Bloomberg Tech at CES

0:00Hello, I'm Stephen Carroll. I'm in Brussels where many of Europe's biggest decisions get made. And I'm Caroline Hepker in London with the hosts of the Bloomberg Daybreak Europe podcast. We're up early every weekday keeping an eye on what's happening across Europe and around the world. We do it early so the news is fresh, not recycled and so you know what actually matters as the day gets going. From Brussels, I'm following the politics, policy and the people shaping the European Union right now. And from London, I'm looking at what all that means for markets, money and the wider economy. We've got reporters across Europe and around the globe feeding in as stories break So whether it's geopolitics, energy, tech or markets, you're hearing it while it happens It's smart, calm and to the point And it fits into your morning You can find new episodes of the Bloomberg Daybreak Europe podcast by 7am in Dublin or 8am in Brussels, Berlin and Paris On Apple, Spotify, YouTube or wherever you get your podcasts

1:02Bloomberg Audio Studios. Podcasts, radio, news.

1:11Bloomberg Tech is live from coast to coast with Caroline Hyde in New York and Ed Ludlow in San Francisco.

1:23Welcome to a special edition of Bloomberg Tech live from CES in Las Vegas, when we will bring you conversations from the biggest names in the industry throughout the week. Of course, coming up on the show, we sit down with the CEO of AMD, Lisa Su, after the company announced a new chip for corporate data center use. Plus, we discuss the global EV and robo-taxi landscape with Lucid Interim CEO, Mark Winterhoff. And then we talk to the CEO of gaming hardware company, Razer, joining us to discuss its latest AI gaming ecosystem. But here on the floor of CEF, we've got to get straight over to Ed Ludlow, who is standing by with the CEO of AMD.

2:06Ed. Thank you, Caroline. And welcome back to Bloomberg Tech. Lisa Su, Helios with MI455X, AMD's first rack scale system solution. but inside it, AMD's first and the world's first two nanometer chip of that type. A lot was made of it when you actually just stood on stage and held it in your hand for the first time. Why is it significant? Well, first of all, Ed, it's great to be here with you at CES. I think CES is always a great way to kick off the year because you get so much perspective. So it was fun giving the keynote last night. Look, Helios is a massive system. You can see it in the background here.

2:48And MI-455 is just an incredibly powerful chip. And probably the context I would give, Ed, is one of the things that we're so clear about is that the demand for AI compute is just continuing to increase. And we have seen that over the last five years when you think about just how much new capabilities have come on board. We've now seen a real inflection in the number of people who are using AI. So if you think today, there are probably more than a billion active users using AI, and we expect that to scale to over 5 billion users over the next five years. So for all of that, you need compute and lots and lots of compute.

3:29And from that standpoint, MI-455 is a significant leap forward in terms of technology capability made up of two and three nanometer chips, 320 billion transistors, just a lot of performance and a lot of capability. What's the timeline for it to be deployed in the real world then? And then who will be the principal first user of it? You'll see it in the second half of 26, and it will ramp from there. And we have very strong partnerships. OpenAI, Greg Brockman, was on stage with us last night talking about all the use cases that they see. We've announced a partnership with Oracle, many others as well.

4:07So given that it is 2H, it's in full production now, it's getting ready to be shipped? We are absolutely getting ready to ship it. That's at one end of the sort of scale and spectrum. At the other, you have MI440X, which is for small data centers. I'm trying to simplify it, but it's basically an enterprise product. What was it that you were trying to solve for with that? Yeah, I think what we're trying to solve for is the world is a very heterogeneous world. You have all kinds of use cases for AI from sort of the very biggest cloud data centers that are doing large-scale training and inference to enterprise applications as well as supercomputers.

4:50And so we actually have a family of chips. At the highest end is our MI-455 for the cloud environment. But we announced last night a MI-440, which is actually using the same basic building blocks, but is now really focused on enterprise applications so that you can go into, let's call it current data centers with the new technology. So we're excited about that as well. There is, enterprises are starting to increase their adoption of AI. In some cases, they want their own control of their data centers in terms of on-prem environments. What are they doing with it, though? I mean, you know, we've been so fixated on frontier models with hundreds of billions of parameters and the scale of infrastructure needed for that.

5:33With MI440, we're talking about something slightly different. I think it's just really interesting if you could explain what the demand is from those enterprises, what they want with the technology. Well, I think you see many enterprises now using AI all throughout their business processes, whether you're talking about things in their workflow. Even AMD, we're using AI through every part of our development process. We're seeing a lot of applications in financial services, in health care. These are areas, especially in financial services, that people actually don't want everything necessarily in the cloud.

