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- [00:02]
A
Hello and welcome to the vergecast, the flagship podcast of the Model Wars. I'm your friend David Pearce and today on the show we're talking about the AI race ongoing between the US and China. For really the last several years, it's been pretty apparent that most of the best models and most of the most ambitious, most impressive AI has been coming out of Silicon Valley. Google, anthropic, OpenAI, this, this handful of companies has been really driving the AI revolution. But then it has increasingly become clear that China is catching up quickly. We had a big moment a year and a half ago where Deepseek all of a sudden showed up with a vastly more efficient, vastly cheaper model that was almost as good as some of the frontier stuff. And that became a big deal. Then just this past weekend, two different companies, Moonshot and Alibaba, made very clear that they have built frontier models that they believe to be just as important as, as anything else coming out of Silicon Valley. There is a race happening between the US and China to win at AI, whatever that means. It's becoming a huge tech story. It's becoming a huge policy story. And I want to figure out what's going to happen if and when China catches up and even passes what's happening in the labs in Silicon Valley. So that's what we're going to talk about. Lauren Feiner and Hayden Field are going to come. We're going to do it. But first, here's everything else happening on the Verge today. This is 90 seconds on the Verge for Monday, July 20, 2026. The Odyssey is a huge hit. It made $264.1 million worldwide this weekend, which is both Christopher Nolan's biggest opening ever and one of the biggest movies of the year so far. I haven't seen it yet. I'm hoping to wait for a 70 millimeter IMAX screening, but those are apparently sold out, like forever. In general, this has been a big summer for the movies. You have obvious wins like Toy Story 5 to surprise breakouts like Obsession. Both great movies, by the way, and it's shaping up to be the best year for movies since before the pandemic, all the way back to 2019. And if going to the movies isn't dead after all, that might be really great news for Hollywood and maybe bad news for the streaming services that we're pretty sure they'd already won this war. Meanwhile, the European Commission just levied its biggest fine ever against the platform AliExpress for failing to prevent illegal, unsafe or counterfeit products being sold on the platform. Honestly, if you've ever been on AliExpress, none of that should surprise you. The commission specifically mentioned things like unsafe toys and dangerous cosmetics and said that AliExpress has until October to come up with a plan to fix it. Temu got a similar fine for similar reasons this year. I don't know if the end of these ultra cheap, relatively unmoderated shopping platforms is coming immediately, but there is a big fight coming, and fast. And finally, a leather jacket once worn by Nvidia CEO Jensen Huang was bought on auction for $960,000. I'm not saying this is the moment to call the top on AI and tech and the economy and everything, but boy, is it getting weird out there, my friends. I don't know. You can read more about all of this@theverge.com that is 90 seconds on the verge for Monday, July 20th
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Joining me now, two people deeply qualified to make this make any sense to me, the Verge is Hayden Field, our senior AI reporter. Hi Hayden.
- [04:20]
C
Hey. Great to be here.
- [04:22]
A
And Lauren Feiner, our senior policy reporter. Hello.
- [04:24]
D
Hi.
- [04:25]
A
All of us are just like deep in China is the bad guy in bizarre and confusing and unknowable ways. So we're going to try to make sense of this along one very particular axis today, and that is AI and Hayden, I kind of want to start with you because I remember you and I talked on this show a while ago about this sort of truism in the AI community that China is six months behind that. That no, whatever happens here in the US Whatever new frontier models, China and its homegrown companies are running about six months behind the state of the art in AI. Is that still sort of the generally considered idea about US versus China?
- [05:00]
C
Right now, six months is basically the best case scenario in terms of, you know, the slowest they could possibly be. It may be that they're already caught up, and it may be that it takes one month, but six months is like the max. That's kind of the consensus right now. And, you know, all of those types of hypotheses were basically made around Mythos and, you know, the cybersecurity aspect of things. So everyone said, you know, they're about six months behind max when it comes to cybersecurity capabilities that Mythos and other models may have, it seems to be that it's even less for, you know, the models we use every day. For a lot of them, they're either equal now or they will be very soon.
- [05:42]
A
Okay. And, Lauren, give me a sense of how much politically that is a thing people are talking about. I mean, we had David Sachs a year and a half ago as the White House czar, trying to figure all this stuff out, yelling about, like, you know, American AI supremacy. This is a thing Trump in particular seems to care about on cybersecurity grounds, like the. The sort of US versus China AI race. Is this relevant politically at this moment in the same way that it is to the people in the AI industry?
