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BG2 PodJensen Huang | Does AI Revenue Justify Capex, '27 AI Bottlenecks, Singularity, Open vs Closed & more
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100 min read · 19,765 words- 0:00 – 0:20
Intro
- JHJensen Huang
This is an existential issue for us
- BGBrad Gerstner
We could easily stop, but if we stop today, we lose.
- JHJensen Huang
Functionality, capability, safety, security, they're all at exactly the same place, priority number one. [upbeat music]
- 0:20 – 5:06
A Week at the White House & the National Medal of Science
- BGBrad Gerstner
It's our third pod back together.
- JHJensen Huang
Yep.
- BGBrad Gerstner
In the last 10 days, you've been, uh, at the Xi State Dinner at the White House. Um, you were at the White House, uh, Summit where we did the accord on superintelligence.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Uh, and just yesterday you were there with your parents, um, when the president, you know, presented you with the National Medal of Science.
- JHJensen Huang
You were the only investor at the table.
- BGBrad Gerstner
Um, I, there-
- JHJensen Huang
You were the only investor at the table.
- BGBrad Gerstner
Well-
- JHJensen Huang
Now that, now that we reflected on it.
- BGBrad Gerstner
Yeah. Well-
- JHJensen Huang
Yeah
- BGBrad Gerstner
... t- tell me, being there with your parents yesterday.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Right? It struck me five out of the six people on stage were all born outside of the United States. Um, how did that feel?
- JHJensen Huang
Uh, well, fir- first of all, uh, it's a great honor all by itself.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and it's a reflection of the, the contribution that the company has made.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and obviously, obviously, uh, we created, we invented a new computing model. This is probably the most pervasive computing model in the world today. Uh, it's the only computing architecture that's in every cloud, it's in every computer company-
- BGBrad Gerstner
Right
- JHJensen Huang
... it's used in every field of science. Um, it's used by gamers, it's used by creators and builders, and it's used by scientists. Uh, it powers intelligence.
- BGBrad Gerstner
Right.
- JHJensen Huang
I mean, just i- if you take a step, step back and you look at what, what the company has accomplished, you know, we started out building a graphics chip for gamers.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And I'm still proud of that, of course. And, and, uh, we've now shipped one and a half, 1.67 billion dol-
- BGBrad Gerstner
Hmm
- JHJensen Huang
... uh, billion units.
- BGBrad Gerstner
Right.
- JHJensen Huang
That's how many generations of... I mean, I raised generations of scientists and kids and designers-
- 5:06 – 6:37
America’s Superpower
- JHJensen Huang
This, this is America’s superpowers.
- BGBrad Gerstner
Right.
- JHJensen Huang
Um, in a lot of ways, uh, the intellectual property, um, creation capability of our nation, uh, is unlike anything else in the world, and the reason for that is we attract the world's best.
- BGBrad Gerstner
That's right.
- JHJensen Huang
You know, we are the place where they wanna come and build their lives, uh, because of the opportunity it provides, the freedom that, that she offers, the opportunity that it provides, the spirit of, of invention and entrepreneurialism and, um, the can-do attitude. You know, in the United States, everything is, is possible.
- BGBrad Gerstner
Right. Hmm.
- JHJensen Huang
We start with, "Of course it's possible. Of course we could do that."
- BGBrad Gerstner
Right.
- JHJensen Huang
Instead of, instead of, you know... I, I do a lot of travel, and, um, "Of course you can't do that. Of course," you know-
- BGBrad Gerstner
In other places
- JHJensen Huang
... it's, in other, other places.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And we take it for granted.
- BGBrad Gerstner
Yes.
- JHJensen Huang
But the spirit, the, the, the, the energy, um, that comes around with the culture that we've created here-
- BGBrad Gerstner
Yeah
- JHJensen Huang
... um, it's just can't be understated. And, and so I think the flow, the inflow of intellectual property Into this com-- into this country is li- unlike anything else the world's ever seen.
- BGBrad Gerstner
It's true.
- JHJensen Huang
And we want that. We want all of the world's great minds to come here, bring their great ideas, you know, make them, realize them here.
- BGBrad Gerstner
Right.
- JHJensen Huang
Realize them here and let us, you know, let us, let us, uh, uh, keep that flywheel going. You know, I, I really-- it's a, it's a delicate system.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
It's a delicate balance I get.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
It's a delicate balance I get, and so we have to do it lawfully. We have to do it rightfully.
- BGBrad Gerstner
Right.
- JHJensen Huang
Um, but we, we surely want to do it.
- BGBrad Gerstner
Yeah, for sure. So I want
- 6:37 – 15:58
Entering the Singularity: Where Are We Now?
- BGBrad Gerstner
to start high level just kind of where we are. Uh, then I want to dig down a little bit, uh, i-into the safety and regulation and getting this right, where we are in terms of the compute build-out, and then finally we're gonna finish up thi-- uh, you know, drilling in a little bit to NVIDIA's growth and, and, and, and what's going on there. But you've been really good at calling the future, right? Two years ago, we were sitting here, and you said that the market was dramatically underestimating the amount of compute build-out that was gonna be required and was going to happen over the course of the next five years. You, you said it's not gonna be a trillion; it's gonna be two trillion at a minimum in terms of cumulative compute build-out, and of course, now we're over that. You said before everybody was thinking about it that inference, right, compute was gonna one billion X because of inference time reasoning and thinking. Um, and then last year, of course, before we saw Opus 4.6, before we saw Claude Code, you said we're entering the age of agents, right, where we're going to unlock a lot of these capabilities. Um, and of course, we saw Opus 4.6 and Claude Code really took off. So where are we now, right? We have Elon and Sam and Jen-
- JHJensen Huang
Those are only three things that I said that came true.
- BGBrad Gerstner
[laughs]
- JHJensen Huang
There, there's another 200. Why don't you just keep on going?
- BGBrad Gerstner
[laughs]
- JHJensen Huang
Uh, no, just let that be the podcast. [laughs]
- BGBrad Gerstner
Um, so our-
- JHJensen Huang
I'm just kidding.
- BGBrad Gerstner
So, so, so our Investor Day in a couple weeks is on, you know, entering the singularity, this acceleration. We have Elon and Sam and Demis all say, "Hey, we're in the foothills or entering the singularity." We have, you know, models solving Navier-Stokes, as you know. Um, so when you look into your crystal ball, where are we? And are we inflecting, are we accelerating, you know, into a different phase of superintelligence?
- JHJensen Huang
Um, and so let, let's unpack that. First, first of all, it's fair-fairly logical why the amount of compute that we're gonna need, uh, is a billion times more than where we were just recently, let's say, call it last year. And the reason for that is because thinking and problem-solving takes a lot more, you know, uh, inferences-
- BGBrad Gerstner
Yes
- JHJensen Huang
... than, uh, repeating something, regurgitating something that you memorized.
- BGBrad Gerstner
Right.
- JHJensen Huang
So when you're a ChatGPT, um, uh, you give it a prompt, most of that, most of that knowledge was encoded into the large language model. Um, unfortunately, of course, it hallucinated, and so the next click was, um, uh, it was, it was a generative, but it was also grounded or conditioned by ground truth.
