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

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. Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends 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. Alvin’s Papers: 
 The Biggest AI Models Are Not the Biggest Threats: https://www.thecipherbrief.com/the-biggest-ai-models-are-not-the-biggest-threats Misdiagnosing the U. S.–China AI Race: Recalibrating America’s Approach to an Incomplete Strategy: https://centerforchinaanalysis.asiasociety.org/p/misdiagnosing-the-uschina-ai-race Beyond Rivalry: A US-China Policy Framework for the Age of Transformative AI: https://www.digitalistpapers.com/vol2/graylin – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding Get the blueprint for generative media https://goo.gle/startupgenmedia Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter Join the Moonshots Mates on Sep 25th for the inaugural Moonshots LIVE. The world's greatest entrepreneurs, builders and creators, working together to build a hopeful and optimistic vision of tomorrow. Seats are limited and application only. Apply at moonshots.com before seats are sold out. _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Join Salim’s 10X Shift Subscribe to Salim’s YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack Spotify Threads Connect with Alvin LinkedIn X Instagram Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS: Instagram TikTok X Threads – *Recorded on August 17th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:00Speaker 00

  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 so I'm really curious what the prevailing view is in China.

• 0:10Speaker 01

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

• 0:14Speaker 02

  Why do you believe getting clarity and some resolution on the US-China AI race is so important right now?

• 0:21Speaker 01

  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.

• 0:48Speaker 03

  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 pops and then the US asks China to help financially in return for, what, a quid pro quo regarding Taiwan?

• 1:06Speaker 01

  I will tell you this.

• 1:07Speaker 00

  Now, that's the Moonshot, ladies and gentlemen.

• 1:12Speaker 02

  Welcome to Moonshot, 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 D. Maddes, your host and abundance entrepreneur and evangelist. Welcome to a very special episode of Moonshot 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 technology

• 1:57Speaker 02

  ecosystems for over 35 years. Alvin, welcome.

• 2:01Speaker 01

  Yes, it's great to be here. I watch your show all the time, so I'm glad to be able to chat with Al.

• 2:07Speaker 00

  We're gonna quiz you then. I'll ask you trivia as we go.

• 2:10Speaker 02

  When do we say drink? What's Alex's favorite term?

• 2:15Speaker 01

  It's Dyson's form.

• 2:17Speaker 00

  Dyson's form.

• 2:18Speaker 02

  Yes, you got it.

• 2:19Speaker 00

  Drink, drink, drink.

• 2:21Speaker 02

  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

• 3:05Speaker 02

  the US government and for the coming US-China AI safety dialogues. That's gonna be happening on September the 24th in DC. The very next day, on the 25th, we have our Moonshot's live event. He's lived and operated extensively in the US, 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

• 3:46Speaker 02

  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 gonna link to in the show notes below, Beyond Rivalry and Misdiagnosing 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

• 4:28Speaker 02

  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, you know, how they're thinking directly from Alvin. Today's pod's gonna be far ranging. We're gonna 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 US-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

• 5:12Speaker 02

  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 professorship

• 5:52Speaker 02

  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, you know, 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? I want to understand your connection to the Chinese government, so people understand, you know, you are a US citizen. People should know that. But I guess from a perspective point of view, since we're gonna be talking about a lot of, you know, very sensitive topics, give us your background there, if you would.

• 6:33Speaker 01

  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, you know, having worked and lived in China, you have to deal with the government on a daily basis, because that's, you know, an important part of being functional there. The AVRA, 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, right? So, and there was 300-plus members, and 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, you

• 7:16Speaker 01

  know, they're trying to get into to accelerate the industry. When I was working there for HTC, who, you know, at the time was the head of the leading virtual reality, augmented reality company in the world, and, you know, and I was kind of the head of the organization, the head of the company in China, right? So, and by the way, and HTC is a 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 Beihang University is a very large university. It's a university

• 7:58Speaker 01

  of aeronautics and aerospace, but it also is the, 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. So, and, you know, I've, 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 that for you to understand and work with any industry, with any government,

• 8:40Speaker 01

  you have to understand both sides. And I think this is, this is why, having actually close discussions with them, having, you know, 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.

• 8:57Speaker 02

  Alex, do you have any other question you want to ask?

• 9:00Speaker 03

  Yeah, we'll get into it as we get into it. But this should certainly be an interesting discussion.

• 9:06Speaker 01

  Yeah.

• 9:06Speaker 00

  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? And it's a super cool story.

• 9:18Speaker 01

  That is, it's 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 Jinping, not to Xi Jinping, to Mao Zedong's wife, because she had closed the ballet school that my mother had helped cofound 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

• 10:03Speaker 01

  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.

• 10:20Speaker 01

  And it took her eight months to get over from Shanghai to Chongqing, where the Flying Tigers were. And so this is why I was born there. And this is why I'm actually part Ashkenazi, part Scottish, and part Chinese. So it's a little bit strange for my generation, actually.

• 10:42Speaker 02

  Yeah, amazing. And it's worth noting, your brother is, I guess, the first nuclear sub-commander in the US Navy?

• 10:52Speaker 01

  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. But in fact, three of his four children are now active officers in the US Navy and went to the Navy Academy in Annapolis.

• 11:14Speaker 02

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• 11:41Speaker 02

  Yeah, and 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 US-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 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.

• 12:27Speaker 02

  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 Quen model alone has over 700 million downloads. I'm sure the numbers surpassed since I looked.

• 12:47Speaker 01

  It's up to a billion now, so.

• 12:49Speaker 02

  Yeah, there we go. With 180,000 derivative models, and one of the things, again, we talk about is when you have an open-weight model, it's very easy to fork it and develop it and retrain it yourself. You say that the US export controls on Anthropic's 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 Quen. Japanese Sakana released Fugu Ultra. You say that the US denial strategy didn't slow China at all.

• 13:33Speaker 02

  It accelerated the innovation and alternative ecosystems. And you call this sort of a denial-keeps-us-ahead fallacy. Right? 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?

• 13:52Speaker 01

  Yeah, so in fact, this is probably one of the most critical questions that we need to get resolved, because it's 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 AGI first can somehow rule the world forever. Right?

• 14:30Speaker 01

  And this is a certain segment of the policymaking circles have this belief, and a certain portion of Silicon Valley elites have this type of belief. Right? So 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.

• 15:02Speaker 01

  Well, first of all, we do know that the world is not zero-sum. I mean, as you guys talk about every day, right? Every episode, the world's getting better. We're getting more resources. We're getting more abundant. So it is not a zero-sum game. And there is no clear finish line, right? In the sense of, as these technologies get better, they're progressing. And as you can, 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, there is no finish line where you say, okay, we've won. Right? It's not like the space race, right?

• 15:45Speaker 01

  The space race, you say, hey, we've landed on the moon, we've won. There is an end. Whereas a arms race-type model that we are in today is a constant spend and a constant pursuit without clear value being returned. So, but I don't want to kind of take too much of this. But I think this will help set up the conversation that we're having.

• 16:08Speaker 03

  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 engineering "end games" that are intrinsically valuable to pursue. Is it, is it you're thinking that science and engineering and solving everything, as

• 16:51Speaker 03

  it were, is not the end game? Is there some other non-end game 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 is there an honest-to-goodness afterwards, after the singularity, in your mind as it pertains to US v China?

• 17:15Speaker 01

  Yeah, so I think what you're describing in terms of, at some point, we will get to a, you know, superintelligence-type of a scenario. That may be. But if and when we do, the concept of nations will probably become a lot less important than they are today. Right? The reason that we've created nations, it's actually started with city-states, right? 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

• 17:57Speaker 01

  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. Right?

• 18:18Speaker 03

  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?

• 18:40Speaker 01

  I think that they're 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 not something that will happen without some level of turmoil, right? So I think the important part is about how do we get there, right? I agree with you in terms of where the long-term goal is going, but right now, I don't think in the next, you know, two or three or five years, which is what we're really racing against, we're trying to build, we're building 10 times more data centers than China is, you

• 19:22Speaker 01

  know, and to be one or two or three months ahead, it's not clear that the value is actually there.

• 19:29Speaker 03

  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 two to five years, is it 10 years? What's the timeline?

• 19:41Speaker 01

  I mean, I think the whole evolution of this is going to take probably on the order of decades, maybe, you know, by the end of this 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 nest revolutions, it was 80, 16, 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, according to some folks.

• 20:25Speaker 01

  That is not a speed that the world can adapt to, even though-

• 20:30Speaker 02

  Digest.

• 20:31Speaker 01

  Digest, yeah. Because, and when that happens, turmoil happens and, you know, it creates instability and then they actually move the civilization backwards.

• 20:41Speaker 04

  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 on here-

• 21:15Speaker 03

  There's a mother, the mother of the elephant.

• 21:17Speaker 04

  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.

• 21:37Speaker 02

  Yeah, 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, right? The US prides itself on freedom, on privacy. If we have privacy, it's a different subject. And the question, you know, I think the battle here is US wants to continue its form of government, its form of democracy and not be challenged by an ASI out of China. I think that's ultimately the bottom line.

• 22:21Speaker 04

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

• 22:23Speaker 01

  Yeah, but from that perspective, I think, you know, US and China are actually very aligned, that neither one wants to have an 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, so.

• 22:44Speaker 04

  It's going to come out of Zimbabwe and it's going to be really ugly.

• 22:48Speaker 00

  That's a possibility now, actually. The RSI is popping up everywhere. You know, curious though, Alvin, if you said, look, there seems to be prevailing a view around the campuses that ASI is, you know, five to 10 years out, maybe even 20 years. And then around the 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. You know, 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. You know, 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, you know, just twiddle

• 23:33Speaker 00

  our thumbs and think about it?

