The New Yorker Radio Hour - The Company Behind the A.I. Boom

Episode Date: December 26, 2025

Across the country, data centers that run A.I. programs are being constructed at a record pace. A large percentage of them use chips built by the tech colossus Nvidia. The company has nearly cornered the market on the hardware that runs much of A.I., and has been named the most valuable company in the world, by market capitalization. But Nvidia’s is not just a business story; it’s a story about the geopolitical and technological competition between the United States and China, about what the future will look like. In April, David Remnick spoke with Stephen Witt, who writes about technology for The New Yorker, about how Nvidia came to dominate the market, and about its co-founder and C.E.O., Jensen Huang.  Witt’s book “The Thinking Machine: Jensen Huang, Nvidia, and the World’s Most Coveted Microchip” came out this year.   This segment originally aired on April 4, 2025.New episodes of The New Yorker Radio Hour drop every Tuesday and Friday. Join host David Remnick as he discusses the latest in politics, news, and current events in conversation with political leaders, newsmakers, innovators, New Yorker staff writers, authors, actors, and musicians. New Yorker Radio Hour listeners, we want to hear from you.  We have a few questions about the show and how you listen to it. The survey takes about twenty minutes, and your feedback will help us make our podcast better.  Take the survey here.

This is the New Yorker Radio Hour, a co-production of WNYC Studios and The New Yorker. Welcome to The New Yorker Radio Hour. I'm David Remnick. 2025 was the year, at least in my experience, that conversations about AI became absolutely inescapable. You heard about it all the time. The economy, the job market, politics, music education, everything. Absolutely everything seemed to gravitate back to AI. Across the country, data centers, huge, industrial complexes are being constructed at a record pace. Virtually all of them are using chips built by the tech colossus,

Invidia. The company has nearly cornered the market on the hardware that runs much of AI. But this is not primarily or not only a business story. It's also a story about the United States and China, about who is building the technology that will shape the future, all of our futures. Back in April, I spoke with Stephen Witt, who writes about technology for the New Yorker, and his book about NVIDIA

and its founder, Jensen Huang, came out this year. It's called The Thinking Machine. Stephen, in all the years we've been doing this show, I don't think we've ever sat down to talk about a microchip company and the CEO of that microchip company, and yet invidia is incredibly important to all of our futures in somewhere or another.

Explain what NVIDIA is and why it's so important. InVIDIA was there at the beginning of AI. They really kind of made these systems work for the first time. We think of AI as a software revolution, something called neural nets, but AI is also a hardware revolution. And these microchips that Nvidia designed used a process called parallel computing, which meant that they split mathematical problems up into a bunch of bits and then solve them all at once.

Now it turned out, and nobody expected this, nobody saw this coming, this software, the neural networks and this hardware, the parallel computing, worked perfectly together, and they needed each other to succeed. And this is really what made the AI revolution possible. So what you tell me, there would be no artificial intelligence. Certainly not on this level, not on this mass level, even in its early days now, without invidia and without their product they produce. Without Nvidia, we would be about 10 years behind on AI. The first AI system that we really would consider a modern AI system. So kind of like the Wright Brothers Airplane of AI was a system that a guy built in his bedroom,

a guy named Alex Krashevsky working at the University of Toronto. And what was that? When was that? That was in 2011 and 2012. In 2012, he built this system and he used two Nvidia gaming cards, like the ones you would buy at Best Buy, retail video game cards to make essentially a jerry-rigged, low-budget supercomputer to run the training for this neural net. And this broke all the barriers in AI.

So as a result, all of the early AI pioneers and scientists gravitated to the Nvidia ecosystem and built all of modern AI around it. So tell me about the origins of Nvidia and its co-founder, Jensen Huang. He's a ferocious entrepreneur. He was born in Taiwan, moved to the United States when he was about 10 years old, and has a degree in electrical engineering. And when he was 30, he founded this company to make video game equipment because that's where they thought the market was.

