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The closer you are to the machine god, the more its voice whispers in your ear. Right. >> That's right. Yeah. I don't think the Beijing is an AGI pilled. >> Kyle Chan, welcome to Interesting Times. Great to be here.
So, at the moment, there are really only two countries that matter for the AI future. The United States and China. Their leaders are meeting in Beijing and the atmosphere is sort of similar to a kind of cold war atmosphere where people think and argue and talk about them being in a kind of arms race. >> We're leading China. We're leading China by a lot. China knows that. >> I think at the moment China is winning. >> There's no second place. It's either going to be the United States or China. >> You are an expert on China and AI. And we're going to talk about that race. Who's winning, what winning even means, whether it even makes sense to talk about the US and China in terms of a race. But I want to just start with a basic question. How is China's current approach to AI different from the American approach?
>> It's quite different actually. So in the US there's a particular focus on AGI artificial general intelligence and to create something approaching an artificial super intelligence some kind of almost machine god that can do virtually everything that any human can do at least on a computer >> and more and more you want to get more right that's that's the super part >> absolutely and you can see that the amount of spending the amount of investment the amount effort that the American big tech companies um and their you know quotequote startups like OpenAI Anthropic which are now close to trillion dollars each are pouring into this um is an indication that they're making a big bet that they can get there at some point maybe in the near future. That's the race to AGI in the US.
China is running a different kind of race. I would argue they're running multiple races. On the one hand they are trying to produce better and better AI models. They do want to try to keep pace with their American competitors, but that's not all they're focused on. They're also focused on efficiency, making these models smaller, cheaper to run, easier to deploy. That's one area. Another area they're focused on is diffusion, trying to get AI into the hands of as many users as possible. And part of that strategy involves open source, right? So this involves kind of giving away your models for free. Um, and that allows other people around the world, including in Silicon Valley, to download Chinese models and to also customize them and tweak them based on their own data and to make them work in a way that's more tailored to their own needs. So that's the advantage of open source. And another major area that China's focused on is applications. Specifically, robotics is a huge area of focus both for the government and for Chinese AI companies, but you don't really hear so much about AGI. You might hear some of the Chinese tech founders talk about this and they sometimes sound a little similar to their counterparts in the US, but overall they're much more focused on these sort of nuts and bolts uses and applications of AI in people's daily lives. That's the key priority.
So, if I went to Shanghai or Beijing right now and spent a couple weeks there interacting with physical reality and digital reality, do you think I would notice a big AI-driven difference versus life in the United States? Just describe like the everyday experience of this strategy to the extent that it makes a difference in how people are living.
>> Yeah. So in the larger cities in China, you might see um autonomous delivery robots um dealing with package deliveries, food deliveries. Um you might see in a restaurant uh a waiter robot bringing your food. This is not super super widespread yet, but it's starting to uh to come about. um hotels rather than having room service be delivered by a person uh pushing a cart coming up the elevator. It might be a delivery robot. Um you have of course the self-driving cars. You might even have drone delivery for coffee or food. But it would be a subtle but probably surprising difference to what most Americans experience in terms of their interaction with AI in the physical world.
So let's just pause for context because you talked about the government versus the Chinese AI companies, right? And I think most viewers and listeners are accustomed to the American situation where you have a set of big companies. They have been extremely lightly regulated by Washington DC and just in the last year we've started to get into dynamics where the Pentagon especially seems concerned about their national security implications. There's talk about regulations, screening of models and so on, but but basically it's been a very traditionally American capitalist environment, not a Manhattan project or anything like that. To what extent is China similar or different just in the relationship between the companies and what is obviously a much more powerful and often repressive state?
>> Yeah. So in China, the state is in charge or specifically I should say the party state, right? The Chinese Communist Party and the various government agencies that they oversee. They're the ones who set the rules. They're the ones who ultimately are shaping the trajectory of China's AI industry. They have quite strict regulations. Um, for example, requiring AI models to be registered in advance. They have certain content and censorship um rules that must be followed. um they have a whole host of ways to uh enforce their rules, have leverage over Chinese AI companies. Um and there are echoes back to a previous era where they cracked down, Chinese regulators cracked down on Chinese internet companies for example.
>> So that's sort of the overarching relationship, but that doesn't mean that the Chinese AI labs themselves are just in lockstep following whatever Beijing says. Um, you know, ironically, China tried a more top-down model to technology in a previous era, and that failed miserably. Um, it did not produce the kind of innovation and flexibility and agility in the marketplace that you would need to have cutting edge technology.
