Advanced Micro Devices, Inc. ($AMD)

Welcome back to this BofA Global Tech Conference. I'm Vivek Arya from BofA's semiconductor, semi-cap equipment research team. I'm really delighted to have the team from Advanced Micro Devices join us this morning: Jean Hu, Chief Financial Officer; and Matt Ramsay, Head of Investor Relations. And I'll go through my questions, but please feel free to raise your hand if you would like me to bring up something. But really warm welcome to you, Jean, and I really appreciate you joining us...

Yes. Thank you.

At the conference. And I guess, exciting times in AI and the semiconductor industry. So maybe, Jean, as a start, just walk us through your state of the union, right? The growth has been very strong, right, since the start of the year. What has surprised you? Which are the areas that you think you are seeing kind of the best growth right now? And which are the areas which have been kind of pushed back because of this?

Yes. First, thank you for having us. Thank you all for joining us. I think the biggest change during the last few months is really the rise and inflection of agentic AI. You can see continued momentum from training to inference, from AI adoption, experimentation, to more adoption at scale. So when you look at that, it's agentic AI, it's not about answering question anymore. It's about orchestration, it's about database access and a lot of tool execution. And all of those require significant CPU performance. And what we are seeing is very significant and incremental demand for our CPU platforms. That has been really exciting. At the same time, we also are seeing the economics of AI keeps changing, right? Is with the token generation going up so quickly, all the customers are really focusing on performance, TCO, and they're really trying to figure out how to use different computes to address different application and workloads. So we see demand for GPU going up, CPU and also a lot of other ASIC LPUs. I think from AMD's perspective, you know our Q1 performance. We had record CPU performance. CPU business grew more than 50%. We guided Q2 CPU performance is going to go up year-over-year 70%. That has been really exciting. So all those things really benefit us because we have been investing in GPU, CPU, adaptive compute, to also address literally end-to-end applications from data center to [indiscernible] to gaming. That feels like right now all the engines are really driving the business revenue growth very significantly.

Got it. So I think the growth in CPU has been kind of the biggest positive drivers this year and we are kind of tracking this 2030 or end of the decade type of addressable opportunity, which I think you were the first to point out, right, would be $60 billion. Then said that doesn't sound that high enough, so they took it up to $100 billion. Then you took it up to $120 billion. And Jensen said, well, could be even more than that, right, up to $200 billion. What do you think is the difference between all these forecasts? This is one of the most frequently asked questions, right, from the investment community. What is the right number? How does one kind of get to it? Is there like a simple unit and are we just all using different ASPs to get to a different number and everyone has the same unit growth?

You're asking a lot of questions here. But I think maybe let's take a step back. You are absolutely right, AMD was the first one. Literally last year, we started to talk about how AI drive the demand of CPUs. So last November, when we had our Financial Analyst Day, we actually outlined how we think about this opportunity under the TAM. We basically said, okay, we are thinking 3 segments. One is the traditional general compute, which we are all very familiar with, has been driving the traditional enterprise application across the board. The second category is the head node, which is really the communication with the GPUs. You want speed to make sure you have the communication. We also outlined agentic AI last November, which is still very early, but our team already see the early signs for agentic AI. That has been the fastest-growing market in our view. That's when we said, okay, we believe the TAM is going to grow 80% CAGR to $60 billion in 2030. Remember, the general purpose CPU used to be just a single-digit growth. So that market expansion, we saw it earlier, but we never estimated that it's going to be so fast. The pace and the speed of agentic AI adoption has been tremendous. So when you look at the January, February, March, all the enterprise adoption started. You see Anthropic, OpenAI, their revenue has been going up very significantly. The demand for CPU continued to go up across all our customers. That's when we had our earnings call, we actually updated our market forecast to more than $120 billion. Frankly, it's still very early, right, when you think about agentic AI adoption. What we are seeing is with agentic AI, it's quite complex. When you have millions of operations you have to execute, when you have a lot of agents concurrently working on different tasks, you actually need a very high core count CPUs. We don't know what other companies, how they think about the TAM and the SAM. For us, we go through the bottom-up and the top-down approach. We know at this particular point, we feel pretty good about more than $120 billion. But it's evolving so fast and more and more complex, so you should expect for the agentic AI portion of the market, because you have so many diverse workloads, so complex, the ASP will continue to increase because the increase, you need a very high core count CPUs, high-performance CPUs. Matt, I don't know if you have other you can add here.