- BGBrad Gerstner
Yes.
- JHJensen Huang
And so it would have to go out and do a search, do a quick search, comes back with the ground truth, and then from that conditioning, augment it with its own, own, what it already learned pre-training, um, and it would generate, uh-
- BGBrad Gerstner
Right
- JHJensen Huang
... new, new, uh, whatever the answer is. Well, most of, most of the things that we want to really do that are, that are interesting requires you to refl-- to, to reason step by step, to come up with several options-
- BGBrad Gerstner
Yeah
- JHJensen Huang
... plan, and you might decide, um, let's see how these things all roll out, and then based on, based on the answers of all of those, I reflect on the best answer so far, the best path so far. I might choose one or two or three of them, roll them out.
- BGBrad Gerstner
Right.
- JHJensen Huang
Okay. Prune the rest of it, and then just keep on doing this.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And, you know, people, we do this. That's the reason why, why we say, um, uh, great strategists love strategic optionality. You don't want to prune things too fast on the one hand, but you, you also have to optimize your resources. Well, AIs are doing that.
- BGBrad Gerstner
Yes.
- JHJensen Huang
Okay? So, so they're, they're keeping their strategic op-- uh, optionality. They're rolling things out. They're pruning. Um, they're, they're reflecting. They're pruning, so on and so forth. And it's all of that thinking, all of that exploration just takes a lot more compute.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and not-- on top of that, because it's able to now do productive things, we're gonna use it for more things. And so the compounding of both, it uses more compute to do its job, but it's doing a good job.
- BGBrad Gerstner
Right.
- JHJensen Huang
And therefore, we're gonna plu-- we're gonna hire it to do more jobs.
- 15:58 – 20:45
Navier-Stokes & the Falling Cost of Intelligence
- BGBrad Gerstner
on?
- JHJensen Huang
Well, Navier-Stokes is, is really a great example. Um, remember, uh, OpenAI did not solve Navier-Stokes from nothing.
- BGBrad Gerstner
Correct. Mm-hmm.
- JHJensen Huang
They solved it from the foundation of a lot of great scientists-
- BGBrad Gerstner
Of course
- JHJensen Huang
... and a lot of great mathematicians-
- BGBrad Gerstner
Yeah
- JHJensen Huang
... and a lot of great previous work. W-- Earlier I said we're at, we're at kind of the tipping point of a lot of these different fields.
- BGBrad Gerstner
Yes. Mm-hmm.
- JHJensen Huang
Because we're kind of at that phase, that, that point, uh, with Navier-Stokes, with a great deal of foundational work-
- BGBrad Gerstner
Yes, yes
- JHJensen Huang
... already been done. If we could just apply the exhaustive exploration of AI-
- BGBrad Gerstner
Yes
- JHJensen Huang
... to the previous, previous done work, we're gonna see one breakthrough after another breakthrough rather quickly. But we do need a lot of compute to do that. And, and, and the reason for that is because a large amount of exploration was necessary.
- BGBrad Gerstner
For sure.
- JHJensen Huang
You know, if it was, if it was simply, uh, somebody resolving some fundamental first principle theory in order to discover the breakthrough, if it didn't require a vast amount of exploration of space-
- BGBrad Gerstner
Mm-hmm
- JHJensen Huang
... uh, search space, not space space, but s-search space, if it didn't require that, then somebody would have found it earlier.
- BGBrad Gerstner
Right.
- JHJensen Huang
You know, people are pretty smart. And so, so I, I think that there are many problems like this that are just on a precipi- you know, precipice and, and really wants to just have that massive amount of intelligence exploration to, to get us there. Um, in the n-in the coming years, you know, my expectation is, is that the, the cost of intelligence would fall fairly, uh, fairly quickly.
- BGBrad Gerstner
Right.
- JHJensen Huang
And the reason for that is because obviously we're bringing more compute online. Um, uh, these models are getting smarter. When you're smarter, you can be more efficient.
- BGBrad Gerstner
Right. Mm-hmm.
- JHJensen Huang
And so the combination of these two things, the, the cost of intelligence will come down, which is, which is of course what they want.
- BGBrad Gerstner
Right.
- JHJensen Huang
And this is no different than Moore's law. If you go back 30 some odd years, we, we have three decades of computing cost decreasing by a factor of two every single year.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and, um, we want intelligence costs to decrease by a factor of two or 20 every single year because we-- the, the consumption of it is gonna- It's more than make up for it
- BGBrad Gerstner
Jensen's paradox
- JHJensen Huang
That's right. More than make up for it. And, and so there's, there's a massive empty space in the world that wants to be filled, empty vacuum-
- 20:45 – 24:27
What Will We Do with Abundance?
- BGBrad Gerstner
Right.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
You know, people say we're going to have more time. I, I completely disagree.
- BGBrad Gerstner
Mm-hmm.
- JHJensen Huang
I think, I think for most people-
- BGBrad Gerstner
Mm-hmm
- JHJensen Huang
... this intelligence is going to unlock more opportunities.
- BGBrad Gerstner
Mm.
- JHJensen Huang
Which is gonna... And they're gonna wanna pursue it because they're ambitious.
- BGBrad Gerstner
Oh, yes.
- JHJensen Huang
You know, give me an example of a family, a father, a son, you know, a husband, a, a wife, a mother, who doesn't want it, who, who don't have ambition for their families to have more? It's just-
- BGBrad Gerstner
Mm-hmm
- JHJensen Huang
... they just don't have the opportunity.
- BGBrad Gerstner
Yeah. It's funny-
- JHJensen Huang
And these things are gonna open up opportunities
- BGBrad Gerstner
... if you go back to 1930, Keynes talked, he made a prediction about the Industrial Revolution, and he said, you know, "In 100 years, the economy will have eight X'd, but the workweek will go to 15 hours a week." He was right. The economy did eight e- eight X, right? We had massive abundance and productivity gains from it.
- JHJensen Huang
Yeah, except we're working 80 hours a week. [laughs]
- BGBrad Gerstner
But, but, but we didn't go to a 15-hour week.
- JHJensen Huang
[laughs]
- BGBrad Gerstner
And what, what he got wrong was the human spirit, right? He didn't realize-
- JHJensen Huang
That's right
- BGBrad Gerstner
... that, that work is purpose.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Discovery is purpose.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Right? It's deeply encoded in, I think, our DNA.
- JHJensen Huang
Yeah, yeah.
- BGBrad Gerstner
And I'm working harder than I ever have-
- JHJensen Huang
Yeah
- BGBrad Gerstner
... having more fun than I ever have.
- 24:27 – 30:36
Physical AI & Robotics
- BGBrad Gerstner
you had a question about robotics in particular, though.
- CTClark Tang
Yeah. I guess, y- you've, you've said, notably said a few times this year that the ChatGPT moment for robotics is here, and I think you've also, you've, you've also said that it could be your next $100 billion market. So I guess, what are you seeing now in the, in the inflection point in this year-
- JHJensen Huang
Yeah
- CTClark Tang
... that this is around the corner?
