Eric Schmidt scores US vs. China: who’s winning the AI race?

The AI race between the US and China is the defining competition of our age. Eric Schmidt, former CEO of Google, advisor to the Pentagon, and current CEO of Relativity Space joins Rapid Response live from Masters of Scale Summit to give his most unvarnished assessment yet. He reveals that the gap he once estimated at two years has narrowed to six months. Schmidt also takes on the open source question that’s keeping Silicon Valley up at night, explains why kicking China’s best PhD students out of the country is one of America’s dumbest own goals, and shares the one thing he believes could keep this from becoming a zero-sum game — even if the current political environment makes it nearly impossible. This conversation was recorded live as part of Masters of Scale Summit on October 22, 2026 at the Presidio Theatre in San Francisco. Visit the Rapid Response website here: https://www.rapidresponseshow.com/ See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:01Speaker 00

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• 1:15Speaker 02

  The China-US competition is the defining competition of your generation, my generation, of our age. AI is the single most important thing that's going to happen for the rest of our lives. Yes, we've got problems. I think it's important that we continue focusing very hard on this. I want it to be America.

• 1:39Bob Safian?

  That's Eric Schmidt, longtime leader at Google and advisor to the US government, talking to me live at the Masters of Scale Summit in San Francisco just a few days ago. Eric Schmidt has singular insights into the critical AI race between the US and China with high-level contacts both in Silicon Valley and across Chinese government and industry. This episode is part of a special series of high-impact episodes from the summit stage that we'll be sharing. So let's get to it. I'm Bob Safian, and this is Rapid Response.

• 2:19Bob Safian?

  We're going to explore one of the highest stakes topics of leadership and responsibility, the AI race between the US and China. Our guest has been in rooms with, most of us will never access, with presidents and generals and tech leaders. He was the CEO of Google for a decade. He helped build the US government's approach to AI and national security. And he's been vocal about what's at stake in the tech competition between the US and China. So please welcome investor, advocate, and current CEO of Relativity Space, Eric Schmidt.

• 2:59Bob Safian?

  There he is.

• 2:59Speaker 02

  Hi, Bob. Nice to see you.

• 3:02Bob Safian?

  Thank you, Eric. Always great. Thanks for doing this.

• 3:06Speaker 02

  And it's good to be back.

• 3:07Bob Safian?

  Yes. So I want to say that I get whipsawed sometimes about the saber rattling and jingoism that might be happening around China's advancement in AI. And I'm glad you can help demystify this for us. The US had a clear first-mover advantage in AI. There's questions about whether that's going to persist or not. You've said the AI gap between the US and China has narrowed to roughly six months. What's changed most recently?

• 3:40Speaker 02

  The biggest change in the last year that's notable for everyone here is that the cost of software has gone from very expensive to almost nothing. And when something falls precipitously in price, you get an awful lot more of it. So when I think about the next few years, all I think about is an enormous amount of software and what will it do, who will do it, how will it work together, how will agents work, and so forth. China thinks the same way. And my own view is that the China-US competition is the defining competition of your generation, my generation, of our age. And the reason is that both are trying very much to develop reasoning and intelligence

• 4:25Speaker 02

  systems that are superhuman. And that doesn't mean like us. It means that they have superhuman or superintelligence capabilities that are beyond human capabilities already. When you look at the Waymos that are running outside, they all have better vision than human drivers, especially because they don't drink. You sort of get the idea. So in the race, I was part of the group that put the restrictions on China some years ago of chips. And I assumed that they would work for about 10 years. A year ago, two years ago, it looked like China was a year or two behind. Now it looks like they're six months behind. And there are many, many studies which show this. And how have they done this? After all, didn't we restrict their access to chips?

• 5:09Speaker 02

  We did, but they're so smart. They figured out a way to do the kind of algorithms that we develop and knowledge that we develop with essentially 1/10 of the energy and some factors less of performance. Now, there's a huge debate in the industry as whether that gap will get slower or bigger. But at the moment, it's fair to say that it's a two-horse race. And that, to me, is the defining one. The race for intelligence is the race of literally a millennium. Because once these intelligences exist, our children, grandchildren, great children, and so forth and so on will all be affected in really fundamental ways by the things that are occurring right here, right now.