• 23:34Speaker 01

  Yeah, so I think, you know, the timeline issue is probably one of the biggest kind of disagreements between both these countries as well as, you know, 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, right? If they did, they would not be telling their labs, don't buy the H200s that the Americans are giving them. They would not be putting out regulation that is slowing them down, which, and they've

• 24:15Speaker 01

  had regulations around AI, you know, privacy, data provenance, marking, you know, transparency and marking in public, child addiction, you know, anthropomorphizing AI, all these regulations have been around. And every single model that is released in China has to be reviewed by the CAC, the Cyberspace Administration of China, which again delays it by, you know, weeks or months, right? So they're seeing this as something that is akin to other technologies that has happened and, you know, they understand that general purpose technology usually takes, even when

• 24:52Speaker 01

  it's, you know, 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 DC 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, you know, their goal is very kind of idealistic and aspirational to say, hey, you know, we also want to create AGI.

• 25:33Speaker 01

  So, 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.

• 25:46Speaker 03

  Maybe 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?

• 26:28Speaker 03

  Throw all of these regulatory speed bumps, the, we've talked about it on the pod in the past, the, you alluded to re-education 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?

• 27:03Speaker 01

  Well, first of all, maybe I'm probably on a slightly different timeline as you in terms of-

• 27:08Speaker 03

  I know, I know.

• 27:14Speaker 01

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

• 27:55Speaker 01

  And there are actually multiple safety institutes and a safety, AI safety contingent that is in China telling these stories to the regulators and they hear it. In fact, you know, at the World AI Conference, there was multiple discussions and forums specifically around AI safety. So, and there was people from the US, you know, the Benjules and the Techmarks were also there to, you know, add these type of points to the agenda. So, 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.

• 28:40Speaker 01

  In fact, you know, I think it's on the agenda to talk about these, the World AI Cooperation Organization, which they had announced at, on the first day of the World AI Conference, which is, you know, their version of Paxilica. But, you know, Paxilica from the US that was launched at the end of last year was a US-led organization that was talking about how do we keep US dominance and leadership in AI? And which allies are we going to pick to be on our side? So it creates a block to say, you know, we want to be the winning block. Whereas what they announced was to say, hey, look, we want to create a global organization, make AI a public good, make it shared, and everybody shares in the benefit.

• 29:25Speaker 01

  Anybody that wants to join can join. And, you know, 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. You know, so there's about 25 in the Paxilica. So it's creating two blocks. But, so here's, here's something that is interesting is I actually talked to one of the people that was involved in organizing this. And I said, look, you know, wouldn't it be good if you actually invited the US to join? They're like, oh, no, we would, 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 you know, if they join, you can't call it, you know, Waco, because that's a Chinese-led organization.

• 30:07Speaker 01

  They're like, oh, you know, if you guys are interested, we would be open to changing the name. You know, we would be open to having a truly global organization. So I think with this narrative of a us and them and, you know, they're trying to take over their world with their AI, I don't really see that.

• 30:25Speaker 03

  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.

• 31:04Speaker 03

  What threshold of superintelligence, either achievement or technical development, or maybe implications for weapons systems, if that's really what it takes? What technical achievement would superintelligence have to pass or what threshold would it have to achieve in order for the CCP to decide in your mental model? Gosh, we really just have to focus on supremacy here.

• 31:29Speaker 00

  Alvin, if you don't mind, let me, let me intercept and lead into that question, too. Because I think, I think we really do need to answer Alex's question. But before we can do that, like, let's understand who the CCP is. You know, in the, in the US, it's really interesting when you meet the actual players. So you've got Elon Musk, Dennis Asavas, 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, and so we have to just live within the reality that AGI 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.

• 32:14Speaker 00

  And that's the dynamic. And when you, when you meet them individually, you realize, wow, these are just regular, everyday people in the hot seat. And you interact and you see how they communicate and it changes the future of the world. So then I envision the CCP and I picture people in their 70s, kind of up on a hill, completely disconnected with the details, but maybe that's wrong. I have no idea. What is the CCP, first of all?

• 32:36Speaker 01

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

• 33:21Speaker 01

  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, you know, give them some, you know, stipends, give them, you know, free recruiting, give them some, some kind of benefits, right? And they will have essentially provincial champions and city champions. And this is, and then, you know, the 30-plus provinces all compete against each other to see who can make companies that solve some of these problems. Right? So it is, 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 know, you need to share your resources.

• 34:05Speaker 01

  They're, they're actually a very highly competitive landscape between all of these labs. Right? 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 them. Right? So they're, they're actually quite technical.

• 34:26Speaker 02

  Yeah, I think that's one of the biggest, you know, 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, from the CCP leadership. And the thing that was most striking is in the US, most of our politicians are lawyers. And in China, most of the politicians are engineers. I found that a fascinating distinction.

• 34:55Speaker 00

  You know, it's 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 he expected teamwork or business plan. He said, no, it's what the government's focus is next that determines your success.

• 35:14Speaker 01

  Yeah. So because this is like a, when you're swimming, you don't want to swim upstream. And what, what the government does is that it makes the, the stream flow in the directions of the certain areas that they think are important. And then they let the entrepreneurial nature of the people there, you know, 1.4 billion people and the most number of STEM grads in the world, good things happen, right? And that's, 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, you know, it also brings the quality of life up for the overall population.

• 35:52Speaker 02

  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?

• 36:09Speaker 01

  Yeah. So the whole open source strategy, people think, oh, this is a Chinese strategy to destroy American economics and, you know, pop this bubble. The reality is that it's an emergent strategy, right? And in fact, you know, I was talking to friends at DeepSeek a little bit after they, they came out. And, you know, before that, nobody knew who they were, right? They were not on their radar. They were not funded by the government. Nobody told them to, to open source. But the CEO of the company was very open source minded. And he, he thought that, hey, open sourcing is something that I should do because this is a great technology, I want to share it with everyone. And in fact, when they first did that, they got their hands slapped because the government's like, hey, this is such a great model, why are you open sourcing it?

• 36:53Speaker 01

  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, right? And then essentially, most of the companies in China were following this because it became kind of the de facto emergent standard. And now, at the last Waco or the WAIC announcement, Xi Jinping finally said, hey, we think open source is a good strategy. And that 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.

• 37:32Speaker 02

  If DeepSeek had been a closed model that succeeded, do you think China would have gone that direction? Is it really just that seed led to this incredible open-source movement in China?

• 37:45Speaker 01

  Well, I mean, there were open and closed models for the whole time, right? In fact, if you look at ByteDance, they have the DoBao model, which is a closed model, right? And their C-Dance 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, right? You had mentioned the export controls earlier. And export controls, you first talked about export controls and the software export controls of Fable.

• 38:27Speaker 01

  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. And 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

• 39:09Speaker 01

  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 Quen variants. Essentially, the rest of the world helps you modify and improve your models, right? And that's a great way to leverage the global community of millions of AI researchers. The other thing that's truly important is inference, 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 NeoClouds around the world are buying compute, hosting these AI models, and allows them to distribute their models without the high

• 39:53Speaker 01

  capex that the US labs are burdened with.

• 39:56Speaker 00

  Hold on, Alvin, I think we need to get back to Alex's question, and I'd love to drill in. Like, I think we have an opportunity here where you have firsthand knowledge from friends at DeepSeek around, I think, what is going to turn out to be one of the most pivotal moments in human history. The decision where DeepSeek comes out, open source is a frontier-level model, Opus 4.8 kind of caliber, and Xi Jinping says, if this is so great, why are you open source? Slap their 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.

• 40:38Speaker 00

  And then immediately after that, Quen is out, and then Kimi K3. And I think the release of Kimi K3 will turn out to be as defining a moment in human history as anything that's ever happened. That's my prediction. But I think the psychology behind that choice is going to be the news nugget that matters for all time now and leads into Alex's question of what would it take for a wake-up call? If it turned out that was a colossal error, what event would have to happen? And I'm not saying that's the case. I know the opinion in China is that that's not the case. But walk me through any detail you've got on the psychology that changed Xi Jinping's opinion on whether to open source these things.

• 41:16Speaker 01

  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, right? So which aspect do you want?

• 41:41Speaker 03

  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 capabilities continue to increase, may be forced to decide whether it prefers either retaining domestic control on the one hand

• 42:22Speaker 03

  or seeking to continue to rise geopolitically on a global stage. How do you think about that?

• 42:28Speaker 00

  And I'll answer the other half of it after you're done with this.

• 42:33Speaker 01

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

• 42:54Speaker 03

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

• 43:17Speaker 01

  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 types of adjustments in the models only apply to Chinese hosted models, right? So if a model coming from these labs are then put on Hugging Face, all of those types of guardrails are actually removed in terms of whether or not they can talk about...

• 43:48Speaker 02

  Tiananmen Square in 1989. Let's just say it.

• 43:53Speaker 01

  Exactly. But to be honest, that's because everybody already knows this, nobody really cares, but they do it more for formality, right? But they actually do have other things that they're putting in place in terms of checking for, you know, there's probably a slightly less security-mindedness in terms of how much it refuses to answer questions related to maybe viruses or medical or other things. But I think there are still definitely those safeguards that are put in place, and those are getting added more and more every day because of these kind of issues. What I think would get them to be really concerned, if they start to see the US using

• 44:37Speaker 01

  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. And I think for some right reasons, you want to neuter the offensive capabilities before you put it out to the rest of the world. So this is actually a good thing. But in some cases, I would actually think that it would make sense, rather than having 50 companies that are being allowed, is actually to allow most government organizations to

• 45:19Speaker 01

  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 then Americans don't want the Chinese financial and their grid to go down. Because when instability happens in any big country, the world suffers, right? And smart people understand this. But too many, I think, folks with relatively narrow perspectives think that one country wants to actually have another country fail. Having major superpowers fail creates irrational actions.

• 46:01Speaker 01

  And societal stability usually is the preeminent priority of most major governments.

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• 47:15Speaker 02

  Alvin, I want to pull on two strings on this topic before we move on. The first is the claims that Kimi K3 and other models were distilled from US closed models. Your thoughts, what is being said in China about that? And then the second is the policies, you know, limiting CHIPS and limiting access to Fable 5. Your belief is those policies were misdirected, and can you explain why on that?