- JHJensen Huang
Yeah, I, I understated the $100 billion because we're, we're already -- the first six months of this year, we did $10 billion in physical AI.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
Physical AI is basically, you know, uh, AI that's somehow interacting with the physical world, and it could be, uh, photon, photon-counting CT machines. It could be ultrasounds. It could be, um, uh, new imaging radars, uh, fi- uh, next generation of 5G.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
Not only does it understand radio waves, it's gonna understand signals of all kinds. It's a sensing-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... network. Um, uh, of course, robotics, self-driving cars, uh, manufacturing systems, visual inspections, uh, you know, ima- uh, uh, geo-geospatial satellites, um, uh, imaging the world and, and reconstructing it into 3D as... And so, so there's, there's -- basically, if you look at the entire electromagnetic spectrum, there's AI stuff going on from visible to invisible spectrums.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
Okay? And, and so, so we -- and we're doing work across that entire thing. That -- and, and, and, and as an AI, uh, there's, there's, uh, the perception part of it, there's the reasoning part of it, and then there's the planning and act-actuation part of it.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
When you finally get into planning and actuation, then that's self-driving cars and robotics and things like that. You know, in, in-warehouse delivery vehicles, uh, pick-and-place, uh, robots that you don't have to program-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... you know, a-as, as precisely because it learns by itself, you know, all the way to people talking about consumer robots, you know, coming into your house, you know, making your bed and things. And so, so -- or healthcare robots, hospital robots-
- CTClark Tang
Mm
- JHJensen Huang
... lots of really good examples there.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
Um, uh, you know, precisely delivering exactly your prescription to the patient-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... um, uh, uh, having, having, uh, robotic care, uh, literally 24/7 every single second-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... uh, to, to, to keep patients safe. Um, and, and so just lots and lots of great examples. Entire s- uh, surgical rooms that are gonna be completely robotic.
- CTClark Tang
Right.
- JHJensen Huang
And so, uh, lots of great technology being deployed. And so if you look at this whole thing, uh, we're the world's largest physical AI company. We, we did $10 billion in the first six months.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
We did $10 billion in the f- last year.
- CTClark Tang
Mm-hmm.
- 30:36 – 36:46
Building Responsibly
- BGBrad Gerstner
But of course, these capabilities cut both ways, which is why, um, you know, we hear a lot of people talking about safety. You've been highly critical of the doomer narrative.
- JHJensen Huang
You can only get there if you build the technology responsibly.
- BGBrad Gerstner
That's right.
- JHJensen Huang
And so the first thing is build the technology responsibly.
- BGBrad Gerstner
Right.
- JHJensen Huang
Notice the word build, it's an engineering word.
- BGBrad Gerstner
Right.
- JHJensen Huang
It's about technology, it's about engineering. Engineers, scientists, researchers, we have to build this technology safely-
- BGBrad Gerstner
Right
- JHJensen Huang
... responsibly. And, and the question is, can you? And the, the, the answer is abs- absolutely yes. Because if you can't, then you shouldn't build it at all.
- BGBrad Gerstner
Of course.
- JHJensen Huang
And so we either have to believe we can, or we shouldn't build it.
- BGBrad Gerstner
Right.
- JHJensen Huang
Okay? And so I believe we can. And so here, let me just reason about it with you. So the first part of it is they say, some people say that, that, um, uh, AI is, is, uh, uncontrollable because it's impossible to align perfectly. Alignment means this, for all the audience. Uh, you tell somebody, um, "I want you to do this."
- BGBrad Gerstner
Hmm.
- JHJensen Huang
And so the mission is clear.
- BGBrad Gerstner
Hmm.
- JHJensen Huang
The mission is clear. And, um, I-- it's clear to you.
- BGBrad Gerstner
Mm-hmm.
- JHJensen Huang
Because you said it in English, okay? And so it could be, uh, "I want you to solve this quadratic equation."
- BGBrad Gerstner
Right.
- JHJensen Huang
And so the, the mission is to solve the quadratic equation. The, the alignment is how do you do it? There are many ways to do it. For example, you memorized it.
- BGBrad Gerstner
Hmm. Right.
- JHJensen Huang
Okay? And so the answer is, you know, whatever it is. Uh, or, uh, you saw the answer in a textbook, so you looked it up.
- BGBrad Gerstner
Right.
- JHJensen Huang
Okay? Uh, you refer to a reference.
- BGBrad Gerstner
Mm-hmm.
- JHJensen Huang
Or you went to a drawer and you s- you, you know that drawer had all the answers. You opened a drawer, you picked out the answer, okay? Some people call that cheating. Um, I call that opening the drawer and retrieving the answer.
- BGBrad Gerstner
Right. Right.
- JHJensen Huang
Okay? And that's what computers do. There's a lot of different ways you could solve that problem.
- 36:46 – 40:59
Safety, Security & the Airbags Analogy
- JHJensen Huang
Safety and security technology-
- BGBrad Gerstner
Right
- JHJensen Huang
... are part of AI.
- BGBrad Gerstner
Right.
- JHJensen Huang
There's some weird- ... formulation that AI technology and safety and security are orth- orthogonal.
- BGBrad Gerstner
Yeah. Mm.
- JHJensen Huang
It's kind of like the airbags and the, and the braking system-
- BGBrad Gerstner
Right
- JHJensen Huang
... and the radars, the cameras, um, the ABS, uh, the, the, the lane keeping.
- BGBrad Gerstner
Right.
- JHJensen Huang
All of that technology is somehow independent of the car.
- BGBrad Gerstner
[laughs] Right.
- JHJensen Huang
Do you guys understand what I'm saying?
- BGBrad Gerstner
Right.
- JHJensen Huang
The only thing that matters to the car is the engine.
- BGBrad Gerstner
Right.
- JHJensen Huang
In fact, the whole car is part of the car's technology.
- BGBrad Gerstner
Right. Mm.
- JHJensen Huang
When I say we need to accelerate AI's technology, what I mean by that is we need to accelerate the security technology.
- BGBrad Gerstner
Yes.
- JHJensen Huang
We have to accelerate the safety technology. They all have to be accelerated.
- BGBrad Gerstner
Right.
- JHJensen Huang
If you ask me right now, I think everybody would say, "Let's accelerate security. Let's accelerate safety technology." Nobody says, "No, let's pace that."
- BGBrad Gerstner
Right. Right.
- JHJensen Huang
We should accelerate that.
- BGBrad Gerstner
Correct.
- JHJensen Huang
It's all part of the same thing. You can't separate capability, functionality-
- BGBrad Gerstner
Mm
- JHJensen Huang
... from safety and security. They go as one.
- BGBrad Gerstner
Mm.
- 40:59 – 43:03
What “America Winning” Means
- JHJensen Huang
is winning.
- BGBrad Gerstner
Yeah. Mm.
- JHJensen Huang
Um, I would reframe winning, not of the technology industry winning.
- BGBrad Gerstner
Right. Right.
- JHJensen Huang
Not of just the AI industry winning.
- BGBrad Gerstner
Mm.
- JHJensen Huang
Um, America winning means every industry in America winning.