>> What what era are we talking about with the more top-down approach?
>> So, I mean, that was I would argue um going back to the Mao era, right? Um, this is the >> pre pre-Deng, pre-1980s, right? >> Exactly. Yeah. That sort of almost Soviet command economy. um style approach. So what you have is sort of a hybrid model in China if I could characterize it in a single word and that would be this sort of broader direction and guidance and certainly support from the central government in China as well as local governments on the one hand but then also trying to create space for competition and innovation from the Chinese AI labs themselves. Whether you're talking about, you know, China's equivalent of the big tech like Alibaba or Tencent, the maker of WeChat, the popular super app, um, or you're talking about China's own AI startups like Z.A.I. or Moonshot, which have become actually quite popular around the world.
>> So, what what are the what are the Chinese equivalents uh to the extent there are of an Anthropic or an OpenAI right now?
>> That's a good question. So, maybe Deepseek would be the closest. Um and then you have the smaller startups and by smaller I mean like on the order of 40 to 50 billion market cap uh and those are some of the more successful ones but it's hard to find that kind of middle ground. Uh DeepSeek now is preparing to take in outside investment. Remember they were actually not originally an AI company. They were part of uh a hedge fund actually that was trying to use AI to develop more sophisticated uh financial models. So they're sort of uh a category unto themselves.
>> And all of these companies though are operating under some basic constraints that don't apply to US companies right now mostly mostly around chips. So can you describe just describe that the landscape of constraint in China and what it means?
>> Yeah so I had mentioned earlier that Chinese AI companies are trying to run uh different races. One of those was efficiency and part of that is in response to the constraints that they're under in particular around compute and chips. So remember right now um the US has export controls on our most advanced semiconductors made by basically Nvidia. Um and we stop those from officially being sold in China. Um we allow the sale of watered-down versions. Um, but the idea is that we keep the best and the most advanced chips for American AI companies in the United States and and for allies and partners. Um, for China that means that they don't have access to the most cutting-edge AI chips. They have some Chinese domestic alternatives and this is a big part of the story, right? One of the leading players in the space is Huawei, right? The heavily sanctioned Chinese tech giant that um rose first in the telecom space, branched into smartphones, and is now in pretty much every other industry, electric vehicles, uh clean technology, and certainly now AI and chips. So, China's trying to build up their own capacity for developing AI chips on their own, not just designing them, but actually producing them. But the problem is they're just not quite as good as the Nvidia chips. And without that, it does put a lot of constraints on what they can do. So, they're trying to squeeze more out of very limited compute.
Why aren't their chips as good? I know this is a simple-minded question, but is it just that Nvidia is so awesome at engineering and China's engineers, even if they have an Nvidia chip, can't quite get there themselves. Like, talk talk to me. Talk to me like a non-chip specialist.
>> This is the $5 trillion question which is currently I think roughly the market cap of Nvidia in the today. Um, there's a couple different aspects to this. One is actually the chip fabrication that is producing the chips. Remember Nvidia doesn't make their own chips. TSMC in Taiwan, they're the ones that make the chips.
>> Conveniently located not that not that far from China.
>> That's right. That's right. um to the consternation of probably a lot of folks in Washington and and maybe other folks uh dependent on those supply chains. But TSMC has been pushing the boundaries for increasingly advanced semiconductors in a whole range of areas and that includes AI and NVIDIA by partnering with TSMC can combine some of the best design work out there with some of the best production capabilities. For example, ASML, a Dutch company that, you know, maybe some people have heard of. It's actually one of the biggest tech companies in Europe now. Um, they make these extremely precise, extremely expensive, um, lithography machines for basically kind of printing uh, chips and they're the only ones in the world that can make this kind of machine. They sell those to TSMC. TSMC can use that cutting-edge technology combined with their own cutting-edge manufacturing processes and work with Nvidia to produce these incredible state-of-the-art chips that keep getting better and better.
>> So, so just essentially then when we talk about the US not allowing Nvidia to sell to China, we're effectively talking about the US cutting China out of just a larger supply chain, right, that runs through Taiwan, through the Netherlands, through all all around the world.
>> Absolutely. Okay, that's that's interesting and very helpful. Um, what does China have going for it then than in terms of AI buildout that the US doesn't have?
