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Gentlemen, Good morning, Hello Michael in the court of gone.
One thousand new clients for AI server, for AI factory.
It's a hell of a jump.
What is it that those new clients fight thousand total are actually building now different to one year ago.
I think that's probably a good place to start.
I think the change we see is it's kind of moved from testing and evaluating into production. And we showed some great examples on stage right with Eli Lilly with one thousand gpussal world. It's Samsung, and these are not things that are on the screen, right, This is in the real world with the largest companies in the world, and so it's propagating broadly across all customers in every
industry and every country. And you know, you see the proovement in all the models, and now we have the augentic capabilities, and so while it is exciting, there's been a tremendous amount of growth, I still think it's just the beginning of this wave, particularly when it comes to enterprise, which is really where you know, we have an enormous opportunity.
What's so fascinating, Jensen, is you spent four years telling me that we needed to change the definition of the computer in context of accelerating computing.
But the big focus was on the Hyperscali's right cloud.
What I took from Michael's presentation was this is happening you said locally, but on trend. What's the nvidior interpretation of that part of this site.
Intelligence has to be performed produced at the point of context, and so wherever the context is, wherever the action is, that's where you.
Want to produce the intelligence.
For most of the early applications of AI, it was in the cloud.
A lot of consumer services are in the cloud.
However, for Lily, Samsung, the future manufacturing, a lot of companies, you want the agents to be on prem because that's where all of your data is, where all your secure data is, You're proprietary data, and all of the skills associated with your company is. And so now we have agents that are here, AIS that can do work right. Chat GPT was fantastic a launched generative AI.
But you just hate content. That was it.
Making content is very important, but doing work is really valuable. And now we're doing productive work incredibly well, that's why they're called agentic AI in this.
New era, what everyone is trying to work out is aren't all the GPUs locked up at the hyperscalers. How is Michael Dell gonna service those one thousand new clients with the GPUs to build their own on frame local AI factory.
Well, the supply chain that Jensen has built, we've built together, is continuing to scale up. And while it's true that there's more demand than supply, there's more supply that's being added, and you know, customers are figuring out how they start to scale these systems up. So, you know, I think what's also happening is companies are understanding that when they reimagine their workflows using this technology, they don't get ten
or twenty or thirty percent improvement. They get ten times or twenty times or one hundred times, And that is really the speed that matters to make up as a successful We're doing it ourselves, and Video is doing it, and so it's not a secret anymore that these things are possible, and every company wants to capture that speed and translate it into competitive advantage and outcomes.
L was the sales channel, right Jensen. Michael's company is very good to selling technology to America's biggest companies. How is that going to change things from VideA going forward? Like the makeup of the types of companies we're talking about are at scale, but there's also that kind of middle market of data center that's being filled different kinds of in the industrial.
Space in healthcare.
Is that something that puts a video into new territory away from the frontier labs, away from the hyperscalers.
Well, in videos a technology company, right, the hyperscalers have the ability to take our technology.
And integrate them, operate them into a service.
Dell has the ability to take our technology turn them into a solution that the lover's impact the customers.
If you look at what.
Has happened, agentic AI has completely As we were talking about earlier.
Reinvent a computer, we had to do several things together. The first, of course, we have to build the brain.
This is the Grace Blackwell ENDLINGK seventy two, the Barrel Ruben Mulling seventy two, giant large language models. The second part now is the VERA CPU that we're now in the process of launching. The fact the highest performance CPU in the world. It's designed for agentic AI and now this will be the harness running the agent itself using the tools.
The third part, what does harness mean?
What harness harness is what UH puts. A puts a.
Harness around the large language model so that it can access memory, access the network, use tools.
Have local scratch, bad memory, working memory, access long term memory.
And so that harness basically turns, if you will, the brain into an agent, okay, into a digital robot.
If you will, that could do work. And so now the agent runs on a CPU. We also worked with.
Dell to create a new type of long term memory for agents called the Dell AI Data platform that's built on in video. The networking to scale it out is built on in video. So the agent, the brain, the long term memory, all of the networking necessary to scale it up, as well as the agent run time itself.
We call Nemo CLAW running in a.
Secure and governed container called open shelf. All of that has been put together, and now the technologies are the technology parts.
What Dell has to do is turn it into a solution that people can use.
Dell will do for the world's enterprises what the clouds do for the clouds makes perfect sense.
What is the Dell story, Michael, around CPU and sort of like general purpose computing in the agentic era. We've talked a lot about the AI factory offering the GPU, but actually there's potential for you in more general purpose workloads.
The buildouts happening either way.
It is, and and the demand is exceeding to supply there as well as you know. And look as you move to these agent frameworks inside companies.
You use a lot more CPUs.
Yeah, and uh, you know, that's that's just the reality of what's what's happening.
And I think, I think that's only gonna good increase.