- BGBrad Gerstner
Healthcare, education.
- JHJensen Huang
That's right. Nothing would give me more joy. The definition of American winning is when we talk about Lilly winning-
- BGBrad Gerstner
Yes
- JHJensen Huang
... Walmart winning, FedEx winning-
- BGBrad Gerstner
Yes
- JHJensen Huang
... every single one. Boeing winning.
- BGBrad Gerstner
Right.
- JHJensen Huang
Um, the US military winning.
- BGBrad Gerstner
Every citizen winning.
- JHJensen Huang
Every citizen winning. And so, um, uh, our universities winning, our high schools winning.
- BGBrad Gerstner
Yes.
- JHJensen Huang
Um, yeah, that's the definition of winning.
- BGBrad Gerstner
Correct.
- JHJensen Huang
The winning... W- there is no winning if it's just a technology won-
- BGBrad Gerstner
Exactly
- JHJensen Huang
... but nobody used it.
- BGBrad Gerstner
Right. Mm. Right. What, what, what-
- JHJensen Huang
The greatest risk is, of course, we're gonna... You know, I, I'll just take it, uh, I'll just say baseline. Uh, there will be no technol- there will be no AI technology industry if we don't build it safely and securely.
- BGBrad Gerstner
Right.
- JHJensen Huang
Okay? Th- this is an-
- BGBrad Gerstner
Right
- JHJensen Huang
... existential issue for us.
- BGBrad Gerstner
Right. Mm.
- 43:03 – 47:07
The Three-Legged Stool: America’s Superintelligence Framework
- BGBrad Gerstner
Most people don't understand what our security framework i- i- is in the country. Um, I've said we have the most robust superintelligent security framework in the world. Um, we're, we're clearly the only country on the planet that's actually sanctioned a model and pulled it off the shelf with Mythos earlier this year. But I describe it as a three-leg stool. We have the frontier model review of every new frontier model by Casey and the Department of Commerce. So they do all their work. If a new model's coming out, they review it. They test it for whether or not they think it's gonna cause a problem in the marketplace. Now we have the White House accord on superintelligence that you helped to architect, internal and external audits, board oversight, and all of the liability that comes with that. And then third, we have the SI Force, now led by Jay Clayton; of course, Emil and Scott and Andrew. And that's doing critical industry coordination, cyber, et cetera. So these three legs on the stool, um, there are people out there, I heard Gates recently saying we're not doing, you know, enough. We need l- new laws on the books and everything else. That three-legged stool seems like a lot to me in a very short period of time that's come together. As a leader of one of the most important companies, obviously, in superintelligence, do you feel comfortable, right, for that future that we're trying to usher in, that that is a good step forward w- where we need to be right now?
- JHJensen Huang
Yeah. The, the best way to get to the future is, uh, uh, uh, take action quickly.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And, and if we, if we, uh, argue about what is the, what's perfect, uh, versus what's first-
- BGBrad Gerstner
Right
- JHJensen Huang
... um, we'll end up arguing about perfection, um, and we'll never get there.
- BGBrad Gerstner
Right.
- JHJensen Huang
And so I love, I love the fact that, that, um, these three-legged stool are actionable.
- BGBrad Gerstner
Right.
- JHJensen Huang
They're tangible. They have real teeth.
- BGBrad Gerstner
Right. Happening now.
- JHJensen Huang
It's happening rou- right now. You could-- You know, we're doing it now. We're taking action now.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and the reason we're taking action now is because it's good for our coun- company, it's good for our industry, it's good for our country-
- BGBrad Gerstner
Right
- JHJensen Huang
... it's good for society. It's good all the way around. And if we don't do these things, um, uh, y- you know, the outcome, the outcome is, is less desirable.
- BGBrad Gerstner
Right.
- JHJensen Huang
We don't get to pursue that optimistic future that we all dream- dreamt about. And so if you go back and look at another industry, I don't remember another industry that is, uh, as... I- it's currently at its current state-
- BGBrad Gerstner
Right
- JHJensen Huang
... and have now formulated all of these cross-company-
- BGBrad Gerstner
Right
- JHJensen Huang
... cross-industrial, um, government to industry, um, coordination-
- BGBrad Gerstner
That's right
- JHJensen Huang
... uh, to make sure that we, we, uh, we advance this in a responsible and optimistic way.
- BGBrad Gerstner
Yeah, I just think it's so important for people to understand because when I hear senators talking about it on television, on both sides, to be perfectly honest, like, they don't even-
- JHJensen Huang
Well, they have to learn about what we're doing here first
- BGBrad Gerstner
They're-- Right. They don't even know what we're doing.
- JHJensen Huang
Yeah, yeah.
- BGBrad Gerstner
Right? Like, we are doing an extraordinary amount. And by the way-
- JHJensen Huang
Yeah
- 47:07 – 51:47
2027 AI Bottlenecks: The Compute Build Out
- BGBrad Gerstner
Um, Dylan, our friend as, uh, at SemiAnalysis has said we're gonna bring on board 43 gigawatts of new AI compute next year. Just to contextualize it, we'll share a chart with people online. That's more than all of the AI compute that exists in the world today. So we're gonna bring that on board next year. The year after that, another 40 gigawatts, uh, of compute. You are the one-- you know where every single GPU is allocated, right? [chuckles] So as you sit here, does that sound right to you? Do you think we're gonna bring on that much compute? Um, and do you think that, you know, some of the things we're hearing out there about permitting, permitting issues or bottlenecks in the supply chain or, you know, uh, pro- local protests, uh, do you think the number's gonna be materially different than that based upon what you're seeing?
- JHJensen Huang
Uh, I think the demand is definitely there and more.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
The demand is definitely there and more. Um, the challenge, of course, is that there are a lot of obstacles. When you, when you move from, uh, when you move from digital to the physical, there are a lot of obstacles.
- BGBrad Gerstner
Right.
- JHJensen Huang
There, there are land permitting. There's power generation that you gotta bring online. Um, of course you gotta, you need construction workers and outfitters and plumbers-
- BGBrad Gerstner
Correct
- JHJensen Huang
... and, you know, all kinds of, you know, electricians.
- BGBrad Gerstner
Created a million new jobs just building these things.
- JHJensen Huang
Create a million new jobs and, and their, their skills are, their skills are not fungible, you know?
- BGBrad Gerstner
Right.
- JHJensen Huang
They, they have a lot of skills, and particularly the, the ones that are building these $50 billion data centers, uh, you're gonna want some people with great skills.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and, and there's a critical part of every single one of the build out of these things where, where you need some very specific skills. And so, um, I, I think that... And then there's, there's of course, um, uh, whatever moratoriums that are, that are happening-
- BGBrad Gerstner
Right
- JHJensen Huang
... um, and what- whatever, whatever issues that are, that are, um, uh, um, uh, that we're seeing around, around the country. And, uh, and so I think, I think this is, this is, um, uh... my guess is that, uh- Land power shell, um, uh, the, the build-out resources-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... uh, will be one of the, the most important obstacles-
- CTClark Tang
Mm
- JHJensen Huang
... to reaching that. And, and so, so our, our company, as you know, now speaking specifically for us, there's several things that we're doing to, uh, mitigate that. And, and one, you know, because we're the only company that serves every CSP-
- CTClark Tang
Right
- JHJensen Huang
... we serve every NCP, um, uh, we have, uh, uh, great enterprise businesses through Dell and HP and-
- CTClark Tang
Yeah
- JHJensen Huang
... Lenovo and others. And because we serve every single industry and, and we're across the entire, uh, life cycle of AI, everything from, you know, of course, data processing to training to post-training to inference to agentic processing, um, and all of the tool use that we accelerate, uh, you know, our exposure to our go-to-market is the largest of all.