- [06:12]
D
Yeah, I think the US versus China race and tech AI specifically, is perennially a big topic in Washington. I think how it ends up playing out has changed over the years a little bit. You know, we started with the Trump administration kind of being more or less in line with the Biden administration on things like export controls. Those have kind of changed over time. So I think the way that it's gone about has changed a little bit. But overall, it's always something that I think a lot of people in Washington care about and care about keeping up with and beating China in this race.
- [06:53]
A
And Hayden, it seems like the big question right now is about distillation. Everybody's all up in arms about distillation. Anthropic is. Is yelling to Elizabeth Warren about distillation. OpenAI has been complaining about it for, like, 18 months. It turns out everybody's very upset about distillation. Can you just explain what. What this thing is? And actually, it seems like kind of the main problem, all of These Frontier labs in the US are looking to the government to solve what is going on here.
- [07:19]
C
Yeah, that's a great question, especially because, you know, it's come up a lot in high profile lawsuits recently. We found out that Elon Musk's grok distilled on OpenAI's models, according to the lawsuit.
- [07:30]
A
And his response was basically like, yeah, everybody's doing this.
- [07:33]
C
Exactly. And he kind of tried not to say and then he had to because he under oath, it was a whole thing. But yeah, so distillation is essentially kind of you having a smaller AI model or a newer AI model learn or extract knowledge from a larger, more established one, a better trained one, in order to become better itself. That's kind of the simplest way to put it. So it's something that smaller or newer AI teams, sometimes with fewer resources, will do because it's an easy way to kind of make your model better very quickly and use fewer resources and just kind of speed everything up. So, you know, if you see an AI company come out of the woodwork, start really soon and then really soon after that they have a new model. And it's just amazing. Everyone's talking about it. A lot of times they use distillation to kind of, you know, bridge that gap. Essentially what happens is companies will collectively generate like, you know, up to millions of exchanges with, you know, another chatbot. So one example is Anthropic put out a statement recently that it believes that three Chinese companies, Deepseek, Moonshot, AI and Minimax, all distilled on Claude and it said that, you know, collectively all three of them generated like 16 million exchanges with Claude or something like that from tens of thousands of fraudulently created accounts. And so basically they just, you know, collect all those responses and, you know, use them to make their own model better. And whether it's from for direct training or for reinforcement learning, where, you know, the AI models may like learn certain decision making techniques through, you know, this type of process. So yeah, it's basically just kind of a get rich quick scheme, but instead of getting rich quick, it's learning very quickly for an AI model.
- [09:24]
A
Right. It's like, it's like catch up really fast shortcut. It seems like you can just basically ask the model questions, take the answers and sort of reverse engineer your way into understanding how it works.
- [09:35]
C
That's why a lot of people thought that Deep Seek sounded a lot like ChatGPT at the time.
- [09:39]
A
Interesting. Including OpenAI thought that and I think continues to think that. Speaking of deep Seek, Lauren, I'M I'm struck by the fact that we like what beginning of last year, there was this deep seek moment where all of a sudden it came out that like, China's tech is, is here, it's moving quickly. China has figured out a way to make these models in a way that is much more efficient, it's much cheaper and, and all of a sudden they have like, competitive technology. And the fact that it wasn't the very best model actually sort of became less and less important over time. And what has the government done between then and here? Obviously we're in this like insane mess of AI regulations that we don't have nearly enough time to try and piece apart. But it does seem to me that, oh no, China's AI is catching up. And we think that's important is a thing people in the government have been saying a very long time. Have they done anything about this in a meaningful way yet?
- [10:30]
D
That whole moment kind of undermined this idea that, you know, if we just make it harder for Chinese tech firms to access advanced US chips, then we can help slow down China's ability to advance in this race. And if Deep Seq was able to get to where it was without, you know, needing the most advanced chips or with, you know, so much less compute, it really kind of under undermined that whole theory. So, you know, I think we've seen, you know, a different approach to export controls. The Trump administration at one point allowed for, you know, greater sales of chips to China. Now there's some bills in the NDAA that could strengthen certain export controls on chips to China. So I think there's still not a ton settled about what's the best way to go about this. But I think it also makes clear that, you know, just cracking down on chips exports might not be the only way to, or might not be as effective as maybe we once thought it was to slow down China's ability to compete here.
