At a private dinner a few months ago, Jensen Huang apparently said what I’ve been thinking for some time. The US is significantly behind China in AI development. Here are some of the reasons.
Huang starts with the ratio of AI developers in China (he estimates 1 million) to AI developers in the US (20,000). That’s a 50:1 ratio. While I think he’s overstating China and understating the US, I use a different metric that gives the same general result. When you’re reading academic papers about the latest developments in AI, count the authors with Asian names1; count the number with European names. For the moment, forget where the authors live or work: could be MIT, could be Alibaba. The Asian names (including South Asia) will be a significant majority.
Now remember where the authors might live, and consider the fact that the US has hung out a big “not welcome” sign for immigrants. Forget about “we only want the good immigrants”; that’s incredibly condescending, and no one of any nationality will believe it, or believe that they’ll be treated fairly once they arrive. Every immigrant worker in the US—or considering coming to the US—has to consider the possibility that he will be in the wrong place at the wrong time with the wrong skin color, and end up on a flight to a death camp. Are we surprised that international workers are leaving? Are we surprised that immigrants are arriving in smaller numbers? A $100,000 price tag on H1B visa applications says “We’ll only let you in if you make it worth our while.” That’s gangster talk, not responsible government. The US’s ability to train high-quality engineers and programmers and provide them with a high standard of living after graduation has historically been one of its greatest strengths. But given the current policies, are we surprised that fewer international students are coming to the US? China has built an impressive network of colleges and universities, particularly for engineering and the sciences. Students can get a first-rate education without the risks of coming to the US, risks that include having said the wrong things on social media and being sent back at the border.
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I read somewhere (might have been Kissinger) that no empire has survived without importing intellectual capital. That’s true of the Romans and the Greeks. That’s true of the British. And it’s true of the US and its massive immigrant workforce. (Unfortunately, providing essential skills and expertise has never protected immigrants from racism.) Joy’s law is about companies rather than nations, but it still applies: “No matter who you are, most of the smartest people work for someone else” is almost a restatement of the same idea. If you want to work with the smartest people, you have to bring as many as you can in from the outside—and even as you’re bringing outside workers in, the supply of good talent that doesn’t work for you will always exceed the talent you’ve managed to acquire. But now, think about what education means for this talent flow: China no longer needs to export students to the US and hope that some of them will return. And they’re in a position to attract talent from elsewhere.
Huang is also right that restrictions on semiconductor exports have not only failed, they are leading China to develop their own technology. China’s homegrown GPU industry has almost reached the level of the US’s and will no doubt surpass it. Restrictions on semiconductor sales have had another effect that Huang doesn’t mention. What do you do when you don’t have the fastest hardware? You make your software more efficient. You optimize it so it runs faster and draws less energy. You build it to run efficiently on older hardware using techniques like quantization. That’s evident in all of the recent models coming from China, from DeepSeek to the newly released Qwen-3-Max-Thinking or Kimi K2.5. The US is trapped in the notion that bigger is better2; China is playing the “better is small, more efficient, and open” card. Guess which one wins?
Electrical power tells a similar story. The top domestic AI companies are talking about building data centers that will require many more gigawatts of electrical capacity. The plan seems to be building that generation capacity with coal, gas, and nuclear—good luck. Those are the most expensive and inflexible ways to build capacity. The current administration has hobbled the development of solar power, wind power, and battery backup. China, while it’s also building out coal, is leading the world in building out solar capacity. It also leads the world in the development of solar and wind technology, only partly because of its rare-earth resources. It’s possible that the cost of coal generation might drop—after all, coal is a commodity that few nations want any more, and lack of demand might lead to a price collapse. But cheap coal and free solar are far from equivalent. If the AI powers-that-be in the US plan to build data centers at scale, they will need to come up with better, less expensive sources of power. That’s another area in which China is way ahead.
After reports of Huang’s dinner talk leaked, he walked back the remarks in some posts on X. But that begs the question: Which version do you believe? I know which version I believe; the evidence—personnel, chips, efficiency, power—all points in the same direction.
Footnotes
- I include names that appear Indian and Arabic; India and the Arab nations are often not taken into consideration. A surprising number of the names in my count are Spanish: undoubtedly European, but also a focal point for anti-immigrant sentiment in the US.
- I see that as cultural baggage, but that’s another argument.

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