- CTClark Tang
Mm-hmm. Mm.
- JHJensen Huang
Um, every, every contract manufacturer in the world is working on my behalf. Um, every go-to-market is, is connected to our architecture. And, um, and so if one particular state, one particular community, um, one particular data center has a hard time-
- CTClark Tang
Right
- JHJensen Huang
... um, you know, our demand is so much greater than our supply at the moment, we'll just adjust our supply chain accordingly. Um, the other thing that we have, and, and I, I don't love this answer as much, um, but as, as you know, NVIDIA is also the infrastructure for the planet. And so, uh, whether it's in Europe or, um, uh, uh, and we- we've got, we've got, uh, early developments now in Africa, in Central Asia, um, in Southeast Asia, in Latin America, in, you know, in Middle East-
- CTClark Tang
Right
- JHJensen Huang
... and so on and so forth. And so I, I don't, I don't love that, that, that, um, United States can't keep up.
- 51:47 – 55:26
50 GW of Chips, 35 GW of Power
- CTClark Tang
street is there's this idea that, you know, maybe there's 50 gigawatts of announced chips, um, that are underway, um, or talked about, and maybe 35 to 40 gigawatts of comput- or land power shell that might come online. So what compute fits into that land power and shell and on what timeline is a question up in the air.
- JHJensen Huang
Yeah.
- CTClark Tang
But, um, I guess, like if we think of-
- JHJensen Huang
This-
- CTClark Tang
... through the entire-
- JHJensen Huang
And, and just-
- CTClark Tang
Yeah
- JHJensen Huang
... Clark, just, just interrupt you there. And, and, um, uh, y- you know, of course, a- as you know, NVIDIA's architecture is the most productive.
- CTClark Tang
Right. Mm-hmm.
- JHJensen Huang
It generates the most tokens per watt.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
And so if the world's, if the world's amount of watt power energy reduces, it shifts their choices to the most productive version, and the reason for that is that they still wanna make their revenues.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
Right. And so, so all of my CEO colleagues, they all wanna-- they all have ex- high expectations for revenues next year, and people have, you know, they need to deliver it, their shareholders counting on them to deliver it, all their partners need to, need them to deliver it. And so when the amount of power reduces, the quality of the compute you put into it has to k- has to be the most ex- most extraordinary.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
We're the most productive computing resource you could put in the world today.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
We're the most rentable.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
We're fungible and-
- CTClark Tang
Right
- JHJensen Huang
... we're durable. And so, so the, the, the, the forces around the world, because of the shortage of resources-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... is, is shifting interest towards us.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
Our market share was already very high.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
But surprisingly to everybody, not only are we a large company and our market share is high, our market share is actually increasing-
- CTClark Tang
Mm-hmm
- JHJensen Huang
... for these reasons.
- 55:26 – 57:20
Elon, Colossus & SpaceX
- BGBrad Gerstner
Elon, um, when he started building Colossus. And we were blown away a couple years ago to see him stand up a couple hundred thousand hoppers, right, in Memphis. Um, and I remember you saying nobody can do it like him. Now he's raising another 40 billion, gonna buy maybe million plus Vera Rubins. Um, he's-
- JHJensen Huang
He's moved from the K's to the M.
- BGBrad Gerstner
[laughs]
- JHJensen Huang
[laughs]
- BGBrad Gerstner
He says he wants to have 10 gigawatts by the end of 2027.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
That's hundreds of billions-
- JHJensen Huang
Yeah
- BGBrad Gerstner
... right, spent on Vera Rubin. It's an unprecedented ramp at scale. You were with him again yesterday when he was also presented with a medal. Is Elon that much better at building compute today as he was then? Is it now obvious to you, is it, is it a foregone conclusion that SpaceX will be the largest AI hyperscaler in the world?
- JHJensen Huang
Well, we, we, we used to, you know, i- in the, in the two p- parts of our chart, um, Elon used to be e- under enterprise. That's the way we reported the numbers.
- BGBrad Gerstner
Right.
- JHJensen Huang
Now he's part of our CSPs.
- BGBrad Gerstner
Of course.
- JHJensen Huang
Yeah, yeah.
- BGBrad Gerstner
Of course.
- JHJensen Huang
And so-
- BGBrad Gerstner
They're massive
- JHJensen Huang
... so I'm, I'm delighted that, that, that, um, I, I love working with Elon. Um, he's using our technology for his own AI, um, in training models and such, uh, deploying models, of course. GrokBot is super cool.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And, and, um, uh, and the, and the demand for GrokBot, the consumption for GrokBot is really skyrocketing. And then, of course, he rents it.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And so the combination of these three things, he's fairly unique in doing that. Um, I guess, I guess, uh, uh, Google does that.
- BGBrad Gerstner
Right.
- JHJensen Huang
Right?
- BGBrad Gerstner
Right.
- JHJensen Huang
That would be another, y- yet another example. And so I think he's, he's, um, uh, also has the, has the, uh, advantage that, that he loves the intersection between computing and the physical build-outs.
- BGBrad Gerstner
That's right.
- JHJensen Huang
You know, he loves that, that whole area, and nobody knows more about energy
- 57:20 – 1:00:33
Data Centers in Space
- JHJensen Huang
than he does. And, and, and, uh, one particular, uh, new market that we're gonna go explore together is putting data centers out in space.
- BGBrad Gerstner
Right.
- JHJensen Huang
And so our two engineering teams are working super closely together, you know, to create a, a new type of server, a new type of architecture, um, that might, might, uh, be super good, you know, you know, in space and on Earth. And so-
- BGBrad Gerstner
Well, we saw that Starship launched last week, you know, had its, its, its first orbital rendezvous and was launching-
- JHJensen Huang
Yeah
- BGBrad Gerstner
... those V3 sats. That literally captured the imagination and kind of broke Twitter for a moment.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Just people mesmerized by watching these launch into space.
- JHJensen Huang
I can't, I can't wait to be a payload.
- BGBrad Gerstner
[laughs]
- JHJensen Huang
I mean, not personally. [laughs]
- BGBrad Gerstner
Do you think... Does that give... Do you have increasing confidence that we will have a material amount of compute in space, you know, via S- via Starship by, let's call it, 2028, 2029? I mean, Elon's put some big numbers out there, but do you think that we can get to material inference in space in that, in that timeframe?
- JHJensen Huang
Only NVIDIA compute.
- BGBrad Gerstner
Only NVIDIA compute.
