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Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

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Speaker 2: Gentlemen, Good morning, Hello Michael in the court of gone.

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Speaker 3: One thousand new clients for AI server, for AI factory.

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Speaker 2: It's a hell of a jump.

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Speaker 3: What is it that those new clients fight thousand total

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Speaker 3: are actually building now different to one year ago.

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Speaker 2: I think that's probably a good place to start.

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Speaker 4: I think the change we see is it's kind of

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Speaker 4: moved from testing and evaluating into production. And we showed

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Speaker 4: some great examples on stage right with Eli Lilly with

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Speaker 4: one thousand gpussal world. It's Samsung, and these are not

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Speaker 4: things that are on the screen, right, This is in

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Speaker 4: the real world with the largest companies in the world,

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Speaker 4: and so it's propagating broadly across all customers in every

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Speaker 4: industry and every country. And you know, you see the

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Speaker 4: proovement in all the models, and now we have the

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Speaker 4: augentic capabilities, and so while it is exciting, there's been

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Speaker 4: a tremendous amount of growth, I still think it's just

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Speaker 4: the beginning of this wave, particularly when it comes to enterprise,

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Speaker 4: which is really where you know, we have an enormous opportunity.

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Speaker 3: What's so fascinating, Jensen, is you spent four years telling

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Speaker 3: me that we needed to change the definition of the

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Speaker 3: computer in context of accelerating computing.

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Speaker 2: But the big focus was on the Hyperscali's right cloud.

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Speaker 3: What I took from Michael's presentation was this is happening

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Speaker 3: you said locally, but on trend. What's the nvidior interpretation

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Speaker 3: of that part of this site.

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Speaker 5: Intelligence has to be performed produced at the point of context,

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Speaker 5: and so wherever the context is, wherever the action is,

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Speaker 5: that's where you.

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Speaker 1: Want to produce the intelligence.

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Speaker 5: For most of the early applications of AI, it was

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Speaker 5: in the cloud.

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Speaker 1: A lot of consumer services are in the cloud.

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Speaker 5: However, for Lily, Samsung, the future manufacturing, a lot of companies,

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Speaker 5: you want the agents to be on prem because that's

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Speaker 5: where all of your data is, where all your secure

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Speaker 5: data is, You're proprietary data, and all of the skills

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Speaker 5: associated with your company is. And so now we have

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Speaker 5: agents that are here, AIS that can do work right.

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Speaker 5: Chat GPT was fantastic a launched generative AI.

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Speaker 2: But you just hate content. That was it.

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Speaker 5: Making content is very important, but doing work is really valuable.

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Speaker 5: And now we're doing productive work incredibly well, that's why

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Speaker 5: they're called agentic AI in this.

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Speaker 3: New era, what everyone is trying to work out is

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Speaker 3: aren't all the GPUs locked up at the hyperscalers. How

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Speaker 3: is Michael Dell gonna service those one thousand new clients

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Speaker 3: with the GPUs to build their own on frame local

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Speaker 3: AI factory.

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Speaker 4: Well, the supply chain that Jensen has built, we've built together,

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Speaker 4: is continuing to scale up. And while it's true that

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Speaker 4: there's more demand than supply, there's more supply that's being added,

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Speaker 4: and you know, customers are figuring out how they start

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Speaker 4: to scale these systems up. So, you know, I think

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Speaker 4: what's also happening is companies are understanding that when they

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Speaker 4: reimagine their workflows using this technology, they don't get ten

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Speaker 4: or twenty or thirty percent improvement. They get ten times

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Speaker 4: or twenty times or one hundred times, And that is

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Speaker 4: really the speed that matters to make up as a

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Speaker 4: successful We're doing it ourselves, and Video is doing it,

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Speaker 4: and so it's not a secret anymore that these things

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Speaker 4: are possible, and every company wants to capture that speed

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Speaker 4: and translate it into competitive advantage and outcomes.