>> Energy is absolutely absolutely huge in China. And this is something that if you're thinking about the broader AI stack, that is not just the chips or the models themselves, but deeper down on the layer, energy is perhaps the most important and least talked about. Um, for the US, this is a major bottleneck. It's very hard now for data centers to build out the power capacity to power all those chips that they're that they're putting together. In China, uh, interestingly, um, they've been building out energy at a very rapid pace, um, clean energy, solar, wind, batteries, and they're trying to leverage that ongoing energy buildout to feed into their compute buildout, which then feeds into their AI development. And so, you see really interesting sort of strategies that the Chinese are taking. For example, they have this effort to try to build data centers out in the western provinces away from the high population urban areas in China. And at first that might not make any sense, right? Don't you want to have your data centers close to where people are actually using them? Don't you want to have that low latency, you know, high response time? And what China's trying to do is they're trying to leverage a lot of their renewable energy resources out in those further off regions. They're also trying to just do sort of good old-fashioned geographical redistribution. Um, concerned always about having these poorer provinces remain poor while the high-tech Shenzhen and Shanghai, you know, speed on ahead. So, this is another area where they're trying to leverage some of their strengths to feed into maybe areas where they're weaker.
So then China is to sort of simplify imagining a future where they're only a little bit behind the US and actually say say what that means. People talk about you know the best Chinese models are 3 months behind the US or 6 months behind the US. H how far behind are they and what does that mean in practice?
>> Overall, I think the consensus is Chinese models are somewhere between 3, six to nine months depending on the time of year and which was the latest model that just came out. Um what that means is that when you look at specific benchmarks um specific evaluations for trying to understand how well these perform on say math or coding tasks or even sort of new agentic tasks um the Chinese models that are released today are starting to get close to the American models that were released you know a couple months back. So that's what that that lead time means. But the thing is it's not just about having the absolute most cutting-edge model because you can have very very strong models that can do a lot that can do a lot of agentic useful tasks like um maybe create a whole PowerPoint presentation for you based and do all the research and analysis that goes into that um or answer your emails. So there's this uh strategy I think right now in China where they're hoping that it's not just all about having the very best models that it's about trying to figure out where to make this work and also to build kind of the broader ecosystem for deploying these models to integrate them into more and more services like into food delivery or into ride hailing or into you know again much more practical sort of real-world applications.
So in the US obviously there's just a lot of anxiety around AI to a greater degree than any sort of big technological change in my lifetime. Certainly there's apocalyptic fears. Uh there's economic fears about job displacement. There's social and cultural fears. There's people who just don't want data centers built in their backyard. So there's a whole range of different moods. If you were going to try and distill the mood in China, the public mood around AI, how would you describe it and how is it different from the US?
>> I think the biggest anxiety right now in China is anxiety around falling behind on technology. So I think in the US there's a lot of worries about job displacement, uh of AI being a net negative force in society. um in China there are some of those concerns and I can come back to that but I think right now um the fear among individuals and companies and workers is that they're not keeping pace with AI that they're not using it enough and they're not savvy enough with this new technology so that they won't be competitive enough in the in the labor marketplace. So, and it's interesting this sort of anxiety at the individual level kind of mirrors China's anxiety at the national level. Um, when ChatGPT first came out and in fact you can you can even go back to when AlphaGo first defeated the world champion human world champion in Go. >> Wow. >> Wow. Wow. Wow. There was a lot of anxiety in China uh among China's AI industry and among policy makers in Beijing worried that China was also falling behind that they were not making the most of this new transformative technology. So it's interesting to see this kind of mirroring where it's not about um how do I keep out this technology from my life. It's about how do I bring it in even more and integrate it and give myself that edge in a very very crowded marketplace.
>> And does that so I see that attitude in the US but it is a very >> Silicon Valley tech and tech adjacent attitude right um it is you know it's spreading but you you see it in a pretty confined zone of the American economy but are you saying that in China it is just much more widespread right that you you don't have to working for Deepseek or Alibaba or something to have this have this like am I falling behind I must add AI protocols mindset.
>> That's right. Yeah. So it's interesting that AI is hitting uh at a time when China was already experiencing a whole bunch of anxieties around labor markets especially for uh young college graduates. Um so for example the unemployment rate for uh for uh young people in China is basically double what it is in the United States uh it's something close to 17% which is extremely high. Um the number of new college graduates hitting the job market um this year alone is 12 million plus uh in China. These are all people competing for many of the same jobs. They don't want to work in the factories. They don't want to have those blue-collar jobs or delivery jobs. They want, you know, in their minds the good jobs and they're worried that if they don't keep up with AI, they might not be able to to get those. So, it's it's a longer-standing concern about this hyper-competitive environment in China. That has been there since as long as I've been going to China, but AI really sort of amplifies and accelerates those anxieties.