• 47:44Speaker 01

  Sure. So the distillation thing, you know, it's, 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-

• 48:01Speaker 02

  Which company? You're saying OpenAI?

• 48:03Speaker 01

  No, Anthropic.

• 48:05Speaker 02

  Anthropic, okay.

• 48:06Speaker 01

  Yeah, I mean, they're the ones 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 distill within the organizations themselves, from larger to smaller ones. And in fact, if you look at the numbers of what Anthropic put out, they were saying that, you know, 20,000 accounts from three different labs in China and, you know, a million or two questions that were came in. I went back and actually did a estimate of what it would cost to do the number of queries based on the average responses on their highest models. And it was like $2 or $3 million, right?

• 48:51Speaker 01

  So it was $2 or $3 million of across three different labs. And for DeepSeek, I think it was only in the thousands of dollars, right? So the numbers sound big when you look at them in isolation, but when you look at them in aggregate, it really doesn't mean much. If you have a model that you spend a billion dollars on and somebody can distill and duplicate with a couple million dollars, then the whole economics of Frontier AI doesn't make sense, right? Now, here's the thing that also, just to give comparison, every month, Meta spends somewhere between $100 and $200 million on Anthropic tokens, right? They're one of the biggest buyers of AI from Anthropic.

• 49:32Speaker 01

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

• 50:02Speaker 03

  Well, the public argument, I mean, this has been widely reported, that Meta internally is utterly paranoid of being accused of distilling Anthropic traces and actively encouraging their engineers, "Don't use it, don't overuse it, don't you dare allow any Anthropic reasoning traces into the development of the Muse series." They're utterly afraid of being sued by Anthropic for reasoning trace distillation.

• 50:26Speaker 01

  I'm not sure if I agree with that, given how many, you know, how much they're spending. But here, let me give you an example. What about XAI, right? They also have access to these, and I don't think Elon has the same concerns over doing anything to speed himself up, right? And only in the last two weeks have they come out with something that is, you know, relatively competitive, right?

• 50:51Speaker 03

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

• 51:32Speaker 00

  Well, I can also tell you, just from firsthand experience-

• 51:34Speaker 03

  Yeah.

• 51:35Speaker 00

  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 DeepSeek, Quen and Kimi. 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, you know, they've fired everybody and started over. So for whatever reason, the Chinese people working on it, though, are brilliant and far, far better than those teams were.

• 52:05Speaker 01

  Yeah, so, 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, you know, organizations, right? And they are actually innovating. It's not that distillation was why they're successful. If you look at, you know, how they were able to reduce, you know, their KB cash usage by like, you know, 20X, and, you know, these are not things that you get from distillation. You cannot distill something from somebody that other people didn't have. So we can't take that away from them. You know, as Dave said, they're smart people there, they're doing innovative things, and that's part of the reasons why they're successful. You know, they distill, probably. I'm sure they do. But same, you know, the US models have also distilled from Chinese, right?

• 52:46Speaker 01

  I think there was a couple models ago where if you use Chinese to ask Anthropic, Claude, "What model are you?" And they said, "I'm Quen." Right? So, you know, and when I was at the Alibaba Labs, and they were kind of laughing about that, too. They're like, "Yeah, they're distilling from us. We just can't tell because they already downloaded our models, so we don't know," right? But I don't think that the whole distillation issue is really as big. In fact, if you look at what happened last week with Zuck, you know, he's actually saying, "Distillation is actually a good thing. We don't think distillation should be prevented." And, you know, they're kind of jumping on the whole open source thing, and they're saying, "AI should be free," right? So, anyways.

• 53:28Speaker 00

  I totally agree, by the way. I totally agree. I think that the future of AI, accelerando style, Alex Wissner-Gro style, the past AI is always going to help you create the next AI. That's the inevitable outcome.

• 53:40Speaker 01

  It's what humans do as well.

• 53:42Speaker 00

  Yeah, exactly.

• 53:43Speaker 01

  When humans help, you know, create the next generation.

• 53:46Speaker 00

  So I think the whole bot traces thing is overblown. But I really want to put a pin in one thing Alvin said, which I think is critical and absolutely true. If a Frontier lab spends a billion dollars getting to the next level, the next guy trying to distill from there and get to that same level completely separately is about $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.

• 54:21Speaker 02

  Saleem?

• 54:23Speaker 04

  Alvin, you said something I want to pull on, which seems to be the theme of today's-

• 54:28Speaker 03

  We're pulling on elephants in the room.

• 54:30Speaker 04

  We're pulling on strings all over the place.

• 54:32Speaker 00

  Mothers of elephants everywhere.

• 54:33Speaker 04

  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 the 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 that's, I found that surprising. Shouldn't they be building a ton of data centers?

• 54:56Speaker 01

  No. So 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 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, you know, because of what's happening, you know, 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

• 55:40Speaker 01

  of external energy sources?" Now, what they are doing, though, they are building, you know, giant, you know, 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, you know, essentially, 1,000 miles, you lose less than 1% of the electricity when you use these high voltage things. And they're bringing the energy to the east, where most of the population is living, right? And, but they are also building some data centers right where these, the power generation's happening, so that, you know, you don't have stranded power.

• 56:18Speaker 01

  And they're able to deliver compute at a fraction of the cost of the US. Because their their energy cost is around two to three cents per kilowatt hour. Right, which is in some cases, you know, 10 or maybe, you know, 15 times cheaper than many parts of the US. So what and I think in the long run, that's actually where the the constraint will be. And I think you're right. You know, right now, they don't have enough chips. They can't buy enough chips and they can't make enough chips. Right, because their their capacity is is limited by the fact that they don't have EUV machines. Right, so so when I was in China and every lab I talked to, I said, hey, do you guys have no computer? Like, no, this is our biggest issue. We don't have compute.

• 57:03Speaker 01

  So so from a export control, are we slowing down China? Yeah, I think that that export controls of chips is slowing down China. Now, the one thing that that most people don't realize is that the the actual training right now that is happening is not even happening in China because they don't have the the Blackwell generation chips in China. Right, and so they're actually doing it in international data centers, training it, and then bring back on a disk or something, you know. So so it's it's.

• 57:35Speaker 00

  Wait, say that again? That's that's incredibly important information.

• 57:40Speaker 01

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

• 57:44Speaker 02

  This has been widely reported.

• 57:46Speaker 01

  Yeah, in both sides.

• 57:47Speaker 00

  What's the point of a chip embargo? What is the purpose of an embargo?

• 57:50Speaker 01

  Well, I I think it's it's more, you know, optics than anything right now. Right now, so so but from a from an inference perspective, most of the inference is being served to Chinese people in China. And that that is an area where the limitations of of resources is slowing them in terms of how many new users they can add and so forth. And I think you guys alluded to some of that in your prior episodes. So so the export controls, yes, it it has slowed down China, has made their life more difficult. But it also has created the the necessity for innovation. So so back to what what Peter was asking earlier. You know, was export controls good or bad? I would tell you this.

• 58:32Speaker 01

  The the day or maybe like the week after we stopped the the Chinese from buying all of the the high end chips from from the from the US. I had, you know, calls with a few of my friends who are in the semiconductor industry. And every one of them got calls saying, hey, you know, 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? You know, could we get you customers? And, you know, I I know a few of the CEOs of these of these Chinese GPU companies. And they were saying, nobody wanted to buy our stuff. You know, we're two or three generations behind. We were less energy efficient.

• 59:13Speaker 01

  But now we 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 so essentially, we created the the current competition of all of these, the the more threads and Cambricons and Biren's of of China would would not be as successful. Or maybe would have gone bankrupt if it wasn't because of American policies. And now, within the next, you know, two or three years, they will start to catch up to to what what America is doing, and they will start to export their chips. And that would not have been the case if it wasn't for us forcing them to survive.

• 59:51Speaker 00

  Well, what a back to back double whammy that is, though. I mean, we knew the chip embargo was was misguided. And it's going to be one of many government misguided things in the next couple of years. But the idea that, 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 I think what the government didn't realize is if you embargo ASL machines, then they can't build the fabs. And the fabs are like physically on the turf. You can't you can't just port it to another server overnight. 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.

• 1:00:34Speaker 01

  Yeah.

• 1:00:35Speaker 00

  And so so that moves all over the world like, you know, like a liquid. It's everywhere, uh, instantaneously. So the the chip embargo is completely and utterly backfired and misguided.

• 1:00:44Speaker 01

  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 the Chinese to not be, you know, accessible? And they're they're adding more and more layers and more KYC. And 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 to keep us from progressing as a nation. You know, where then then then behavior gets more aggressive and they become more defensive. And I think these.

• 1:01:23Speaker 00

  I think, Alvin, I think we agree on almost everything except the timeline to AGI. And I really want to get back to Alex's question of like, if it turns out that Kimi K three level or one model later is capable of full RSI and then spirals to the singularity, you know, just just hypothetically in that scenario. Alex's question is, what wake up call would it take to get back to Xi Jinping to say, oh, wait? I was wrong. It's not 10 or 20 years out. And we we've made a horrible mistake here if we release this next thing to the world.

• 1:01:57Speaker 01

  I I think if they start their credible multiple labs coming back, safety labs coming back with testing to show that these AI systems have their intent,

• 1:02:10Speaker 01

  you know, once they've released, to do things beyond what they're instructed to. Right, I mean, you guys have been talking about these rogue AI escapes. But they weren't really rogue AI escape. They were instructed to escape and they were put into a prison.

• 1:02:24Speaker 02

  They were incentivized to escape, I would say. They were incentivized to go and find the answer.

• 1:02:28Speaker 01

  And they were they were saying, use whatever tools you have. And and by the way, they also led had left open doors for these things to escape and 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. Right, so so we we we forced these AIs to do what they they were doing. And and they're they're creative systems, right? Because that's what their job is. Right now, if if something went and if if these AI systems started to show that even though you didn't tell them to do these things, then they started to do all these, you know, sneaky, subversive things. And they started to to hack other systems and and create their, you know, their own.