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Speaker 3: L was the sales channel, right Jensen. Michael's company is

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Speaker 3: very good to selling technology to America's biggest companies. How

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Speaker 3: is that going to change things from VideA going forward?

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Speaker 3: Like the makeup of the types of companies we're talking

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Speaker 3: about are at scale, but there's also that kind of

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Speaker 3: middle market of data center that's being filled different kinds

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Speaker 3: of in the industrial.

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Speaker 2: Space in healthcare.

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Speaker 3: Is that something that puts a video into new territory

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Speaker 3: away from the frontier labs, away from the hyperscalers.

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Speaker 5: Well, in videos a technology company, right, the hyperscalers have

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Speaker 5: the ability to take our technology.

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Speaker 1: And integrate them, operate them into a service.

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Speaker 5: Dell has the ability to take our technology turn them

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Speaker 5: into a solution that the lover's impact the customers.

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Speaker 1: If you look at what.

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Speaker 5: Has happened, agentic AI has completely As we were talking

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Speaker 5: about earlier.

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Speaker 1: Reinvent a computer, we had to do several things together.

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Speaker 1: The first, of course, we have to build the brain.

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Speaker 5: This is the Grace Blackwell ENDLINGK seventy two, the Barrel

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Speaker 5: Ruben Mulling seventy two, giant large language models. The second

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Speaker 5: part now is the VERA CPU that we're now in

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Speaker 5: the process of launching. The fact the highest performance CPU

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Speaker 5: in the world. It's designed for agentic AI and now

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Speaker 5: this will be the harness running the agent itself using

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Speaker 5: the tools.

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Speaker 2: The third part, what does harness mean?

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Speaker 1: What harness harness is what UH puts. A puts a.

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Speaker 5: Harness around the large language model so that it can

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Speaker 5: access memory, access the network, use tools.

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Speaker 1: Have local scratch, bad memory, working memory, access long term memory.

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Speaker 5: And so that harness basically turns, if you will, the

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Speaker 5: brain into an agent, okay, into a digital robot.

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Speaker 1: If you will, that could do work. And so now

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Speaker 1: the agent runs on a CPU. We also worked with.

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Speaker 5: Dell to create a new type of long term memory

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Speaker 5: for agents called the Dell AI Data platform that's built

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Speaker 5: on in video. The networking to scale it out is

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Speaker 5: built on in video. So the agent, the brain, the

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Speaker 5: long term memory, all of the networking necessary to scale

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Speaker 5: it up, as well as the agent run time itself.

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Speaker 1: We call Nemo CLAW running in a.

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Speaker 5: Secure and governed container called open shelf. All of that

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Speaker 5: has been put together, and now the technologies are the

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Speaker 5: technology parts.

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Speaker 1: What Dell has to do is turn it into a

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Speaker 1: solution that people can use.

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Speaker 5: Dell will do for the world's enterprises what the clouds

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Speaker 5: do for the clouds makes perfect sense.

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Speaker 3: What is the Dell story, Michael, around CPU and sort

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Speaker 3: of like general purpose computing in the agentic era. We've

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Speaker 3: talked a lot about the AI factory offering the GPU,

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Speaker 3: but actually there's potential for you in more general purpose workloads.

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Speaker 2: The buildouts happening either way.

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Speaker 4: It is, and and the demand is exceeding to supply

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Speaker 4: there as well as you know. And look as you

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Speaker 4: move to these agent frameworks inside companies.

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Speaker 1: You use a lot more CPUs.

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Speaker 4: Yeah, and uh, you know, that's that's just the reality

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Speaker 4: of what's what's happening.

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Speaker 1: And I think, I think that's only gonna good increase.

