Commerce Sec. Lutnick and Nvidia CEO Jensen Huang in a fireside chat at G20 meeting — 9/2/2026

Well, I've been a tech CEO longer than any CEO in the world. The longest-running tech CEO in the world. I've seen countless technology transitions in the last 40 years. And of course, this is the biggest technology platform shift in human history. And we're transforming how computing works and what it means.

This is the first time in history that all of us have been using computer technology where you're not buying a device, but we're producing economic infrastructure. This is the big idea: economic infrastructure. And in fact, the first time you and I met, you realized that. And if I could say, Secretary, that the pro-energy growth initiative and agenda to reindustrialize manufacturing, to use this opportunity to reindustrialize manufacturing in the United States, to secure our supply chain, because you recognized that the infrastructure buildout is not going to be in the tens of billions, but is going to be in the tens of trillions, that supply chain security is going to be necessary. That was our first conversation, if you recall. And since then, we've made enormous progress in reindustrializing the United States, moving manufacturing back into the United States, and using the economic drivers of artificial intelligence and this new platform shift to modernize the American energy grid, because for the first time we can now invest in energy with market dynamics by itself. We could use market dynamics to fund manufacturing back into the United States. And of course, what is happening as a result is we're building an infrastructure that translates energy to valuable, productive intelligence that we're now monetizing throughout the United States. We've now turned a corner in the investment of artificial intelligence, and it is now productive infrastructure. And so this idea that we used to think about chips and technology and computers as phones and PCs, but now thinking about it in the same way we think about energy, internet, infrastructure — that psychological change for policymakers, for the industry, for companies is really transformative. So we'd like to spend the day today helping our G20 partners understand our view of growth and your view of growth. So is your view that compute will produce revenue, will produce economic value for their countries, and so the world really needs to build data centers in order to harness that growth? So can you talk a little bit about how compute produces economics?

Yeah, this is a big, strange idea. The idea is called a token, and this token is a mathematical outcome of a lot of computation, and this token represents intelligence. You take all of these tokens, these numbers, you reformulate them in such a way that it creates an image, writes a paragraph, answers questions, solves problems, creates new ideas. These tokens are mathematically produced in these computers that we make. And in a lot of the same ways, if you go back a hundred years, a couple hundred years, the world discovered this new idea called energy, and you monetize it — dollars per kilowatt-hour. Today it's dollars per million tokens. It's the same idea. It's kind of invisible. It's hard to understand, but it's incredibly valuable. And it's no different than us recognizing that intelligence fundamentally has value. You know, how do you put your arms around, how do you put your hands around intelligence? How do you measure it? You know it when you see it, and it solves real problems. But it's intangible. It's kind of vaporous. Intelligence is kind of hard to — you know, it's not atomic. It's conceptual, and which is the reason why artificial intelligence is rather difficult for many people to grasp. But the moment you start using these AI applications, you recognize how incredibly valuable they are, because they help you become more productive. They help workers become more capable. They help engineers become more capable. For countries that have a large young population, they're going to accelerate your education. For countries that are developing your science and your technology capability, it's going to elevate you very quickly. This technology has democratized, just as energy production has democratized, of course, power for every country. Artificial intelligence democratizes intelligence and capabilities for the G20 countries. For the countries that invest in it, they'll help elevate your society, elevate your industry much, much more quickly than you possibly could have imagined before. And so, in a lot of ways, this is the great equalizer. You know, if you just take a step back and think about computer technology in the last 50 years, computers have been a tool for about, you know, 10, 20 million people. And if you don't know how to — the only way to take advantage of this capability is to know how to program the computer, design the computer. And so that's my career, designing computers and programming computers. It's really narrowly focused on 10, 20, 30 million people around the world. For the first time, anybody in the world can program a computer. You could program a computer using human language. And so we've now democratized this computing technology that is so valuable to society, and we've elevated everyone. And this is one of the reasons why I really encourage everybody to engage artificial intelligence. It bootstraps you, it elevates you, it enables you. You know, it's a great, great equalizer.

Well, the first thing is to recognize what is AI. You know, I've been using this word infrastructure, but when you break it all down, AI is, if I could simply say, a five-layer cake. At the lowest layer is energy. You can't produce something without energy. It transforms electricity into mathematics. And so, first layer is energy. The second layer are chips. That's the world that I'm in. The third layer is infrastructure. Basically, these large data centers — land, power, shell — that incorporates all of the computer technology, and energy is plugged into it, and money starts spewing out. Okay, so the next layer is essentially infrastructure. The layer above that is where AI models live, and most people think that that's what AI is. But in fact, AI is a five-layer cake. And AI models — you know, for many of the countries that are here, I work across many of your countries already today, whether it's in startups, established companies, researchers. And each one of the regions around the world specializes in something really important in artificial intelligence, because it's not just language. Artificial intelligence can learn and understand and predict almost any information that has structure. So biology has structure, chemicals have structure, the laws of physics have structure. And so each one of the regions around the world specializes in different areas in AI, and AI cuts across all of it — different languages, different technologies, different information theories. And so AI cuts across all of that. And there's a whole bunch of AI models. But the most important part of AI is the fifth layer, the layer above that, which is data and applications. The way to benefit — you know, the United States is more deeply invested in inventing, building, developing the entire five-layer cake. However, every single region, every single country should decide which one of the layers they want to invest in. You don't have to win in every single one of them. You don't have to develop all of them. The most important part is that every single country should advocate for AI diffusion, or the adoption of AI into your industries. And the industries that we're talking about span everything from education to healthcare to manufacturing to sciences — you know, every single industry in between. And so the way to think about AI is just to think about it from the five-layer stack. And the United States is going to lead in the development of AI across these five-layer stacks. But we love to partner with everybody so that everybody could take advantage of this. Nvidia has built it in such a way that every single model in every single field of science and every single modality runs — and so it runs American models, it runs international models, it runs models in biology and chemicals and, you know, physics and robotics.