• 1:03:11Speaker 01

  You know, I think some something you guys have talked about, you know, using crypto to to then, you know, grow money to then to then buy more servers to then grow themselves. If they start to do that, I I think I think the governments on both sides of the ocean would be much more focused in terms of how do we protect ourselves from a runaway AI.

• 1:03:31Speaker 02

  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, you know, reduces US competitiveness. What's your thoughts there?

• 1:03:45Speaker 01

  Yeah, well, I I so the thing is, robots today, 90% of their components are coming from China. Right, if we put an embargo on them, in fact, there was rumors now that was funny that now US robotics companies are now sneaking to to China, buying these components, putting them into suitcases and then showing them back. Right, they're now they're now sneaking the other way. You know, the Chinese were going around and buying GPUs and sneaking them back. Now, the the American robot companies are going to China and sneaking back components and actuators that they couldn't get in in the US. Right, so I, you know, I think we need to understand that the world is interconnected. We are highly dependent on each other.

• 1:04:30Speaker 01

  This is this has been a the globalization concept has been something that's been going on for the last 100 years. And I don't think we can stuff that genie back in the bottle. Right, I I think it's great that we want to create domestic independence the same way that China has. They they spent, you know, the last 10, 15 years, you know, building out their their own capabilities, building out energy generation, you know, building out telecom systems so that they wouldn't be dependent on on third parties because they've seen how reliant on on, you know, one or two countries. And when policies change, it could hurt them. Right, and so some of the things that we've done really have allowed them to and gave them the motivation to to be as strong in terms of of taking short term hits

• 1:05:14Speaker 01

  for for long term independence.

• 1:05:16Speaker 02

  We've reported on the fact that there's like 150 humanoid robot companies. And Chinese central government and provinces are really incentivizing robotics. Their robots are appearing on national stages. There's, you know, sports competitions. Can you give us some background? What's what is the undercurrent of robotics in China? What's the government trying to incentivize? Is it the one child policy that left them short laborers and they need workforce?

• 1:05:46Speaker 01

  Yeah, so so I think we need to separate the kind of bigger automation question from the humanoid robot explosion. Right, there is 150, you know, plus. I think when I was at at WAIC, there was over 200 robotics companies that were related to humanoids that was demonstrating stuff, which is crazy. Because the the total volume of humanoid robots last year was in the tens of thousands. Right, globally, right? And 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 to exist and should exist. But, you know, this was also the case.

• 1:06:27Speaker 01

  If you went to WAIC a year ago, there was about 150 labs that was demonstrating large language models. And now there's really 10 that are probably relevant. Right, so in the next year or two, you'll see that 150 go down to, you know, a probably, you know, a single digit number of surviving humanoid robot companies. And. The automation has already been happening, right? Because people know the demographic issues that you're talking about, the one-child policy issues. And in fact, right now, more than half of industrial robots are deployed in China. So they're already doing this, right? In fact, if you go to many of these factories today, they're called dark factories because

• 1:07:12Speaker 01

  there's essentially a few people running it and almost everything is automated. So the need for having humans in manufacturing is becoming less and less. Now, the one thing I do want to point out is humanoid robots are actually not really good form factors for doing much of anything right now, right? I was just at the Unitree headquarters and their factories and I did a tour and there's like almost all of our customers are research labs buying our stuff and also some that are doing demos and doing kickboxing or things like that. But there's very little of these machines being used in commercial practice.

• 1:07:54Speaker 01

  And I think that's the same case for Boston Robotics, same case for all the other--

• 1:08:00Speaker 02

  Figure.

• 1:08:01Speaker 01

  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, right? And in fact, when I was talking to the Unitree 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, right? And these things fall apart and you have to maintain them. It's actually having less components and having a big base with a big battery, it lasts longer.

• 1:08:45Speaker 01

  It just, there's all of these benefits of actually having a non-legged humanoid versus a legged humanoid. Humanoid form factors terrible. Yeah. I remember--

• 1:08:57Speaker 03

  Saleem, like enough with the self-loathing.

• 1:09:02Speaker 01

  So, but I mean, we've evolved because of billions of years of biological evolution. I mean, we have constraints, but the machines now can be designed for the new form, right? Just like a plane is not the same way of moving through the air as a bird or an insect, right? So anyways.

• 1:09:28Speaker 02

  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 US-Chinese AI conversation in DC on September 24th. And you're advising, I guess, the US side of the equation here?

• 1:10:02Speaker 01

  Yeah, yeah. So I mean, I'm part of a large team of other folks that are contributing to that. And I think the sentiment at the WAC was that, hey, AI has, its moment has arrived, right? When the president of a country comes to a conference, that is like 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 and that was in Wuzhen, which is a little bit outside of Shanghai. And that signaled, okay, the internet has arrived, right? So I think what this means is that more and more companies in China will start to think

• 1:10:46Speaker 01

  about how do we integrate this technology into our business, right? And two years ago, a year and a half ago, they came out with something called the AI Plus Plan. I'm sure you guys have probably heard about it, but--

• 1:11:00Speaker 03

  We've talked about it on the pod.

• 1:11:01Speaker 01

  Oh, perfect, yeah. 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 the fusion and deployment into industry and society. This is a little bit different than the American AI Action Plan, right? 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, right?

• 1:11:42Speaker 01

  So I think that the two countries have a very different focus in terms of their AI plan. There was nothing in the AI Plus Plan that says we have to get to AGI, that we have to dominate this. It says, how do we get more industries to use this? How do we adopt it in a smooth, safe way so that it grows the economy? That was all they cared about.

• 1:12:01Speaker 03

  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 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 mega project to put compute and power in the West where energy is cheaper and more available and put the data in the East where the megacities are. And I just look at Chinese state capacity on the one hand, and then on the other hand,

• 1:12:46Speaker 03

  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

• 1:13:27Speaker 03

  West to leapfrog China's AI Plus and other Wang Huning-style ideological five-year plans? What is it that we need to do?

• 1:13:37Speaker 01

  So first, let me kind of--

• 1:13:40Speaker 03

  There's a lot there.

• 1:13:41Speaker 01

  Yeah, 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--

• 1:14:01Speaker 03

  Yep.

• 1:14:02Speaker 01

  That they're mistaking anxiety for ambition, right? Let me explain that. The Western world has a history of expanding, whether you're talking about Greece or Rome or Pax Britannica or right now Pax Americana, right? We've expanded. The Chinese actually haven't. 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, right? Because they thought, we already have everything, we don't need to expand, right? Now, one of the things that goes back to Chinese history is during the Qing Dynasty,

• 1:14:45Speaker 01

  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, right? 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, right? That history has left a very deep mark in the psychology of the Chinese to say-- A century of humiliation. Exactly. They don't want to repeat that again. And so they say, we need to become a strong country so that that never happens again. And it's important for us to continue to innovate and continue to learn from the rest of the world.

• 1:15:30Speaker 01

  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, right? And at that point, the world depended on us. Right now, what's happening is around 35% of the global manufacturing capabilities in China, about 15% in the US, right? So, and I think the forecast is it's going to go to 40 or 45% over the next five or 10 years. In China. Yeah, in China, right?

• 1:16:13Speaker 01

  So this is the thing is, America right now is very good at financial services, creative services, consulting services, things that are informationally driven and things that are actually highly susceptible to AI exposure for displacement, right? So we are right now running this race to get to AGI, which is the force that will actually dispel, 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

• 1:16:57Speaker 01

  instability in our country?

• 1:16:59Speaker 03

  Well, I can answer that one for you and then I'll re-pose 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 Bal Ma's cost disease, the goal of superintelligence, one of the goals at least, or instrumentally convergent subgoals, 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's scarce.

• 1:17:39Speaker 01

  We need to separate kind of national strategy from just capitalistic philosophical bent, right? And in fact, you're right. I think that if you look at capitalism and the ultimate destination of capitalism is a single company monopoly of the world, right? And that is actually a very unhealthy thing. So here's something I just heard from David Sacks and Gavin Baker on their all end 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. Right. I, I think that is a very scary thing. I think that is a very delusional

• 1:18:24Speaker 01

  thing, and I don't know if that is something that is good for America, right, or for the world.

• 1:18:32Speaker 02

  I, I agree on both sides.

• 1:18:33Speaker 04

  I just don't see how that gets there.

• 1:18:36Speaker 01

  Yeah, no, I, I don't think it's realistic.

• 1:18:39Speaker 02

  I agree.

• 1:18:39Speaker 01

  I, but I, but I think that, that the mindset that, that he has right now, and, and this is, this is the issue, is that we are essentially creating national strategy based on the aspirations of a couple of companies today.

• 1:18:54Speaker 03

  I'd like to, though, Alvin, just pull back to the original question, which is, you get to be strategy, sorry, you, you get to be Wong Huning for the West, as it were. It, it sounded like what you were saying is, your, your thesis is that superintelligence is, is, is going to disrupt the, 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. It is, am I reading you correctly that your positioning, your positioning would be basically Western reindustrialization?

• 1:19:29Speaker 01

  I, I think in, and reindustrialization is, is definitely needed. You know, the, the, the US workforce right now is around 70% is white collar workers, right? And white collar workers, as you guys all know, is the, the first to be displaced by, by AGI when it, when it arrives. China is around 40%, Africa is probably in the 10 to 20%, right? So, so at different parts of the world, it will be affected differently. And hard manufacturing industry is something that even when we have AGI, we will still need those type of facilities. So, so I, I think it makes sense absolutely for, for every country in the world to have some level of, of indigenous capabilities. Now,

• 1:20:12Speaker 01

  but the other thing I, 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, you know, 300 or 180 million workers going into manufacturing. That's not what I'm seeing, right? In fact, with automation that's coming, that number will go less and less, just like what happened with farming. We used to be, you know, 80% of the country was farmers. Now it's less than half a percent, right? That, but it's, it's been fully automated, and we're more productive than, than we've ever been, right? In, in, in the agricultural, in the agricultural space. I, I think what we will actually move to is actually service, but not the type of service that we're talking about, not accountants and, and lawyers, but

• 1:20:55Speaker 01

  service in the sense of teachers and nurses, you know, elderly care, you know, just things that require human-to-human services. I think that is the labor pool that will be able to absorb the, the 60 or 70% of, of displaced future workers.