- [11:46]
A
Yeah, I've enjoyed doing the research on this subject because on the one hand you get a bunch of people who are like, well, it's China, so there's essentially nothing we can do. And this is, this is sort of a long running thesis that actually all of our legal and regulatory fights with China really don't ever amount to anything, so just full nihilism, who knows what'll happen? And then on the other side, I've heard a theory that I think kind of borders on conspiracy theory that what we've seen, like with Mythos recently, where they're actually taking steps to not release these things to the public in the same way and is actually a way of keeping them out of the hands of these companies that want to do distillation. My sense is none of that is actually what's going on and that in fact what's happening is everybody is still desperately trying to figure out how to do anything here. Is that fair or is there, is there some four dimensional chess thing in progress, do you think?
- [12:38]
D
I mean, it's hard to say. I think, I feel like, I tend to agree that we don't really. It's hard to know what any of these actors are going to be doing in the next six months, one year. You know, we're really at the start of this race and it's just becoming more and more clear how many different ways all these companies are going to have to compete. And that, you know, the, the path to getting to the finish line here, so to speak, could look a lot different than we once thought. So it's really hard to predict or really know like who, who, who really has the best strategy here or what's going to pan out. So I feel like everyone is kind of making their bets on what's going to work and it'll remain to be seen what actually does.
- [13:27]
A
Okay, so I have the same question for both of you that I want you both to answer from, from sort of very different perspectives of this question. And the question is essentially what happens if China starts to win? Right. I think at this point, Hayden, like you said at the very top, at, at this point where China is either a little ways behind or barely behind, but I don't think there's anyone who would really try to make the case that China's AI, either its products or its Frontier Labs or its models are, are ahead. It doesn't strike me as completely inconceivable that that might change. So Hayden, you spent a lot of time talking to these companies, talking to the people who make the products. We're in a weird economic moment with all of these AI companies. But like in theory, if all of a sudden the next deep seat comes out and it is, it is by obvious measures the best AI product anyone makes anywhere, what happens?
- [14:18]
C
That's a great question. And I think that the fact that we have no idea is what's fueling a lot of these fears. I've seen a ton of OpenAI employees leave the company and write huge manifestos about their fears about what will happen if China overtakes us. No one's really been super specific about what that actually looks like besides, you know, potentially just data privacy issues and just giving China more power on the world stage.
- [14:48]
A
Lauren, call me crazy, this sounds like TikTok. Like we just did this with TikTok. You have been on the show talking about this with TikTok, right? Like this idea that if we let China get ahead, it will, it will gain this economic and sort of cultural soft power that will make it take over the world in some unknowable but problematic way. Like, are we just doing this again with AI?
- [15:11]
D
It's a decent analogy. And I could think of it as like, what would happen if, you know, one of these Chinese AI firms had indisputably the best AI product and everyone had to use it. You know, it's like if Huawei indisputably had the best phones out there and everyone had to have them, but we can't because, because of restrictions here in the U.S. you know, that would pose a major issue and a major question of how should policymakers deal with a product like that. And I think it would just bolster the arguments from tech companies who say we really need a long leash here to do what we need to do to innovate because we have to beat China. And I think if China got ahead in whatever way that looks like, that would, you know, maybe make some policymakers think twice about putting additional restrictions on US tech firms.
- [16:08]
C
I think this is really making the case for diversification and it's why, you know, essentially, yeah, if an AI, if a Chinese AI firm indisputably has the best model, clearly that has a lot of trickle down effects and that's what the US is worried about war wise. That has a lot of effects, surveillance, everything. And so, you know, US AI companies would quickly have to catch up and the US may be, you know, theoretically using a second best model. And is that going to make them second best at everything? So I think that's what they're most worried about here, like Lauren said. And it's hard because, yes, these are all real fears, but also we've seen these models leapfrog each other every week. So. So it's like if China was the best for a certain amount of time, would we really not? It's just hard to predict one country coming out on top forever when we've seen so much change happen stateside every day or every week.
