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Home » NVIDIA CEO Jensen Huang on China, AI & U.S. Competitiveness at CSIS (Transcript)

NVIDIA CEO Jensen Huang on China, AI & U.S. Competitiveness at CSIS (Transcript)

NVIDIA founder and CEO Jensen Huang joins CSIS President John Hamre in Washington, D.C. on November 24, 2025 for a high‑stakes conversation on how AI is reshaping global power, national security, and the U.S.–China tech rivalry. Huang breaks down AI as a five‑layer “industrial platform,” explains why energy, chips, and infrastructure will determine who wins the next industrial revolution, and warns against ceding China the world’s second‑largest AI market. He highlights Huawei’s rapid rise, China’s massive lead in AI talent and open‑source models, and the risk that U.S. export controls could accelerate Beijing’s drive to build a fully domestic AI stack. The discussion also covers re‑industrializing America, securing semiconductor supply chains, and why Huang still believes the coming AI decade could be the most prosperous in U.S. history. Following is the full transcript of the interview:

Introduction

DR. JOHN J. HAMRE: Well, welcome to all of you out in cyberspace. And I have a wonderful collection of colleagues here in physical space. We’re going to have an interesting conversation with Jensen Huang.

I would waste your time by introducing him. Everybody knows Jensen, but what you may not know is that he started from fairly humble roots. Your mom was a school teacher, your dad was a petroleum engineer. You and I share one thing in common—we both started off, our first job was running a dishwashing machine in a restaurant, Denny’s.

JENSEN HUANG: What was your restaurant?

DR. JOHN J. HAMRE: It was at Mount Rushmore when I was off. But you did better than I did. He became a busboy and later a waiter, and then I guess led him to NVIDIA.

You know, it’s a remarkable story. I think it’s the quintessential American story that we welcome people who come with just energy and imagination and creativity, and they make an astounding success. Congratulations and thank you for joining us.

We’re going to have a very interesting conversation today, colleagues. NVIDIA is not only a huge economic success, but it’s a national security platform. And I think we want to talk about that today. I’ve been looking at your website and you do talk about NVIDIA being a platform.

Understanding NVIDIA as a Platform

JENSEN HUANG: What does that mean, a platform? A platform is something that you build other things upon. NVIDIA is the largest pure play technology company the United States has ever seen. In fact, we’re the largest pure play technology company the world’s ever known. We create technology out of nothing. Our final product is pure technology.

And in order to use it, you have to create software and applications for various industries above it. If you look at most of the technology companies today, some of it could be in social media, some of it could be in e-commerce, some of it could be in information search. And these are all amazing technology companies whose business models are something else. Our business model is purely technology.

Now the way that AI works and our technology works is that in the final analysis, the technology platform is built in layers. And that’s one of the reasons why we think of it as a platform. You’re standing on top of it. An application or an industry stands on top of that platform.

That platform starts with energy on the bottom. One of the reasons why this administration has made such a huge difference right away is this pro-energy growth initiative. Its attitude about energy is that if we don’t have energy, we can’t enable this new industry to thrive. It is absolutely true. So layer one is energy.

Layer two are essentially the chips and systems—the chips, that’s where NVIDIA comes in.

Layer three is a whole bunch of software and we build a whole bunch of software on top of our chips. We’re well known for this piece of software called CUDA. But there’s hundreds of different pieces of software that we create that enables people to do AI for different fields of science or language or images, whatever it happens to be—robotics and manufacturing and such.

But that third layer is called infrastructure, basically software. Now people historically have thought of infrastructure really as cloud, but increasingly it’s really important to realize that infrastructure includes land, power, shell, because this industry spawned another industry altogether. But the third layer is basically infrastructure, and that infrastructure includes financial services because it takes an enormous amount of capital to do what we do.

And historically all of that software, the layer above that—and this is where people largely focus on when they talk about AI—which is the AI models. This is the revolutionary, of course, ChatGPT, incredible work that Anthropic does with Claude and Google does with Gemini and what xAI does with Grok. But the important thing to realize: those are four of the one and a half million AI models in the world.

AI is not just intelligence that understands English or language, but it’s AI that understands genes, proteins, chemicals, the laws of physics. AI that understands quantum, AI that understands physical articulation, otherwise known as robotics. AI that understands patterns across long sequence of time—financial services.

AI that understands longitudinally across multiple modalities—healthcare. And so AI has all of these different reaches and domains. We talk about this one area, we just have to be very careful to understand that AI spans basically every form of information across every field of science, across every single industry. One and a half million AIs around the world.

On top of that are all the applications. And we never should forget that in the final analysis, these AI models are technologies. But technologies are about enabling application and use. Whether you’re in healthcare, you could be in entertainment, manufacturing, self-driving cars, transportation. Each one of these industries have AIs that deeply affect them.

And these are the five-layer stack. NVIDIA is at the lower level, the platform level. The reason why we say that we’re an AI company that works with every single AI company in the world is because we’re the platform by which we are able to work with all of these technology companies and all these application companies across all these industries.

And so that is a platform that we created.