Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: Gentlemen, Good morning, Hello Michael in the court of gone.
Speaker 3: One thousand new clients for AI server, for AI factory.
Speaker 2: It's a hell of a jump.
Speaker 3: What is it that those new clients fight thousand total
Speaker 3: are actually building now different to one year ago.
Speaker 2: I think that's probably a good place to start.
Speaker 4: I think the change we see is it's kind of
Speaker 4: moved from testing and evaluating into production. And we showed
Speaker 4: some great examples on stage right with Eli Lilly with
Speaker 4: one thousand gpussal world. It's Samsung, and these are not
Speaker 4: things that are on the screen, right, This is in
Speaker 4: the real world with the largest companies in the world,
Speaker 4: and so it's propagating broadly across all customers in every
Speaker 4: industry and every country. And you know, you see the
Speaker 4: proovement in all the models, and now we have the
Speaker 4: augentic capabilities, and so while it is exciting, there's been
Speaker 4: a tremendous amount of growth, I still think it's just
Speaker 4: the beginning of this wave, particularly when it comes to enterprise,
Speaker 4: which is really where you know, we have an enormous opportunity.
Speaker 3: What's so fascinating, Jensen, is you spent four years telling
Speaker 3: me that we needed to change the definition of the
Speaker 3: computer in context of accelerating computing.
Speaker 2: But the big focus was on the Hyperscali's right cloud.
Speaker 3: What I took from Michael's presentation was this is happening
Speaker 3: you said locally, but on trend. What's the nvidior interpretation
Speaker 3: of that part of this site.
Speaker 5: Intelligence has to be performed produced at the point of context,
Speaker 5: and so wherever the context is, wherever the action is,
Speaker 5: that's where you.
Speaker 1: Want to produce the intelligence.
Speaker 5: For most of the early applications of AI, it was
Speaker 5: in the cloud.
Speaker 1: A lot of consumer services are in the cloud.
Speaker 5: However, for Lily, Samsung, the future manufacturing, a lot of companies,
Speaker 5: you want the agents to be on prem because that's
Speaker 5: where all of your data is, where all your secure
Speaker 5: data is, You're proprietary data, and all of the skills
Speaker 5: associated with your company is. And so now we have
Speaker 5: agents that are here, AIS that can do work right.
Speaker 5: Chat GPT was fantastic a launched generative AI.
Speaker 2: But you just hate content. That was it.
Speaker 5: Making content is very important, but doing work is really valuable.
Speaker 5: And now we're doing productive work incredibly well, that's why
Speaker 5: they're called agentic AI in this.
Speaker 3: New era, what everyone is trying to work out is
Speaker 3: aren't all the GPUs locked up at the hyperscalers. How
Speaker 3: is Michael Dell gonna service those one thousand new clients
Speaker 3: with the GPUs to build their own on frame local
Speaker 3: AI factory.
Speaker 4: Well, the supply chain that Jensen has built, we've built together,
Speaker 4: is continuing to scale up. And while it's true that
Speaker 4: there's more demand than supply, there's more supply that's being added,
Speaker 4: and you know, customers are figuring out how they start
Speaker 4: to scale these systems up. So, you know, I think
Speaker 4: what's also happening is companies are understanding that when they
Speaker 4: reimagine their workflows using this technology, they don't get ten
Speaker 4: or twenty or thirty percent improvement. They get ten times
Speaker 4: or twenty times or one hundred times, And that is
Speaker 4: really the speed that matters to make up as a
Speaker 4: successful We're doing it ourselves, and Video is doing it,
Speaker 4: and so it's not a secret anymore that these things
Speaker 4: are possible, and every company wants to capture that speed
Speaker 4: and translate it into competitive advantage and outcomes.
Speaker 3: L was the sales channel, right Jensen. Michael's company is
Speaker 3: very good to selling technology to America's biggest companies. How
Speaker 3: is that going to change things from VideA going forward?
Speaker 3: Like the makeup of the types of companies we're talking
Speaker 3: about are at scale, but there's also that kind of
Speaker 3: middle market of data center that's being filled different kinds
Speaker 3: of in the industrial.
Speaker 2: Space in healthcare.
Speaker 3: Is that something that puts a video into new territory
Speaker 3: away from the frontier labs, away from the hyperscalers.
Speaker 5: Well, in videos a technology company, right, the hyperscalers have
Speaker 5: the ability to take our technology.
Speaker 1: And integrate them, operate them into a service.