>> And I mean, part of the debate in the US has also been about the welfare state. And you have, you know, tech leaders talking about um sort of how the welfare state has to adapt if there is AI-driven unemployment. You have Elon Musk promising not universal basic income but universal high income. Um China does not have a safety net to any degree like the United States or like Western Europe, right? Is there a welfare state debate in China, a UBI debate, anything like that?
>> Increasingly so. I mean the great irony here is you know I was speaking about the Mao era earlier. Um that is the era of the iron rice bowl of the idea that you were a worker at a state firm at a state organization and you basically had your job for life. Um and this idea of job security is no longer there in China unless you're working for again a state-owned enterprise or within the government. Um and so that concern is coming back and there's actually more discussion now including among policy folks in Beijing about the potential issues related to AI job displacement and what China should do about it from a welfare and and policy standpoint.
>> I mean, how far I mean are there like sort of actual policy ideas sort of in the wind? Is is there a you know UBI under communist conditions? It's it's still early stages and >> from each according to his ability to each according to his needs makes a comeback >> to get rich is glorious but also >> but also they are the Chinese Communist Party after all. Um, yeah, I think it's still early days for that discussion and there's still a pivot that's happening from the sort of all-in, you know, hit the gas pedal on AI progress, including from the policy makers where they were emphasizing, you know, all the new jobs that would be created by AI. You know, don't worry about those other jobs that might be affected. You know, that's part of the industrial revolution that's happening now, industrial revolution 4 or 5.0. Um but now now that conversation is starting to shift.
>> And what about the central government's concern about social effects of AI because one one notable thing in China you mentioned earlier the crackdown on internet companies. There was and has been a deep anxiety about the internet's effect on social life. You've had attempts to write crackdown on video gaming among young men. All all of the things that sort of American commentators worry about at a sort of speculative level have actually sometimes been been actual policies in China. And this is connected to the reality that China has a bigger problem than the US with falling birth rates, falling marriage rates. Are China's leaders looking at AI through that lens and worrying about, you know, the AI girlfriend, AI boyfriend future?
>> Definitely, they are very worried about that. And in fact, they are already rolling out policies and regulations around AI boyfriends and AI girlfriends. You know, it's so funny. They they like they have a very sort of um uh negative view of wasting time basically of what they see the folks in Beijing what they see as sort of nonproductive activity. And in that earlier era of a tech crackdown, you know, they saw video games as not really part of the Chinese vision for a, you know, high growth technologically powered future when everyone's at home playing playing video games. And they also cracked down on the education market. Um, so there was a lot of private tutoring. EdTech startups were were sort of sprouting up. and they saw that as also kind of wasteful because it was sort of a race to the bottom in terms of preparing for exams and feeding into that kind of cutthroat academic environment. So I think right now we're seeing something similar happen again with worries that AI companions could end up being a big time sink for Chinese youth when they should be engineering the future and building up the startups and the future Chinese versions of SpaceX for example.
But is there also a sense that this is the solution if China never fixes its birth rate that that robots are just the way that aging low birth rate societies compete? Is that is that also part of the the theory or the mindset?
>> Definitely that's a big part of the story. So China has a shrinking workforce. I think their labor force uh size peaked actually over a decade ago and they're heavily dependent on manufacturing. They don't want to let that go. Uh they see that as the engine for the whole economy. Um so how do you reconcile those two factors when people don't want those factory jobs anymore? Uh and young people want sort of different jobs uh and there's just not enough people to fill the factories. One solution is robots. One solution is to increasingly automate factory production to put robots of many different kinds, whether they're your classic six-arm industrial uh six-axis industrial robot arm, >> the classic the classic six armor, >> you know, that can lift up a you know a car in in one go. Or now this big push with humanoid robots is seen as being yet another potential solution, if not a perfect solution to this ongoing labor issue. So, China wants to continue to become more and more competitive, to move up the value chain, and to make better and more high-value stuff, but they don't have the workforce. So, AI and robotics is seen as as the way to fill that in.
>> Yeah, it's it's interesting just thinking about you mentioned like robot waiters, right? So one thing that has been sort of encouraging I think to people worried about job displacement in the US is the extent to which robotics in restaurants, fast food places, supermarkets and so on has not so far radically displaced human workers. And in fact, places like McDonald's and Starbucks that have tried to sort of really, you know, move to kind of automatic ordering and so on have often found themselves sort of maintaining human staff beyond what they expected or expanding human staff even. In the in a context though where like the Chinese birth rate is maybe 2/3 the US birth rate at this point depending on which stats you look at, >> you're just in a different landscape, right? where you're maybe you're worrying less about whether the robot waiter displaces workers and more about whether you have a waiter at all and so the robot waiter is is welcome and necessary. I mean that seems like it could be a big point of >> sort of the divergence ultimately between how the US and China relates to robots.
