Jensen Huang Thinks A.I. Alarmism Has Gone Too Far
episodePreviously titled “Jensen Huang vs. the A.I. Doomers” — renamed by the publisher on Sep 23, 2026
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What does Jensen Huang see as the biggest influence of Nvidia on AI?
I'm John Caramonica, a critic at the New York Times. And I'm Joe Cascarelli, a culture reporter at The Times. Together we host Popcast, a weekly pop culture chat show where we speak to the biggest musicians, actors, internet celebrities, and more. We've had Bad Bunny, Olivia Rodrigo, and Ann Hathaway. We've also hosted live performances with Andre 3000 and Erica Badu. Plus, we end every conversation with a snack. Catch new episodes of Popcast every week on YouTube. And anywhere You get your podcasts.
If they believe they're out of control, then don't ship products until they're in control. Don't think for a second just because you're an alarmist that you're doing a social good. But what if it's what they believe? I can't talk to you about what they believe. I can tell you what I believe.
Over the course of these last few weeks, where the whole world has been talking about artificial intelligence, the voices people have been hearing most loudly are from the Frontier Labs, both their CEOs and leaders and their staffers. These are the labs making the very advanced AI models like Claude and ChatGPT and Gemini and others. But they're not the only perspective on AI. Probably the single most influential person in artificial intelligence is Jensen Huang, the CEO of NVIDIA. NVIDIA is now the largest company in the world, $5.4 trillion in market cap. I found this statistic amazing. Since 2023, 15 cents of every single dollar the American stock exchange has returned has been from NVIDIA stock.
And the reason is that NVIDIA is the material and software substrate on which modern artificial intelligence is built. NVIDIA's chips are not popular because AI is popular. AI in its modern form was made possible because NVIDIA's chips were popular. They were originally made for graphic processing, video games, that kind of thing. But it turned out the kind of parallel computing they were doing and the way they were programmable was exactly what was needed to make Deep learning in its modern form work. Huang is not just influential in terms of controlling one of the central resources for training new AI models and using them to answer questions and create intelligence in the world. He's also become very, very influential in the Trump administration.
And Huang has a very different perspective than some of the lab leads. He's worried about safety, but sees it as a very solvable engineering problem. He is worried about the direction things are going in, but does not want to see new regulation to change it. And so I wanted to see how Huang perceives AI, what his model is for thinking about it, what he thinks is going wrong, and what he thinks would need to happen for it to go right. So I came out to Santa Clara to Nvidia's headquarters to interview him. He joins me now. Jensen Huang, welcome to the show. Thank you. It's great to see you. So you've described AI as a five-layer kick. Walk me through the layers.
Well, first of all, it's a new industrial revolution. And uh this in this industrial revolution, this industry requires production. It manufactures things. I know that in the end, when people experience it, it is a software product, but it requires energy. the chips that go into these data centers, these AI factories. The next layer above it is basically the AI factory. What people enjoy as infrastructure or cloud services. And the layer before above that is the the models. And the important thing to realize there's language models, but there are models of all kinds, chemical models, biology models, physics models, articulation models, robotics, uh navigation models, self-driving cars, all kinds of different types of models.
And and then above that is the most important layer and the layer that I care most about that our country takes advantage of is the application layer. So this is, you know, applications for legal services, for um uh health services, for manufacturing, so on and so forth. All every single industry is involved.
So I want to go through this, but I want to go from the top down. Because as you're saying, the way people will interact with it, the way it will will or will not change their life, is at what you call the application layer.
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Chapters
8 chapters
1
What does Jensen Huang see as the biggest influence of Nvidia on AI?
0:00–13:46
2
How does Huang describe the five‑layer AI stack and its impact on industries?
13:46–26:06
3
What is the role of AI in radiology and how does it affect jobs?
26:06–40:32
4
Why does Huang argue that AI will create more jobs than it destroys?
40:32–53:49
5
How does Huang view the safety and regulation challenges of advanced AI?
53:49–1:04:39
6
What are Huang’s thoughts on open‑source versus closed AI models?
1:04:39–1:16:36
7
How does Huang envision the future of computing and energy for AI?
1:16:36–1:30:36
8
Which books does Huang recommend for understanding technology and strategy?
1:30:36–1:49:38