Nvidia CEO Jensen Huang was interviewed on Monday at the All-In Summit 2026. You can watch the full video here.
Huang was asked about Jacob Coxon’s whistleblower posts and Anthropic CEO Dario Amodei’s “We Must Pace the Fronter” essay. They both moved markets and dominated the mainstream media zeitgeist the past week.
Here are the 9 most important highlights from Jensen:
On former Anthropic researcher Jacob Coxon and the current Anthropic safety researcher’s 10%+ extinction risk prediction:
“The Coxon whistleblower is a very serious matter. Whenever you have a whistleblower, you have to take it very seriously. I thought Coxon had great courage to put out what his concerns were. And even then, there were some issues that were kind of conflated within that.”
“I think the whistleblowing is fine. I think the scientific prediction about the future is less fine because it’s not grounded on science. And it was expressed by a scientist, but it was obviously not grounded on science. And so I take issue with that.”
“Pausing, pacing, those are all the voluntary things that they could do if they feel that their company is out of control if Coxon saw something, obviously we don’t know what Coxon saw.”
On 10%+ extinction prediction figure:
“It’s made up .. these are well-educated. They’re called researchers. Obviously, they’re working in a lab. And so the confluence of these words and then the prediction is alarming and troubling, and it shouldn’t be done. It’s irresponsible.”
“Now, the fact of the matter is, let’s go back and look at the real facts. The facts are there was a prediction that in five years’ time, radiology will be completely taken over by artificial intelligence, and there’ll be no radiologists in the world. That has proven to be exactly the opposite. We need more radiologists than ever in the world.”
“There was a prediction that within 6 to 12 months, wasn’t it just last year, within 6 to 12 months, 90% [coders] would already be generated by AI. That has turned out to be wrong.
Within 6 to 9 months, that was predicted last year, 50% of entry jobs would be wiped out. That has proven to be wrong. Let’s see, what else has proven to be wrong?
I mean, all of these predictions have been wrong. We have to take accountability. We have to take account for all of the stupid predictions that were made.”
“These are some of the most consequential companies in history, extraordinary engineers, extraordinary researchers, really fantastic work. On the one hand, I work very closely with them as companies to companies. On the other hand, we have to have conversations like this in public, and it’s really unfortunate.”
On what AI fronter labs should do:
“Get engineering right.”
“All of the actual problems so far have come from the labs. .. the reason for that is because they have the most compute. Right? And the reason for that is because they’re trying to solve the frontier problems. And so in their defense. It’s sensible that the labs, the frontier labs, will be where the most danger come from. It is unlikely that a high school student did something. Because they just simply won’t have enough compute. And so it’s unlikely that a startup will be the reason. Because they won’t have enough compute. In fact, you can look across the planet and everybody won’t have enough compute with the exception of the frontier labs.
And so now the question is, if you look at what actually happened, and they’re doing pioneering work. It’s really very hard. They’re transitioning from research to engineering. I could imagine, and they’re obviously building some of the most consequential technology and companies in the world. They’re building their company. They’re building their culture. They’re building the technology. They’re building engineering, building products all at the same time.
And so I can understand it’s a little bit hair on fire, but nonetheless, the four incidents from one lab, the one giant incident from the other lab, the first thing that you have to do is just root cause the problem from an engineering perspective.
What happened? What could we have done differently? And what are we going to implement and institutionalize, whether it’s technology or methods or processes, and make sure that we don’t let it happen again.
Now, I would bet you money that in every single one of those cases it’s within their control in the future to prevent it. Because the alternative, if it’s not in their control, and I’m sure that they are, I’m sure those four incidents won’t happen again, I’m sure they root-caused it and fixed it. I’m sure they have now much better technology for, sandboxes and runtimes and monitors and continuous monitors.
And so I’m certain they have much, much better technology now. The alternative is also unlikely, which is for them to say, look, we had these incidents. After we’re done analyzing it, we came to the conclusion we don’t know anything that happened, and we have no idea how to control it, and we’re asking society for help.
Now, if that’s the case, then we ought to, a bunch of companies with engineers ought to send engineers in. I mean, and we should advise them if we can. But I doubt it.
I think they have extraordinary people. They got this handled.”
On RSI:
“Well, this is the new sexy phrase. But as you guys know, RSI is a combination of a system of ideas. It starts everything with in-context stuff. It starts with skills. It starts with reflection. It starts with reinforcement learning and synthetic data generation.
And these are all very sensible ideas that causes AI to get better at solving a problem over time. And you could also have low rank. All of that stuff doesn’t include the weights. You could actually improve the weights, and it’s called LoRA. LoRA could be improved in synthetic data generation, reinforcement learning, enhance it, without training the base model itself. And then over time, you could train the base model again with all of that experience.
And so I think it’s a sensible thing that you’re going to use the technology to enhance productivity of all kinds of tasks, including building AI. I think that’s a very logical idea. And I’m certain that everybody is using it in some degree.
