Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2: We'd like to welcome in video CEO Jensen Wang to
Speaker 2: the program, and Jensen, it's been an astonishingly busy day
Speaker 2: for you in Washington, DC. So I'm grateful for your time.
Speaker 2: You're sold out of Blackwell, that's what you said, but
Speaker 2: also that five hundred billion dollar forecast, which is Blackwell
Speaker 2: Rubin has room to grow. How do those fit together?
Speaker 1: I said, sales are after charts for Blackwell and in
Speaker 1: video GPUs in the cloud are sold out. We got
Speaker 1: plenty of Blackwells to sell you. We have lots of
Speaker 1: Blackwells coming, We're making a lot of Blackwells, and we
Speaker 1: have a bunch of Vera Rubens coming and so business
Speaker 1: is very very strong. But we we've planned our supply
Speaker 1: chain incredibly well. We have the largest supply chain in
Speaker 1: the world. Our partners TSMC, our memory partners, s k Heinex, Micron,
Speaker 1: Samsung are doing a fantastic job supporting us. And all
Speaker 1: of our systems partners, fox Con and Quantum and Wistron
Speaker 1: are packaging partners. Everybody's doing a fantastic job supporting us.
Speaker 1: And we've done a good job planning for a very
Speaker 1: very strong year, and we've done a good job planning
Speaker 1: for Vera Rubin, so sales are off the charts and
Speaker 1: video GPUs and the cloud is sold out, but we've
Speaker 1: got a bunch of Blackwells to sell.
Speaker 2: Jensen, what's the road ahead for Vera Rubin. It's one
Speaker 2: of the most common questions we get for you of
Speaker 2: how that ramp will go relative to what we saw
Speaker 2: with the Blackwell generations.
Speaker 1: Well, the silicon for Vera Rubin, seven different chips are
Speaker 1: back in our labs and the bring up is happening
Speaker 1: across engineering teams. Probably a couple of twenty thousand people
Speaker 1: are working on bringing up Vera Rubin. From silicon to systems,
Speaker 1: to software to algorithms. People are working around the clock
Speaker 1: and this bring up is going beautifully. We're on track
Speaker 1: to deliver Vera Rubin about Q three timeframe of next year,
Speaker 1: continuing our once a year cycle. Vera Ruben is already
Speaker 1: assured a huge success. Everybody's incredibly excited about it. Can't
Speaker 1: wait to show everybody. And then one last thing is
Speaker 1: that the Rack architecture, the Rack scale architecture, is completely revolutionary.
Speaker 1: It includes a scale up switch called the mvy link
Speaker 1: mvy Link seventy two. Our fifth generation is the only
Speaker 1: one of its kind in the world. This rack architecture,
Speaker 1: which is incredibly complex, started with Grace Blackwell, then Grace
Speaker 1: Blackwell Ultra. It is transitioned to Grace Blackwell Ultra is
Speaker 1: incredibly seamless. The same rascale architecture is going to be
Speaker 1: used for Vera Rubin, and so the supply chains are
Speaker 1: used to it this complexity that we enjoyed with Grace
Speaker 1: Blackwell transition. We're now incredibly smooth running and so I
Speaker 1: think Vera Rubin is going to be just really smooth
Speaker 1: and we're gonna rt it really hard.
Speaker 2: Jensen. I tried to go through what the CFO Collect
Speaker 2: Crest said about China in the quarter gone It seemed
Speaker 2: like there was not meaning for h twenty sales because
Speaker 2: the demand wasn't there even if you were permitted to
Speaker 2: sell each twenty. And then in the current period and
Speaker 2: going forward in video seems committed to working with both
Speaker 2: the United States and China to sell what Collect called
Speaker 2: more competitive compute. Where do we stand with that and
Speaker 2: could you just clarify what Collect was talking about in
Speaker 2: the current state of play for China.
Speaker 1: The most important thing she said is that we've said
Speaker 1: for some time now our forecast for China is zero.
Speaker 1: All of our forecast guidance that we showed zero, we
Speaker 1: should start. That's the most important thing that she said.
Speaker 1: She also said that effectively, China is a very important
Speaker 1: market to us. It's very important to the United States,
Speaker 1: it's very important to China. We would love the opportunity
Speaker 1: to be able to re engage the Chinese market with
Speaker 1: excellent products that we deliver and to be able to
Speaker 1: compete globally. The Chinese market is very large this year.
Speaker 1: My guess is probably about fifty billion dollars. It's great
Speaker 1: for the American people that we're able to compete in
Speaker 1: the Chinese market. It's great for the China market that
Speaker 1: we're able to provide Nvidia's technology to them. It's great
Speaker 1: for the rest of the world as Chinese software companies
Speaker 1: and Chinese open source models leave China and are used
Speaker 1: all over the world. And so I think it's fantastic
Speaker 1: that we're able. It would be fantastic if we're able
Speaker 1: to participate in the China market, but for now, we
Speaker 1: should just assume our nvidious forecast for China market is zero.