• 5:52Bob Safian?

  Some people say that pointing to China's AI advances is sort of an excuse and a rationale to worry about regulating later. Is there any truth to that? Do you worry about that at all?

• 6:06Speaker 02

  People make up all sorts of stuff. And the question, so I've been heavily involved with the China-US discussions. Dr. Kissinger and I set them up before he died in his last visit to see President Xi, which I did with him. And the Chinese understand what the race is about. They understand the dangers of AI, and they're not stopping. So one way to answer your question is to say, how would a slowdown work? So how many frontier labs are there in America? Five, six, seven? Some number like that. How many are there in China? Five, six, seven. So you have a 12-body problem.

• 6:48Speaker 02

  On the Chinese side, presumably, the government can order them to do what they want. In America, you'd have to have some kind of voluntary agreement. So now it's a two-body problem. How are we going to convince the Chinese to slow down, given they already think that they're behind? Not happening. We have to come up with other ways to ensure that this technology is safe while advancing it ahead of them.

• 7:11Bob Safian?

  I mean, China has, in some ways, a structural advantage because the government can dictate AI as a national strategy, and everyone can align behind it. America's advantage, you've argued, is its diversity and decentralization. These are very different approaches. Are there things that China's AI community has done that American leaders could learn from?

• 7:37Speaker 02

  Well, I'll give you a simple framing. China has infinite energy, most of it renewable, something we said we were going to do in our country 10 years ago and we failed to do. They don't have interconnection queue waits that go on seven years. They don't have the kind of debates. They're building the data centers, and they're building them massively. Furthermore, even with a much more restricted financial market, the Chinese have been able to fund the startups. DeepSeek is now seeking funding. It's illegal for us to invest in DeepSeek. I know because I tried. And so, trust me, it's illegal. And so, US law, I might add. DeepSeek just did a huge raise.

• 8:20Speaker 02

  The funding looks like it's going to show up. Now, in China, you never know if it's really the government or really the private sector. My friends in China say it's the private sector, that the economics are going to work. There's a complex question involving open source, which we can talk about. But fundamentally, they're on their way. They just don't have the chips. In the United States, we've got everything we need. We've got the smart people. We've got all the controversy. We've got incredibly deep funding markets. Where in the world could you get $50 billion on a text message? I mean, it just doesn't exist. Thank God that the American financial industry is financing our hobbies here. We'll see.

• 9:03Speaker 02

  What we don't have is the energy, and we don't have the data centers. And the correct answer for this is build your own power systems. One of the great things about America, there's an old quote from DeTocqueville about America, this is 250 years ago. "America is a great country because of the optimism of its people, the abundance of the land, and the absence of a king." 250 years ago. And at least, you can score the three. We've got a lot of land.

• 9:35Speaker 02

  And so lots of empty land. Put these data centers in the empty land. It's good for the local economy and so forth. And build the power plants yourself. And that's what we have to do. Current estimate is we need somewhere between 60 and 80 gigawatts of power to get through 2030, 2031. We'll see if we can get that financed. One gigawatt is about $50 billion in cost. By the way, one gigawatt is about one nuclear power plant. The last time I checked, we weren't building them at a very high rate.

• 10:04Bob Safian?

  Yeah. You mentioned open source. China's leadership in open source models or open weight models. It's fueled the reach of its AI globally. For the business leaders in this room, does it make sense for them to build on Chinese open source models or not?

• 10:23Speaker 02

  So let's define terms a little bit. There's something called open source. I was part of the beginning of open source movement back when I was at Berkeley and very proud of that. It was a long time ago. And my code is still open source and still available for you if you want to look at very old code. And then there's something called open weights, where the training benefits. And you know, you spend all this money, then you take the numbers, which there's many, right? Trillions, trillions of numbers. And then you make those available. China's strategy is largely open source and open weights. And America's strategy is largely closed source, closed weights. On the American side, it makes perfect sense. These things cost $100 million to $500 million for one, one model, right?