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Speaker 5: So instead of humans using tools, it's now agents using tools,

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Speaker 5: and agents, as you were talking about earlier on stage there,

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Speaker 5: we're gonna have we have a billion people, will have

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Speaker 5: hundreds of billions of agents. People use tools every now

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Speaker 5: and then agents are gonna use tools all the time,

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Speaker 5: and agents use tools very quickly, and so we're gonna

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Speaker 5: need a lot more CPUs. And those CPUs are connected

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Speaker 5: to GPU brains so that the CPUs know how to think,

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Speaker 5: how to reason, how to plan, and how to use

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Speaker 5: those tools.

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Speaker 1: So that's basically how it works.

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Speaker 2: Gentlemen, What is the biggest supply constraint. What will meant

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Speaker 2: for you right now?

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Speaker 4: Well, certainly, you know memory is a challenge.

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Speaker 2: I think it is memory.

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Speaker 4: The advanced node semi conductors are still challenging.

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Speaker 1: You know. It's it's really I mean, we think about

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Speaker 1: it from the things that.

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Speaker 4: We're producing, and the semiconductor supply chain is ramping, but

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Speaker 4: the demand's growing faster than the supply.

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Speaker 5: In our case, we provide the technology integrating and so

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Speaker 5: the memory comes with our technology. We've been planning our

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Speaker 5: supply chain for a couple of two three years. We

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Speaker 5: have the largest supply chain in the world. Our partners

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Speaker 5: have done a great job securing supply for us, and

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Speaker 5: so all of the pieces go together. The co OSS

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Speaker 5: is lined up with the HBM, which is lined up

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Speaker 5: with a grace black weals, and the CPU as a

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Speaker 5: co OS are the COSS L the COSS. All of

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Speaker 5: it is all lined up. The silicon photonics is lined up,

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Speaker 5: or everything is all lined up. It's just that the

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Speaker 5: demand is much greater than the overall capacity of the world.

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Speaker 3: So the overall capacity Jensen, should I put my textbook away,

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Speaker 3: because if I get my textbook out, it tells me

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Speaker 3: that memory historically is cyclical, it's boom and bus, and

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Speaker 3: so you both kind of have to convince the memory

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Speaker 3: makers of the permanency of this to build the capacity

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Speaker 3: that won't sort of fool away. Is that the right

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Speaker 3: way of looking at it, that this is not a

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Speaker 3: boom and bus cycle, it's just a complete change in

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Speaker 3: the structure of that market.

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Speaker 1: Well, Michael and I do this all the time. We

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Speaker 1: spent a lot of time with the supply chain.

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Speaker 5: I mean, if you ask Sanjay Metro over a over

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Speaker 5: a Micron, they'll tell you three years ago during a meeting,

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Speaker 5: I explained the future to them exactly as it is

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Speaker 5: happening right now, and I was really grateful that the

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Speaker 5: Micron and video really lined up to.

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Speaker 1: Line up all of our roadmap.

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Speaker 5: Tony will tell you over at sk that we did

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Speaker 5: the same thing years before. And so it's our job

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Speaker 5: to make sure that the vision of the future the

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Speaker 5: industry we convey upstream to our supply chain so that

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Speaker 5: they are building for it. We also have to convey

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Speaker 5: it downstream to people who have power generators and land

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Speaker 5: and financing and so on and so forth, and so

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Speaker 5: we have to make sure that the supply chain upstream

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Speaker 5: and downstream are.

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Speaker 1: Prepared for this future.

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Speaker 5: It is true that the simple logic is this that

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Speaker 5: we have now reached a level of agentic AI useful

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Speaker 5: AI productive AI capability, and the way to think about.

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Speaker 1: These agents is kind of like just digital workers.

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Speaker 5: Right, we have hundreds of millions of digital workers in

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Speaker 5: the world. We're going to have billions of AI agents

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Speaker 5: in the world, and they're going to be working twenty

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Speaker 5: four to seven. And so just as we give every

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Speaker 5: digital worker a laptop and a small to the data center,

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Speaker 5: we're gonna have to give every agent essentially a computer

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Speaker 5: and a little bit of stories in the data center

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Speaker 5: to use.