- JHJensen Huang
And l- l- let, let me tell you why. Uh, it's not, not just about the technology. Uh, NVIDIA's performance per unit energy is the world's best, and so we call it performance watt. And but the most important thing is, is this: The productivity of NVIDIA's compute is so good, meaning the return on investment, invested capital is so good-
- BGBrad Gerstner
Yes.
- JHJensen Huang
... that you could put it out in space, and the launch cost is a small percentage of it.
- BGBrad Gerstner
Okay.
- JHJensen Huang
The launch cost is not inconsequential.
- BGBrad Gerstner
Right.
- JHJensen Huang
And so you're not gonna put s- low-cost computing out there.
- BGBrad Gerstner
Correct, correct.
- JHJensen Huang
You're gonna put high-value computing out there.
- BGBrad Gerstner
Correct.
- JHJensen Huang
And so we're the highest value computing system you could imagine, the highest computing system in the history of computing, and so we're the perfect fit, really, to launch into space right now.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
Irrespective of the com- the launch cost, it'll still be excellent ROI.
- BGBrad Gerstner
So do we get 500 megawatts in space by '29?
- JHJensen Huang
Well, I'll, I'll let, let him tell you.
- BGBrad Gerstner
[laughs]
- 1:00:33 – 1:06:04
Does AI Revenue Justify the Capex?
- JHJensen Huang
SpaceX.
- BGBrad Gerstner
Um, it costs trillions of dollars to build all this Capex. You guys have leveraged your own balance sheet to help folks like the Neoclouds build that out. In order for finance people to get it to pencil out, they need to see payback, right? Um, you talked about, you know, some companies seeing one-year payback, right? $50 billion in the first year, you know, some, some spot pricing out of, out of SpaceX perhaps. Um, but if I look at the total incremental offtake, right, the revenue of all the labs this year. So if I add up, you know, the two frontier labs... Oh, yeah, get yourself a snack.
- JHJensen Huang
[laughs]
- BGBrad Gerstner
And we add up, you know, some of the inference labs. It's about $200 billion, okay? Um, we need to see that double next year to four hundred billion. We need to see it double the year after that to eight hundred billion, right? In order to get in the zip code of the payback on trillions of dollars of Capex. Um, we, we had this massive unlock this year with, with Claude Code that led to a 10X increase in Anthropic's revenues. What's your confidence that the labs can continue to two to 3X their revenues every year in order that we get the payback that's gonna be required just to, to, to build out trillions of dollars of Capex? I mean, you're investing in these companies. You have, you have big investments in these companies, right? Do you see that level of growth continuing-
- JHJensen Huang
Oh, yeah
- BGBrad Gerstner
... in these companies?
- JHJensen Huang
Oh, yeah. People misunderstand what's going on. So first of all, particularly, I mean, NVIDIA represents, call it 80% of the revenue share of I- AI infrastructure in the world today.
- BGBrad Gerstner
Correct.
- JHJensen Huang
And so it's-- And so my description of, of the universe of computing and video computing matters here. There are really basically, call it three segments, three large segments. It's, it's, it's probably slightly more than that, but let me just kind of categorize it in three large segments. The first segment of our computing is just baseline computing, just meaning you use it for data processing, molecular dynamics, physics simulation, um, fusion simulation, fission simulation, you know, you name it-
- BGBrad Gerstner
Right
- JHJensen Huang
... right? Quantum chemistry, quantum physics, you know, and so everything.
- BGBrad Gerstner
Right.
- JHJensen Huang
Okay? The world of simulation and data processing, not to mention computer graphics. And, and so all of that processing done on our GPUs, if you just kind of said there was no AI at all, just classical machine learning, uh, XGBoost at Visa, Mast- Mastercard, uh, you know, for fraud detection-
- BGBrad Gerstner
Right
- JHJensen Huang
... our recommender systems-
- BGBrad Gerstner
Correct
- JHJensen Huang
... to figure out what news to recommend to you, I mean, just all of that stuff combined-
- BGBrad Gerstner
Correct
- JHJensen Huang
... classical computing-
- BGBrad Gerstner
Right
- JHJensen Huang
... not AI, not deep learning-
- BGBrad Gerstner
Right
- JHJensen Huang
... not agentic systems, I'm gonna call it a third of our business.
- BGBrad Gerstner
Yeah.
- CTClark Tang
Mm.
- JHJensen Huang
And that business is growing, you know, call it 30%, 40% per year.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
Okay? In the absence of any AI labs, NVIDIA's not zero, right?
- BGBrad Gerstner
Right. Right.
- JHJensen Huang
We're, we're quite a large company. And so that's number one. The second part is, um, the AI labs, people see two, but we work with every one of them.
- 1:06:04 – 1:11:35
Open vs. Closed Models
- JHJensen Huang
And then one observation, uh, open models. You, you know that, that I, I've been a great advocate of open models, and the reason for that is because open models opens up new opportunities. If you look at all these startup companies, 80% of them use open models.
- BGBrad Gerstner
That's right.
- CTClark Tang
Mm-hmm.
- JHJensen Huang
And, and they're not using it to compete with the frontier labs. They're using it to unlock a new opportunity somewhere else.
- BGBrad Gerstner
That's right.
- CTClark Tang
Mm.
- JHJensen Huang
You know, it could be in physical AI, could be manufacturing, could be healthcare. They're doing something completely, completely different.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And, and they're taking, um, these open models and, and many of them taking Nemotron, and the, these models are then customized into superintelligence.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And so if you will, I kind of see the, the, the cons- the general, the general closed labs will be artificial general intelligence, and it'll get super good.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And then you have all these vertical companies that are focused on a particular domain, and they have very proprietary data.
- BGBrad Gerstner
Yes.
- JHJensen Huang
They teach it to do something very specific, and they achieve superintelligence for their domain.
- BGBrad Gerstner
Right. So you don't see, you know, so again, um, if, if we go to your compute math, which I think w- a lot of people are using to forecast the future revenues of, of, of the labs, for example. You know, you said, "Hey, if you stand up a gigawatt of this compute, you can get, you know, $40, $50 billion out the other end." But if we took the number we talked about earlier, 40 gigawatts of compute coming online next year, and if you took 40 billion out the other end, then that would be 1.6 trillion of revenues coming out the other end of that factory. But of course, there's something, you know, it, it doesn't work that way, right? At the end of the day, there's, you gotta look at the demand curve and the rate of diffusion to determine, right, the revenue that's gonna come out the other end of the factory. And what I hear a lot is that people are nervous, right? They've seen over the course of the year maybe the labs revenue slowing down a little bit, and they're nervous that, you know, at some point you're going to have the proverbial bubble popping, right, where we have more supply coming online than we have demand at a moment in time, that AI is more like these step functions rather than just this parabolic line straight up. I guess the question to you is do... Are you worried about, you know, a moment in time where everybody gets nervous about financing the build out, right, and, um, and then we don't get the build out?