>> Yeah, definitely. It's like you're going to have to err on the on one side or the other. you're going to have to err on the side of going too slow and then um you might not have the ability to do all these things because there's not enough workers there or you might err on the side of going too fast and I feel like that's the concern in the US more. Let's pull up to to the back back to the AGI super intelligence question. How do you think China's leaders actually think about the American fixation or the tech world Sam Altman Dario Amodei fixation on on AGI? Is it and two options you can tell me if there's a third right? One option is that the Chinese basically think that our tech companies are high on their own supply that there is not you know that there's never going to be some insane return to super intelligence and it's always going to be fine to be you know 3 to 6 months behind but then you have catchup. Another option would be that China is actually worried about super intelligence and is basically trying to figure out what are our contingency plans if the Americans seem to be pulling much further ahead. Do either of those describe China's mindset to the extent that you can you can sort of read the tea leaves in Beijing?
So I mean one, you know, sort of interesting corollary question is, is China trying to do an AGI Manhattan project somewhere buried underground in a bunker with data centers that can't be seen by satellites and powered by >> Yes. Are they? >> And my inclination is no. And you don't >> do you think they could do something like that without the US being aware of it? So I don't think that they would be able to do that without the US being aware. I think that it would require such a scale of production of amassing resources and construction that we would detect something and we would start to wonder what is going on. And I mean we already are watching everything about the nuclear buildout for example in China uh nuclear weapons buildout. So I I would I would be very doubtful that we would miss something of that scale because you really would need massive scale in terms of compute and energy to power something that would be like a Manhattan project for AGI. So they're not they're not secretly trying to win the race. Whatever they're doing, they are sort of accepting this position of being in our draft on the racetrack or whatever metaphor you want for now, right? But is that just making a virtue of necessity or do they think that we're deluding ourselves in our in our race to to super intelligence?
>> I think they just see the technology quite differently and they just don't have that kind of um transcendent view of technology. I think that um you can see this in other approaches that they've taken to the internet or to the IT revolution which they were obsessed with as well. Um so they were really focused on just trying to integrate the internet and IT infrastructure into just basic services, education, healthcare, government services. And I think they see something similar with with AI. Now, you know, one thing that I one kind of thought experiment I often uh think about is what would be the signs that they were trying to do a secret AGI program. And one of the signs I think would be about those Nvidia chips that I mentioned earlier. Um where right now um Trump has relaxed some of the export controls and allowed H200 Nvidia chips to be sold to China. Those are better than what China had gone before, but not the very best. And China has basically said thanks but no thanks. The AI companies to be sure in China really really want those chips. But here's the divergence because Beijing they don't necessarily want to be dependent on the US and they want to bolster their own semiconductor program. So if they were really sprinting today for AGI, I think they would have gobbled up those ships as quickly as possible not knowing when that window might close. So that is one sort of indicator um that they are kind of seeing this as a medium to long-term bet. Um
>> so so there might be people at Deepseek >> who believe in the super intelligence future more strongly than people in Beijing.
>> Yes. Yeah. I think um the AI >> the closer you are to the machine god the more its voice whispers in your ear. Right. >> That's right. Yeah. I don't think the Beijing is an AGI pled.
What about what about espionage which obviously played a big role in the early Cold War arms race um with nuclear secrets. Is there an equivalent sort of spy-based solution for China if the US seems to be pulling too far ahead?
>> So there is something called distillation and that's where you take a weaker model and you actually train it on the outputs of a stronger model and distillation is a common practice uh for AI developers when it's done with full knowledge and full disclosure and and total authorization. What's seems to be happening now is some of the Chinese AI labs seem to be distilling on American AI models without authorization and they're using it seems uh a number of different sort of proxy accounts so they can get around efforts to block these campaigns. So,
>> but they're not that doesn't require stealing secrets from Anthropic. It just requires using the Anthropic model in a way that you're not supposed to be able to use it.
>> That's right. It's sort of its own category. It's not quite like outright IP theft. It's not like taking the source code for uh from Anthropic or OpenAI. It it hearkens back a little bit to an era where you know Microsoft was always trying to cut down on uh black market copies of Windows and and Microsoft Office.
Does it work in the sense that like can you you know can you just have a Chinese Claude distilled that works as well as Claude?