• 11:08Bob Safian?

  Right. Why just give that away if you're going to spend that money?

• 11:11Speaker 02

  Well, this is what the lawyers say. Now, I spent 50 years arguing with lawyers that you should give things away because it creates a platform. So the open source movement basically is create a platform that people build on top of it. The closed source movement exemplified by Microsoft and basically Bill and C way back when, closed source, focus on the end user, do a good job or not and so forth. And that was the test. Open source has largely won in America as the foundation for what we work on. But the large models are largely closed for good reasons. I'm not criticizing them. There are a couple of examples. One is called Reflection AI that's just released a 500 billion parameter model.

• 11:54Speaker 02

  Nematron, which is the Nvidia product, has a similar sized model. They're both very powerful. Google has something called Gemma 4, which is also a very powerful, smaller model. You can download these things. So it's not completely China versus US. China chose open source, open weight because it was the most reasonable strategy for them. They were behind. They needed to get users quickly and they're willing to take the thieving risk, if you will. And it looks like it's working because at least they're getting funded. So the contest of open source, open weights versus closed source, closed weights is the defining question. If you talk to the people here in San Francisco who are in closed source, closed weight companies, they'll all explain to you that their strategy is better because they'll stay ahead.

• 12:38Speaker 02

  If you talk to the Chinese people, they'll say their strategy is better because it's going to stay ahead. So we have a real competition here. There are some issues and I want to highlight one that I believe is today unsolvable. And we spent a lot of time working on it. If you think about it, the closed source weights have the property that it's controlled by a company. The company is controlled by the laws of that country. The CEO is subject to the law. In Chinese, they'll just arrest you, you know, whatever. So there's real control over what those labs are doing. If you release an open source weights model, open weights, open source model, such as the Chinese models, you put what are called guardrails in it.

• 13:20Speaker 02

  And there's a technique called obliteration, which allows you to basically remove those restraints and then you get the raw model. This is a problem because those raw models can be used for cyber attacks. And it looks like, remember what I said about the beginning, the cost of software coming to zero? The software, the rate at which software capabilities are expanding in the next few months is so extraordinary that the technical people here in San Francisco and elsewhere are really worried, really worried. And this is the source of this, hey, can we slow down kind of optimism, which is very difficult to do. So I don't fully understand how we're going to navigate through this open source, open weight stuff when it gets into the hands of terrorists.

• 14:03Speaker 02

  You can be sure China does not want this stuff to be misused against themselves. After all, they're a one party state. And if they're going to attack the US, they won't do it through that. They'll do it through their own active cyber war and the same thing, US versus China, although I'm not suggesting that we should do that. This is a hard problem and many people believe that there will be some kind of a cyber event in the next 12 months that will illustrate this point.

• 14:27Bob Safian?

  And if, as a business leader, I decide, oh, I'm going to try to use that Chinese model because it's cheaper for me, is that unpatriotic? Is that short sighted?

• 14:38Speaker 02

  Well, I think American CEOs are patriotic to a point. They're also very focused on money.

• 14:45Bob Safian?

  Yes, they are.

• 14:46Speaker 02

  Welcome to capitalism. And there are many examples where people are using small servers with open source weights to solve some problem because the token cost is lower. The token costs are about three to five times cheaper if you run your own and so forth. They're not as functional. So one model for what's going to happen, which worries, everything worries me, right? Is that the frontier models will dominate the things that we care about here. These incredible achievements in math and chemistry and so forth. I mean, you know, we have Armageddon for mathematicians. You know, it's like all of a sudden their whole world, which has not changed in 50 years since, you know, Gödel, Gödel's hypothesis, basically like was, everything was overthrown in one month, right? They have an existential crisis.