And in fact, Invidia did not have a great reputation. They were really viewed as a second-tier company for about 20 years. Second-tier to whom? Second tier to Intel. Second-tier to Qualcomm. Second-tier to all the kind of big microchip majors that you would have heard of. And Intel and Qualcomm weren't working on the possibility of AI the way Nvidia was?

In fact, even Nvidia wasn't working on it. It came as a surprise to them that AI worked so well in their system. Invideo was looking for something like this. They couldn't have told you it was AI specifically, but they were certain that if they made these powerful systems for computer scientists, somewhere down the road, they would unlock some incredible functionality. Does Jensen Huang's success come from his business acumen or from technical skills that he learned as an engineer?

Technical skills. His technical skills, he is a world-class computer scientist, world-class engineer. And in fact, he runs his company like an engineer. He's thinking, what are computers capable of doing? What can I make them do that's never been done before? And then downstream of that somewhere, profits will appear. And so this is how NVIDIA works, and this is why they've become so successful. I use chat GPT like an idiot, right? I just play around with it, and I ask her to question as, you know, how? How much does this ball player make or, you know, what happened in 1965? Very simple questions, and what spit back at me is kind of wiki-like answers. Obviously, there is much more sophisticated ways to use even chat GPT, much less more sophisticated programs. What is Nvidia anticipating and does it own the market? I think Jensen is anticipating that these systems will kind of enter. robots in the real world. So Jensen is building essentially a giant digital playground called

Omniverse, where these robots can learn to move around in this kind of digital simulacrum. And once they've learned how to do that, he's going to download those brains and stick them into kind of real world machines and they're going to move around. I think he thinks this is in the five to 10 year time frame, although it's already starting to happen with automobiles. and other kind of like more primitive robots. Okay, this is what we really have to break down, his vision of the world, that he's seeing five years down the road.

Let's, let's, what is life going to be like in his terms? What is, what is the world that he's seeing? So Jensen hates science fiction, and in fact has never read a science fiction book, he told me. I think what he's seeing today is that within the next five years, Well, first, almost all sorts of entertainment will be intermediated by AI. So anything you see on a screen is going to be enhanced or passed through some kind of AI filter on the fly. What does that mean?

You know, so if I'm talking to you, I'm feeling that my face isn't looking that great today, it's going to be sort of very subtly turn on the face tune thing to make me look better. You know, my voice will maybe sound a little different. I mean, if these systems are already in place, but they're going to be. to get more sophisticated. I think for stuff like planning a vacation, you're just going to ask the AI agent to go bring you back some options. You're going to see the one you like and you're going to click yes, and then it's going to do all the work. It's going to book all the flights. For something like a medical diagnosis, I think the doctor will consult with kind of an AI

avatar and return with perfect diagnosis. And then moving forward into the future, Jensen currently is trying to train robots on more difficult tasks, like washing dishes without breaking them. I think probably they're going to have something like that online within the next two or three years. And you can imagine demand for something like that will be pretty substantial. The dishwashing robot? Oh, yeah. Yeah, no.

So Faye-Fei Lee at Stanford did a survey of thousands of people. And she asked them one question. How much would you benefit if a robot did this for you? At the bottom of the list was opening presence. So nobody Nobody wants a robot to open their presence for them. Okay, fair enough.

At the very top of the list was cleaning the toilet and washing the dishes. What else? What else is up there? Cleaning up after a wild party. That was the other one. So if you went through a big party,

you know, the kind of the reason you don't do that is because the place is going to be trashed afterwards. So you had some... So you're going to have robots like in the Jetsons. You're not old enough to remember it,

but the Jetsons were a cartoon about the future, and it had a robot house cleaner and also dressed up like a French maid of long ago pre-feminism mythology. And that's what it looked like. But what you're describing isn't all that different except for the French maid bit.