6:10They'd like to be able to have their own on-prem deployments or private cloud deployments. And in this case, you don't want to have to build a brand new data center for every new generation of chip. MI440 allows us to use some of those existing data centers and upgrade with the new capabilities. Welcome. If you're watching us on Bloomberg Television or you're listening on Bloomberg Radio, we're live in Las Vegas and we're with AMD's CEO, Lisa Su. and we're talking about the latest generation of accelerators, what makes this generation of AMD accelerators the better option, particularly for on-prem and at the edge, over what NVIDIA is offering right now?

6:52Well, the best way to think about it, Ed, is we're in this place where AI is at an inflection point. We're seeing AI now in every part of compute. We see it in the largest models when you're thinking about things like ChatGPT and Gemini and Grok. We're also seeing many use cases in new capabilities like video production, entertainment, health care, where you're doing drug discovery, all of these various things. Our claim to fame is really outstanding performance at very advantaged total cost of ownership. And the other thing that we believe very strongly in is an open ecosystem and deep partnerships with our overall ecosystem coming together.

7:41So when you put those things in perspective, I think we have a great set of applications that will take advantage of these newest generation chips. You mentioned that Greg Brockman, who's the OpenAI president, was on stage with you last night. And one of the basic points that he made was there are tools and functions they would love to release and put out into the world, but they're compute constrained. I often ask you to quantify demand. But is there a way to quantify the severity in the lack of compute, you know, the deficit that's out there right now? Well, let me just give you some numbers to kind of ground what we think the demand environment is looking like.

8:21So if you think today we have about a billion active users, and we're ramping that to 5 billion over the next five years, and we have about, let's call it, 100 zeta flops of compute all around the world. I mean, that's just a generic number that aggregates all of that. We think we have to increase compute by another 100 times as you go over the next four or five years. And I introduced a term last night, the Yotta Flop. People are like, what is a Yotta Flop? A Yotta Flop is actually 10 to the 24th in terms of flops. So that's a one followed by 24 zeros. And to give you just a view of just how much things have really increased, I mean, that's another 100 times more compute than we have today.

9:12So that gives you an idea. Now, you think, what are you going to use all that compute for? I mean, the truth is the models that we have today are great. I mean, they do amazing things. You know, we talked about a number of use cases. You know, perhaps one that hits very close to home is writing software. Like, you know, people are using the AI tools right now to significantly enhance the productivity of software developers. But it's good, but it can get so much better. And, I mean, I think that's the key point. You know, we like to say that AI is really going to be everywhere, and it's really for everyone.

9:48And it's for each one of us to make our businesses more productive, you know, each one of us more productive, you know, going forward. And so we're still in the very early innings of really unlocking the power of AI. So where we stand is, okay, there's a compute deficit, and software has kind of hit the limits of what current generation compute can offer. help us understand the bottlenecks and barriers to deploying that compute. A lot at the moment about memory chips. What else? Energy, electricity. What's crossing your desk, Lisa, that gives you pause and say, this is a problem right now? Well, our job as a technology industry is to push the bleeding edge.

10:32I mean, that is our job. And so when we think about the MI-455 deploying 2-nanometer and 3-nanometer chips, having the latest generation memory, high bandwidth memory that is out there and really deploying these big systems. The important thing is that the entire ecosystem come together and we plan together for this next big inflection in compute. And that's exactly what we're doing right now. I think we're working very closely with the entire supply chain to ensure that we have the resources to expand this compute environment. And yes, some of the things that you mentioned are, let's call it, constrained.

11:13Which is most severe, Lisa? I don't think that's any one thing. I think we're all looking at how do we build faster. Certainly power is one of those areas where you see throughout the world power is being brought online as fast as possible. Certainly from a silicon standpoint, we're ramping our production capabilities with our partners. From a memory standpoint, our partners are ramping as well. So it's not any one thing. I think it's all of these things have to go sort of in tandem. And that's why partnership is just so important in this business. We started this conversation talking about Helios, first rack scale architecture and infrastructure from AMD.

11:56Could you talk about the future and how much of the content you want to own in a server? You know, we started this story with the GPU. Frankly, if you look at what NVIDIA is doing, they want to increasingly own all of what's inside the box. Is that something that AMD is focused on too? You know, what's most important for us is to ensure that we have turnkey solutions that are very, very easy for our customers to deploy. Because when you think about, you know, how do you use all of this AI compute most effectively, you want it to go into the data center and really be up and running on day one. And for that, you have to optimize a full system.

12:35But from that standpoint, we are very focused on an open ecosystem. So yes, we design the CPUs and the GPUs and some of the networking elements, but we also work really with a broad ecosystem of partners with industry standards. It's all about ensuring that we get the best of all worlds when we put our solutions together. Looking ahead to MI500 2027, that has 1 ,000 times the performance of the MI300 generation. So your last generation of real-world deployed gear, something's coming that's 1 ,000 times better. How did you make it 1 ,000 times better? It is just incredible engineering at every level.