- JHJensen Huang
Well, you know, all these different things, you just, just gotta break it down.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
Break it down, back down to first principles. And, and, um, uh, the, the part that people are trying to extrapolate, the 100, 100 b- $100 billion of AR or $125 billion-
- BGBrad Gerstner
Right
- JHJensen Huang
... of AR they're trying to extrapolate is a small part, not a small part.
- BGBrad Gerstner
Right.
- JHJensen Huang
It's, it's just a part-
- BGBrad Gerstner
Right
- JHJensen Huang
... of the overall infrastructure-
- BGBrad Gerstner
For sure
- JHJensen Huang
... build out.
- BGBrad Gerstner
For sure.
- JHJensen Huang
And, and so, so the question is, are people gonna continue doing shopping online?
- BGBrad Gerstner
Right.
- 1:11:35 – 1:13:26
Too Much Pressure on Two Labs
- BGBrad Gerstner
But you saw the pullback in a lot of the infrastructure companies-
- JHJensen Huang
Mm
- BGBrad Gerstner
... right, on the fear that, oh my gosh, OpenAI doesn't have the money, won't have the money in order to pay for the infrastructure.
- JHJensen Huang
Mm.
- BGBrad Gerstner
I think the point that you're hammering home-
- JHJensen Huang
Mm
- BGBrad Gerstner
... is that when we look at the 40 gigawatts of infrastructure build out next year, at least a third of it is just going to, right, general purpose compute replacement, the, the, the, the basic stuff out of the hyperscalers, that a third of it's going to kind of Neocloud, sovereigns, enterprises, everybody else who's using this, all the startups, and a third of it's going to not two labs, but to many labs, right, including Groq and Thinking Machines and all the other-
- JHJensen Huang
That's right. We're putting way too much pressure on two labs.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
I'm delighted to partner with them and, and support them. Uh, they're gonna be, uh, two of the most consequential technology companies ever built in history. Uh, they're gonna be magnificently successful.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
But they don't have to be anywhere near a trillion dollars in revenues to be successful.
- BGBrad Gerstner
Right.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Right.
- JHJensen Huang
And I think we're putting way too much pressure on that. And then the rest of the industry, we still do have to build out a few trillion [laughs] dollars of computing infrastructure.
- BGBrad Gerstner
Um, just to keep going, um, let's, let's shift a little bit.
- JHJensen Huang
How good is this, you guys? Come on.
- BGBrad Gerstner
By the way, what are, what are these called?
- JHJensen Huang
These are dried plums.
- CTClark Tang
Yeah.
- BGBrad Gerstner
Dried plums. The old dried plum.
- JHJensen Huang
Yeah. This, this one part- particular store in Taiwan is one of my favorites.
- BGBrad Gerstner
Kind of a licoricey-
- JHJensen Huang
There is licorice, yeah. Licorice. A little licoricey.
- BGBrad Gerstner
Right. Vanilla.
- JHJensen Huang
Uh, salt, sugar, cinnamon.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Has a little twang to it.
- 1:13:26 – 1:17:37
AI Supply and Demand Dynamics
- JHJensen Huang
I'll come to work, I'll come to work every day.
- BGBrad Gerstner
You said very confident and plenty of time to work with the supply chain to do even better. You expected to do even better and to not disappoint customers So are, are things going even better? And has the order book continued to grow? 'Cause the other part of that is, right, you took a snapshot at a moment in time, and of course people are continuing, you know, to place orders. So it... Do you think there's enough slack in the supply chain you can squeeze more out? And is the g- order book continuing to grow as more of these capabilities are unlocked?
- JHJensen Huang
The... First, let me just tell you why-
- BGBrad Gerstner
Yeah
- JHJensen Huang
... I told everybody. Um, the challenge that we have is we have giant order books. Every single CSP, every single NCP, every single OEM had already placed orders on us. Startups, big companies, small companies, they already placed orders on us. And, and the reason for that is because we work with them on a, on a, depending on, on the size of the customer, at least a year, um, for the, the largest ones, two years forecast. And so, so we already have a, a very large order book. And because I was in the process of allocating, and what I was allocating to all of our customers is a lot less than-
- BGBrad Gerstner
They wanted
- JHJensen Huang
... they wanted.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
If I, if I was, if I didn't publicly say-
- BGBrad Gerstner
Right
- JHJensen Huang
... what we had-
- BGBrad Gerstner
Right
- JHJensen Huang
... everybody would be second-guessing-
- BGBrad Gerstner
Right
- JHJensen Huang
... are they short-changed-
- BGBrad Gerstner
Right
- JHJensen Huang
... are we being... You know, and so, and so it was m- it was my way of, of essentially handling, um, every single conversation where I'm disappointing people.
- BGBrad Gerstner
Right.
- JHJensen Huang
Um, and let them know that-
- BGBrad Gerstner
So pretty much every customer would buy more from you if you could deliver more to them.
- JHJensen Huang
By far.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And then, and then since then, of course, you know, we have new orders-
- BGBrad Gerstner
Right
- JHJensen Huang
... almost, almost weekly and daily. And, and so, so, um, uh, in, in addition, however, uh, we're getting more supply, and some of the supply that, that is limiting us is lamp power shell downstream.
- BGBrad Gerstner
Correct.
- JHJensen Huang
And so a couple of weeks ago we announced two gigawatts in Australia.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And so that's a very big deal. Two gigawatts to us is like $80 billion.
- BGBrad Gerstner
Yeah, it's huge.
- 1:17:37 – 1:19:40
Review of Wall Street Consensus
- BGBrad Gerstner
a look at this chart. Um, you know-
- JHJensen Huang
This is like a deposition.
- BGBrad Gerstner
No, yeah, sure. [laughs] Okay.
- JHJensen Huang
Excuse me. As m-
- BGBrad Gerstner
That's great. [laughs]
- JHJensen Huang
No, usually it goes like this. Um, Mr. Huang-
- BGBrad Gerstner
[laughs]
- JHJensen Huang
... please, please now-
- BGBrad Gerstner
Exhibit A
- JHJensen Huang
... please now look at Exhibit A.
- BGBrad Gerstner
The deposition. Okay, so the gray line, this is, was the consensus at the start of 2025. This was the consensus for NVIDIA at the start of 2025. The blue line was Altimeter's forecast way back then, so we were a lot higher than the consensus. The green line is now where the new consensus is based upon your guidance. And so one of the things that's blows my mind about this is the 25 people who get paid to just forecast what this company is going to do, their consensus of all their ideas, right, was off by a couple hundred percent, right? Just at the beginning of '20, uh-
- JHJensen Huang
Or-
- BGBrad Gerstner
Oh, no, it's- This time last year ... at this time last year, not even '25.
- JHJensen Huang
This gray line?
- BGBrad Gerstner
Yeah. Yes. That was the consensus. That wa- that was the consensus- Yeah ... at this time last year.
- JHJensen Huang
Okay, we did, we did that last week.
- BGBrad Gerstner
[laughs] Okay? So in a year, the consensus forecast has shifted up by 100 to 200% for this company.
- JHJensen Huang
Mm-hmm.