I think it's going, they think it's going to be at least a multi-trillion dollar industry, and Jensen wants to be right in the middle of it. He wants to build that thing's brain. That's where AI is going? That's what you think of. Dishwashing. I mean, think about it.

It's a huge market. I mean, it's going everywhere. But the consumer home use, the thing that people, when you ask them, what do you really want a robot for? They say, God, you know, it's nice not to wash the dishes anymore. And what jobs will be eliminated? Other than those. All of them? I mean, this is the question that I kind of put to Jensen.

Like, I can't imagine, David, what we're going to do. I mean, I think maybe like live theater. I guess we'll play video games with little triangle. Yeah, we'll play video games or we'll interact with the AI or maybe like in-person events, live theater will suddenly be more exciting. Maybe that's going to happen. You're making me glad that soon I'll be dead. Well, and it's funny because this question has absolutely split the AI community. Jensen is an optimist.

He thinks this is the greatest thing since the invention of electricity. And in fact, this is a comparison. Not just the amelioration of labor, the elimination of labor. No, complete elimination of almost all forms of labor. We published a profile of Jeffrey Hinton, who is deep into the AI world. This is a piece by Joshua Rothman, who looks at this future that you're describing as a dystopia. And he's, you know, as a creator of AI, a godfather of AI even, he is extremely wary. of this future. What you're telling me is that the head of invidia is the absolute opposite.

Hinton is the godfather of the software. He thinks that we are in big trouble. He quit his job at Google to warn humanity full time about the risks of these systems. Jensen is the godfather of AI hardware. He thinks Hinton is crazy. He thinks Hinton is being ridiculous and it's as pointless to argue against this as it would be to argue against, say, electricity or the industrial revolution or agriculture. I'll tell you, Jensen's winning. But it sounds like he's both an absolutist and a complete utopian thing. I just does.

Did he convince you, Stephen? Yeah, so when I brought these points up to him, Jensen started screaming at me. I showed him. That's a very winning approach to conversation. You know, I don't think he can help. He started screaming at you? Oh, yeah. He did not like, well, I should say I repeatedly questioned Jensen on this on every

every interview because I thought it was such an important question. And he was very dismissive of me. But I wanted to kind of push him a little, so I found this old clip of Arthur C. Clark at the dawn of kind of the 2001 era. A space odyssey. 1964, talking about how in the future machines may be smarter than men. And I wanted to show this to Jensen, and it just made him so mad. Why?

I don't know. I mean, I think... But it confirmed his own prejudices and vision. In fact, Arthur C. Clark was optimistic, too. This was the really surprising thing. But I think that he... Well, up to a point. Things don't end well in that movies, as I recall. You know, Jensen was like, I have never read an Arthur C. Clark book. His exact phrase was, I didn't read those effing books. I mean, except he swore. He just was not having it. He's completely candid. No BS. Absolutely speaks his mind. And this is really rare for a tech CEO. What is politics? None.

He's not in that kind of right-leaning libertarian Silicon Valley camp. Jensen was the most powerful figure in Silicon Valley not to attend Trump's inauguration. As far as I can tell, he has never made a political donation or taken a political stance in his life to a candidate. He wants to avoid this or because he doesn't have politics at all? I think he thinks politics is tribal. and irrational. We're talking about an engineer. We're talking about a guy who moves forward from data and who reasons forward from data and is willing to change his mind wherever the data takes him. That's just not how politics works. I'm talking with Stephen Witt, who is the author of the thinking

machine. We'll continue in a moment. This is the New Yorker Radio Hour. This is the New Yorker Radio Hour, and I'm David Remnick. I've been talking today with tech journalist Stephen Witt about Nvidia. For much of the past year, Nvidia has been rated the most valuable company on the planet, currently sitting near evaluation of $4.5 trillion. Stephen Witt's book about the chipmaker, Nvidia, The Thinking Machine, was just picked as the business book of the year by the Financial Times. I spoke with Stephen Whit in April. Now, Nvidia's stock market value was just above $3.5 trillion at the start of the year. In January, it also saw the largest single-day loss in the... stock market history. That's a $600 billion loss. So what happened? That was due to a new Chinese