Well, AI is intelligence, and it starts with software. And in fact, if you look at AI in the last year, we started by talking about large language models. This LLM — you know, this concept that the world would know what LLM stands for — it's kind of an amazing thing. And so large language models: what made AI useful is putting an exoskeleton around the LLM. That exoskeleton is what is called an agent harness. This essentially gives the brain the parts necessary to retrieve knowledge, have working memory, use tools, be able to collaborate, so on and so forth, and so solve problems. And so the first thing is that the digital version of AI is what is called an agent. When you take that digital version, you could put it — instead of using a tool like a spreadsheet or PowerPoint or Excel or web browsers — you could make it use a tool, essentially a machinery. And so this agent would be embodied inside a physical body, and all of a sudden it becomes a robot. You could take this agent and put it inside a machine that has four wheels — self-driving cars. You could put this agent inside a manipulator, and it becomes a pick-and-place or a manufacturing robotics arm. You could put this agent inside something that essentially is a grocery delivery or a logistics delivery vehicle, or a surgical robot, or an autonomous drug-discovery laboratory. You know, all of these different versions are basically the same idea: large language models with an agentic system around it. You could use this agentic system to operate whether it's digital tools or physical tools. Now, in the end, what every single country will have to do is you need to recognize that this is infrastructure, just as it's water, roads, electricity, the internet. Every single country needs to build infrastructure so that you could support your own local economy. It becomes the capacity, the intellectual capacity, the digital intellectual capacity for you to support your researchers and students and society and industries and startups. And every single country that we've worked with — and there's so many here that we've partnered with already — when the moment we create an infrastructure locally, all of a sudden the startups, the researchers just really get activated. And so it's really a fantastic investment to make. We've had the benefit in the United States to have built one of the infrastructures, and because of the pro-energy growth and the speed and the regulatory environments in the United States, we've been able to build out really quite substantially. And you look at what's going on in the United States — AI is now generating jobs across every single sector, from chip fabs to computer plants to AI factories. Boy, just the number of jobs that we're creating is just hundreds of thousands. And as you know, this year alone we're going to invest close to a trillion dollars into the United States infrastructure, and that's generating enormous economic growth and, of course, a lot of jobs.

Well, as with all new technology, at first it seems magical. You could just imagine in the beginning of the production of electricity that somehow you could be away and all of a sudden, you know, a light could turn on. It seems like magic. And in the beginning of all technology innovations, it seems like magic. But the fact of the matter is, all of us who are building it — this is engineering. There's computers, there's software, there's mathematics involved, there's probabilities involved, and there's a lot there. Just as in every technology industry, when we're building something, whether it's a car or a plane, it is the responsibility of the people building it to do it safely and responsibly, and to continue to advance the technology so that as it advances it becomes safer. I prefer to drive today's car with so much more technology in it than to drive a car from 100 years ago. I prefer to fly in a plane today, with all of the technology advances, than a plane 100 years ago. And so in a lot of ways we want to accelerate the advancement of the technology so it could be more functionally able to deliver on its promise, so that it's safer to use. And so the same thing is going on with AI. We have to remind the industry — and I think the dialogue around safety and security is all fantastic. However, if you think about each one of your countries, what is the worst outcome that could happen in this technology industrial revolution? The worst outcome is that you don't take advantage of it, that you are left behind. That is the single worst outcome. And that outcome could happen if we talk about the technology with fear, with uncertainty. The leadership talks about it with so much concern, so much fear, and all the conversations around safety and security — it has to be balanced with a lot of conversation about prosperity and a lot of conversation about what it can do. And so I don't think it's about one or the other. We have to make sure that we're balanced in talking about it. You probably know that in the history of all of the technology advancements, one of the stories I was just reading about recently has to do with the airline industry. There was a time when all of them spent, you know, a lot of their advertising dollars and marketing campaigns on 'my plane is safer than everybody else's plane.' Turns out nobody wanted to hear about that. They wanted the companies to take care of that. What they wanted to hear was that the airlines could take them to new places, expand their horizon, make the world smaller so that we could learn about each other's culture, create new economies. That's what they wanted to hear about. They wanted it to be our responsibility to make it safe, not to make it their burden to think about safety all day long. And so I think this is the same thing that happened in the auto industry. It happened to the power generation industry. It happened to the airline industry. And so I think it's a responsibility for all of the leaders, all of us, to make sure that we take safety and security and building the technology properly as our responsibility, and working with regulators. And of course, there's so many regulations and so many laws already. Intelligence is a digital version of what we do, and so you would think digital version of some task that humans do. So in fact, humans have regulations across so many different domains already, whether it's the FDA or NHTSA or whatever it is. There's so many different agencies that already have regulations. I'm sure there's a way to formulate AI into that. So I think the balance of precise regulation — don't regulate hypothetical, theoretical harm; regulate actual and pragmatic harm — and give this technology, which is at the early stages of the S-curve of innovation, an opportunity to advance quickly so that it could be safe. And so some of the people — if you just go back and think about some of the ideas of slowing down technology advancement three years ago when it was just being formed. In fact, the advancement is what made it safer. The advancement made it not hallucinate, grounded on real truth, iterate until the answer is scientifically sound. All of those technologies were made possible through technology advancements, and so we're making it safer but advancing it more.