So instead of humans using tools, it's now agents using tools, and agents, as you were talking about earlier on stage there, we're gonna have we have a billion people, will have hundreds of billions of agents. People use tools every now and then agents are gonna use tools all the time, and agents use tools very quickly, and so we're gonna need a lot more CPUs. And those CPUs are connected to GPU brains so that the CPUs know how to think, how to reason, how to plan, and how to use those tools.
So that's basically how it works.
Gentlemen, What is the biggest supply constraint. What will meant for you right now?
Well, certainly, you know memory is a challenge.
I think it is memory.
The advanced node semi conductors are still challenging.
You know. It's it's really I mean, we think about it from the things that.
We're producing, and the semiconductor supply chain is ramping, but the demand's growing faster than the supply.
In our case, we provide the technology integrating and so the memory comes with our technology. We've been planning our supply chain for a couple of two three years. We have the largest supply chain in the world. Our partners have done a great job securing supply for us, and so all of the pieces go together. The co OSS is lined up with the HBM, which is lined up with a grace black weals, and the CPU as a co OS are the COSS L the COSS. All of it is all lined up. The silicon photonics is lined up,
or everything is all lined up. It's just that the demand is much greater than the overall capacity of the world.
So the overall capacity Jensen, should I put my textbook away, because if I get my textbook out, it tells me that memory historically is cyclical, it's boom and bus, and so you both kind of have to convince the memory makers of the permanency of this to build the capacity that won't sort of fool away. Is that the right way of looking at it, that this is not a boom and bus cycle, it's just a complete change in the structure of that market.
Well, Michael and I do this all the time. We spent a lot of time with the supply chain.
I mean, if you ask Sanjay Metro over a over a Micron, they'll tell you three years ago during a meeting, I explained the future to them exactly as it is happening right now, and I was really grateful that the Micron and video really lined up to.
Line up all of our roadmap.
Tony will tell you over at sk that we did the same thing years before. And so it's our job to make sure that the vision of the future the industry we convey upstream to our supply chain so that they are building for it. We also have to convey it downstream to people who have power generators and land and financing and so on and so forth, and so we have to make sure that the supply chain upstream and downstream are.
Prepared for this future.
It is true that the simple logic is this that we have now reached a level of agentic AI useful AI productive AI capability, and the way to think about.
These agents is kind of like just digital workers.
Right, we have hundreds of millions of digital workers in the world. We're going to have billions of AI agents in the world, and they're going to be working twenty four to seven. And so just as we give every digital worker a laptop and a small to the data center, we're gonna have to give every agent essentially a computer and a little bit of stories in the data center to use.
Think about it this way.
You know you do individual work, you know as a person, and you send it on to somebody else, and you know there's interactions.
Well, now you might have hundreds or thousands.
Of you know, digital agents working for ED right supervised that you supervise, and that's going to help you be way more productive, get way more things done, expand your creativity. Now, it does require a lot more computing and memory and storage and networking and all the things that we're doing together.
Last one on this site, Jensen outline being the Micron and the ESK example, three years ago, you gave them the heads up.
Do they believe you? Are they sort of acting.
On that they're investing?
I mean, it's we're managing through it. But these things are very hard to predict. Right if you tried to predict, you know, in twenty twenty three, what the demand was going to be in twenty twenty seven, you would have a hard time doing that. So it does take a long time to build these factories. But we've got great relationships with these partners we have for decades. That's helping us, and they see that we're winning and so they want
to work with us even more. And it's really a great long term partnership, even though we'd like more.
Right now, we're in the beginning of the AI build out. This is literally the very beginning of the agentic AI build out. We're gonna be building this out for a decade maybe more, because after this digital agents will be a physical agents.
When we go to the physical AI.
We haven't even started that. I mean, you saw some examples of that, you know, in the keynote, But that is a way bigger market and it will require all sorts.
Of new infrastructure capabilities. We're gonna for the very first.
Time bring it to the world's ninety trillion other industry, and so there's a giant industry ahead of us to build towards.
Now.
Meanwhile, the supply chain is more than doubling every year. I mean, it's probably quadrupling every year. But we'll still have a hard time keep up with the build out for at least a decade.
My sense, China, Jensen, you just returned from China on Friday on Air Force one. The President said that H two hundred came up, but that China's position is it wants to support its own industry. Could I just ask what the net outcome was of your trip to China and your understanding of what is not or is allowed with H two hundred in the customers that you have or do not have in China.
The President wants America to win everywhere, right, the President wants America to lead the AI revolution, and so H two hundreds are licensed to sell to China. The Chinese government has to decide how much of their local market do they want to protect and how much of their local market do they want to expand with more AI capacity. My sense is that the demand in China is so incredible, just like it is here.
Agentic Ai is also making enormous product us there. My sense is that over time the market will open.
President she was very clear that he wants China to be an even wider open market. Premier Lee Chang was very straightforward and to explain very eloquently that that China will be an open market. So I'm looking forward to China being a more.