Speaker 5: Dell has the ability to take our technology turn them
Speaker 5: into a solution that the lover's impact the customers.
Speaker 1: If you look at what.
Speaker 5: Has happened, agentic AI has completely As we were talking
Speaker 5: about earlier.
Speaker 1: Reinvent a computer, we had to do several things together.
Speaker 1: The first, of course, we have to build the brain.
Speaker 5: This is the Grace Blackwell ENDLINGK seventy two, the Barrel
Speaker 5: Ruben Mulling seventy two, giant large language models. The second
Speaker 5: part now is the VERA CPU that we're now in
Speaker 5: the process of launching. The fact the highest performance CPU
Speaker 5: in the world. It's designed for agentic AI and now
Speaker 5: this will be the harness running the agent itself using
Speaker 5: the tools.
Speaker 2: The third part, what does harness mean?
Speaker 1: What harness harness is what UH puts. A puts a.
Speaker 5: Harness around the large language model so that it can
Speaker 5: access memory, access the network, use tools.
Speaker 1: Have local scratch, bad memory, working memory, access long term memory.
Speaker 5: And so that harness basically turns, if you will, the
Speaker 5: brain into an agent, okay, into a digital robot.
Speaker 1: If you will, that could do work. And so now
Speaker 1: the agent runs on a CPU. We also worked with.
Speaker 5: Dell to create a new type of long term memory
Speaker 5: for agents called the Dell AI Data platform that's built
Speaker 5: on in video. The networking to scale it out is
Speaker 5: built on in video. So the agent, the brain, the
Speaker 5: long term memory, all of the networking necessary to scale
Speaker 5: it up, as well as the agent run time itself.
Speaker 1: We call Nemo CLAW running in a.
Speaker 5: Secure and governed container called open shelf. All of that
Speaker 5: has been put together, and now the technologies are the
Speaker 5: technology parts.
Speaker 1: What Dell has to do is turn it into a
Speaker 1: solution that people can use.
Speaker 5: Dell will do for the world's enterprises what the clouds
Speaker 5: do for the clouds makes perfect sense.
Speaker 3: What is the Dell story, Michael, around CPU and sort
Speaker 3: of like general purpose computing in the agentic era. We've
Speaker 3: talked a lot about the AI factory offering the GPU,
Speaker 3: but actually there's potential for you in more general purpose workloads.
Speaker 2: The buildouts happening either way.
Speaker 4: It is, and and the demand is exceeding to supply
Speaker 4: there as well as you know. And look as you
Speaker 4: move to these agent frameworks inside companies.
Speaker 1: You use a lot more CPUs.
Speaker 4: Yeah, and uh, you know, that's that's just the reality
Speaker 4: of what's what's happening.
Speaker 1: And I think, I think that's only gonna good increase.
Speaker 5: So instead of humans using tools, it's now agents using tools,
Speaker 5: and agents, as you were talking about earlier on stage there,
Speaker 5: we're gonna have we have a billion people, will have
Speaker 5: hundreds of billions of agents. People use tools every now
Speaker 5: and then agents are gonna use tools all the time,
Speaker 5: and agents use tools very quickly, and so we're gonna
Speaker 5: need a lot more CPUs. And those CPUs are connected
Speaker 5: to GPU brains so that the CPUs know how to think,
Speaker 5: how to reason, how to plan, and how to use
Speaker 5: those tools.
Speaker 1: So that's basically how it works.
Speaker 2: Gentlemen, What is the biggest supply constraint. What will meant
Speaker 2: for you right now?
Speaker 4: Well, certainly, you know memory is a challenge.
Speaker 2: I think it is memory.
Speaker 4: The advanced node semi conductors are still challenging.
Speaker 1: You know. It's it's really I mean, we think about
Speaker 1: it from the things that.
Speaker 4: We're producing, and the semiconductor supply chain is ramping, but
Speaker 4: the demand's growing faster than the supply.
Speaker 5: In our case, we provide the technology integrating and so
Speaker 5: the memory comes with our technology. We've been planning our
Speaker 5: supply chain for a couple of two three years. We
Speaker 5: have the largest supply chain in the world. Our partners
Speaker 5: have done a great job securing supply for us, and
Speaker 5: so all of the pieces go together. The co OSS
Speaker 5: is lined up with the HBM, which is lined up
Speaker 5: with a grace black weals, and the CPU as a
Speaker 5: co OS are the COSS L the COSS. All of
Speaker 5: it is all lined up. The silicon photonics is lined up,
Speaker 5: or everything is all lined up. It's just that the
Speaker 5: demand is much greater than the overall capacity of the world.