>> So it can help somewhat, but you need to have that foundation to start with. So I think that this is probably one area where it'll be hard still to get uh concrete data on exactly what the net effect is. Um, but I would say that if you or I were building a model from scratch, we would not be able to use distillation as a way to catch up to the frontier. If you were one of the better Chinese AI labs, you might be able to use some of this to improve your model, especially on areas where you're weaker, like uh on coding, for example. You might be able to use uh Anthropic's um Claude models to support your long-term coding capabilities. So, there is that aspect to this whole uh AI race in a world where there is some kind of takeoff. And and I should say one of the theories that animates the American AI companies is the idea that at a certain level the AIs start training the new AIs and you get this kind of acceleration where suddenly being 3 or 6 months behind it becomes impossible to catch up. Again, this would be the theory. Suppose that starts to happen. Does China just invade Taiwan? Like well seriously, right? like you you have I mean it's just a kind of fascinating circumstance that you have a kind of arms race. Maybe China doesn't think of it as an arms race, but it is sitting next door to a central hub in the supply chain that makes the arms race possible, right? Like like is that >> is that the natural Chinese move in the event that they seem to be falling incredibly behind?
>> So I think ironically if that were really starting to happen uh taking over TSMC would be a move too late because the chips are already made and installed and are already running and training the models and feeding into this feedback loop in the United States. So at that point um all bets are off and you're kind of you're kind of out of uh out of options um for what to do. Um the the a big question here is how fast that can happen and whether this could happen without being detected. Um, you know, there's always speculation about you know is there a version of the latest AI models that hasn't been shared or even disclosed to the public in say the US uh, you know, or maybe even in China where um they have gotten the inkling of this recursive feedback loop that will lead to this super intelligence explosion. So that that question is sort of hard to know. And then how quickly can you actually get there?
>> But I I want you to be prescriptive for a moment because we're having we're having a summit. We've been talking about sort of what China is doing, how China is thinking and so on. What does all of this mean for the United States in terms of our our policies? Does it mean that we should treat China as a fundamentally more benign actor than our current policy treats them as? Or is it an indicator that in fact our policy is working by shaping a Chinese perspective that is not as engaged in the race as it could be?
>> Yeah, I think at this point what we should do is take a step back from this all-out race framework because I think right now that race mentality is driving a kind of recklessness I would argue from the American side. Um to bring up like the threat of uh Chinese AGI um you know we should think about that but I don't think that that's what they're so focused on. So, but if we're only focused on that, that means we need to get rid of the guardrails. We need to not bind ourselves. We need to not have any kind of regulation or restrictions. We need to have as many data centers as possible everywhere. And I think right now that approach is starting to run into some some problems in the United States. And you know whether you're talking about the backlash to data centers or you're talking about now some of these models getting so capable that they might not be at you know whatever AGI level but they are at the level potentially of causing greater damage either in terms of cyber attack capabilities or maybe even in terms of uh augmenting what um a relatively unsophisticated group could do with uh bioweapons. So there are all these sort of questions that the AI community has been talking about for a long time. But certainly for the Trump administration, if you recall, you know, JD Vance's speech last year where he said basically we should not have hand-wringing over AI safety slow down the progress of American AI development. In other words, in this trade-off, and he viewed it as a trade-off, we should err on the side of going faster rather than putting on a seatbelt. And I think now we're reaching that point where we need to think about still making progress as fast as possible, competing with China, making sure we do have the best AI models so that we can keep, but does it have to come at the expense of wearing a seatbelt or having some basic safeguards?
Would you also suggest that the US should adopt a more Chinese vision of the goal of diffusion and sort of building the best the best possible AI-enabled technology right now? Cuz I mean a different way to frame this is that the US and China are in a race but China thinks it's running a race to build the self-driving cars and the robots that every single country in the world will use. and the US will be stuck sitting here with its pretend machine god while China you know sells to India, Africa and Latin America successfully. Do you think the US in in being less breakneck should also be pivoting to a strategy of essentially integration and sales?
>> Yes, I think we need to focus a lot more on deployment. One of those areas is actually open source, which because of the commercial incentives, is not a high priority for the top American AI labs, right? They're focused on selling access to their models through subscriptions, through APIs. And the thing is that open-source approach has been really, really powerful for these Chinese AI models to gain adoption, not just in China, but around the world. And so it feels like right now the US is seeding a really important channel of competition um when it's so expensive. It can be the most powerful AI model but you you don't want to pay for it. Um that that can put limits on on your growth.