13:19So MI-455 is 10 times better than the chip that we just launched six months ago, the MI-355. And MI-500 is another 10x on top of that. We are using the most advanced technology out there. We have a very clear focus on hardware, software, system, code design. And it is clearly pushing the bleeding edge of capabilities. What is the status of AMD's ability to sell products into China right now? So China is an important market for us. We actually sell a broad range of chips into China, including our PCs as well as other embedded chips. In the data center context, of course. In the data center context, certainly we see China as an important market.

14:12We did get some licenses from the U.S. government late last year as it relates to some of our previous generation, our MI308 chips, and we are in the process of applying for new licenses with our MI325 chips that were recently allowed to apply for licenses. We haven't gotten those licenses yet, but we continue to view China as an important market for us. The reason I ask about it is in part because a lot of the work that's being done in open source models and bridging the gap between open and closed is being done in China to some extent. There's been a lot of discussion about the demand being there in China.

14:53But could you reflect a little bit on that demand, but also what the Chinese government's attitude is to you taking a later generation of tech to the country? Well, I do think the demand for AI in general and in China is high. for all the reasons that we talked about. I think we are in a demand environment where more compute is beneficial across the world. We think China is an important market for us, and it's very active in having our solutions deployed. So we continue to view it as something that's important. We're working with the U.S. government as well as our Chinese customers to find good solutions there.

15:34And there are signs from both governments that the license process is moving. Commerce is kind of notorious for things sitting on a desk for quite a long time. I think we are optimistic that we'll have an opportunity to get some of those licenses granted. You're watching Bloomberg Television. You're listening to Bloomberg Radio. This is Bloomberg Tech, and we're live in Las Vegas with the AMD CEO, Lisa Su. Last question, really, in the data center context is the markets and investors want data and signs that you're taking market share. What would the metrics be that you'd point to, either that already exists or over the coming 12 months, that would evidence that?

16:13Well, I think MI-455 is a clear inflection point in both our technology capability as well as the deep partnerships that we have across the industry. So we're excited about what we see in front of us. And we've talked about tens of billions of dollars in AI revenue as we get into 2027. And I think these are important metrics for us as a company when we think about the AI potential. For all the focus on data centers, some forget that AMD is leader in PC in many respects. The forecasters have very different opinions of what will happen this year. Some see shrinking market. Some see modest growth driven literally by just AI PC.

17:03You've been able to take market share and grow, irrespective of what the broader conditions are, but they haven't been great. How have you done that, and do you expect that to continue to be the case? Well, the PC market is a very good market for us. We grew a ton in the PC market in 2025, and that really came from the strength of our product portfolio. We bet early in AI PCs, so it was a clear area where we believed that the technology would generate demand. We also went through a refresh cycle with Windows 11. And as we go into 2026, I think we'll want to see how a few quarters play out. I think the general demand for computing is certainly there.

17:48There are some supply chain constraints that we're working through and we want to watch going forward. But our case is one where we are still underrepresented in parts of the market. We are very, very strong in gaming. We're very strong in consumer. I think we're underrepresented in enterprise laptops, and we view this as a growth area for us. Does AIPC change that? AI PCs absolutely help in terms of just the upgrade cycle coming in. We're excited about some of our work with AI development systems as well. We announced a new AI development system last night that we think will be also very attractive.

18:29Those constraints you were talking about in the PC context are specifically DRAM or it's broader than that? It's more around the memory side. So when you think about memory overall, I think we have so much demand coming from, let's call it, AI data center compute that we want to see how it impacts sort of the rest of the memory market out there. One of the other areas that you discussed with Greg Brockman on stage from OpenAI was sort of the net or broad economic impact of AI, not just for the companies. I think you were talking more about global economy. Again, very difficult, Lisa, but how does one measure progress in whether AI has or has not had a direct positive economic impact around the world in any given year?

19:18You know, it's true. It's hard to deconvolve all of the things that are happening. But I think from a sense of what we see in the business, many people want to see direct return on investment for a particular set of investments. What I would say is that we know that AI is making a difference in the productivity of companies. We know that. I can see that within AMD in terms of as we deploy AI, we're able to get products to market faster. We're able to significantly improve some of our business processes. So as we go forward over the next several years, I think you're going to see that much broader in enterprises.

19:58Every CEO that I talk to is talking about AI. It is front and center in terms of how to build a better company, how to build a better portfolio. And so, you know, I think what, you know, Greg was talking about is when you aggregate all of that, AI has to impact, you know, the world at a GDP level. And we'll see that over the next few years. You're watching Bloomberg Television. You're listening to Bloomberg Radio. This is Bloomberg Tech. And we're live in Las Vegas. We're speaking to AMD CEO Lisa Su. You are an investor in generative bionics, also a technology partner, and they have unveiled a humanoid robot here at Las Vegas CES.