Speaker 3: So the overall capacity Jensen, should I put my textbook away,
Speaker 3: because if I get my textbook out, it tells me
Speaker 3: that memory historically is cyclical, it's boom and bus, and
Speaker 3: so you both kind of have to convince the memory
Speaker 3: makers of the permanency of this to build the capacity
Speaker 3: that won't sort of fool away. Is that the right
Speaker 3: way of looking at it, that this is not a
Speaker 3: boom and bus cycle, it's just a complete change in
Speaker 3: the structure of that market.
Speaker 1: Well, Michael and I do this all the time. We
Speaker 1: spent a lot of time with the supply chain.
Speaker 5: I mean, if you ask Sanjay Metro over a over
Speaker 5: a Micron, they'll tell you three years ago during a meeting,
Speaker 5: I explained the future to them exactly as it is
Speaker 5: happening right now, and I was really grateful that the
Speaker 5: Micron and video really lined up to.
Speaker 1: Line up all of our roadmap.
Speaker 5: Tony will tell you over at sk that we did
Speaker 5: the same thing years before. And so it's our job
Speaker 5: to make sure that the vision of the future the
Speaker 5: industry we convey upstream to our supply chain so that
Speaker 5: they are building for it. We also have to convey
Speaker 5: it downstream to people who have power generators and land
Speaker 5: and financing and so on and so forth, and so
Speaker 5: we have to make sure that the supply chain upstream
Speaker 5: and downstream are.
Speaker 1: Prepared for this future.
Speaker 5: It is true that the simple logic is this that
Speaker 5: we have now reached a level of agentic AI useful
Speaker 5: AI productive AI capability, and the way to think about.
Speaker 1: These agents is kind of like just digital workers.
Speaker 5: Right, we have hundreds of millions of digital workers in
Speaker 5: the world. We're going to have billions of AI agents
Speaker 5: in the world, and they're going to be working twenty
Speaker 5: four to seven. And so just as we give every
Speaker 5: digital worker a laptop and a small to the data center,
Speaker 5: we're gonna have to give every agent essentially a computer
Speaker 5: and a little bit of stories in the data center
Speaker 5: to use.
Speaker 1: Think about it this way.
Speaker 4: You know you do individual work, you know as a person,
Speaker 4: and you send it on to somebody else, and you
Speaker 4: know there's interactions.
Speaker 1: Well, now you might have hundreds or thousands.
Speaker 4: Of you know, digital agents working for ED right supervised
Speaker 4: that you supervise, and that's going to help you be
Speaker 4: way more productive, get way more things done, expand your creativity. Now,
Speaker 4: it does require a lot more computing and memory and
Speaker 4: storage and networking and all the things that we're doing together.
Speaker 3: Last one on this site, Jensen outline being the Micron
Speaker 3: and the ESK example, three years ago, you gave them
Speaker 3: the heads up.
Speaker 2: Do they believe you? Are they sort of acting.
Speaker 1: On that they're investing?
Speaker 4: I mean, it's we're managing through it. But these things
Speaker 4: are very hard to predict. Right if you tried to predict,
Speaker 4: you know, in twenty twenty three, what the demand was
Speaker 4: going to be in twenty twenty seven, you would have
Speaker 4: a hard time doing that. So it does take a
Speaker 4: long time to build these factories. But we've got great
Speaker 4: relationships with these partners we have for decades. That's helping us,
Speaker 4: and they see that we're winning and so they want
Speaker 4: to work with us even more. And it's really a
Speaker 4: great long term partnership, even though we'd like more.
Speaker 5: Right now, we're in the beginning of the AI build out.
Speaker 5: This is literally the very beginning of the agentic AI
Speaker 5: build out. We're gonna be building this out for a
Speaker 5: decade maybe more, because after this digital agents will be
Speaker 5: a physical agents.
Speaker 1: When we go to the physical AI.
Speaker 4: We haven't even started that. I mean, you saw some
Speaker 4: examples of that, you know, in the keynote, But that
Speaker 4: is a way bigger market and it will require all sorts.
Speaker 1: Of new infrastructure capabilities. We're gonna for the very first.
Speaker 5: Time bring it to the world's ninety trillion other industry,
Speaker 5: and so there's a giant industry ahead of us to
Speaker 5: build towards.
Speaker 1: Now.
Speaker 5: Meanwhile, the supply chain is more than doubling every year.