Speaker 1: We're going to continue to engage the US government, continue
Speaker 1: to engage the China government to advise them and to
Speaker 1: encourage them to allow us to go back and compete
Speaker 1: in the open market. And so until then we should
Speaker 1: assume zero Jensen.
Speaker 2: During the call, the US Commerce Department issued a statement
Speaker 2: saying that you are now permitted to export up to
Speaker 2: thirty five thousand Blackwell chips each to both Saudiast humane
Speaker 2: and to the UAE through G forty two. But there
Speaker 2: are some requirements that the US has a view, in
Speaker 2: particular around controls of preventing tech transfer to China through
Speaker 2: the Middle East. What can you tell us about your
Speaker 2: understanding of what the US government's asking of you.
Speaker 1: There That that UH that that that element UH is
Speaker 1: has been around for a long time is to prevent diversion.
Speaker 1: Of course, over the years, people have speculated about diversion.
Speaker 1: We've chased down every single concern and UH we've repeatedly
Speaker 1: UH tested and sampled data centers around the world and
Speaker 1: found no diversion. And so this is a this is
Speaker 1: an area that that will continue to be rigorous on
Speaker 1: and UH there's a lot of different ways to uh, comply.
Speaker 1: And one of them, of course, is to have it
Speaker 1: be run by American Cloud. Another way is just to
Speaker 1: make sure that we have measures put in place, whether
Speaker 1: technology or processes, to ensure that no diversion happens.
Speaker 2: Jensen, the number one question I get for you is
Speaker 2: always about energy. How severe is the energy shortage in
Speaker 2: the context of AI expects and would you talk a
Speaker 2: bit about power and whether power is a bigger constraint
Speaker 2: for this buildout than the chips themselves.
Speaker 1: When you're growing at the rate and scale of Nvidia,
Speaker 1: Remember we're growing some sixty percent a year. Just quarter
Speaker 1: to quarter growth of our company is ten billion dollars.
Speaker 1: We grew an entire size of a company just in
Speaker 1: one quarter. And so the scale and the rate at
Speaker 1: which we're growing, everything's a challenge, which is the reason
Speaker 1: why Nvidia has to be world class at our supply chain,
Speaker 1: working with incredible providers and suppliers like TSMC and the
Speaker 1: memory partners and all of our systems partners, but also
Speaker 1: working downstream to work with energy providers, power generator companies,
Speaker 1: all of the land power and shell providers, so that
Speaker 1: we could make sure that as we launch into the marketplace,
Speaker 1: as we deploy into the marketplace, land Power and Shell
Speaker 1: will be ready for us. One of our great advantages
Speaker 1: is that we have such a large network of go
Speaker 1: to market. We're in every single cloud. Every single cloud
Speaker 1: service provider is a customer of ours. We're in every
Speaker 1: single GPU cloud, and so we have a large network
Speaker 1: and not to mention OEMs, not to mention, all around
Speaker 1: the world. Our customer base, our network of partners is
Speaker 1: so large that we will find nooks and crannies of
Speaker 1: power and large scale, medium scale, small scale in different
Speaker 1: parts of the world. And so this is a huge
Speaker 1: advantage of ours, and it stems from the fact ed
Speaker 1: that Nvidia's architecture literally runs every model and today, yesterday
Speaker 1: we announced a big news with Anthropic and so now
Speaker 1: the premiere frontier models, open AI, Anthropic, XAI, Gemini, all
Speaker 1: the open sources, biological models, physical AI models, everything in
Speaker 1: the world runs on Nvidia. And as a result of that,
Speaker 1: irrespective of which cloud provider you are, it is fantastic
Speaker 1: that we can deploy in your cloud because the off
Speaker 1: take will be incredible.
Speaker 2: Jensen. We can see where the hyperscalers are getting the money,
Speaker 2: where they have the money to deploy and build. But
Speaker 2: you mentioned anthropic. With Anthropic or indeed open ai, they
Speaker 2: have tens of billions of dollars of commitments around the world.
Speaker 2: Very simple like, how do you know the open ai
Speaker 2: is good for it that it will be able to
Speaker 2: find the money.
Speaker 1: Well, we're thoughtful along with open ai, thoughtful in aligning
Speaker 1: on and taking into consideration visibility of demand and their
Speaker 1: financing capabilities. All of that has to be in accordance,
Speaker 1: has to be aligned, has to be coherent before we
Speaker 1: start to build out. And so I think the ambitions large,
Speaker 1: but the execution is disciplined, and that's really really important
Speaker 1: to recognize. We're very disciplined with our investment. We're disciplined
Speaker 1: with our buildout. These are very large scale investments, and
Speaker 1: so the two teams are quite disciplined, very disciplined in
Speaker 1: thinking through the investment levels. Now, it's also important to
Speaker 1: take a step back and realize that open Ai, Anthropic,
Speaker 1: these are the fastest growing company in the history of humanity.