Do you think you get that shift organically if there is a slightly stronger regulatory hand like because again the US does not we have industrial policy I'll put it in quotation marks right but we we don't have the kind of steering uh of economic strategy that China has right so it's not like you can say oh you know the United States should be more focused on deployment and there's a button to push in Washington DC that makes that happen but do you think it would happen naturally if it was a little bit harder and a little bit more challenging just to sort of maximize compute and capacity for existing AI companies.
>> I think there's a way to tweak the incentives in a way that is not like the Chinese approach that is not about a top-down steering of the whole industry um but is more about trying to create maybe some of that commercial or even research space for say open-source models. Um, yeah. I just think right now, right, you can think about a number of different markets where this is happening where there's a focus on the high end of the market on consumers or businesses that are willing to pay a lot. Um, but there's less focus on sort of mass adoption and sort of that broader marketplace. And we we're seeing some of this, right? Like I I should be clear that, you know, Nvidia is trying to release um open-source models. They have a commercial incentive because the more AI gets adopted, the more their chips are needed, right? So there's that that closed loop there. Um and uh Google DeepMind, they have some some relatively good uh open-source models, but the incentive the commercial incentives as they stand are not are not quite there.
Do you think we should sell more chips to China? Like as a sort of token of a different a different model.
>> It's a very difficult topic because anyone who tells you yes or no on chips of China is really flattening the whole story. On the one hand, you do have real near-term effects on China's ability to produce the most cutting-edge AI models. So, by limiting chips, that does slow down China's AI development in the near term. And that can be useful, for example, for giving our companies that edge and cyber attack capabilities, right? With Mythos coming out, um, even a few months of being able to test on our own systems first is very useful versus a Chinese model having this capability and they're testing on our systems, right? >> So, that's important. But at the same time, there's the other side of this whole equation, which is accelerating China's own chip development, right? And that's an area that they're they've been really focused on and they've been focused on because of our export controls, right? So, it cuts both ways. In the near term, it will slow down their AI development. In the longer term, it could speed up at least their ability to have a more resilient uh self-reliant semiconductor supply chain that is not as affected by US actions. So somewhere in there is a sweet spot and it's really about where you draw the line rather than just saying more chips or less chips.
And also how short timelines are >> overall, right? And I'm just going to make the hawk's case against against your your case and see how you respond. Right? Because the h the hawk says, you know, look, we've been at this for an incredibly short amount of time, right? Since the ChatGPT appeared in the pandemic, there's been tremendous acceleration. the people who have predicted acceleration keep being vindicated, right? Um, and yes, if you're talking about like a 20 to 25 year time horizon for the point at which you know you sort of hit maximum super intelligence capacity, then yeah, you have a lot of room to sort of figure out the optimal regulatory balance and all of these things. But if you're talking about two to four to six years, then maintaining a 3 to six month lead over your leading rival, uh, who by the way is an authoritarian government, right? Seems like it may be really, really, really important. And the slowdown that you're advocating is one that could could give up that advantage, right? So how would you respond to that that kind of argument which seems to be the mindset that certainly not just people at the Pentagon but a lot of people in Silicon Valley >> have.
>> Yeah, so that timeline comes up again and again like in so many different debates within the US as it relates to the US China AI competition and fundamentally um it it's impossible to say right how that timeline will play out. So I think for example >> that is what I yeah I've discovered that in in interviewing people yes it's impossible to say >> on the timeline question. I mean then it really boils down to uh what your views are about um this AGI timeline and how likely this is to happen. And another factor that I I will throw in there is as a thought experiment um imagine that China did have access to the most cutting-edge American AI chips. um would they be more AGI pilled? Would would Beijing be more AGI pilled? You know, forget about Deepseek or the actual tech founders themselves. And even on that, I'm not so sure that they would be so AGI pilled that my guess would be that they would try to deploy certainly better models, but basically run their current playbook just amped up a whole bunch. Um and and I think it goes back >> but even their current playbook right like includes cyber warfare includes you know a lot like you just mentioned the fact that just a three-month advantage in the deployment of >> a cyber warfare capable model like Mythos makes a big difference right so it's not it's not as though the current Chinese playbook is sort of >> innocent of conflict with the US >> that's right yeah so that's why I see it in as different sets of risks. One is this AGI risk that you're talking about and that I think is uh I would I would argue has been sort of overblown. Um but what I don't think has been overblown and in fact maybe even underestimated up until recently is the cyber risk and the biosecurity risk. These are sort of more I mean it's kind of crazy to say this but those are sort of like more medium risks relative to the AI catastrophic like total takeover by super intelligence. So those those sort of more intermediate risks I do worry about and I do worry about US competition visa v China and so I think that would be to in my mind a reason for maintaining the export controls that we currently have um and not kind of fiddling with them and not agreeing to these side deals uh with Xi Jinping for example. So that's why I try to find that balance. But in terms of the AGI question, that's where I'm just less convinced that we're really all in this sprint towards AGI, that China is really all in the sprint for the for AGI.