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Speaker 1: Think about it this way.

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Speaker 4: You know you do individual work, you know as a person,

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Speaker 4: and you send it on to somebody else, and you

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Speaker 4: know there's interactions.

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Speaker 1: Well, now you might have hundreds or thousands.

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Speaker 4: Of you know, digital agents working for ED right supervised

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Speaker 4: that you supervise, and that's going to help you be

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Speaker 4: way more productive, get way more things done, expand your creativity. Now,

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Speaker 4: it does require a lot more computing and memory and

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Speaker 4: storage and networking and all the things that we're doing together.

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Speaker 3: Last one on this site, Jensen outline being the Micron

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Speaker 3: and the ESK example, three years ago, you gave them

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Speaker 3: the heads up.

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Speaker 2: Do they believe you? Are they sort of acting.

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Speaker 1: On that they're investing?

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Speaker 4: I mean, it's we're managing through it. But these things

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Speaker 4: are very hard to predict. Right if you tried to predict,

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Speaker 4: you know, in twenty twenty three, what the demand was

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Speaker 4: going to be in twenty twenty seven, you would have

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Speaker 4: a hard time doing that. So it does take a

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Speaker 4: long time to build these factories. But we've got great

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Speaker 4: relationships with these partners we have for decades. That's helping us,

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Speaker 4: and they see that we're winning and so they want

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Speaker 4: to work with us even more. And it's really a

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Speaker 4: great long term partnership, even though we'd like more.

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Speaker 5: Right now, we're in the beginning of the AI build out.

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Speaker 5: This is literally the very beginning of the agentic AI

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Speaker 5: build out. We're gonna be building this out for a

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Speaker 5: decade maybe more, because after this digital agents will be

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Speaker 5: a physical agents.

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Speaker 1: When we go to the physical AI.

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Speaker 4: We haven't even started that. I mean, you saw some

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Speaker 4: examples of that, you know, in the keynote, But that

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Speaker 4: is a way bigger market and it will require all sorts.

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Speaker 1: Of new infrastructure capabilities. We're gonna for the very first.

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Speaker 5: Time bring it to the world's ninety trillion other industry,

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Speaker 5: and so there's a giant industry ahead of us to

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Speaker 5: build towards.

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Speaker 1: Now.

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Speaker 5: Meanwhile, the supply chain is more than doubling every year.

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Speaker 5: I mean, it's probably quadrupling every year. But we'll still

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Speaker 5: have a hard time keep up with the build out

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Speaker 5: for at least a decade.

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Speaker 3: My sense, China, Jensen, you just returned from China on

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Speaker 3: Friday on Air Force one. The President said that H

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Speaker 3: two hundred came up, but that China's position is it

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Speaker 3: wants to support its own industry. Could I just ask

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Speaker 3: what the net outcome was of your trip to China

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Speaker 3: and your understanding of what is not or is allowed

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Speaker 3: with H two hundred in the customers that you have

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Speaker 3: or do not have in China.

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Speaker 5: The President wants America to win everywhere, right, the President

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Speaker 5: wants America to lead the AI revolution, and so H

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Speaker 5: two hundreds are licensed to sell to China. The Chinese

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Speaker 5: government has to decide how much of their local market

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Speaker 5: do they want to protect and how much of their

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Speaker 5: local market do they want to expand with more AI capacity.

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Speaker 5: My sense is that the demand in China is so incredible,

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Speaker 5: just like it is here.

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Speaker 1: Agentic Ai is also making enormous product us there. My

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Speaker 1: sense is that over time the market will open.

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Speaker 5: President she was very clear that he wants China to

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Speaker 5: be an even wider open market. Premier Lee Chang was

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Speaker 5: very straightforward and to explain very eloquently that that China

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Speaker 5: will be an open market. So I'm looking forward to

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Speaker 5: China being a more.