• 15:30Speaker 02

  That's going to occur because of the frontier models. For most of us, we don't need that kind of math to solve the problem of financial accounting. It just, it isn't that complicated, trust me. And so, so the idea is that many people will use these cheaper open weights models for little things. Is that okay? It's likely to be legal in the US. Is it a good idea? Depends on what your view of Chinese threats and espionage threats and so forth and so on is. In China, of course, they'll use the open weight models.

• 16:01Bob Safian?

  Yeah. Coming up next, Eric gives us a point by point scorecard on who's ahead in the AI race, plus what he calls the no surprise rule. We'll be right back.

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• 18:12Bob Safian?

  Before the break, Eric Schmidt laid out what's at stake in the AI competition between the US and China. Now he gives us a scorecard on key elements in the race, talks about what he calls the no surprise rule and explains why AI development is and isn't a zero sum game. Let's jump back in.

• 18:35Bob Safian?

  So this is complicated. I'm going to try to simplify it, or have you simplify it for us? I'm not sure if this is going to work. But Carrie, can we pull up the scorecard? So we created a scorecard. We're going to try to play a game. So I'm going to ask you, I'm going to give you some factors. Okay. And you tell us who's got the edge, China or the US? So model performance?

• 18:58Speaker 02

  The US.

• 18:59Bob Safian?

  The US.

• 18:59Speaker 02

  The US, the US, by all the benchmarks is ahead. And one of the ways to understand it is that every lab has the one that they've released and then a next one. The indications from the labs are that the next ones are incredibly performant, that we're still in the scaling law and there's amazing things coming.

• 19:17Bob Safian?

  All right. Next one, model cost?

• 19:20Speaker 02

  China, because as I mentioned, the token cost is at least three times cheaper. In many ways, that's actually because they were forced to be cheaper. We didn't give them the powerful chips. And so they found algorithmic improvements, supervised fine tuning, other kinds of things that are very, very impressive. And the interesting thing about their inventions is the moment that Chinese invents something in open source, we copied it in America. Thank you, China.

• 19:49Bob Safian?

  All right. So energy and compute, I assume that's China because you'd mentioned that earlier.

• 19:54Speaker 02

  This is, I'm supposed to answer.

• 19:56Bob Safian?

  Oh, sorry, sorry, sorry. Energy, tell me what, tell me what the answer is.

• 20:00Speaker 02

  Okay, you are correct.

• 20:05Bob Safian?

  I'm trying to pay attention.

• 20:06Speaker 02

  No, no, no. China had, I think the number was 560 gigawatts was produced last year. It's an extraordinary number. This is the benefit of industrial policy in an authoritarian country. If they need energy, they've built an enormous amount of it, largely renewable.

• 20:24Bob Safian?

  All right, let's, let's try something like leadership and talent?

• 20:29Speaker 02

  I'd give that one to the US.

• 20:31Bob Safian?

  Okay.

• 20:32Speaker 02

  And we are doing some really stupid things in our country. Not that that's a surprise to this audience. Taking the smartest people and arresting them and kicking them out of the country is like a bad strategy. Denying them high stakes visas to come to the country. My favorite are that we take these graduate students, typically from China, but others, we give them a PhD and then we kick them out. That's really smart, right? That's really smart. So my favorite there is the guy who is, is leading the quantum program for China was such a person, wanted to stay in America and we kicked him out. And by the way, do you know who our quantum adversary is? China and this guy. So QED, stupid.

• 21:14Bob Safian?

  All right, let's try.

• 21:16Speaker 02

  Sorry.

• 21:17Bob Safian?

  All right, I got, I've got four more for you. Let's see. Military and defense AI?

• 21:24Speaker 02

  The Chinese model is opaque to me. I work on military matters. I've done a lot of work in the Pentagon and in Ukraine and helping the US in the Iran war and things like that. There are studies which indicate that the Chinese models have been used in, by the Russians, for example, but not in an extensive way. You have to assume that China will, should there be a war, which is to be avoided, trust me, that China will immediately use the dominance that they have in consumer drones and other kinds of things, and they'll move more quickly than the West. That's a challenge for the West.

• 22:01Bob Safian?

  But so who gets the point?