AI model called DeepSeek, which ran much more efficiently or trained much more efficiently than any model that had come before. And people at first thought that maybe this would mean there would be less demand for NVIDIA's microchips. But Jensen has said that the market got it completely wrong. And in fact, they recouped all of that. It went all the way back up within a few weeks afterwards. So what actually happened? Because as I understand, a deep seek, it seems to be a cheaper AI option for one, but it also uses Nvidia chips. So why was there such a panic about it? There was a panic because it used an older version of Nvidia chips.

It used antiquated Nvidia chips, not the cutting edge ones. And so they retooled these old chips to get state-of-the-art performance, which really shocked and surprised a lot of people. And was that level of performance validated on a level that you would believe, much less Huang would believe? I think so. It seems like the results are legit. You know, and Nvidia was the most valuable corporation on Earth. And so it's going to have these kind of wild swings. For a long time, all of his manufacturing came from the Taiwan Semiconductor Manufacturing Corporation. They're the ones who really, the only ones who had the capability to build these

advanced microchips, so they would outsource production to Taiwan. Why couldn't he bring it here? Because Taiwanese engineers work 14 hours a day, six to seven days a week, and they're incredibly dedicated and incredibly gifted. Computers kind of segmented into almost two spheres. All of the hardware was going to be built in Asia and all the software was going to be built in Silicon Valley. And each side was just going to pursue its kind of competitive advantage. And that's unchangeable. It was unchangeable. Now with Trump, it's starting to look a lot different.

The Taiwan Semiconductor Manufacturing Corporation is coming to the U.S. They're making the single largest foreign direct investment in the history of the United States. And they're building this incredibly huge factory on the outskirts of Phoenix, where it's so hot that they have to put ice in the concrete to pour it so that it sets. The thing they're building out there is huge. It looks like an airport. And once they're done, it will probably be able of, capable of doing most of the manufacturing for NVIDIA. And in fact, NVIDIA is banned from selling its most advanced equipment to China.

Now, maybe what's happening is that people are starting to say, hey, this kind of like labor advantage that Asia had over the United States for a long time, maybe in the age of robots, that labor advantage is going to go away. And then it doesn't matter where we put the fact. factory. The only thing that matters is, you know, is there enough power to supply it and is there any geopolitical risk involved? And so in an age where robots are doing most of the work in the factory, I think the calculus of globalization and offshoring starts to look very different. Is he ultimately interested in bolting Taiwan to avoid the potential specter of China taking over Taiwan one form or another? Jensen loves Taiwan He loves it

It's where he was born He speaks Taiwanese natively He goes back all the time And he's a folk hero there He's in the night markets Buying food Just like a normal guy But he doesn't fear losing out

For this loyalty Taiwan has long benefited From what they called The Silicon Shield I was just in Taiwan I should mention And it was the only thing Anyone talked about

was the relationship between Nvidia and TSMC and if that relationship collapses or deteriorates and if Nvidia no longer needs Taiwan well then what happened What's the state of play about competition for Nvidia? Even in the software realm of AI

you've got a pretty rich competitive you've got open AI you've got meta you've got a number of huge players and the hardware system is just them The barriers to entry for building a neural net are quite low. Actually, a student can do it. The barriers to entry to shipping several billion microchips each year are very high.

Competitors who've tried to compete with Nvidia just haven't been able to bring the juice. They can't match what Nvidia can do. Is anybody trying? They're trying. Oh, yeah, a lot of people are trying. But when they try and bring it to the AI scientists, the AI scientists use it a little bit. And one of two things happen. Either it's not fast enough, or the scientists have to rewrite a million lines of code to make it work.