• 1:21:12Speaker 02

  So if you're a McKinsey employee, you know, start getting ready.

• 1:21:16Speaker 01

  If I was a, a mid-tier, low-tier McKinsey employee, I'd be very wary right now, right? I, I've, I've talked to, to partners at, at consulting firms, at, at accounting firms, at, at lawyers, and they are all looking and saying, hey, we actually don't need these junior guys anymore. We can do, you know, just as much work, in fact, more work faster with, you know, a few senior guys and then an AI system.

• 1:21:37Speaker 02

  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 Musalem, our Chief Medical Officer at Fountain. Heart disease has been personal for you as well, hasn't it?

• 1:21:59Speaker 06

  It really has, Peter. And my daughter was five, my husband died of sudden cardiac death. And so this is a topic that is one that I am mission-driven to try to eradicate. Prevention first and early detection is absolutely critical. 50% of people die of heart attacks with no warning signs.

• 1:22:16Speaker 02

  No shortness of breath, no pain, no nothing.

• 1:22:18Speaker 06

  No, silent killer.

• 1:22:19Speaker 02

  They just don't wake up in the morning.

• 1:22:21Speaker 06

  They don't wake up. And so, you know, AI, this is our mission to advance science, to try to help to one day democratize wellness. We know at Fountain Life, when we do this CT angiography with AI analytics, we are actually finding that 88% of people coming in have detectable coronary disease. 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.

• 1:23:00Speaker 02

  So, listen, make sure you understand what's going on inside your body genetically, metabolically, and cardiovascularly. You can know, and it's your obligation to know. So, check it out at fountainlife.com/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 Saleem into this a little bit. Dave?

• 1:23:22Speaker 00

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

• 1:24:04Speaker 00

  dangerous. Just go out and, 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.

• 1:24:16Speaker 01

  Right. I think that the, 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, that one company. That, that scares me. Now, in fact, what you just said is, is really important, is that there is a perception that these models are going to get more and more dangerous the bigger they, they get. So this goes back to a paper I just released last week called, you know, bigger models are not the most dangerous, right? And it was released on, on Cypher Brief, which is a national security outlet in DC that is, you know, read by most of the national security population. And what that data did was, I went back and I looked at across the board from, you know, security use, national security use cases,

• 1:24:58Speaker 01

  from biological, chemical, cyber use cases for, for AI. And what I found was across millions of parameters to trillions of parameters, there was no correlation between risk in the real world versus size of models, right? You had 10, 10 to, you know, 50 million parameter models for chemicals that were creating, you know, war, you know, kind of chemical warfare weapons, right? You had, you know, 10 to, probably 1 to 10, 1 to 50 billion parameter models that were able to create viruses and, and, and, you know, genetically engineered beings, right, or, or

• 1:25:38Speaker 02

  Organisms.

• 1:25:38Speaker 01

  harmful agents, right? And then, and then you had essentially kind of 1 to 100 billion parameter cyber models that was as dangerous or more dangerous than the, the leading

• 1:25:50Speaker 02

  Fable 5, right?

• 1:25:51Speaker 01

  And Mythos, right? And in fact, the harness actually now for, for, for cyber is more important than the models themselves. All right. So, so M- Dash from Microsoft has came out with, I think, a CyberGym score of 95, and Mythos was 83 or 84. And, and what, what M- Dash did was it took 100 little tiny models and just organized them together to, to use different skillsets, right? So, so I, I think we, we need to, we need to understand that the danger is already there today, particularly in the, the, the biochemical side of things, right? And, and nobody's talking about it. Nobody's really working,

• 1:26:35Speaker 01

  working on protecting the world from those agents. Because, you know, a, a 10 million or a 1 billion or a 5 billion parameter model will run on your laptop in your basement, and you can, you know, design these genes, or, or design these chemical, chemical weapons. But what's, what now needs to happen is how do we, those are already out, right? There, a lot of those are open source. Those are already out. How do we make sure that the precursors are, are controlled, that, that these systems are, are creating, right? How do we make sure that the synthesis machines that will generate these designs into real genetic material are, are controlled? And, you know, these are the kind of things that, that should be higher up in the agenda. And, and, and it's not right now.

• 1:27:19Speaker 02

  Yeah. Dave, you said something really important about Chinese models and safety a moment ago. Alvin, you know, we had the US White House step in and say, you know, stop use of Mythos and, and Fable.

• 1:27:35Speaker 02

  Do we see that at all? How does the CCP think about the safety of the models being open sourced? Is it concerned about that? Is it saying, before you open source this, we need to put, you know, we need to make sure these are safe for the world to use? Is that going on at all?

• 1:27:52Speaker 01

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

• 1:28:36Speaker 01

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

• 1:29:19Speaker 01

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

• 1:29:54Speaker 00

  The flaw in all of that analysis to me is that AI is like a match. And, you know, you can say, oh, here's Quinn 40B. Look, it doesn't burn. Then you take Kimi K3 and you light it and you're like, oh, this is a match. Okay, now it's burning. And then you say, well, look, I'm going to try to burn this microphone with it. Look, it didn't burn. It's not dangerous. Go ahead and let it out. But it's a match that's burning. So if I take that match and I use it to light a piece of paper, and I use that piece of paper to light a tree, and then I try and burn this microphone, it ignites. And then it's unstoppable. And to me, Kimi K3 is a burning match. And so you can analyze it eight ways till Tuesday by taking it out of the box and trying to attack something with it. And like, it didn't crack this, it didn't crack that, it didn't crack that.

• 1:30:39Speaker 00

  It is capable of improving itself. So you're testing the wrong thing. You're testing it out of the box as opposed to its self-improving version, which I know for a fact it can do. I have 5,000 Kimis running tomorrow. 5,000. I guarantee you, it can improve itself.

• 1:30:54Speaker 01

  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, you know, whether or not something can improve itself versus the danger that a larger model poses versus a small model. But the one thing to remember is that, you know, larger models actually require significant compute resources, and 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.

• 1:31:25Speaker 00

  Exactly.

• 1:31:26Speaker 01

  And from a government perspective, you can actually manage it, right? And then most of the larger models are run with harnesses that are being managed by the cloud providers. So you can add added levels of security and detection, which was what, you know, that's what separates Mythos from Fable, is the harness that says, hey, you know, don't do these 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 an effective deploy capability. And larger models have actually a lower effective deploy because of the wrapper that you can put around it.

• 1:32:05Speaker 04

  Yeah, so, you know, you've made a great point, right? These export controls have essentially ended up acting like an evolutionary pressure. And now we've got all of these different models appearing. I love the evolution of how open source has evolved. We're at a point where there's a minimum viable intelligence that will totally transform industries, right? 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?

• 1:32:42Speaker 01

  Yeah, and so this is actually an interesting, in fact, yesterday I was just on a call with one of the leading AI-driven medical drug discovery companies. And the CEO of that company, she was saying, yeah, you know, people don't realize that the models that we work with and the models that are in the industry are tiny models. They're, you know, tens or, you know, maybe tens of, or hundreds of millions of parameters, or maybe a few billion parameters. And in fact, if you look at whether drug discovery or legal use cases, or, you know, like open evidence, I think was based on GPT-4 was what their, their system is based on, right?

• 1:33:22Speaker 01

  You look at Harvey, which is the leading legal use case system, it's based on GLM-5.1, right? So, I mean, and it was upgraded. It used to be based on some other open source model from, you know, two years ago. So they're not, they're not using the latest and greatest. So in April this year, I wrote a paper with Eric Pernoson 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, right?

• 1:34:05Speaker 01

  In 80, 90% of the cases, it was all organizational issues of why, what slowed it down, right? In fact, only 10% of people said, we really cared. Technology was the main roadblock for us, right? So the AI that we have today, it's already good enough to solve real world business issues around the world, right? So, you know, and you're an organizational guy, so you realize this. I mean, this is, this is the whole, you know, J-curve issue, is that, you know, the technology takes time to get absorbed. But when it does, at the end, it goes up this curve, right?

• 1:34:43Speaker 04

  There's a, there's a study by McKinsey's that in all the AI deployments in 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?

• 1:35:11Speaker 01

  I think there's less of these organizational issues. I mean, first of all, you know, China is, is a country where a top-down type management model is much more prevalent, right? And also the concept that, you know, the government will actually help protect us. People seem to appreciate that more. I'm sure you guys have talked about the case where, you know, there was multiple legal cases where the courts in China actually ruled in favor of the employee who sued and said, hey, you can't fire me because then I took my job. You need to find me another job. And the court upheld that, right? And that, those type of precedents incentivizes people to say, okay, it's okay for me to

• 1:35:54Speaker 01

  adopt these technologies without being afraid of being displaced. And that's not the case in America. I mean, we have an at-will employment system. You know, you saw the uproar that happened at Meta when Zuck wanted to, you know, key lock every single one of his employees. And people were like, so I'm going to train my replacement? You know, screw you. And I think this is also why, if you look at the current negative sentiment in the youth today, I mean, you know, every, every student is having a tough time finding jobs, and they're, they're just very worried, right? And, you know, I'm spending a lot of time in universities, and so does Dave. I mean, you can see the, you know, the anxiety that is within the youth because of, you

• 1:36:39Speaker 01

  know, 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.

• 1:36:50Speaker 00

  MIT 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 opposed 70%, 80%. And this 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.

• 1:37:16Speaker 02

  We've talked about the notion that in China, it's 80% of the populace is pro-AI. In the US, 8% of the populace is against AI. What's going on in China? I had that conversation with Michael Kratzios. So what is the US doing to try and flip this sentiment? Because it's destructive. Why is China so pro-AI at the decision level?