It’s just this [RSI] phrase is now being used to weaponize the technology .. you could RSI all day long inside your company. But when you release a product, you’ve got to evaluate it, don’t you?
You have to test it again, don’t you? You have to make sure that there’s no regression, right? And so the basic process of control, these labs are going to, as they move from labs to engineering, they will have much, much better control.
And when they have much better control, and control comes from methods and knowledge and practice and tools and technology. All of those things that lead to better control, verification and evals, it’s going to enable RSI to be done inside the company and for good products to be released outside.”
On Hugging Face acquisition and the need for open models:
“The world needs both closed models and open models. You want to use, I use as much closed models as I can. This weekend, I used four of them. And they work terrifically. They’re frontier. They’re great experience. They work incredibly well. They’re getting better all the time. ..
This is no different than all kinds of commodities that we use in the world. You need both [closed and open].
Now, in the case of open, the reason why you need it is because it could be for sovereignty reasons, privacy reasons, proprietary technology reasons. Look at the facts. The facts are, in the last six months, $400 billion of venture funding went into AI-native companies. 80% of them use open models. If not for open models, how could they build their dream? Because their dream could be different.
Obviously, it would be different than the labs, the frontier labs’ dreams. And America has so many different ways to innovate. That’s one of our core strengths.
Great ideas just coming out of the fountain. And so open models enables that. Open models enables every single, if we want to win the AI race, it’s not about a few technology companies winning the AI race. It’s about every company in America. Every company, every industry, every researcher, every teacher, every student, every startup, everybody wins. Some of them will use closed models. A lot of them will use open models.”
On AI job creation and data centers:
“AI is creating an enormous number of jobs. The thing that [President Trump] wanted more than anything at the beginning of the administration and my first phone call with him, my first time I met him, is that he wants to create jobs in America. He wants to reindustrialize the United States.
He wants to make sure that the United States has the energy to support the next industrial revolution. Without energy, there’s no industrial growth. And so he wants to make sure that there’s energy growth, that there’s job growth, that we’re re-industrializing the supply chain.
Look at everything that we’re doing right now. All of it is happening right now as we speak. We’re creating more jobs than ever.
We’re creating software jobs. We were just talking about earlier, $400 billion of venture financing went into the AI industry just recently. Six months. Well, that’s created a ton of jobs. That’s created a ton of jobs. It’s created, you know, obviously enormous amount of demand for compute, which I’m happy about, which is also creating a lot of demand for data centers.
And we ought to talk about that. I was just talking to Governor Abbott of Texas, and he wants to appeal to the industry to make sure that we are empathetic to the small communities as we’re building data centers all across America, just to be better listeners.”
On why Nvidia invests in the supply chain:
“Well, we’re creating, this is a new industrial revolution. And every aspect of it is true. This new industry requires manufacturing.
“This industry isn’t just about the model. It’s not just about the chips. It’s mostly about the applications on top. It’s mostly about the infrastructure layer, the data centers, and all the infrastructure, the construction, the electricity, the power generation. All of that is involved. And so I look across the entire ecosystem and look for bottlenecks.
And if there are places where extraordinary companies are being built [that have] constraints. .. Maybe it’s a supply chain that has to get scaled up so that when we’re ready to deploy compute, that they’ll be ready for us, land power shell. .. I probably think about the long-term supply chain more than most because our company is really large.
And in order for us to succeed, a whole bunch of companies has to support me. You know, it’s got a Corning has this, Corning has to support me, Lumentum and, you know, TSMC, of course, and memory companies. And so we started working with all of these companies long before the revolution, the growth came, so that the growth could happen.”
On why neoclouds exist:
“I’m surprisingly uncompetitive. ..That’s not my thing. You know, my thing is kind of, like, for example, I’d be more than happy with five hyperscalers. However, the reason, notice the early customers of all the neoclouds, all the what we call NCPs, all the early customers were the hyperscalers.
And the reason for that is because the hyperscalers plan once a year, but the market dynamics is so volatile right now that they’re always almost wrong. And so with all these regional clouds who are agile, they can move fast, they know their state or they know their country, they know their region, they’re securing land, power, and shell in a way that’s hard for somebody who sits in Seattle or sits in Palo Alto to be able to see the planet.
And so we now have basically a large-scale distributed network of companies that are building, securing land, power, and shell for us. And now countries realize it’s strategic. So many countries are saying, I’m going to take my power and only give it to my own companies.”
On AI’s future:
“Slowing down is definitely the wrong strategy.”
“The future is great and we want to get there .. I want all of you guys there with me. We’re all going to be there. We’re going to be enormously successful together as humanity. And in the meantime, we got to encourage them, urge them on. They’re doing really, really important work, as you guys know, and I want them to succeed. I also would love for us to tone down the drama. And most importantly, we need all of America to come with us. That’s how we make it.”
[Tae’s easter egg: I noticed Jensen already uses a foldable phone. It looks like the Galaxy Z Fold8 from the video close ups.]