• 22:03Speaker 02

  I'd say it's, it's either 0-0 or slightly US.

• 22:08Bob Safian?

  Slightly US. Carrie, you get to decide whether you want to give that point to the US or not. Safety controls. Oh, look at that. Clearly in America.

• 22:17Speaker 02

  That is a patriot.

• 22:21Bob Safian?

  Safety controls.

• 22:22Speaker 02

  The US has a better safety control system. There have been a series of meetings which I've been part of, where the various labs have agreed to exchange safety practices and so forth. It's kind of obvious. I think that as a general rule, we should expect the government will, will regulate AI. Not that I'm welcoming it, but that AI is so pervasive in society that there are going to be bad outcomes and those bad outcomes will cause regulation. And safety is the most obvious one, human alignment and so forth. So I'd give that one to the US.

• 22:55Bob Safian?

  To the US. Okay. Speed of deployment?

• 22:59Speaker 02

  I'd say China.

• 23:01Bob Safian?

  China.

• 23:01Speaker 02

  And I'll tell you why. We are the ones inventing the frontier. They're the ones doing deployment. And I was just, I'm going there in the next month and I was there a few months ago. And the rate at which AI is being deployed into everything, digital, mechanical and so forth, is astounding. And they love to show you their demo. And there's no equivalent product in America. For those of you who are building hardware, I encourage you to go to China to look and understand because they're beating us in this area. That's clearly China.

• 23:32Bob Safian?

  All right. And global influence?

• 23:38Speaker 02

  If you measure it in terms of impact over 10 years, it will be China.

• 23:43Bob Safian?

  It'll be China.

• 23:44Speaker 02

  And the reason, I'm sorry to say, and here's why. What's the difference between a free product and an expensive product? More users for the free product, right? The vast majority of countries do not have the economics, they do not have the wealth to really support the kind of costs and token costs and other things that we impose, which I understand, I'm not arguing. It's pretty clear to me that eventually the majority of the world is going to be using Chinese models. That has huge geopolitical implications. The average geopolitical person I talked to has not figured this out yet. It's obvious if you think about it.

• 24:24Speaker 02

  Free, cheap, good enough, expensive, powerful, reserved for elites, people who are wealthy, important companies, great research institutions.

• 24:34Bob Safian?

  So but by our scorecard, at least in this rough way.

• 24:37Speaker 02

  She awarded one of them to the US.

• 24:39Bob Safian?

  They're tied. Well, is it, I just, I wanted to ask you, are we, are we missing anything? Is there any scenario where the US and China both win like that? Or is it a zero sum game?

• 24:51Speaker 02

  I don't think AI is a zero sum game. This is, China's not our enemy. And I've worked in markets where two companies, although they are competitors, fundamentally create a whole new market. The best possible scenario, which of course is not possible with the current administration, is you'd have some rational conversation between, sorry. So you'd have some rational conversation between the US elites and the Chinese elites, saying, how are we going to manage this? So let's agree to some things. So for example, a no surprise rule. In my Pentagon work, I learned that when you launch a missile,

• 25:31Speaker 02

  you notify all the other countries and they train their satellites on your missile launch, which is two reasons. One, they make sure that you did what you said. And second, they get to train their, their missile launch watcher. It's an example of an accommodation to keep everyone safe. You don't want random missile launches and not know where they're going. Makes perfect sense. These decisions were made 50 years ago. So there's a list that I think is quite rational for collaboration in order to achieve human flourishing. And let me finish by saying that AI is the single most important thing that's going to happen for the rest of our lives. AI is the underpinning of scientific progress, which is what I'm working on.

• 26:14Speaker 02

  That scientific progress creates wealth, wealth creates opportunity, blah, blah, blah, well-being and for society. The future for our children and grandchildren is very, very bright because of what we're doing in AI. Yes, we've got problems. I think it's important that we continue focusing very hard on this. The innovations are coming faster than even I can keep up and I've been doing this a long time. And second, I want it to be America.

• 26:38Bob Safian?

  And for the, for the, yes.