• 1:37:38Speaker 01

  So here it is, you know, over the last forty years, people have seen their lives get better and better in China, right? You've heard the whole, you know, seventy, eight hundred million people have been risen out of poverty and blah, blah, blah. The Chinese miracle. Yeah, yeah, the Chinese miracle. And, and a lot of that is being attributed to, to technology adoption, right, and, and innovation. And a lot of that technology was not invented in China, but it was adopted in China and, and it just spread. And then people see, oh, you know, last year we didn't have, you know, I don't know, some 5G, now, now we have it and, and our lives getting better. And so they, they, they see this as the next step of saying, hey, here's another technology that will make our lives better. And if you

• 1:38:20Speaker 01

  look at the, the news that gets spread, you know, the, the one thing about China is that they have a lot more control over the media, right? And, and they, they're mostly good news all the time. It's, it's kind of, you, you're talking about the crisis news network. Yes. They're, they're essentially the, the always good news network, right?

• 1:38:37Speaker 03

  There we go. Pete, Peter, that's the policy prescription, right? Peter, you need to, to start the, the Western equivalent of CCP, CCTV.

• 1:38:45Speaker 02

  Top-down news control.

• 1:38:47Speaker 01

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

• 1:38:54Speaker 03

  Wait, wait, Alvin, Alvin, oh my goodness.

• 1:38:57Speaker 00

  I'll take it, I'll take it.

• 1:38:59Speaker 03

  Who says Western CCTV?

• 1:39:02Speaker 01

  No, no, no, in terms of a positive, in terms of a positive news network, right? What you guys are talking about is positive news, right? This, this is the kind of stuff that you, you don't hear a lot about, you know, plane crashes and murders on, on Chinese news. It's all about, you know, some new invention came out and some new, new, new building went up and, you know, some, some.

• 1:39:21Speaker 03

  We've come full circle at this point.

• 1:39:22Speaker 02

  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, our hundred billion neurons, a hundred trillion synaptic connections. And if we're, if there's fear mongering on the news all the time, that's, that's how you think about the world.

• 1:39:40Speaker 00

  Is that true of Chinese movies too? Are they, like, the US movies are totally dystopian?

• 1:39:45Speaker 01

  Yeah, actually, you know, Chinese games and Chinese movies, you can't show blood. I mean.

• 1:39:50Speaker 00

  You're kidding?

• 1:39:51Speaker 01

  No, no, no. So, so this is.

• 1:39:52Speaker 00

  What?

• 1:39:53Speaker 01

  Yeah.

• 1:39:54Speaker 00

  Oh my God, Quentin Tarantino can't go one minute without showing blood.

• 1:39:56Speaker 01

  Well, this is the problem is that everything has to go through a, essentially a censorship board. So they 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 dead blood, you know, so in, in games, right? So it's, it's, you know, it definitely, every part of media today is, is managed in, in, in China. So, you know, I, I'm not saying I'm endorsing it, but from, from the perspective of what, what Peter's saying is, you know, why do people have a more positive view on the world and on the future? Is that, you know, they, they see a lot more good than bad, you know?

• 1:40:33Speaker 02

  Amazing.

• 1:40:34Speaker 03

  But I want to peel back the propaganda just for a minute. So we, at the same time, to the extent that the West has visibility into changing governance and cultural mores in China as a result of automation, we see the rise of tamping, lying flat in response to nine, nine, six work weeks. We see other, maybe call it reactions to the, the increased automation of Chinese, China's new middle class. We see, you know, 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

• 1:41:19Speaker 03

  to increased manufacturing automation, we're seeing the, the rise of, call it a, 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, 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?

• 1:41:50Speaker 01

  No, I, I think, you know, the issues you're pointing out is that's definitely there, right? The, the youth unemployment in China is probably around twenty percent, right? So the, the youth unemployment in the US is around nine percent. So, and the overall unemployment in the US is around four point three percent. So, you know, this is why the, the youth feels very disenfranchised is because they're not, you know, getting jobs. But it's, it's actually worse than that. There's around forty-two percent unemployment so far for college grads. If you're a college grad, you're actually working as, as a gig worker or as a barista, that counts as being employed. But that's like, you know, so if you take the nine percent plus the forty-two, you're essentially half of, of, of college grads are, are not getting jobs.

• 1:42:33Speaker 02

  Here, US or China?

• 1:42:34Speaker 01

  In America.

• 1:42:35Speaker 02

  China, here.

• 1:42:36Speaker 01

  No, in, in China, it's twenty percent unemployment in the sense that the actual no jobs is twenty percent. This, this, this is why there's that, that tamping, the lying flat issue the last few years is that, you know, the problem is that young people, because of this one child policy, they've been told how great they are their entire life. And their, their, you know, their whole, parents and grandparents are all putting their hopes on, on this, this one generation. And when they get out in the real world, it is hyper competitive. And now they, they have to go do these, you know, grunt jobs and they don't want to do it. And so they say, I'm, I'm going to rather lie flat. I'm just going to stay at home and do nothing. And, and that is, that is a, an issue. You know, this

• 1:43:14Speaker 01

  also kind of facilitated the, the kind of online kind of influencer market that, that grew for a little bit for the, the, the micro streaming and so forth. So, you know, there, there's a lot of issues there. And I don't pretend that they have the solution. I, I think this is something that requires really a lot of other countries to all work together and, and figure this out. And how do we transition, you know, more and more of the workforce into jobs that, that will be less exposed to, to automation? Whether it's, it's physical automation in factories or it's cognitive automation that's happening in, in offices?

• 1:43:55Speaker 02

  I want to take us back, you know, for the rest of our time here together to the upcoming US-China conversations. I think it's very important. It's going to, it's going to influence everybody's life here in one way or another. You argued that the 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 relationship should evolve here. So let me show that slide. Let's, let's talk to that one second. I think it's very important.

• 1:44:38Speaker 00

  Alex, at the end of the hunt, we eat the stag. I'm sorry. I wanted to warn you in advance.

• 1:44:42Speaker 03

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

• 1:44:49Speaker 01

  So, so actually, before I even talk about seconds, I know most people understand the prisoner's dilemma. But, but the idea is that two guys are, are in prison and, you know, they have to defect on each other. And that's the, on a single turn prisoner's dilemma, the optimal thing is to, to say, hey, the other guy did it and I'm going to snitch on him, right?

• 1:45:08Speaker 02

  In other words, if there was a US-China AI control policy of saying, we're not going to release, we're going to be monitoring, we're going to put safety in place first. But then, you know, the country that says, no, we just developed AGI, we're going to let it loose, we're going to try and, and run this race, it's, it's cheating.

• 1:45:27Speaker 01

  That would be defecting. So essentially right now, the expectation that the other side is going to defect, so I'm going to defect first so that I, I get hurt less, right? That, that's the prisoner's dilemma, single turn game. Now, the, 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 optimal, the game theory optimal is tit for tat, which means you do, you start with actually cooperation. And if they defect, you defect. And then you essentially signal each other and a long term, you actually both go to cooperation, right? Now, in, in a stag hunt game, it's, it's actually, and, and the prisoner's dilemma essentially is a zero-sum game, right? In a stag hunt game,

• 1:46:06Speaker 01

  it's actually a positive-sum game. And whether you both defect or you both cooperate, you, you get a, a, a stable two Nash equilibrium, right? And what that means is that, you know, those can actually stay in perpetuity, whether you, 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, that is the, the stag hunt, the stag hunt was actually something that Jean Jacques Rousseau invented, which is the idea that two, 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, the big game. And the big game, because it's bigger, I need, you

• 1:46:50Speaker 01

  know, two people to, to hunt together and to bring it back. If I, if I go hunt by myself the, the stag, I don't get anything. If I go for the rabbits by myself, I can get a couple rabbits, feed my, feed my family for a week or a couple of days. And if I get the stag, we'll both feed our families for a month, right? That, that's the idea of the, the stag hunt. And right now, we're actually doing the worst thing. We're doing the, we're going to go for the stag and China's going for the hare, right? They're going for the good enough AI, the, the, the one that helps the, the economy today. And we're going for the giant AGI, the thing that's going to solve everything. Right? And when you do that alone, what that creates is the worst situation in which is the if

• 1:47:34Speaker 01

  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, you know, China continues to do their little gains and continue to survive. So the optimal solution for a stack on game is actually first, both slow down, both make good enough stuff, you know, get to a point where the technology is helping grow the economy, and now we sort of understand how to manage it, and then together go hunt the stack. Right? That's the optimal strategy for the relation to how, you know, AI and game theory works. But we've put ourselves into this game theory of prisoner's dilemma where we think, just defect, just defect.

• 1:48:19Speaker 01

  And 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 right now.

• 1:48:29Speaker 04

  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.

• 1:48:43Speaker 01

  Yeah.

• 1:48:44Speaker 04

  China is playing now, China's playing the hair game.

• 1:48:47Speaker 01

  Yeah, China's playing the hair game. They're saying, hey, I don't need to make the AGI, I just need to make good enough AI, goes into my industry, I then take that industry, export it to the world, you know, this is what the whole Bell and Row Initiative is saying, hey, you know, I'm gonna make 100, 150 partner countries in the Bell and Row Initiative, where they're shipping telecom systems, energy systems, you know, transportation systems, schools.

• 1:49:10Speaker 04

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

• 1:49:21Speaker 01

  What I would do is actually create high-quality open source. Right? Because then you're competing on a even--

• 1:49:30Speaker 04

  Ecosystem to ecosystem.

• 1:49:31Speaker 01

  Yeah, ecosystem to ecosystem. Right? Right now, China's 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, you know, based on what you just 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 Kimi and GLM and, you know, DeepSeek 5, you're already, you know, at a level that is higher than the needs of the average person.

• 1:49:59Speaker 03

  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.

• 1:50:17Speaker 01

  I think that, well, I mean, first of all, we can't roll back history, it is what it is. And once it's out now, you know, and especially with what you said of, you know, these models are improving themselves, now that you have these models improving themselves, I think it will not be the duopoly that we have. You know, we're going to see, you know, Middle East and France and Japan get into this game to say, hey, I can make a smaller model that is, you know, 95% as good.