- [17:09]
B
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- [19:20]
D
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- [20:22]
A
I do wonder, though, I think it seems like, at least so far, there has been great pride both in Silicon Valley and in D.C. about the fact that most of the best technology here is coming from the United States. Right. That the ones leapfrogging each other, by and large, are Google, Anthropic and OpenAI, three companies inside of the United States. Right. There's not even really a company that, outside of kind of occasional deep Seqi blips, has launched itself even into that stratosphere in the way that, like in a lot of other tech, there are roughly equivalent Chinese companies to a lot of the stuff that we have in the United States. Right. So there is a sense that you can have a Chinese version of things and you can have an American version of things. This idea that the American version of AI is way ahead seems like economically and politically very important at this particular moment in time. And I guess from a. From a just pure sort of American exceptionalism standpoint, Lauren, is. Is there something to that here where it's like, it's actually, it is like, weirdly important to America's concept of itself right now that we are winning at AI because of all of the other stuff right now that is so tied up in US winning at AI?
- [21:37]
D
Yeah, I mean, I definitely think it is, but I think it's not just this, like, theoretical, like, we just want to have, like, patriotism about our US AI companies. I think there's also a practical element of it. And I think the reason I jumped to kind of Huawei as, you know, a potential example, is like, you know, AI, like Hayden is saying, is something that's going to be built into so many different technologies and systems. And I think whose AI is built into those systems is a big, important geopolitical question. And, you know, if you think about kind of telecom infrastructure and, you know, the fight over different Chinese telecom infrastructure around the world and issues that have come up with that in the U.S. i think that's maybe a good analogy here when we think about, like, what kind of AI model is Europe going to be integrating into its health systems, weapon systems, whatever it is, and, you know, if China has the best model to use on, you know, across many different use cases, maybe they have no choice but to use that. So I think there is something there that goes beyond just kind of like the national pride of, like, who is going to have the best model that'll be built in across the world. And you know, what sort of privacy, surveillance issues might that carry with it?
- [23:04]
A
Hayden, does this make the American Frontier Labs more or less powerful in this sense? Because I think about all this in the context of anthropic and this giant fight with the US Government about what it can and can't do and who is and isn't in charge of the AI models. And you sort of alluded to this a minute ago, that what the tech companies are saying is you need to give us a longer leash. You need to give us more room to run, because that's how we win. You can't, you can't hamstring us. We have to go win. Does this, does this maybe bode well for these companies who are like, trust us, we need to. We need to do what we need to do, and only you can get out of our way?
- [23:41]
C
Yes, I think that's exactly what's happening here. No matter what happens with this power struggle, we've seen the Trump administration kind of try to take power back and then give them a longer leash. We've seen a lot of back and forth here. But ultimately, the tech companies do have a ton of power because the government's biggest fear is China overtaking us in AI right now. We've seen a ton of executive orders, memorandums, things coming out about how speed wins and we must at all costs be the fastest and the best. And so I think that, yeah, ultimately the AI labs have a lot of power here. They're saying, look, you know, we can work with you. We will deign to voluntarily, you know, abide by some of these frameworks you've created. But at the end of the day, you must let us do our thing and kind of just turn away until we're done, because that's the only way we're going to win. And that is something that government seems to really believe and will let happen.
- [24:36]
A
Interesting. Yeah, it's very funny to put that next to some of the other parts of the AI business where increasingly these labs are like, please, dear God, regulate us, because we don't want to be held accountable for all the stuff that happens on our models. We want you to tell, like Demis Hassabis coming out and being like, we need a, we need an AI watchdog that reviews all of the models. That's a probably a reasonable idea and B, a really easy way for the companies to absolve themselves of a bunch of responsibility for the outcomes of their models. But then to point that at, like, the, the defense contractor side of these companies who are like, you know, we have to be able to run as fast as we can and do everything that we can because we have to beat China. It's like we, we've, we've spent a lot of time, all three of us in our professional lives listening to people explain why you have to do wild things with technology in order to beat China. And I don't know, I, maybe it will, will be more successful politically and you know, as in product terms than it was last time. But it, that, that argument rings a little more hollow to me every single time I hear it. Lauren, what do you make of the political moment that we're in? We're heading into the midterms. Everybody's really mad about data centers. We are, we are in a moment where these companies are hugely powerful, they're potentially about to go public, there's a lot of money about to be had. Like, are we, are we headed toward US vs China? AI either becoming or a bunch of people trying to make it a huge story politically over the next few months.