Sure. First off, thank you, Vivek, for hosting us and for you guys all coming. I think there's a couple of things, Vivek, that I would maybe add to Jean's comments. One is, I think, for this whole audience, and us included, we were trying to figure out when was the primary driver of AI CapEx going to go from almost predominantly large model training and start the shift towards inference being a primary driver of CapEx. And we're seeing that happen in real time. And I think the more powerful thing for our business and maybe the more transformative thing architecturally is, during that transition, you're seeing chatbot inference become agentic inference. And what agentic inference does as a workload, right, you daisy-chain or can catenate all these automated agentic flows together. And between each inference task, there's a lot of CPU diverse work. So post-processing and data, figuring out what to tell the AI to do next often based on the result of the prior inference. Where do I get the data from for the next step? Is it in a cloud? Is it in an ERP system, a payment system, a CRM system, wherever? Get all of that data, come back. Post-process the data from that step and feed it into the next agentic step for the AI. And that workload is quite diverse. And that's what we're seeing driving the demand for Turion now in real time. And as the order book fills in for the 256 core 2-nanometer Venice parts that are going to launch in a couple of months and be the primary workhorse for next year, that's where we're seeing the order book really expand.

Got it. Is there a way to segment that market, whatever it happens to be, right, $120 billion, right, plus, in those 3 segments, Jean, that you described, the kind of the traditional applications, the part of, let's call it, part of the AI cluster, and then agentic kind of stand-alone CPUs?

Yes. I think the traditional segment, it's very clear. I think 2025, different third party, I would say that's a $25 billion to $30 billion market opportunity. It will continue to grow. As Matt has mentioned, you actually have an agent doing more work on the traditional database. So that traditional general purpose CPU, it's probably steady growth, but not as high. The head nodes, which is working with the GPUs, you can see that's when people talk about the ratios. Traditionally, it's 1 head node CPU manage 8 GPUs, and then become 2 to -- yes, it's getting more and more. So all the time that ratio is changing. So we do think the head node segment of CPU will also grow very fast, much faster than the traditional general CPU. But the most exciting portion of the market is actually agentic AI. So agentic AI, you actually -- you are seeing agentic AI server rack sit in between the traditional servers and the GPUs. And those racks are handling all those different workloads that really make sure all the agentic agents work. That market, we think, whatever, the $120 billion or $200 billion market opportunity, is the majority of that large market.

Over 50% of that market you think is that stand-alone...

Agentic, yes. It is still very early right now. But if you just think about what Matt said, how complex, how dynamic those workloads will be, and we do see significant productivity improvement, especially software engineering side. Those are very complex workload. You really need a different core counts, you need really high-performance, high core counts. You also need a simultaneous multithread, all those high-performance, you can manage millions of agents potentially.

Right. And the final question there is -- actually 2 last questions. One is x86 versus ARM. So if let's say that agentic opportunity does capture the dominant share of whatever that time number happens to be, what advantage, and if I dare ask, what disadvantage does x86 have versus ARM in capturing that?

Yes. I'll start. Matt can talk about the more technical side, is the way AMD has been thinking about, there has never been, "Oh, x86 architecture or ARM architecture." It's more about how we provide the best TCO for customers. So for us, the performance is number one. And secondly, what we have been trying to build is the breadth and the depth of platform portfolio. So if you look at our CPU platform, we have gone through fiber generation at the Turion, and the Venice is next generation. We had the breadth from the core count to 8, to 16 core count addressing enterprise applications to the Venice will have 256 core count. So for us, we have all different configurations, design points to meet all the different compute to give them best TCOs. I don't know technically you can provide them.