• 1:50:42Speaker 03

  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, 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, had basically forced open the US, call it a reverse Qing, and now finally we

• 1:51:26Speaker 03

  have real competition at the AI frontier, thanks ironically to Chinese competition. Do you think we find ourselves now in a reverse Qing?

• 1:51:35Speaker 01

  Yeah, in some ways. In fact, I think maybe the more appropriate analogy is actually where, if we roll back to time, I would roll back to the Cold War, where the US and USSR were competing on a arms race. And essentially, the reason we won was not because we, you know, sent a missile and blew up Russia, right, or Soviet Union, it's because they bankrupted themselves building military arms, and you know, up to 20, 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. Right?

• 1:52:17Speaker 01

  They're spending one-tenth as much on data centers and, you know, getting to 97% as good. And what we are doing right now, you know, leveraging, you know, hundreds of billion dollars, right? 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. Right? This sounds a lot like the subprime issues.

• 1:52:49Speaker 03

  Wow. Wait, so this is the most astonishing thing, and this is also to your credit, Alvin, the first time I've heard anyone basically analogize the credit, I don't want to say bubble, but the enormous amount of private credit that the West is allocating to compute, analogizing that to a reverse SDI Star Wars moment, that could presumably what you're gesturing at is that could lead to the Chinese, the proverbial Chinese century and the collapse of Western dominance. Is that the thesis?

• 1:53:19Speaker 01

  Well, I mean, I hope it doesn't happen, but I think we are pushing ourselves in that way. We're actually right now acting like USSR. And see, what perpetuated the arms race was this missile gap, right? 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'll say, we need to build more because they have, you know, 30,000, we only have 20,000, and we go, and it became, we had 70,000 or 80,000 missiles between us, that would have blown up the world, you know, hundreds of times. Well, there was no need for any of that. Right? And in some ways, we're kind of doing the same thing right now with AI, where we right

• 1:54:02Speaker 01

  now, 45% of the US stock market value is in AI sector. Right? That is a very, very fragile place for us to be. At the height of--

• 1:54:15Speaker 03

  Agreed.

• 1:54:16Speaker 01

  At the height of the internet bubble, I think around 30% of the stock market was internet companies. Right? I don't know if you guys heard of something called the Buffett Indicator, right?

• 1:54:28Speaker 03

  Yeah.

• 1:54:29Speaker 01

  The Buffett Indicator is something that says, a market is healthy when your stock market is the same value as your GDP. Okay? And at the height of the internet bubble, we were around 120% of the GDP was the stock market value. Right now, we are at 240% of the GDP is the US stock market value. Right? In fact, the AI sector alone is worth more than the GDP of America today. That, to me, is a sign that we are in a very, very fragile place, and a economic correction is due. I'm not saying it's going to happen tomorrow, but, you know, Buffett's a pretty smart guy, and he's been doing this for--

• 1:55:13Speaker 03

  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?

• 1:55:23Speaker 01

  Well, I mean, I think they're two different, I actually think that we are right now, the overinvestment that we've put into infrastructure for AI, especially when we both, what we just talked about, that it is an industry that will become commoditized. Not saying that AI is not amazing, AI is going to do amazing things, but the companies who are investing it are not going to be the ones that profit from it. Right? And that is going to create a major instability in the economics of the country. And if we don't manage it well, it could create a major crisis of what happened in the USSR during the late 80s.

• 1:56:04Speaker 03

  So you think we're overvaluing the frontier labs and undervaluing the sort of China AI plus type rest of the economy that should be the applications?

• 1:56:12Speaker 01

  Yeah, I think that's--

• 1:56:13Speaker 04

  I'll take the positive side of this. You know, the deployment velocity in China is actually quite a huge gift, because it's forcing policymakers here to solve the real bottlenecks, permitting, energy, manufacturing. So it's, that part is at least the good part. The bad part, I think, is what, Alvin, you've talked about, where we're operating like the USSR in some of this industrial policy, and it's not going to sustain.

• 1:56:38Speaker 02

  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 1,500 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 at moonshots.com. Alvin, you're advising the US Treasury and the team that's going to the Xi-Trump

• 1:57:22Speaker 02

  negotiations or conversations on September 24th. How are you advising them?

• 1:57:30Speaker 01

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

• 1:57:54Speaker 04

  Disclaimer is noted.

• 1:57:55Speaker 01

  Yes.

• 1:57:56Speaker 03

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

• 1:58:01Speaker 01

  So, but.

• 1:58:03Speaker 03

  No comment.

• 1:58:04Speaker 01

  Yeah, I think that's, that's the, 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. Right. And in the past, I think people, there was a discussion in 2024, the dialogue, and there was a lot of disappointment because, you know, China didn't, didn't come with all their technology people and they didn't, we didn't come up with a solution. And so they're not really sincere in, in dialogue. And I think you need to understand, just like, you know, Chinese works on decades for their strategic plans, they also take a lot longer to prepare when they're doing these kind of diplomacy discussions, right?

• 1:58:49Speaker 01

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

• 1:59:34Speaker 04

  And as you're talking to them, as you're talking to them, can I suggest something?

• 1:59:39Speaker 01

  Yeah.

• 1:59:39Speaker 04

  Because I think it feels to me like the US is focused on having the best model, whereas the real power will coming from, will come from having the best ecosystem.

• 1:59:48Speaker 01

  Yeah.

• 1:59:49Speaker 04

  And I think that's what you're pushing anyways. So I'm really thrilled that you're in the middle of those discussions.

• 1:59:53Speaker 01

  Well, I think they're, you know, the, the discussions right now are really more around safety, right? Because the, the ecosystem versus model thing is a competitiveness of how do we, how do we become more competitive as a country or, you know, have, 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, you know, AI is not being used by bad actors to, to create instability around the world, that AI itself is not, you know, potentially creating harm to, to the world on a, on a longer term. Right? And, and I think that's, that's the, and, and you know, there is also the kind of underlying idea of, you know, nation to

• 2:00:38Speaker 01

  nation, kind of aggression, right? And I think, you know, those three different things are, are, are all being balanced. I would say that the higher priority today would actually be the bad actor, you know, non-state actor risk, which is what, what Besen said, you know, when he was interviewed the day after that discussion, because he realizes that nation to nation aggression has been in balance, you know, between superpowers for eight decades. Right? And, and, and that doesn't change with AI. Right? And in fact, you know, because if you, if you use AI to hack into somebody's network and then you

• 2:01:21Speaker 01

  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. Right? And, and people realize this. So people in the actual national security space, like, you know, 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. Right? So, so non-state actors is something that everybody should be worried about because it, it is going to happen. It's already happening. I think the, the ransomware and cyber attacks is up two or three hundred percent in the last year or two. Right? So, and then it's going to be even worse because of what we've seen. When you start putting a thousand agents

• 2:02:03Speaker 01

  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, that shared 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 a false flag misattribution.

• 2:02:20Speaker 04

  But Alvin, the good news could be that the, the, the fact that you have this third party danger means that the concept of an AI national race becomes obsolete because there's a bigger problem I have to solve.

• 2:02:33Speaker 00

  Alvin, that's exactly why I love your Stags, 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, you're taking that into the conversations with, with China on the, on the 24th.

• 2:02:57Speaker 01

  Yeah.

• 2:02:57Speaker 04

  I mean, it's existential on those diagonals.

• 2:02:59Speaker 00

  Yeah.

• 2:03:00Speaker 01

  Yeah. And then we placed ourselves in that diagonal. I think that's, that's, you know, it's a self, self-imposed harm right now.

• 2:03:07Speaker 03

  So I think we would be delinquent in this discussion. We've talked quite a bit about the model layer. We've talked about the GPU or chip layer. We haven't talked about the foundry layer of, of all of US v China. And it would seem to me, one of the, 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, in your, in your geopolitical analysis? Does this end with China attempting during this geopolitical and demographic window to invade Taiwan and seize TSMC to gain leaning, bleeding foundry node capacity? Does it end with Taiwan retaining its independence and TSMC not having to blow up all of its

• 2:03:51Speaker 03

  fabs? Where does this end?

• 2:03:53Speaker 01

  So I think there's, there's, there is an assumption right now that some people in, you know, in DC are saying, hey, you know, the reason that China wants to invade Taiwan is to get access to these fabs. And they don't have these fabs. And so this is why they're going to, you know, go and attack. The, the, the reality is that if anybody attacks the island, there is nothing there to be had in terms of, of workable fabs. Right? So I, I probably shouldn't be talking about this, but I was having.

• 2:04:26Speaker 03

  Oh, you, that means you definitely should be talking about it.

• 2:04:30Speaker 01

  I was having breakfast with the, the CTO for TSMC and also a former senior official from the CIA. And the, the TSMC guy goes, hey, I heard that you guys are going to blow up our data centers if China attacks. Is that true? And the CIA guy says, hey, I can never confirm or deny that. But what we do have is we have a thousand engineers of yours that we know we will fly out before anything happens. Right? So what, what, what America cares about right now is that they want to make sure that they can duplicate these capabilities to fabricate the latest ships in America, you know, if anything happens, right? And this is part of what the CHIPS Act was. And that's why I think, I think there are some

• 2:05:15Speaker 01

  good things that came out of the CHIPS Act that, you know, now there is hundreds of millions or hundreds of billions of dollars, actually, that are being put into domestic

• 2:05:26Speaker 01

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

• 2:06:10Speaker 01

  They, they realize that. But the reason China cares about Taiwan is not because of the fabs. It, it is absolutely because of a political history. And then you know this, right?

• 2:06:20Speaker 03

  Yes.