• 26:44Bob Safian?

  And, and for the folks in this room, you know, like, is there some message that they should take away? I mean, is there something they should do differently in order to make it be America?

• 26:57Speaker 02

  Start by using it. I love these people who come up and they talk to me about AI. And I asked them, have you actually been using it? And they said, no, no, no.

• 27:06Speaker 02

  All right. Maybe they're smarter than I am. You got to use this stuff. What, what really did me in was when I started having it do long chain, long chain of thought, deep, deep reasoning. And I went, oh my God, it has arrived. Now the it, I don't know that I understood exactly what it was, but I knew it had arrived. It changed the way I thought about my life, the way I work, the way I invest, the way I run companies. It's very obvious, for example, that the finance function, I'll use an example, lots of business people here. Finance is relatively easy for an AI system. Why don't you have the AI produce the financial reports and you and the CFO can have a conversation? Very interesting.

• 27:50Speaker 02

  What about manufacturing inventory? What about security? What about cash forecasts? Stuff like that. And you sit there and you go, oh, that's boring. No, it's transformative. Because once your mindset is in that, then you'll have another idea and another idea and another idea. That's why this is such a precious moment to be alive.

• 28:10Bob Safian?

  Well, Eric, this has been fascinating.

• 28:13Speaker 02

  Well, you're, you're the best, Bob. You know that.

• 28:15Bob Safian?

  Thank you. Thank you so much.

• 28:16Speaker 02

  Thank you very much.

• 28:17Bob Safian?

  Thank you.

• 28:19Bob Safian?

  Super. Thank you.

• 28:23Bob Safian?

  Eric is both optimistic about AI and cautious about how missteps could derail things, whether economically or geopolitically. This balancing act was a central theme at the Masters of Scale Summit, one we'll be returning to in subsequent episodes in our special summit series. We'll talk about managing our careers and our lives in a time of chaotic change, subversive brands, challenging convention, how to avoid being corrupted by greed and more. So stay tuned. I'm Bob Safian. Thanks for listening.

• 29:04Speaker 04

  We all know the really prominent technology podcasts out there, but they're not actually helping the majority of people understand this space. With Future Proof, that's what we want to do. We want to talk to everyone from the top AI labs to the real builders, the people who are rolling up their sleeves, building this technology on a day-to-day basis. I'm Reid Alberdotti. I've been covering technology for more than a decade. If you want to really learn, whether you're in the tech industry, adjacent to it, or just curious about it, subscribe to Semaphore's Future Proof, wherever you get your podcasts or watch it on YouTube.

• 29:37Speaker 05

  Humans will never be more intelligent than AI.

• 29:40Speaker 06

  There's going to be two types of companies. Those who are great at AI and those that went out of business because they weren't.

• 29:45Speaker 01

  How do we build a future that is human centered?

• 29:50Speaker 05

  I'm Rana Elkhayubi. And on my podcast, Pioneers of AI, we answer that question and so many more. As an AI scientist, entrepreneur and investor, I know what it takes to build AI that works for everyone. Every week, I sit down with the pioneers shaping our future and we take you behind the scenes of the AI that's transforming our lives. Find Pioneers of AI wherever you tune in.

• 30:19Bob Safian?

  Hey listeners, Bob here. If you listen to Rapid Response on Masters of Scale, you may be missing half the show. Because every Friday, we release a second Rapid Response exclusively in the Rapid Response feed. The guests and topics are just as compelling and timely, from Ford CEO to NASA's administrator, to the lessons from the devil wears Prada. It takes about 10 seconds to find. Just search Rapid Response wherever you listen to podcasts and hit follow to make sure you never miss an episode. I hope to see you there.

• 30:59Bob Safian?

  Rapid Response is a Wait What original. I'm Bob Safian. Our executive producer is Eve Trow. Our senior producer is Alex Morris and our associate producer is Masha Makutonina. Mixing and mastering by Aaron Bastinelli and Brian Pugh. Our theme music is by Ryan Holiday. For more, visit rapidresponseshow.com.