Yes, Vivek, I think they're -- as Jean talked about the 3 different buckets, right? The traditional server workloads for enterprise, I think there is an affinity towards x86 because of the codebase. And many of those servers are deployed on-prem, some of them are deployed in third-party cloud. But it's basically the same workload depending on where you want to deploy it. And I think as these agents generate more traffic to all those traditional systems, then the x86 system is well positioned there. Then you have the head nodes. I think that what you really need in head nodes is really high single-thread performance, really high bandwidth to -- I don't know, it's not a technical term, but feed the beast of these really expensive accelerators that are in the box, right? We will do our own head nodes for Helios. I think our large competitor in their NPL racks will basically do their own head nodes. And then there's a bunch of different XPU programs that are going to be launched by the industry. And I think when we have those conversations with customers, it's much more about what is the performance of your CPU such that I get the best utilization out of this really expensive XPU that I'm buying? It's not an Intel or AMD or x86 versus ARM conversation. It's a: what's the best server part? And then when you talk about these agentic racks, they're -- it's really about how many concurrent agents can you run per rack or per megawatt of compute. And as Jean mentioned, really, really high-thread and core-count products, I think our road map is differentiated there. And another thing that doesn't get mentioned but I think is important, is if you think about the dollars of CapEx that are going to come into the server market, the mission-critical nature of these systems, both head node and agentic racks, some of the RAS features and the security features of the x86 ecosystem, it's not an X86 architecture thing, it's just we and our x86 competitor have been put through the paces by every hyperscaler and most enterprises on all of these security features for a decade. And you might imagine, you get into these automated flows where those agents have access to mission-critical data, and you want to really have servers that have robust security features there. So we feel we get brought into essentially every RFQ that's in the industry for these servers, and I think we're positioned to win a very high percentage of them.

Got it. Now your x86 competitor, right, has their own fab, right? They are adding up -- or they're planning to add a lot more capacity on the server CPU side. I guess this year, every CPU is being sold, right? But do you think that there is a scope for share shifts given that your competitor has incremental capacity to devote to this? Or do you think you will be adequately served by your foundry ecosystem?

Yes. We have been very pleased with our share gain trajectory. I think the last Q1 we just announced, we actually, from a value share perspective, we got to like 46%. When you think about it is our success is really tied together with TSMC. From day 1, we have been using TSMC. We work together with our triplet design, with the packaging technology to come up with the best performance server platforms, that continue to benefit us going forward. We have been planning for this ramp since last year. So if you look at the Q1 performance and the Q2 guidance, when we guide year-over-year 17% increase, and a lot of you actually know is right, the wafer started 6 or 9 months ago. So it is the early planning, how we work with the TMSC to make sure we get support to continue to drive the ramp of the supply. The demand is tremendous, supply is still tight. So I think for us, for this year, next year, every supply we can get, we can provide to our customers. We're going to continue to do that. It's the planning beyond the 2027 right now, for the longer term, I think we'll continue to work with the TSMC and prioritize data center as how we drive the business growth going forward.

Vivek, one little thing that I would add to what Jean mentioned there is when we have conversations with the investor community on this particular topic, I think one thing that I've noticed is supply is tight. 3-nanometer is tight, there's a lot of other areas that are tight. And we're -- I think we're very well positioned with the relationships Lisa has personally with the executives in that space to get maybe more than our fair share of the incremental. But it is tight. I think what I've noticed is maybe the investor scoping of what Lisa and the team initially asked for in '26 and '27 maybe didn't imagine how much growth we had already planned for in supply. So things are tight, but we've already asked for and already been sort of "granted from TSMC," I think, is a different I think we're having the right conversation there, but maybe not at the right starting point from what we were sort of allocated initially.

Got it. And then final one on the CPU side, on price. So you mentioned 50% plus growth in Q1 and then 70% plus. I think there was a sense that one would sustain this, right, for the rest of the year. How much of this, Jean, is pricing versus unit growth? And then let me just quickly part B to that, as that agentic, right, that third segment becomes a bigger portion, do you think that can command much higher ASPs? When I talk with the ARM camp, they are talking about ASPs in the $3,000, $4,000, $5,000 range, which is well above the ASPs, right, that AMD is able to get. So just unit versus ASP and just the trend of ASP.