Speaker 5: I mean, it's probably quadrupling every year. But we'll still
Speaker 5: have a hard time keep up with the build out
Speaker 5: for at least a decade.
Speaker 3: My sense, China, Jensen, you just returned from China on
Speaker 3: Friday on Air Force one. The President said that H
Speaker 3: two hundred came up, but that China's position is it
Speaker 3: wants to support its own industry. Could I just ask
Speaker 3: what the net outcome was of your trip to China
Speaker 3: and your understanding of what is not or is allowed
Speaker 3: with H two hundred in the customers that you have
Speaker 3: or do not have in China.
Speaker 5: The President wants America to win everywhere, right, the President
Speaker 5: wants America to lead the AI revolution, and so H
Speaker 5: two hundreds are licensed to sell to China. The Chinese
Speaker 5: government has to decide how much of their local market
Speaker 5: do they want to protect and how much of their
Speaker 5: local market do they want to expand with more AI capacity.
Speaker 5: My sense is that the demand in China is so incredible,
Speaker 5: just like it is here.
Speaker 1: Agentic Ai is also making enormous product us there. My
Speaker 1: sense is that over time the market will open.
Speaker 5: President she was very clear that he wants China to
Speaker 5: be an even wider open market. Premier Lee Chang was
Speaker 5: very straightforward and to explain very eloquently that that China
Speaker 5: will be an open market. So I'm looking forward to
Speaker 5: China being a more.
Speaker 3: Openly clarified as you were able to meet with those
Speaker 3: officials directly to discuss whether or not you can sell
Speaker 3: to those Chinese tech companies.
Speaker 1: I did.
Speaker 5: I didn't discuss directly with him about age two hundred, right.
Speaker 5: I was there to represent the United States, and I
Speaker 5: was honored to do so. I was there to support
Speaker 5: President Trump and really glad to do so.
Speaker 1: But that was really the focus of my trip. President
Speaker 1: Trump had.
Speaker 5: Some conversations with the leaders, and I'm looking forward to
Speaker 5: to what they decide.
Speaker 3: Michael, you did not go to China, But I think
Speaker 3: what's interesting is you are a member of the President's
Speaker 3: Council Advisors for Science and Technology, as is Jensen. You'll
Speaker 3: or net conclusion on whether or not China will become
Speaker 3: open to American technology companies to do business there.
Speaker 1: You know, we have a bus in China. Obviously, we
Speaker 1: comply with all.
Speaker 4: The restrictions and you know, various controls that are in place.
Speaker 4: But I hope that there's more economic collaboration between the
Speaker 4: United States and China that ultimately as well lead to
Speaker 4: greater outcomes of prosperity for everyone and you know, a
Speaker 4: greater likelihood of you know, a successful relationship between the
Speaker 4: countries and you know, around the world.
Speaker 3: The final question on that trip, Jensen, is the sharpest
Speaker 3: rhetoric was probably on Taiwan. We've talked about the supply chain,
Speaker 3: but but what did you take from those comments from
Speaker 3: from President g On on.
Speaker 2: The issue of Taiwan.
Speaker 3: Of course, from a manufacturing capacity standpoint, TESSEMC as a
Speaker 3: critical partner. You and I have discussed it in the past,
Speaker 3: about it at this moment in time, how top of mind.
Speaker 2: Is a view the security of supply from Taiwan.
Speaker 5: We none of us were involved in any of those
Speaker 5: conversations except for President Trump.
Speaker 1: With respect to Taiwan.
Speaker 5: Obviously, Taiwan is still epicenter of the world's technology manufacturing
Speaker 5: and technology development. The supply chain is rich in Taiwan.
Speaker 5: We're also, of course reindustrializing the United States, bringing manufacturing
Speaker 5: back to the United States. We're doing so at a
Speaker 5: time when demand for AI and this beginning of this
Speaker 5: new computer revolution is happening, and so demand is extraordinary.
Speaker 5: So as a result, we're building more factories here in
Speaker 5: the United States, chip factories, packaging, computer factories, AI factories
Speaker 5: of course, so we're building factories of all kinds here.
Speaker 5: They're also ramping up capacity, and the reason for that
Speaker 5: is because the demand is just so.
Speaker 1: Great across the board.
Speaker 5: I think the answer is that we want to have
Speaker 5: it is possible to have supply chain diversity and resilience,
Speaker 5: and we everybody should be seeking to improve that. And
Speaker 5: it's also very true that Taiwan will continue to be
Speaker 5: one of the epicenters of the world's technology hub.