- [26:00]
D
I think it's always something that, you know, tech companies are going to try to use to wedge some supporters into their camp. So I do definitely expect to hear that narrative. I think how successful that is could depend in part on like, do we see a big moment happen where China feels like it's getting ahead in some way? Because right now, you know, like you said, we have all this backlash to AI data centers. There's a lot of just fear around AI and you know, do we even want what we're seeing it being made into? Do we want the sort of consequences of it? So I think that's made it hard to push forward proposals that would, you know, just like, shut down regulation on AI. But at the same time, I think if we had a big moment of like, oh man, are we really behind here? I think that could put some momentum behind some policymakers who say no, we really do need to kind of just let these companies do their thing.
- [27:02]
A
It is true. I feel like we've, we've talked on this show a few times about how if you want to get anything done in Congress right now, your moves are either say you're protecting children or say we have to do this or else we'll lose to China. Like those might be the only two winning moves in Congress right now. And it's, it kind of feels like we are, we are headed right towards that again. Hayden, what do you think these companies are looking at from the like, non political side? Again, they're they're desperately trying to go public. There is so much money in this space right now. Is, are they just pushing it this as hard as they possibly can because they're like, well, if we beat China, we win the world or are they feeling this existential risk of oh my God, we might lose?
- [27:42]
C
I think they're feeling both for sure because I mean, they're incredibly terrified of China winning. You know, that this is why they're constantly researching which labs are distilling them, you know, putting out reports, writing open letters to the government saying please help us because we have proof of this and that. So yeah, I mean they're, they're terrified. And that's why some of these employees are leaving these labs and writing also big manifestos about it. They're all terrified of China winning. And I think they also just realize how easy it would be and how close China is to potentially overtaking us because of. Yeah, I mean, not only the distillation stuff, but also the fact that China has figured out how to train models more efficiently and cheaper. And yes, part of that is distillation, but also part of it can't be explained by that. So, you know, there's a lot of open questions here. And I think the kind of government narrative of we can't let China beat us, do anything you can at all costs to prevent this is seeping into everything too. So, yeah, I mean they're, they're definitely thinking about going public and trying to, you know, shore themselves up for the best possible look for their investors and stuff. But they also have this, I think, deep seated fear of China and the unknown.
- [29:00]
A
And my sense is that those things are actually really intertwined. Right. That part of the reason over the deep sea panic last year was that it was a thing from China that kind of came out of nowhere and nobody expected it. It was like a tech firm run inside of a hedge fund that made one of the best AI models anyone ever. Like, that was frightening to a lot of people for China reasons. It was also frightening for people because somebody else had made a much cheaper, much more efficient, didn't require bleeding edge chips that our economy is based on right now and was readily available to anybody who wanted to use it. And I think like you could if you wanted to make the same argument against like open source AI that there, some of these companies are worried about that for the same reasons that it is economically terrifying if somehow we get very cheap models that are almost as good. And that is the thing that China in particular seems to be very good at at this particular moment in time.
- [29:49]
C
Yes, that's actually something I was going to bring up, the open source AI thing because, yeah, I mean, it feels like AI labs are kind of protecting their house of cards right now. I've talked to a lot of clients and customers of these labs that are constantly upset about the AI money squeeze, you know, the costs being passed on to them, and they're having to do tons of work internally. You know, whatever industry they're in, they have to do all these kind of like, evaluations internally to see which model they should route, which type of query to, just so they can, you know, pinch pennies. And it's not even pennies. It's a lot of money they're saving, but they're really having to pinch millions. And so, yeah, it's just, you know, I think that a lot of them that I've been chatting with have considered going open source instead. It'd be a lot cheaper. But also, you know, those models aren't the same in terms of some of these niche, really important, like, reasoning capabilities that they need. So, you know, we'll see what happens. Right now, some of them are playing with, you know, porting everything over. Some of them are, you know, experimenting with just some of their queries. But that is a big question right now.
- [31:00]
A
It also seems like a lot of what happens next, Lauren, is going to be contingent on whether the AI industry in the United States and the government are friends or enemies. And that seems to change kind of constantly, all the time, as is the weird management strategy of the Trump administration. But especially in this next phase, right, like, like Hayden mentioned, Anthropic is being very clear about what it wants.