Yes, I think as you mentioned, both the more than 50% growth in Q1, and that we guided Q2 70% year-over-year, more than 70% year-over-year increase, 2/3 of that actually are unit growth. So majority of our revenue growth actually come from unit expansion versus ASP increase. But to your point on the ASP going forward, especially with agentic AI is a great point, is what we're seeing is we're at the early inning of agentic AI adoption. You can already see with the software engineering part of agentic work -- autonomous agenetic workflow, you really need very high performance, high core count CPUs. That tend to have a higher ASP. So I think generation over generation, when we go to 2-nanometer with Venice and the future generation to handle complex workload to provide the performance, you tend to see the CPU price to continue to increase. The other thing I would say is because we have really large platform, the CPU ASP is really determined by the mix and by the different configurations for different workloads. So it's not necessarily -- for enterprise per core ASP is very high, but because the core counts are relatively low, so ASP is relatively low. But the gross margin is great. So it's a very nuanced from our business because of how big our platform is and how complex our different design point we are helping our customers.

Got it. We spent 2/3 of the time on CPU, so let's talk about GPU now. So you were at the start of launch of a major rack scale system to your portfolio. Maybe give us a status update of how you're feeling when your competitor launched their first large scale up product. It took a while, right, for the industry to get ready, liquid cooling and all those things to get ready. So how do you think about your progress so far? How excited are you about the second half? .

Yes. We are on track. We sampled MI 450. We expect to be launching in second half or Q3 starting point, and Q4. As you know, we have been preparing for this launch for a long time. We acquired ZT Systems in 2024. The whole reason we're acquiring ZT Systems is to help us to add capabilities in system-level design. And we also have worked on the networking side. So the whole team has been working to prepare this launch. We know it's very hard. It's very complex, very hard. But from an execution perspective, our team has been on track, meticulously prepared for all different aspect launch, not only technology, software side, but more importantly, the supply chain side, how you make sure the design redundancy with all the components, but also supplies even very small components. So you have to make sure you have supplies. That has been the whole team's execution track record. We feel pretty good right now.

Yes. Vivek, I think we're anticipating, as Jean said, the -- we already have sampled and we have a number of customers that have full Helios racks in their own data center running their full production workload now and testing and doing all those things that you would expect us to be doing at this point in time. I mean we learned -- the customers learned a lot, we learned a lot from some folks that blazed the trail, as you mentioned. And we're going to really focus on a concentrated set of ODMs as we launch for the first number of months until we get up to scale. And not like a few systems, but billions of dollars of scale. And then we'll be expanding the ODM ecosystem pretty significantly as we move through next year and get towards the MI 500 series and whatnot. So we feel good about where we are. The initial work that the customer base is doing in their own labs with sample systems has gone very, very well. And so now it's about let's get, then we'll see a pretty significant jump in the fourth quarter of revenue and a fairly significant jump in Q1. And then we'll kind of go from there. So it is wood, so touch wood. Everything is going exactly as we hoped it goes. I mean when you're doing anything like this, there's -- day to day, there's always something, right? But our job is to keep the [ duck ] calm on the top as we take on the bottom and get ready to ramp this thing starting in Q3.

Got it. When you've been asked, Jean -- or Lisa has been asked, you've always mentioned the opportunity for multi-gigawatt scale deployments. I think they've heard about 2 of them, OpenAI and Meta. You think there is still the scope for us to be pleasantly surprised with more such announcements even for '27? Or do you think that just given how tight the industry is, that more incremental announcements could be further spaced out on that? .

Yes. We talked about we're really pleased to lead our partnership, a very long-term partnership, with both OpenAI and Meta, last year, we established those relationships and we actually see the forecast from those customers are actually above our original plan for 2027. I think one of the key milestones we're really focusing on this year is to continue to expand and deepening the customer adoption of MI 450. We definitely expect there will be other Meta gigawatt customers. We have both across the board the hyperscaler customers, the model companies and even AI-native companies, who we have been engaging, working with. I think it's important for us to continue to expand this customer base and with the large scale deployment.

All right. Makes sense. And then how do you expect the 2 customers you have announced to allocate market share? Because they have a number of supplier options. I know you have a somewhat unique engagement with them through the granting of warrants and whatnot. But just if you set that aside, how is your visibility into getting, I think, the 2-gigawatt each, right, from those customers for next year? .

Yes. Vivek, as you know, the lead time for MI 450 is quite long. So we really have to start to plan and have the orders from customers for next year for the second half launch and the next year. I think the supply chain overall is tight next year. But since we have been preparing to support our customers, we do want to ensure we get supplies for what they need. I think both are coming higher than our original plan, but we are continuing to increase the supply. Those are 2 our most important anchor customers. Of course, we also have a warrant, which we're going to be able to share the upside if we get more revenue. Our start out price is higher, they will share upside too. That is absolutely the common interest for both companies who want to drive the adoption of MI 450. We feel pretty good, with the both of them, we think we can get the right supplies to support that.