The biggest competitor on the horizon is Huawei or some other kind of Chinese manufacturer. Because Invidia can't sell its advanced equipment to China, it's illegal, this actually creates room in China for other firms to move. And in fact, this, I was recently in China. This was the question everyone was asking, How can we build, basically, NVIDIA, China? We think we have the talent. We think we have the work ethic. You know, we think we have the equipment.

Like, what do we need to do? Well, some people would say that the Chinese have been very successful in to be delicate about it, imitating or copying, or to be indelicate about it, ripping off technology from abroad and replicating it at home. Why can't it be done with NVIDIA? Because NVIDIA is always leapfrogging ahead. So, NVIDIA has, they're like the first. fashion business. They have a fall and spring release cycle. And they're constantly packing

the latest features into their microchip. So it's going to take you a year or two to knock off what they just built. And by that time, it's irrelevant. It's obsolete. This stuff moves so fast. Stephen, I've got to ask you in closing, what's the future for people who write books in the robotic world that you described earlier?

Oh, I have thought about this so much. I'll tell you something. This is going to sound weird, but hear me out. you know, I did a ton of interviews for this book, a couple hundred hours of interviews, tons of research. I mean, you've done this. You know what it's like. And maybe one percent of what you do ends up in the book. And you're constantly having to make these tough editorial decisions about what to keep and what to toss, trying to guess or extrapolate what the kind of general median reader is going to want to read. But what if you knew more about the reader? What if, for example, you were able to the reader was coming to you and saying, you know, I have 10 years of my

microchip manufacturing engineering experience, I want this book to be more technical. Or what if they're a student? And I want this book to be less technical and easier to read, it more explanatory. And then the AI takes the skeleton of what you've written and rewrites it on the fly to meet the demands of the reader. That's actually possible. We could do that. And so maybe the future of the book evolves into something, at least the nonfiction book, something more like a knowledge database?

I don't know if it's never really happened. I think narrative's very important. Stephen, you're freaking me out here. But it could happen. And the other thing it's really good at is taking complex technical subjects and basically, you know, dumbing them down for a lay audience. So the question I asked it constantly was, oh, explain how a microchip clock cycle works. But imagine I'm 12 years old and I don't know anything about this. Give me a very concise and simple explanation.

And what it produced was fantastic. I mean, I could barely improve on it myself. In fact, I couldn't. I mean, I didn't copy and paste, but I was like, well, that's how you explain this. That happened several times. And so, you know, I think when it comes to tough technical subjects, when it comes to research, as you say, and even when it comes to certain kinds of descriptive writing, it is a world-class tool that definitely can. save the writer a lot of time. Whether or not they want to

open that Pandora's box I think it sounds like the box is already flying open as it is. Stephen, we'll have you back before anybody's any robots are doing my dishes for sure. Okay, for sure. Thanks so much. Thank you. This was a great talk. You can read Stephen Witt on

technology at New Yorker.com and you can subscribe to the New Yorker there as well. New Yorker.com. Now, one update to note, when Stephen and I spoke, he explained that it was illegal for NVIDIA to sell advanced chips to Chinese firms. This month, the Trump administration reversed that policy, and they're going to allow the sale of one of NVIDIA's most advanced chips,

called H-200, to certain approve Chinese firms, so long as the U.S. gets a cut of the sales at 25%. I'm David Remnick, and that's our program for today. Thanks for listening. Today and always throughout the year, and I hope you have a good new year to come. The New Yorker Radio Hour is a co-production of WNYC Studios and The New Yorker. Our theme music was composed and performed by Merrill Garbus of Tune Arts, with additional music by Louis Mitchell.

This episode was produced by Max Bolton, Adam Howard, David Krasnow, Jeffrey Masters, Louis Mitchell, Jared Paul, and Ursula Summer. With guidance from Emily Boutin and assistance from Michael May, David Gable, Alex Barish, Victor Gwan, and Alejandra Deccan. New Yorker Radio Hour is supported in part by the Trurina Endowment Fund.