- [31:25]
C
Right.
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A
It's, it's like we need a coordinated attack against these distillation attacks. We need a. We need a certain kind of regulation that makes sure that we can both be safe and responsible, but also be fast and powerful. And when this has military effects, this has cybersecurity effects, all this stuff. What's, what's your sense on sort of the, the now and immediate future of the relationship between the Trump administration and the AI industry? It seems to change, like, every 15 minutes.
- [31:54]
D
It does. Things have seemed like they're, you know, there's good relations between the industry and the Trump administration. You know, after David Sacks departed, you know, you kind of have one less advocate in the White House. And I think as we go toward the midterms, you know, not that it's always been so easy to pass anything in Congress anyway, but you know, if even one chamber of Congress flips to the Democrats after the midterms, it's going to be even harder to get anything across that the Trump administration might want to see in terms of legislation which, you know, really just leaves executive action to enforce these kinds of policies. And, you know, sometimes that can be. Not have the same force or, you know, be more legally, legally questionable. So I think there's a lot up in the air right now. And, you know, if one of these companies crosses the administration in some way, maybe we see a big change. So I think it's always hard to predict how that's going to pan out.
- [33:01]
A
I am no political operator, but it sounds to me like what you just described is basically the best case scenario. If I'm a China tech firm, like, what's the Game of Thrones saying? Like, chaos is a ladder. If I'm China, I'm like, terrific. Keep fighting, keep having weird ideas, keep litigating, you know, whether AI training is fair use or not. We're just going to sit over here and keep making mocks and we're going to win before you can figure out what to do about it. Hayden, is this what they're terrified of? That, like, I sort of wonder at this point that the AI labs must feel like all the chaos, all the nonsense, all the yelling, at some point you're like, we have to actually be friends in a room long enough to figure this out or else we're going to end up getting run over before we can do anything together.
- [33:43]
C
Yes, that's exactly what's happening. And that's exactly, I think, what Chinese AI labs are doing. They're like, yeah, go ahead, you know, do your thing. We'll just be over here doing the same thing we've always done and catching up. And so that's why I think we're seeing, you know, the three leaders of DeepMind, Open, AI and Anthropic actually kind of converge behind closed doors on regulation ideas. They're like, you know what, we got to come together and kind of agree on this. This is eventually going to affect all of us. I think seeing what happened with, you know, Fable getting sidelined and then, of course, OpenAI new model getting sidelined for two weeks, they're all kind of realizing that it's a one size fits all approach right now and that this chaotic approach to regulation is not going to work and they need something better. And so they're like, you know what? Let's all just come together and kumbaya and figure out what the best way looks like for all of us, because clearly something's happening and the chaos is not good for any of us with the China fears. So, yeah, that's exactly what's happening.
- [34:46]
A
Yeah. Unfortunately for everybody, it doesn't seem like ending chaos is the strong suit of either the AI industry or the United States government at this moment in time. But hey, maybe, maybe the prospect of fixing the economy or losing the economy might, might get it done. All right, we're gonna have to come back to this because I think between now and even the midterms in November, there's a bunch of stuff left to talk about. But this lays a lot of land for me. This is very helpful. Thank you both for doing this. It's good to see you both.
- [35:14]
C
Thanks.
- [35:15]
D
Thanks for having us.
- [35:16]
A
All right, that's it for the show. Thank you to Hayden and Lauren for being here and thank you as always for watching and listening. If you have thoughts, feelings, questions, if you have any input on all of this AI US China stuff, it's messy, it's political. I would love to hear all of your thoughts. Email us vergecastheverge.com, call the hotline 866-verge-11. We absolutely love hearing from you. And if you want to support everything that we're up to, the best thing you can do is subscribe to the Verge. Theverge.com subscribe it gets you all of our podcasts ad free, including this one. It gets you all of our exclusive newsletters. It gets you all of our coverage of AI and everything else. Theverge.com subscribe. You won't regret it. The Verge cast is Verge production and part of the Vox Media Podcast Network. This episode is produced by Josh Kahas, Eric Gomez, Brandon Kiefer, Travis Larchuk and Aaron Locasio. See you tomorrow. Rock and roll.
- [36:05]
D
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- [36:13]
B
Good news.
- [36:14]
D
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