20:40In fact, if the magic of television can happen and we cut to the wide shot, you'll see it in the background. You know, this is the first tangible sign I feel we've seen from AMD on how you intend to play in physical AI. Yes. Explain your strategy. It is the next big market, right? Yes, and I wouldn't say it's the first time, but it's probably one of the areas where we don't highlight as much because there's so much focus on data center and cloud, and the opportunities there are very much in front of us. But when we look at physical AI, starting from all of the work we've done in FPGAs and embedded real-time capability, we have been in this space for a long time.

21:24We already power a lot of robotic applications out there. But I think as we go into the humanoid capability, and we're excited about our partnership with G-Bionics and the work with Angeen One, I think that takes us to another level in terms of capability and intelligence and what we're trying to do. Is the business model to be all things, the brain inside of the humanoid robot and inference side, the underlying software being trained on AMD accelerators? What's the go-to-market, I guess, is what I'm asking. You should expect that our partnerships extend through all of those levels. So we have the components that can power the humanoid robots, sort of real-time local capability, which is very, very important.

22:12And then we also have the technology behind that in terms of how to train and inference on these humanoids. when last we met in person, it was in Washington, D.C., and the president had just outlined a broad strategy for America in AI, and it really centered around infrastructure, deregulation, allowing those building the infrastructure to move faster. That was kind of in the second half of last year. In the months that have followed, have you seen any signs that it worked and anything that you could point to that says, yeah, people are able to build faster, maybe to address some of the compute deficits we discussed?

22:54Well, I can say for sure, you know, the president's AI action plan, you know, when we met, and I think this was back in July when it came out, I was very optimistic about having a really forward-leaning strategy from, you know, sort of the whole view of what does it take for the U.S. to lead in AI. And I think we've made a ton of progress along the way. And, you know, I had Michael Kratios joined us last night on stage as well to talk about the Genesis mission, which is, you know, another, you know, sort of public-private partnership approach to really advance science in the United States. And when you look at, you know, all of these things, you know, building faster, ensuring that we have, you know, the right export controls so that we're able to have the U.S.

23:42stack adopted across. Do we have the right export controls currently? We are certainly working very closely with the various parties in the U.S. government to ensure that we have the right balance there. And we also have this notion of how do we invest more here and ensure that in the United States that we are running as fast as possible to bring AI capacity online to help us in science and the broader economic benefits. Lisa, what happens in 2026? What happens in the world of AI? And what do you think will define this year in terms of the progress that your industry hopes to make? Well, I started our keynote last night with the sentence that, you know, you ain't seen nothing yet.

24:30That's really how I feel. I mean, we're sitting here in January, and it's just amazing how much progress is made. every week and every month when we see how these models are developing, when we see how the use cases are developing, and then when we see the tangible results on businesses and outcomes. I believe that we saw a good amount of that come to fruition in 2025. We're going to see much more of that in 2026, so that everyone should understand that AI is not just hype out there. It's not just sort of things that people are talking about in the investment community. It's things that people are using every day, real time, and feeling like, hey, my life is better because I have this technology.

25:16And I think we're going to see that in 2026. Lisa Su, AMD CEO, AMD with its and the world's first two nanometer chip going into Helios, its first rack scale system solution. Caro, back to you on set in Las Vegas.

25:33What an extraordinary conversation, Ed Ludlow, as always, with Lisa Sue of AMD, who, of course, took to the stage last night alongside Greg Brockman of OpenAI. And we're just going to check in on the shares because there were significant statements coming from Lisa throughout that interview with Ed. We are off by 3.3 percent, even as she continues to articulate how much computers are going to need to increase. 100 times in the next four to five years, talking about the early innings that we're at in terms of unlocking AI and really talking up the MI455, pushing at the bleeding edge of capability.

26:05We're also talking about the demand they have in AI for China. In particular, Chinese demand is high. They're working with the government as it stands for finding solutions to be able to ship through China. Also talk about how they're underrepresented in enterprise laptops as well. We're up by 3.3 % though, because seeing JPMorgan saying, look, like NVIDIA, AMD's outlook for compute demand is very bullish and they're hearing about the MI500 series coming on course for 2027 launch but not much new according to Morgan Stanley in terms of brand new information. NVIDIA is up four tenths of a percent.

26:36It's maybe we've got a little bit more detail on the Rubin unveil and the fact that six chips have already come back on their next innovations the next architecture for their compute and we're seeing that they're already back they're likely to be shipping in the course of 2026 but also talking up the future of self driving vehicles with NVIDIA, a new platform to rival maybe even a Tesla. Elon Musk says, I'm not losing sleep over that. But we're also hearing about the future robotics coming from NVIDIA as well and demand for H200s coming from China. So much to digest on these particular stocks.