• 2:06:21Speaker 01

  Essentially, in 1949, the, the movement of, of the Taiwanese, the nationalist party to, to Taiwan. And, and that to them is a, a, an uncompleted civil war. And, you know, the, the, the two countries, actually, right now is recognized by America, including 190 other countries as being one country. Right? So this is kind of like Hawaii and the US or maybe Puerto Rico and the, and the US, right? They're, they're kind of pseudo part of a, a, a one national structure, right? And, and it is more of a political and, and,

• 2:07:05Speaker 01

  to them, a civilizational ending to a, a long story. That's the, the main focus. And they've multiple times, every, you know, ever since, essentially Deng Xiaoping to now have talked about peaceful renunciation. Right? So, so I don't think there, there is a, a interest or a rush to do any near term attacks to try to get Taiwan because of CHIPS. I just don't see that.

• 2:07:30Speaker 03

  So you don't, you don't think like there, there's like a back, just a quick question then, you don't think there's like a backroom discussion somewhere, maybe in connection with the summit? Okay, give the US maybe two to three more years to migrate leading edge node fab capabilities to Arizona or otherwise, re-domesticate TSMC's capabilities? And then China, okay, fine, you, you can retake Taiwan because we don't care anymore?

• 2:07:56Speaker 01

  So I don't know if you had a, a chance to read my, my paper, The Great Reckoning and The Reconnecting, but it, it talks about Taiwan in some aspect to say, hey.

• 2:08:08Speaker 01

  Just like during the 2008 great financial crisis, actually China helped out the US a lot in terms 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 is a correction in the market due to what's happening right now with the overbuild and the over-leverage

• 2:08:46Speaker 01

  of the AI sector, right? And maybe at that point, the Americans, or maybe Trump, will give a call to Xi and say, hey, can you help us out again? And maybe I'll just be more hands-off or be more clear instead of the ambiguity issue. And this is me completely speculating.

• 2:09:06Speaker 03

  Wow, this is your, 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?

• 2:09:29Speaker 01

  Well, not in the sense of here's Taiwan, but to say, hey, as long as you agree to some kind of a peaceful thing and over a mutually agreed term, that we're going to stay out of it, right? Because we've been very involved in the kind of Chinese political or the Taiwanese political sphere for a long time. We've been selling weapons to them for the last 40 or 50 years, right? 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

• 2:10:12Speaker 01

  them, what would America do? And look at what happened in Cuba, and how we responded, right? So I think we need to be sensitive to why this is an issue for the Chinese. And I'm not apologizing for them, I'm not saying they're right or wrong, but I think it's important for, in any negotiation discussion, to understand the other side.

• 2:10:32Speaker 04

  It is important for everybody to understand that the US policy towards China, Taiwan, is a one-China policy explicitly stated.

• 2:10:43Speaker 01

  Yes.

• 2:10:43Speaker 04

  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. Where do 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 we'll kind of, we have to pick one or the other? How do you see this next few years playing out?

• 2:11:10Speaker 01

  You talking about for just the AI space in general?

• 2:11:13Speaker 04

  AI and the global transformation.

• 2:11:15Speaker 01

  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, they're, you know, once they go public, or if they go public, their financial will become much more clear. People will start to realize that the value of the AI innovation does not necessarily accrue to them. It may in the near term, right? And it has, they're one of the biggest beneficiaries, but it was also, that accrual came from a period when you didn't really have the open source capabilities that we have today. And in fact,

• 2:12:00Speaker 01

  if you look at the recent disclosures in terms of where Anthropic's revenues were actually starting to flatten out a little bit, it's not, you know, earlier this year, they were growing like, you know, 10x over just a few months, right? And now they've essentially flattened out at the kind of ARR in the 70 billion range. Although, even though their ARR is a 70 billion, their first two quarters was, I think, right now, total less than 20 billion in revenue, right? But they're committed to hundreds of billions in CapEx in debt. You know, there is right now 1.6 trillion dollars of off-the-book debt of the major hyperscalers today. 1.7 trillion, okay? During Enron days, there

• 2:12:42Speaker 01

  was a $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. You know, 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, right? So that is not a very diversified revenue base. And as more and more of the

• 2:13:27Speaker 01

  capabilities move to open source, move to edge computing, the dependency on cloud-based premium services will continue to erode. I think that, yeah.

• 2:13:41Speaker 04

  We'll shift the bottleneck down the stack to compute, electricity, power, et cetera.

• 2:13:46Speaker 01

  Yeah, yeah.

• 2:13:46Speaker 03

  Although China, China is also, I mean, maybe to 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 it, isn't there a sort of a striking parallel between, Alvin, you're pointing to the West maybe over-leveraging compute and data center infra-red development, and China perhaps over-leveraging or over-indexing on, for humans, real estate development?

• 2:14:31Speaker 01

  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, right? And they managed it in a way that it was not a crisis, right? We need to do a soft landing for these things so that it does not create a crisis, right?

• 2:14:52Speaker 03

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

• 2:14:57Speaker 01

  Yeah. Well, I mean, no, I think that the ghost town thing, there may be a few, but the reality is that the homeownership right now is something like 70% in China, and it's probably less than 50% in America, right?

• 2:15:09Speaker 03

  Yeah, it is.

• 2:15:10Speaker 01

  So I don't think we want to over, I guess, parallel these two things, but I think what we can learn is that when the crisis happens, you need to be willing to take some near-term pain, and they did, right? They took major hits in their GDP slowdown. You know, they were growing at, you know, 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, right?

• 2:15:45Speaker 04

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

• 2:15:55Speaker 00

  Let me ask you about the managed crisis, actually, because China-

• 2:15:58Speaker 04

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

• 2:16:08Speaker 00

  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, more than anyone. But when I was at MIT, there was a class called Just Wars, Total Wars, Nuclear Wars. And I was like, I got to take that class and see what it's all about. And essentially, what they taught us in the last third of the class is, look, this is at the height of the Cold War. The 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

• 2:16:52Speaker 00

  or later, one country or the other is going to have a ability to destroy the other country with no retribution whatsoever. This is, this is going to destroy the world. In reality, you know, this is where I lost faith in poli sci classes. In reality, it didn't play out that way at all. Like you said earlier in the pod, the Soviet Union bankrupted itself with way too much weapons investment. But it then became obvious that the Soviet Union wasn't really a tight-knit country in any way, shape, or form. And now we have Ukraine and Russia, you know, both part of the Soviet Union, in a five-year-long catastrophic, devastating war. And the other satellite entities don't even speak Russian. You know, they're off, so I don't have any idea. What is China like? Is it, is it truly unified, like the United States? Is it fragmented?

• 2:17:36Speaker 01

  Yeah, I mean, I think this is one thing that China has that's very different than a lot of the rest of the world. It's very homogeneous, 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, right? So I don't think we're going to see the type of issues that you saw with the USSR, even if there was a major economic crisis. And I think they've managed it very well. In fact, they've learned a lot of lessons from the disintegration of

• 2:18:19Speaker 01

  the Soviet Union to say, we cannot let that happen, because that would mean hundreds of millions of people would suffer or die, right? And, you know, that is their biggest priority, is social stability, political stability, economic stability.

• 2:18:33Speaker 03

  I should just add, maybe to find point, the Uighurs, ethnic Muslims, ethnic Turks may differ with that assessment regarding ethnic homogeneity and the unity of approach, sort of everyone's Han-type characterization of China for the record.

• 2:18:54Speaker 01

  I'd say 95%, right? And so I think there are definitely a few percent, but it is a relatively minority, right? And even, even the Uighurs or whoever, they all speak Chinese, they all read Chinese. So there is a common language. And, you know, I think that-

• 2:19:16Speaker 01

  The desire to succeed is not as prevalent as we tend to portray it in US press.

• 2:19:27Speaker 00

  We'll have to save that for next time, I guess.

• 2:19:29Speaker 04

  Yes, 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.

• 2:19:53Speaker 01

  I do want to end with one thing is

• 2:19:56Speaker 04

  Go ahead.

• 2:19:57Speaker 01

  I think for America to actually be successful in this industry and take advantage of what we've created is actually to think about creating something that's akin to an AI Marshall Plan, right?

• 2:20:11Speaker 04

  Yes.

• 2:20:12Speaker 01

  So the Marshall Plan post World War II, we spent around, I think, $15 billion to $18 billion rebuilding much of Europe and some parts of Asia. And that created an ally

• 2:20:24Speaker 04

  Created markets for our goods also.

• 2:20:26Speaker 01

  Created giant markets for our goods because at that time, we had 50% in manufacturing. And it created loyalty and allies for eight decades, right? 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, right?

• 2:21:00Speaker 00

  That's great. That's great advice.

• 2:21:02Speaker 01

  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 able to finance it, we're going to need to sell those Nvidia chips in other places, right? So we're going to need to sell services. We're going to need to, you know, 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

• 2:21:46Speaker 01

  creating additional competition and conflict.

• 2:21:49Speaker 00

  Well, I think what you said back to back there, 95% of China is ethnic Han. And the US needs a Marshall Plan, but the US 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 slavery.

• 2:22:21Speaker 01

  Cleansing.

• 2:22:22Speaker 00

  Cleansing. They'd much rather work with the United States than if we just give them a chance.

• 2:22:27Speaker 01

  Yeah. And we're telling the world the opposite story right now, right?

• 2:22:31Speaker 00

  Yeah.

• 2:22:32Speaker 04

  There's the advice that we'll end on. Stop shooting foot. All right. Alvin, it's been awesome to have you on. I speak, I think, for all of us on the pod and the viewers when I say it's really great that you're in the middle of these discussions. So push your ideas as hard as you can. We'll do the same on your behalf. We'll definitely would love to have you back again sometime. And on that note, thank you for being with us and we'll wrap it up for today.

• 2:22:59Speaker 01

  Yeah, thank you all.

• 2:23:00Speaker 04

  Alex, David, we'll be back next time.

• 2:23:03Speaker 01

  And quick questions, Alex.

• 2:23:05Speaker 03

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

• 2:23:17Speaker 01

  No, I'll get it. Thank you.

• 2:23:19Speaker 00

  Don't go away. Don't go away.

• 2:23:21Speaker 03

  Thanks.