Got it. Do you think having someone like a TSMC is almost adding a level of discipline, right, in the system? Because it's just harder to double count if everyone has to kind of go to the same source, right, to get -- I mean I know it sounds obvious, but do you see that also?

They're quite disciplined. I think they will continue to be. I mean these are sensitive topics for us to talk about in these forums. But like we really, really, really appreciate the support the TSMC giving us as a partner and the way that they're working with us to bring more capacity online to support not just the Helios and 450 growth, but the significant server TAM expansion that we're seeing and planning for, not just for this year, but for all of next year and conversations going into 2028 on wafer capacity to support demand. So we really appreciate the work that they're doing on our behalf. And I think that they're being, as they've always been, disciplined in the way that they bring capacity online and do their diligence to [indiscernible] deepen the customer base to understand where the organic demand is coming from to support the capacity that they're bringing on.

Makes sense. And then the final one, Jean, is on just memory cost inflation, right? I guess when you wake up and see DRAM, I'm sure DRAM price is not what you see when you wake up, but when you see that the cost inflation every day, is that a good thing because it gives you more pricing power? Or is that a bad thing because now you have to absorb that cost and hunt for more supply? What are kind of the pros and cons of that memory cost inflation for you?

It's really a great question. First, for us, right, we really want to make sure if there is a longer-term agreement with our suppliers, we can secure the capacity. That is the number one thing. When you have a large business at our scale, you have to plan ahead. And secondly, we think more strategically, if there's memory cost increase, we do need to figure out a way to share with our customers to absorb that increase together. I think the most important thing for us is we actually don't want to use the shortage here on control of memory to just increase the price. We want to make sure customers help us to absorb the cost increase, but we are more strategic with the long-term relationship. I think from an industry perspective, the memory cost increase at this kind of level, we have never seen, right? The price is really high. I think it does increase the CapEx spending for end customers where they spend the CapEx. I think in the longer term, just like all the industry, you always have a new capacity add up. You also have a new innovation on how you utilize memory more efficiently. It will figure out itself in the longer term. That's what we believe.

Got it. But do you have long-term agreements in place for the majority of your memory needs? Or do you think that this is a cyclical high, right, and maybe there will be kind of more normalization of that input cost?

Yes. From a planning perspective, because our manufacturing cycle is so long, if we plan for the MI 450 ramp this year, we had to start to talk to our suppliers last year or year before. Similar situation is right now not only with a very tight supply chain environment, not only we're planning 2027, we are planning 2028. So for us to continue to make sure we can support our ambitious plan to grow the company, we have to plan ahead.

Vivek, in the server market and in the PC market, the majority of -- the vast majority of the DRAM is actually acquired by our OEM and ODM partners and the hyperscalers themselves, right? The DRAM doesn't run through our P&L. And we work really, really hard with all of the customer base to try to make sure that we're matching like the memory supply that they're able to get and the CPU supply -- or the GPU supply that we're able to provide together to where there's not mixed matching of supply in the industry or hoarding of anything. And so we've been working really hard on that. But there's certainly increased input costs to end devices in certain parts of the consumer and gaming market where there have been some anticipated market impacts. And I think we've given you guys our current view of that and the guidance that we've talked about. But we're working really hard on behalf of the whole customer base to try to make sure that the memory pricing and the matching of components is relatively seamless in a time like this.

Got you. And just final question before we close. When you look across your customer base, Jean, how far is the visibility like that they are willing to provide to you now? And what -- when you get that, what are you doing differently in your business operationally to kind of deliver to those?

Yes. I think because the supply chain environment is really tight, the customer really plan ahead. So we have a very good visibility into 2027 and beyond. I think our customers and ourselves, especially when you think about the data center investment, very large CapEx planning, very long planning cycle, they actually plan way ahead 2027. We feel really good about both the visibility of the demand side and the visibility of the supply side. And of course, 2028 and beyond, that's everybody is working on.

Okay. On that positive note, thank you so much, Jean.

Thank you.

Appreciate your time.