>> But even even on the medium risks, which I agree seem to me to be the most plausible risks, right? You are then making a calculation where you're saying, what am I most afraid of? Am I most afraid of China with the capacity to do unprecedented cyber warfare against the US or a rogue AI or disastrous AI model that you know crashes the entire US power grid for some inscrutable you know AI-related reason right like it's that balance that you're worrying about.
>> Yeah, yeah, exactly. And it and it comes to this question too about how the US should engage with China about AI because if we are focused just on China's cyber attack capabilities relative to our own um then you might say don't bother engaging right we're both in this arms race essentially on cyber capabilities but if you're thinking about the rogue agent or say a non-state actor using uh either uh a set of American models a set of Chinese models or maybe
They even do sort of arbitrage across, you know, even, you know, this is sort of like maybe 4D chess, but, you know, they deliberately are playing this geopolitical competition, uh, against each other, uh, and trying to distribute an attack across all these different models, uh, in order to disguise their origins, right?
Um, those are areas where I do think that one, it would be useful to talk to the Chinese side about these, and two, where I think it would be in the US national interest. It wouldn't just be about binding ourselves and slowing ourselves down relative to China. It would be about this extra third factor that, you know, we want to take seriously.
And this, this is a good place to end because a lot of people in Silicon Valley will say, oh yeah, in theory, we could engage with China and negotiate a sort of mutual AI slowdown, but in practice, either it's not clear that China wants to do that, wants that kind of negotiation, or it's just unimaginably complex to verify some sort of AI control agreement in the way that we did with nuclear missiles during the Cold War. Do you think a kind of Cold War-style ongoing AI control negotiation with China is possible?
I think we should not have high expectations, and I certainly don't. I think that we should start by talking. We should start by sharing, uh, our approach to AI safety and AI risk mitigation. We should try to convince the Chinese to take this more seriously, and they are starting to take this more seriously. We should also have a discussion about, uh, open source models, actually, um, because as those get better, right, on the one, on the one hand, we want those to diffuse more, but on the other hand, they could also pose a risk if they get into the wrong hands. So we can talk about all those, all those areas, but I would be very hesitant, certainly at this stage, to even think about binding constraints, verification agreements, a kind of arms control treaty for AI between the US and China at this stage. It's way too early. Let's just start talking.
If it's too early for that, is it just because of the sheer difficulty of imagining such a thing, or is it a dynamic where precisely because Beijing's attitude is that we're not in some Cold War-style race, they aren't act, they're actually less interested than they otherwise would be in that kind of negotiation?
I think overall, it really boils down to one thing, which is an extremely low degree of trust between the US and China, and an unwillingness for either side to subject ourselves to invasive verification, monitoring, surveillance by the other party. And yeah, there could be, you know, interesting technical solutions that would make that more feasible, but it boils down to this geopolitical reality where we don't trust them, and they don't trust us. Um, and so we might be able to make progress on areas that affect both of us, but when it comes to, you know, letting say, Chinese regulators come into the US, or letting American regulators go inspect data centers in China, I think that is pretty, pretty far out there at this stage.
And do you think that that only changes on the far side of some disaster, conflict, some sort of event? Because I mean, one, one theory that I sort of, I don't just toy with, I guess I hold, is that a lot of the negotiations around nuclear weapons were only possible because they'd been used, and people were aware of how destructive they are. Is there a world where the only way that the US and China come to terms is a world where something tragic has to happen first?
Yeah, that's a scenario I think about too, and I think about what would be the level of incident, and what could the response be? You can, you can think about, uh, sort of a most extreme case where you have some major cyber attack incident, or even bioweapons incident related to AI, where, um, there, there are real lives at stake, for example, um, and that could cause both countries to just unilaterally put a pause on all their AI development because they realize that this is such a big issue with such huge risks. That is possible. Um, so I do wonder, and I do worry that we might be waiting for that incident to happen before we take action in advance, before you even start to talk to each other about how to take action.
All right, on that somewhat dark note, Kyle Chan, thank you for joining me. Thank you.