Speaker 2: Michael, I grew up using a del com Peter.
Speaker 3: You know that we discussed it in the past, desktop laptop.
Speaker 3: You and I never talked about computers in that context.
Speaker 2: We're always talking about supercomputers accelerating computing.
Speaker 4: But no, and I think you should Upbrade. I mean,
Speaker 4: now we have the new XPS fourteen or sixteen. That
Speaker 4: would be my choice for you.
Speaker 2: So what is the story?
Speaker 1: These are the best notebooks we've ever had.
Speaker 3: Talked about AIPC. But we're gonna get Gensen's take to finish.
Speaker 3: But what is the role of the PC in this
Speaker 3: agentic age? Like I'm using a computer at my desk
Speaker 3: to do work?
Speaker 4: Yeah, well, look, I mean it's still the device that
Speaker 4: is the center of productivity for knowledge work and it
Speaker 4: is right there in front of everyone, and you know,
Speaker 4: we have a great business there. And those devices are
Speaker 4: evolving too. You saw on stage we're you.
Speaker 1: Know, embedding the.
Speaker 4: Ability to run the small models and the local models
Speaker 4: inside your PC. And you know what's happening is customers
Speaker 4: are wanting more powerful PCs because they want to be
Speaker 4: able to do all this this this great hybrid AI.
Speaker 4: And so it's it's a it's it's a great business.
Speaker 4: It's still very much alive, and it also gives us
Speaker 4: incredible scale and strengthen our supply chain which helps us
Speaker 4: secure all the you know, needed ingredients.
Speaker 1: That we need.
Speaker 3: So you spent thirty one years working on the services
Speaker 3: design together accelerated computing.
Speaker 2: That's the scale we're talking about. Let me just be reading, Well,
Speaker 2: we started with the PC, but why don't.
Speaker 1: We just team up? I was I was trying to
Speaker 1: sell them a gaming GP.
Speaker 2: So what's going to happen between the two of you?
Speaker 3: A PC with a powerful GPU inside it?
Speaker 2: Why doesn't have that?
Speaker 1: Ye?
Speaker 2: And what's the plan going forward for that?
Speaker 1: Well, we can't tell you the plan right now.
Speaker 5: Tell me very very soon, we're like to tell you
Speaker 5: there's there's a Well, let's let's think think.
Speaker 1: About think about the arc, think about them. I'm interested
Speaker 1: in computing, no doubt. Uh, think about the arc of computing.
Speaker 5: It When when Michael and I came into the industry,
Speaker 5: it was at it was kind of at the tail
Speaker 5: end of mainframes. Not that it was a tail end
Speaker 5: of mainframes because mainframes go away. There was a tail
Speaker 5: end of of its growth and it was the beginning
Speaker 5: of personal computers.
Speaker 1: Uh.
Speaker 5: We're now seeing the beginning of of course AI in
Speaker 5: the cloud, and that's going to continue to grow. But
Speaker 5: we're also going to see personal AI instead of personal computers,
Speaker 5: my personal AI. So the question is, and the reason
Speaker 5: for that is just we were talking about earlier.
Speaker 1: AI needs to be where the context is.
Speaker 5: If all the information that I have is on my
Speaker 5: laptop and I need I need help. I need AI
Speaker 5: to help me do work on my laptop. Then I
Speaker 5: need AI to run kind of locally. And if I
Speaker 5: have UH, if I have a factory, then I need
Speaker 5: agents to run.
Speaker 1: In the factory.
Speaker 5: If I have if I have a hospital, I need
Speaker 5: agents to run the hospital.
Speaker 4: That's the operating room, in the operating It can't can't
Speaker 4: be running somewhere else.
Speaker 5: Right, because that's where the context is, That's where the
Speaker 5: action is.
Speaker 4: Yeah, if you've got an autonomous vehicle, right, THEI has
Speaker 4: to be running the car inside the vehicle. And so
Speaker 4: this idea of distributed intelligence and unmetered intelligence right where
Speaker 4: you can generate as many tokens as you want ed
Speaker 4: on your new XPS sixteen.
Speaker 1: You just have to get Blueberg to get you one.
Speaker 1: You know, I'm sure we can.
Speaker 3: Michael Dell taman Is CEO of Dell Technology is tens
Speaker 3: and one CEO and video live in Las Vegas once again.
Speaker 2: Dell Technology is Well twenty twenty six