Openly clarified as you were able to meet with those officials directly to discuss whether or not you can sell to those Chinese tech companies.
I did.
I didn't discuss directly with him about age two hundred, right. I was there to represent the United States, and I was honored to do so. I was there to support President Trump and really glad to do so.
But that was really the focus of my trip. President Trump had.
Some conversations with the leaders, and I'm looking forward to to what they decide.
Michael, you did not go to China, But I think what's interesting is you are a member of the President's Council Advisors for Science and Technology, as is Jensen. You'll or net conclusion on whether or not China will become open to American technology companies to do business there.
You know, we have a bus in China. Obviously, we comply with all.
The restrictions and you know, various controls that are in place. But I hope that there's more economic collaboration between the United States and China that ultimately as well lead to greater outcomes of prosperity for everyone and you know, a greater likelihood of you know, a successful relationship between the countries and you know, around the world.
The final question on that trip, Jensen, is the sharpest rhetoric was probably on Taiwan. We've talked about the supply chain, but but what did you take from those comments from from President g On on.
The issue of Taiwan.
Of course, from a manufacturing capacity standpoint, TESSEMC as a critical partner. You and I have discussed it in the past, about it at this moment in time, how top of mind.
Is a view the security of supply from Taiwan.
We none of us were involved in any of those conversations except for President Trump.
With respect to Taiwan.
Obviously, Taiwan is still epicenter of the world's technology manufacturing and technology development. The supply chain is rich in Taiwan. We're also, of course reindustrializing the United States, bringing manufacturing back to the United States. We're doing so at a time when demand for AI and this beginning of this new computer revolution is happening, and so demand is extraordinary.
So as a result, we're building more factories here in the United States, chip factories, packaging, computer factories, AI factories of course, so we're building factories of all kinds here. They're also ramping up capacity, and the reason for that is because the demand is just so.
Great across the board.
I think the answer is that we want to have it is possible to have supply chain diversity and resilience, and we everybody should be seeking to improve that. And it's also very true that Taiwan will continue to be one of the epicenters of the world's technology hub.
Michael, I grew up using a del com Peter.
You know that we discussed it in the past, desktop laptop. You and I never talked about computers in that context.
We're always talking about supercomputers accelerating computing.
But no, and I think you should Upbrade. I mean, now we have the new XPS fourteen or sixteen. That would be my choice for you.
So what is the story?
These are the best notebooks we've ever had.
Talked about AIPC. But we're gonna get Gensen's take to finish. But what is the role of the PC in this agentic age? Like I'm using a computer at my desk to do work?
Yeah, well, look, I mean it's still the device that is the center of productivity for knowledge work and it is right there in front of everyone, and you know, we have a great business there. And those devices are evolving too. You saw on stage we're you.
Know, embedding the.
Ability to run the small models and the local models inside your PC. And you know what's happening is customers are wanting more powerful PCs because they want to be able to do all this this this great hybrid AI. And so it's it's a it's it's a great business. It's still very much alive, and it also gives us incredible scale and strengthen our supply chain which helps us secure all the you know, needed ingredients.
That we need.
So you spent thirty one years working on the services design together accelerated computing.
That's the scale we're talking about. Let me just be reading, Well, we started with the PC, but why don't.
We just team up? I was I was trying to sell them a gaming GP.
So what's going to happen between the two of you?
A PC with a powerful GPU inside it?
Why doesn't have that?
Ye?
And what's the plan going forward for that?
Well, we can't tell you the plan right now.
Tell me very very soon, we're like to tell you there's there's a Well, let's let's think think.
About think about the arc, think about them. I'm interested in computing, no doubt. Uh, think about the arc of computing.
It When when Michael and I came into the industry, it was at it was kind of at the tail end of mainframes. Not that it was a tail end of mainframes because mainframes go away. There was a tail end of of its growth and it was the beginning of personal computers.
Uh.
We're now seeing the beginning of of course AI in the cloud, and that's going to continue to grow. But we're also going to see personal AI instead of personal computers, my personal AI. So the question is, and the reason for that is just we were talking about earlier.
AI needs to be where the context is.
If all the information that I have is on my laptop and I need I need help. I need AI to help me do work on my laptop. Then I need AI to run kind of locally. And if I have UH, if I have a factory, then I need agents to run.
In the factory.
If I have if I have a hospital, I need agents to run the hospital.
That's the operating room, in the operating It can't can't be running somewhere else.
Right, because that's where the context is, That's where the action is.
Yeah, if you've got an autonomous vehicle, right, THEI has to be running the car inside the vehicle. And so this idea of distributed intelligence and unmetered intelligence right where you can generate as many tokens as you want ed on your new XPS sixteen.
You just have to get Blueberg to get you one. You know, I'm sure we can.
Michael Dell taman Is CEO of Dell Technology is tens and one CEO and video live in Las Vegas once again.
Dell Technology is Well twenty twenty six