- BGBrad Gerstner
Extraordinary. Like, in, in my 20-plus years of doing this, you don't often see consensus being off by that much, and yet the stock's only up 20%. Okay? You literally doubled-
- JHJensen Huang
We, we are-
- BGBrad Gerstner
... what the revenue forecast was- [laughs] ... and the free cash flow f- forecast was for the company. You're now trading at 13 to 14 times earnings, depending upon who you're looking at. So what do you think the market is saying about NVIDIA or about the confidence in the expectations of the market, right, to cause that to be the case? Because usually if you see it shift up by that much, the stock would have shifted up by a lot more.
- JHJensen Huang
Uh, first of all, the, the, for a company to be as large as us gaining share tells you something about the resilience-
- BGBrad Gerstner
Yes
- JHJensen Huang
... and the, the, the size and scale of our advantage.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and, um-
- BGBrad Gerstner
Is that advantage increasing or decreasing?
- JHJensen Huang
Increasing.
- BGBrad Gerstner
Is your moat increasing or decreasing?
- JHJensen Huang
Increasing.
- 1:19:40 – 1:23:49
Vera Rubin Ultra Orders
- JHJensen Huang
Yeah. Let me give you an example. Let's just do a thought experiment right now.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
If you had to hand somebody a $100 billion check to-
- BGBrad Gerstner
Mm
- JHJensen Huang
... place a purchase order-
- BGBrad Gerstner
Yes
- JHJensen Huang
... right now for a next generation-
- BGBrad Gerstner
Yeah
- JHJensen Huang
... if you, if you wanna get in line Um, for Vera Rubin Ultra, it's close to placing order time.
- BGBrad Gerstner
Wow.
- JHJensen Huang
Sight unseen.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
Right?
- BGBrad Gerstner
But they have the confidence.
- JHJensen Huang
And so let's say there's a -- you gotta place $100 billion on somebody.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
One, uh, how do you know it's gonna be any good?
- BGBrad Gerstner
Right.
- JHJensen Huang
But because NVIDIA builds it, you know it's gonna be better than Vera Rubin.
- BGBrad Gerstner
Right.
- JHJensen Huang
And Vera Rubin's awesome.
- BGBrad Gerstner
Right. Right.
- JHJensen Huang
And the reason why Vera Rubin y- the reason why everybody had confidence in Vera Rubin is because Grace Blackwell was awesome.
- BGBrad Gerstner
Exactly. Yeah.
- CTClark Tang
Mm.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And so, a- and the world of computing, the, the workloads that these computers do are so complex. You can't just have, like, measure one benchmark.
- BGBrad Gerstner
Right. Right.
- JHJensen Huang
You know, it's $50 billion.
- BGBrad Gerstner
Yes.
- 1:23:49 – 1:35:57
Global Reach: Europe, Japan & Beyond
- JHJensen Huang
like your customer-- You want to serve customers in Europe. You want to serve customers in Japan. Well, it turns out we're already there.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
NVIDIA's c- NVIDIA's infrastructure's already there. So OpenAI wants to go to Europe, n- we'll take them there in a heartbeat. If they want to go to India, in a heartbeat.
- BGBrad Gerstner
Right.
- JHJensen Huang
If they want-- Isn't that right? If Anthropic wants to go to Japan, Korea, in a heartbeat. We're already there.
- BGBrad Gerstner
Right.
- CTClark Tang
Mm.
- JHJensen Huang
All of these architectures are already there. And so I think the, the... If you take NVIDIA in whole, and then you come back and you say, "Okay, I want to do the thought experiment. I want to place $100 billion on somebody."
- BGBrad Gerstner
Right.
- CTClark Tang
Mm.
- JHJensen Huang
How do you do it?
- BGBrad Gerstner
A year ago, we were sitting here, and the consensus forecast was that you were gonna be flat or shrink in 2027. Now, the consensus forecast is you're gonna grow 74%.
- JHJensen Huang
Right.
- BGBrad Gerstner
Okay? So, you know, I, I just want to let people let that sit in, because a lot of people follow these consensus forecasts, right? And it was really wrong.
- JHJensen Huang
Yeah.
- BGBrad Gerstner
Okay? It, it, they were forecasting-
- JHJensen Huang
If they go back and listen to your podcast from last time-
- BGBrad Gerstner
Right, you told them
- JHJensen Huang
... yeah, I explained everything.
- CTClark Tang
[laughs]
- JHJensen Huang
Listen, ladies and gentlemen, I did explain everything.
- BGBrad Gerstner
[laughs] And so I look-
- JHJensen Huang
No.
- BGBrad Gerstner
I look out at 2029.
- JHJensen Huang
There was a, there was a, uh... Wasn't it an ROI question?
- BGBrad Gerstner
Yes.
- JHJensen Huang
And then there was, there was this, um, uh-
- CTClark Tang
CO2 question
- JHJensen Huang
... custom.
- CTClark Tang
Yep.
- 1:35:57 – 1:39:52
The Decade Ahead: 99.99% Confident
- JHJensen Huang
just in, in, in, in, in service, in honor of, of, of a good friend not using zero and 100.
- BGBrad Gerstner
[laughs]
- JHJensen Huang
Um, I'm 99.99%, nine month p- percent confident that, that, um, uh, too many of us care too deeply that the outcome turns out well.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
That we will dedicate our might, our intellect, our resources-
- BGBrad Gerstner
Yes
- JHJensen Huang
... to ensure we get there responsibly and optimistically.
- BGBrad Gerstner
Yeah.
- JHJensen Huang
And so there's just so many people doing the right things. Now, oftentimes, you know, there, there, there's, there, there are people who pontificate about these things, and they're informed by several th- several things, and they f- and they, they don't realize that there are a lot of people, industries, incredible researchers and engineers outside of their sphere-
- BGBrad Gerstner
Mm
- JHJensen Huang
... of information that are doing amazing things all by themselves, independent of them.
- BGBrad Gerstner
Right, right.
- JHJensen Huang
Just because they didn't say-
- BGBrad Gerstner
Right
- JHJensen Huang
... they didn't say it doesn't mean a lot of smart people are doing smart things.
- BGBrad Gerstner
Right.
- JHJensen Huang
And, and, you know, I say this all the time inside the company. Even without my leadership-
- BGBrad Gerstner
Right
- JHJensen Huang
... without strategies, the company is doing smart things all by itself.
- BGBrad Gerstner
Mm.
- JHJensen Huang
Smart people do smart things.
- BGBrad Gerstner
Mm.
- JHJensen Huang
They do more impactful things when you organize a line.
- BGBrad Gerstner
Right.
- JHJensen Huang
But amazing people are doing smart things all by themselves. And so when somebody tells me that, that, you know, you're, you're worrying about us, it's good that we worry.
- BGBrad Gerstner
Right.
- JHJensen Huang
And we should express our worries. We should express our concerns, but we shouldn't predict the end of the world.
- BGBrad Gerstner
Things. Yeah.
- JHJensen Huang
Yeah. Because they're underestimating the human condition. They're underestimating the human capacity. And they think for some, some reason with... Maybe it's just hubris. Maybe it's arrogance, that unless they do it, it won't get done.
- BGBrad Gerstner
Right, right, right.
Episode duration: 1:39:52
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