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Speaker 3: Openly clarified as you were able to meet with those

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Speaker 3: officials directly to discuss whether or not you can sell

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Speaker 3: to those Chinese tech companies.

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Speaker 1: I did.

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Speaker 5: I didn't discuss directly with him about age two hundred, right.

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Speaker 5: I was there to represent the United States, and I

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Speaker 5: was honored to do so. I was there to support

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Speaker 5: President Trump and really glad to do so.

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Speaker 1: But that was really the focus of my trip. President

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Speaker 1: Trump had.

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Speaker 5: Some conversations with the leaders, and I'm looking forward to

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Speaker 5: to what they decide.

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Speaker 3: Michael, you did not go to China, But I think

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Speaker 3: what's interesting is you are a member of the President's

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Speaker 3: Council Advisors for Science and Technology, as is Jensen. You'll

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Speaker 3: or net conclusion on whether or not China will become

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Speaker 3: open to American technology companies to do business there.

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Speaker 1: You know, we have a bus in China. Obviously, we

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Speaker 1: comply with all.

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Speaker 4: The restrictions and you know, various controls that are in place.

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Speaker 4: But I hope that there's more economic collaboration between the

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Speaker 4: United States and China that ultimately as well lead to

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Speaker 4: greater outcomes of prosperity for everyone and you know, a

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Speaker 4: greater likelihood of you know, a successful relationship between the

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Speaker 4: countries and you know, around the world.

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Speaker 3: The final question on that trip, Jensen, is the sharpest

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Speaker 3: rhetoric was probably on Taiwan. We've talked about the supply chain,

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Speaker 3: but but what did you take from those comments from

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Speaker 3: from President g On on.

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Speaker 2: The issue of Taiwan.

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Speaker 3: Of course, from a manufacturing capacity standpoint, TESSEMC as a

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Speaker 3: critical partner. You and I have discussed it in the past,

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Speaker 3: about it at this moment in time, how top of mind.

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Speaker 2: Is a view the security of supply from Taiwan.

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Speaker 5: We none of us were involved in any of those

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Speaker 5: conversations except for President Trump.

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Speaker 1: With respect to Taiwan.

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Speaker 5: Obviously, Taiwan is still epicenter of the world's technology manufacturing

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Speaker 5: and technology development. The supply chain is rich in Taiwan.

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Speaker 5: We're also, of course reindustrializing the United States, bringing manufacturing

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Speaker 5: back to the United States. We're doing so at a

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Speaker 5: time when demand for AI and this beginning of this

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Speaker 5: new computer revolution is happening, and so demand is extraordinary.

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Speaker 5: So as a result, we're building more factories here in

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Speaker 5: the United States, chip factories, packaging, computer factories, AI factories

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Speaker 5: of course, so we're building factories of all kinds here.

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Speaker 5: They're also ramping up capacity, and the reason for that

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Speaker 5: is because the demand is just so.

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Speaker 1: Great across the board.

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Speaker 5: I think the answer is that we want to have

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Speaker 5: it is possible to have supply chain diversity and resilience,

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Speaker 5: and we everybody should be seeking to improve that. And

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Speaker 5: it's also very true that Taiwan will continue to be

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Speaker 5: one of the epicenters of the world's technology hub.

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Speaker 2: Michael, I grew up using a del com Peter.

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Speaker 3: You know that we discussed it in the past, desktop laptop.

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Speaker 3: You and I never talked about computers in that context.

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Speaker 2: We're always talking about supercomputers accelerating computing.

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Speaker 4: But no, and I think you should Upbrade. I mean,

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Speaker 4: now we have the new XPS fourteen or sixteen. That

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Speaker 4: would be my choice for you.

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Speaker 2: So what is the story?

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Speaker 1: These are the best notebooks we've ever had.

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Speaker 3: Talked about AIPC. But we're gonna get Gensen's take to finish.

