The AI race between the U.S. and China is the defining competition of our age. Eric Schmidt, former CEO of Google, adviser to the Pentagon, and current CEO of Relativity Space, gives his most unvarnished assessment yet. He reveals that the gap he once estimated at two years has narrowed to six months, and takes on the open-source question that’s keeping Silicon Valley up at night. He also 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 is an abridged transcript of an interview from Rapid Response, hosted by former Fast Company editor-in-chief Robert Safian and recorded live at the Masters of Scale Summit 2026. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with today’s top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode.
I get whipsawed sometimes by the saber-rattling and jingoism that may be happening around China’s advancement in AI, and I’m glad you can help demystify this for us. The U.S. had a clear first-mover advantage in AI. There are questions about whether that’s going to persist or not. You’ve said the AI gap between the U.S. and China has narrowed to roughly six months. What’s changed most recently?
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. 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: 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-U.S. competition is the defining competition of your generation, my generation, of our age. The reason is that both are trying very hard to develop reasoning and intelligence systems that are superhuman. That doesn’t mean like us. It means they have superhuman or superintelligence capabilities that are already beyond human capabilities. When you look at the Waymos running outside, they all have better vision than human drivers, especially because they don’t drink. You sort of get the idea, right?
In the race, I was part of the group that put restrictions on China some years ago on chips, and I assumed they would work for about 10 years. A year or two ago, it looked like China was a year or two behind. Now it looks like they’re six months behind, and there are many studies that show this.
How have they done this? After all, didn’t we restrict their access to chips? We did, but they’re so smart they figured out a way to do the kind of algorithms we develop, and use the knowledge we develop, with essentially one-tenth of the energy and, in some factors, less performance. Now, there’s a huge debate in the industry as to whether that gap will get smaller 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 literally the race of a millennium. Because once these intelligences exist, our children, grandchildren, great-grandchildren, and so forth will all be affected in really fundamental ways by the things that are occurring right here, right now.
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?
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 failed to do. They don’t have interconnection queue waits that go on seven years. They don’t have the same 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. So trust me, it’s illegal under U.S. law.
DeepSeek just did a huge raise. 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.
Yeah.
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? It just doesn’t exist, except, thank God, that the American financial industry is financing our hobbies here. We’ll see.
What we don’t have is the energy, and we don’t have the data centers. The correct answer is to build your own power systems. Current estimates are that we need somewhere between 60 and 80 gigawatts of power to get through 2030 or 2031. We’ll see if we can get that financed. One gigawatt is about $50 billion in cost. By the way, 1 gigawatt is about one nuclear power plant. The last time I checked, we weren’t building them at a very high rate.
You mentioned open source. China’s leadership in open-source models, or open-weight models, has 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?
The open-source movement basically says: Create a platform that people build on top of. The closed-source movement, exemplified by Microsoft and basically Bill [Gates] and Steve [Ballmer] way back when, focused on the end user: Do a good job, or not, and so forth. 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, which just released a 500 billion-parameter model. Nemotron, which is the Nvidia product, has a similar-size 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 the U.S. 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 we have a real competition here. There are some issues, and I want to highlight one that I believe is, today, unsolvable, and we’ve spent a lot of time working on it. If you think about it, the closed-source weights have the property that they’re controlled by a company. The company is controlled by the laws of that country. The CEO is subject to the law. In China, they’ll just arrest you, whatever. So there’s real control over what those labs are doing.
If you release an open-weights model, an open-source model such as the Chinese models, you put what are called guardrails in it. 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 cyberattacks. And it looks like—remember what I said at the beginning about the cost of software coming to zero—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. This is the source of the “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.
Are we missing anything? Is there any scenario where the U.S. and China both win like that, or is it a zero-sum game?
I don’t think AI is a zero-sum game. China is not our enemy. 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 that you’d have some rational conversation between the U.S. elites and the Chinese elites saying, “How are we going to manage this? Let’s agree to some things.”
