fabs. It is absolutely because of a political history. And you know this, right?

Alex: Yes.

Alvin Graylin: Essentially in 19, 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 US or maybe Puerto Rico and the the US they're kind of pseudo part of a one national structure. It is more of a political and to them a civilizational ending to a long story that's the main focus. And they've multiple times ever since essentially Deng Xiaoping to now have talked about about peaceful reunification. 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 you don't

Alex: think there's a back. Just quick question then. You don't think there's a backroom discussion somewhere maybe in connection with the summit? Okay, Give the US maybe two to three more years to migrate leading edge nodes, fab capabilities to Arizona or otherwise redomesticate TSMC's capabilities and then China, okay, fine, you can retake Taiwan because we don't care anymore.

Alvin Graylin: 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 US a lot in terms of of keeping the financial stability. I 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 over leverage of the AI sector. 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? And maybe I'll just be more hands off or be more clear instead of the ambiguity issue. This is me completely speculating.

Alex: Wow, 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 US is using to finance its data center. Build out the bubble, assuming it exists Pops. And then the US asks China to help financially in return for what? A quid pro quo regarding Taiwan.

Alvin Graylin: Well, not in the sense of here's Taiwan, but to say, hey, as long as you agree, agreed 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. We'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, but I'm not saying that they're right or wrong. But I think it's important, important for in any negotiation discussion to understand the other side.

Salim Ismail: There's important for everybody to understand that the US policy towards China, Taiwan is a one China policy, explicitly stated. And they leave the tensions, it's called strategic ambiguity. I think they leave it 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 we think we, you think will kind of. We have to pick one or the other. How do you see this next few years playing out?

Alvin Graylin: You're talking about for just the AI

Salim Ismail: space in general, AI and the global transformation.

Alvin Graylin: So 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 and then 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. In fact, if you look at the recent disclosures in terms of where Anthropic's revenues are actually starting to flatten out a little bit earlier this year they were growing 10x over just a few months and now they've essentially flattened out at the kind of ARR in the 70 billion range. Although even though their ARR is the 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 capex 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. If you look at Amazon and OpenAI revenues when they talk about AI, most of that, probably more than half of it comes from two companies. That is not a very diversified revenue base. As more and more of the capabilities move to open source, move to edge computing, the dependencies on cloud based premium services will continue to, to erode. I think that, yeah, we'll shift the

Salim Ismail: bottleneck down the stack to compute electricity, power, etc.

Alvin Graylin: Yeah, yeah.

Alex: And 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 the real estate to generate their own local revenue. How is, I mean I don't want to over analogize, but isn't there sort of a striking parallel between. Alvin, you're pointing to the west, maybe over leveraging compute and data center infrared development and China perhaps over leveraging or over indexing on for humans real estate development.

Alvin Graylin: So actually you make a really good point and I think they did the hard thing. Right. 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.

Alex: We're building the houses for the AIs and China was building the houses for ghosts.

Alvin Graylin: 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, to be willing to take some near term pain. And they did. 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. In fact, it started to decline and they had to make up for it with other types of industries.

Salim Ismail: So global policy folks are talking about, about this China, this managed crisis that they've done as a, as a hallmark case study on how to do it in the future.

Peter Diamandis - 1: Let me ask you about the managed crisis actually, because China.

Salim Ismail: Guys, we're going to take one last comment. Dave, last question and then we've got to wrap it up. Alvin, we got to have you back. We got 100 more questions, but we'll do that some other time.

Peter Diamandis - 2: Dave, over to you.

Salim Ismail: And then we'll have a.

Peter Diamandis - 1: 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, the. But this is at the height of the Cold War. The US is over here, the Soviet Union's over there, 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 an ability to destroy the other country with no retribution whatsoever. This is going to destroy the world. In reality, this is where I lost faith in polycyclos. 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. 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 Russia.

E: Russian.

Peter Diamandis - 1: So I don't have any idea what is China like? Is it truly unified like the United States? Is it fragmented?

Alvin Graylin: Yeah, I mean, I think that 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 you know, they may speak other local dialects because there are hundreds of local dialects, but they all speak Mandarin and they all. The written script is the same across all the different provinces. 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, 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, would suffer or die.

Salim Ismail: Right.

Alvin Graylin: And that is their biggest priority is social stability, political stability, economic stability.

Alex: I should just add maybe fine point. The Uyghurs, ethnic Muslims, ethnic Turks may differ with that assessment regarding ethnic homogeneity and the unity of oppression approach. Sort of everyone's Han type characterization of China.

Alvin Graylin: For the record, I said 95%.

Salim Ismail: Right.

Alvin Graylin: 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 I think that the desire to succeed is not as prevalent as we tend to portray it in US Press.

Alex: We'll have to save that for next time.

Salim Ismail: I guess I'll 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.

Alvin Graylin: I do want to end with one thing.

Salim Ismail: Go ahead.

Alvin Graylin: 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 a AI Marshall Plan. So the Marshall Plan post World War II, we spent around, I think 15 to 18 billion dollars rebuilding much of Europe and some parts of Asia. And that created a ally, created markets for our goods, also created giant markets for our goods because at that time we had 50% in manufacturing and it created loyalty and allies for, 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.

Peter Diamandis - 1: That's a great advice.

Alvin Graylin: 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 stop 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. We're going to need to. There's a lot of good things that can be had and we also hopefully will then have a place to. 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.

Peter Diamandis - 1: Well, I think what you said back to back there, 95% of China is ethnic high. 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. It's a 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 slave slavery cleansing, they'd much rather work with the United States if we just give them a chance. Yeah.

Alvin Graylin: And we're telling the world the opposite story right now, right?

Salim Ismail: 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 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.

Alvin Graylin: Thank you all.

Salim Ismail: Alex Davis. Peter will be back next time.

Alvin Graylin: Questions.

Alex: Alex, you know what someone has to ask them. I like to say my job here is to call the balls and strikes, including requests regarding China. But thanks for being a good humored recipient of the balls and strike calls.

Alvin Graylin: Okay, thank you.

Peter Diamandis - 1: Don't go away. Don't go away.

Salim Ismail: Thanks.

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