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Speaker 3: But what is the role of the PC in this

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Speaker 3: agentic age? Like I'm using a computer at my desk

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Speaker 3: to do work?

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Speaker 4: Yeah, well, look, I mean it's still the device that

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Speaker 4: is the center of productivity for knowledge work and it

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Speaker 4: is right there in front of everyone, and you know,

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Speaker 4: we have a great business there. And those devices are

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Speaker 4: evolving too. You saw on stage we're you.

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Speaker 1: Know, embedding the.

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Speaker 4: Ability to run the small models and the local models

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Speaker 4: inside your PC. And you know what's happening is customers

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Speaker 4: are wanting more powerful PCs because they want to be

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Speaker 4: able to do all this this this great hybrid AI.

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Speaker 4: And so it's it's a it's it's a great business.

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Speaker 4: It's still very much alive, and it also gives us

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Speaker 4: incredible scale and strengthen our supply chain which helps us

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Speaker 4: secure all the you know, needed ingredients.

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Speaker 1: That we need.

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Speaker 3: So you spent thirty one years working on the services

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Speaker 3: design together accelerated computing.

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Speaker 2: That's the scale we're talking about. Let me just be reading, Well,

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Speaker 2: we started with the PC, but why don't.

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Speaker 1: We just team up? I was I was trying to

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Speaker 1: sell them a gaming GP.

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Speaker 2: So what's going to happen between the two of you?

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Speaker 3: A PC with a powerful GPU inside it?

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Speaker 2: Why doesn't have that?

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Speaker 1: Ye?

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Speaker 2: And what's the plan going forward for that?

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Speaker 1: Well, we can't tell you the plan right now.

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Speaker 5: Tell me very very soon, we're like to tell you

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Speaker 5: there's there's a Well, let's let's think think.

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Speaker 1: About think about the arc, think about them. I'm interested

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Speaker 1: in computing, no doubt. Uh, think about the arc of computing.

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Speaker 5: It When when Michael and I came into the industry,

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Speaker 5: it was at it was kind of at the tail

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Speaker 5: end of mainframes. Not that it was a tail end

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Speaker 5: of mainframes because mainframes go away. There was a tail

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Speaker 5: end of of its growth and it was the beginning

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Speaker 5: of personal computers.

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Speaker 1: Uh.

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Speaker 5: We're now seeing the beginning of of course AI in

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Speaker 5: the cloud, and that's going to continue to grow. But

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Speaker 5: we're also going to see personal AI instead of personal computers,

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Speaker 5: my personal AI. So the question is, and the reason

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Speaker 5: for that is just we were talking about earlier.

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Speaker 1: AI needs to be where the context is.

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Speaker 5: If all the information that I have is on my

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Speaker 5: laptop and I need I need help. I need AI

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Speaker 5: to help me do work on my laptop. Then I

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Speaker 5: need AI to run kind of locally. And if I

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Speaker 5: have UH, if I have a factory, then I need

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Speaker 5: agents to run.

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Speaker 1: In the factory.

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Speaker 5: If I have if I have a hospital, I need

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Speaker 5: agents to run the hospital.

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Speaker 4: That's the operating room, in the operating It can't can't

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Speaker 4: be running somewhere else.

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Speaker 5: Right, because that's where the context is, That's where the

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Speaker 5: action is.

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Speaker 4: Yeah, if you've got an autonomous vehicle, right, THEI has

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Speaker 4: to be running the car inside the vehicle. And so

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Speaker 4: this idea of distributed intelligence and unmetered intelligence right where

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Speaker 4: you can generate as many tokens as you want ed

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Speaker 4: on your new XPS sixteen.

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Speaker 1: You just have to get Blueberg to get you one.

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Speaker 1: You know, I'm sure we can.

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Speaker 3: Michael Dell taman Is CEO of Dell Technology is tens

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Speaker 3: and one CEO and video live in Las Vegas once again.

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Speaker 2: Dell Technology is Well twenty twenty six