Speaker 1: They're off take their end market demand is absolutely real
Speaker 1: and absolutely incredible, and you could see that they're really
Speaker 1: struggling to keep up with the demand that they have.
Speaker 1: The engineering teams. We work incredibly hard to make sure
Speaker 1: that we bring them on more capacity, but also optimizing
Speaker 1: their stack so that the usage of whatever capacity is
Speaker 1: as sufficient as possible. And meanwhile, there's so many new
Speaker 1: use cases that they want to put back put out
Speaker 1: into the world, and it's currently limited by the capacity
Speaker 1: they have, and so this is a really important time.
Speaker 1: You're seeing an exponential growth in the amount of compute
Speaker 1: demand necessary for AI, You're seeing an exponential growth of
Speaker 1: adoption and use of AI, and the number of applications
Speaker 1: that are going to be using these AI is also growing.
Speaker 1: And so we've got to do our best to support
Speaker 1: the scaling out of two of the most consequential companies
Speaker 1: in history, and we're delied to be partnered with them.
Speaker 2: Jensen investors have been worrying about depreciation. Software can actually
Speaker 2: extend life, like there are a one hundreds out there
Speaker 2: in the real world still at full utilization. Are people
Speaker 2: underestimating how long your chips stay useful or are they
Speaker 2: kind of misunderstanding in the context of depreciation, how oh
Speaker 2: you're handling generation to generation updates of GPU.
Speaker 1: Nvidia's architect Nvidia is unlike any other accelerator and The
Speaker 1: reason for that is because of Kuda's diversity of capability
Speaker 1: and versatility. Remember I said two things earlier. I said
Speaker 1: the fact that Nvidia participates and could accelerate every phase
Speaker 1: of AI, pre training, post training, and inference. Were the
Speaker 1: only architecture in the world that does that fantastically. The
Speaker 1: second thing we do, we run every single model, and
Speaker 1: so most agentic systems, most clouds are running so many
Speaker 1: different diverse type of models language models, vision models, biological models,
Speaker 1: chemical models, for all the different fields of science. Nvidia
Speaker 1: could be used across the entire lifespan of the technology.
Speaker 1: And so if you look at products that we shipped,
Speaker 1: Ampier A one hundred we shipped six years ago. But
Speaker 1: because we're continuing, our installed bas is so large, our
Speaker 1: diversity is so great, we could continuously update our software
Speaker 1: bring value to our customers on the one hand, but
Speaker 1: because our versatility is so great based on the capability
Speaker 1: they need, they could use our GPUs for a very
Speaker 1: very long time. Now, remember A one hundred and six
Speaker 1: years old. However, it is still an order of a
Speaker 1: magnitude faster than any CPU could put the bear. So
Speaker 1: it is still the best computer. It is still the
Speaker 1: best processor for much of the workload in the cloud,
Speaker 1: and most people misunderstand that because unlike US, most accelerators
Speaker 1: are kind of singular use, because they don't have diversity,
Speaker 1: because they don't have versatility, because they're not great at
Speaker 1: every phase of AI, once they're used for whatever they
Speaker 1: were designed to do of value fast off a cliff.
Speaker 1: That is not true with n video Jensen.
Speaker 2: My final question is a point of clarification, if I may.
Speaker 2: You were asked on the call about content and in
Speaker 2: video's contribution to any given piece of AI infrastructure, and
Speaker 2: what you said was Hopper around twenty to twenty five
Speaker 2: Blackwell about thirty with those figures billions of dollars in
Speaker 2: dollar terms on a one gig of what data center?
Speaker 2: Or are you talking about percentages of total cost?
Speaker 1: Oh, thank you, billions of dollars billions of dollars. Yeah,
Speaker 1: And so for our ver Rubens system, a one gig
Speaker 1: of what data center is probably something along the lines
Speaker 1: of fifty to fifty five, and video's contribution is probably
Speaker 1: about thirty five of.
Speaker 2: That video CE one billion noted. I was asked to
Speaker 2: ask you, the question has been asked answered astonishingly. Busy
Speaker 2: day for you in the nation's Captain.
Speaker 1: That's a great question. The difference between percentages and billion
Speaker 1: is a big deal. Yeah, it's a brilliance.
Speaker 2: The stakes are high, but we're always grateful for your time.
Speaker 2: I know it's been a busy day. Thank you for
Speaker 2: joining us on Bloomberg Television. That's Nvideo CEO Jens Wang