Advanced Micro Devices, Inc. (AMD) Earnings Call Transcript & Summary

Okay. Good afternoon, and welcome to -- again, welcome to the second day of JPMorgan's 52nd Annual Technology, Media and Communications Conference. My name is Harlan Sur. I'm the semiconductor and semiconductor capital equipment analyst for the firm. Very pleased to have Jean Hu, Executive Vice President and Chief Financial Officer at Advanced Micro Devices here with us today. Jean, thank you for joining us this afternoon.

Yes. Thank you. Thank you for having us.

Yes. I think one of the best places to start is, obviously, one of your customers, Microsoft is having their Build event, and there were a couple of, I think, key announcements, product launches using the MI300 GPU platform from AMD. I don't know if you wanted to maybe spend some time maybe talking about that.

Yes. It's really exciting. So we announced it today, with the Microsoft Build conference, our end-to-end partnership with Microsoft from, of course, AI PC to MI300. On the MI300 side, MI300X and the ROCm software together actually power the Microsoft's virtual machine both for the internal workload, the ChatGPT, with open-source use, and also external workload, the third-party workload. And Microsoft actually said, right, from MI300X and ROCm, it's the best price performance to power the ChatGPT for inference. So that's really a proof point for not only MI300X from hardware, how competitive we are, but also from ROCm software, the maturity, how we have worked with our customers to come up with the best price performance. It's very exciting. And on the third-party workload side, the [ hacking phase ] is also using Microsoft's virtual machine powered by AMD's MI300X and the [ hacking phase ] has almost 0.5 million models, which you can all run on MI300X. So we have made tremendous progress, not only from MI300X competitive in inference training. But more importantly, software has been really critical investment we are making. And today, we really can run a lot of models if they're writing the models based on the open-source ecosystem framework, we can run them out of boxes. And then we also help the customers optimize their models to make it most efficient to provide the best TCO to our customers. So it's very exciting.

So the Microsoft announcement, like you said, was in 2 portions, right? So first is Azure is just offering MI300x instances, right, to their public cloud customers?

Yes, that's the third party.

Exactly. And then the partnership with OpenAI, right, they announced the Azure OpenAI Service, right, that allows customers to take advantage of prebuilt models, right, to quickly bring training and inference and bring their models to the market. That also is using your MI300X platform, right?

Yes. Yes, because the MI300 is powering the ChatGPT 3.5 and the 4, all the Copilot, all the different version, the team, Copilot, all of those applications, it's really one of the most important AI infrastructure in Microsoft Azure data center. So we are really pleased with our partnership with Microsoft.

No, congratulations on that. We'll talk a little bit more about MI300. But I did want to start off with -- and thank you again for joining us today. I did want to start off with some of the near-term sort of business environment questions. Server shipment TAM forecast for calendar '24 is sort of low mid-single-digit sort of growth this year. You expect to grow your data center business this year by strong double-digits percentage points. Within that, it looks like your server business ex GPUs is going kind of 25% to 30% and implies 15% or better second half versus first half growth, right? You did talk about continued adoption of Genoa and improved -- improvement in enterprise demand dynamics. Like what demand dynamics are you tracking, customer programs, adoption of Genoa, Bergamo, ramp of Turin, that gives the team confidence on a better second half and strong growth in your server business this year?

Yes. Great question. We are very pleased with our data center performance. If you look at the market opportunities, it's the largest fast-growing opportunity. And we have been investing in data center and the momentum you can see both from GPU side and the CPU side. So when you look at our CPU business, we -- in Q1, we saw double digit -- strong double-digit growth year-over-year. And in Q2, we're going to see another strong double-digit year-over-year growth. All of those have been driven by the ramp of Gen 4 family of processors, which including Genoa, Bergamo and others, the significant adoption in both cloud and enterprise customers. I think fundamentally, because our processors provide the best TCO for our customers. And if you look at the market this year, in Q1, the third-party market share shows we are reaching 33% market share from the Silver CPU side. I think we do expect the second half to be better than first half. The first one is in cloud. Cloud market demand continued to be a little bit mixed, but since we are providing best TCO for our customers, we do see both hyperscale cloud customers and the Tier 2 cloud customers continue to adopt our Gen 4 processors across their different workloads, both external workload and internal workload. And we talk about -- we have almost like 900 public instance available globally for customer adoption. I think that really have been helping us to drive the growth. Secondly, in enterprise, we actually start to see some demand improvement because today, all the CIOs in enterprise, they are actually facing a couple of challenges, right? The first is all their workload continue to be more. The data is more, application is more, so they do need to have a marginal compute. At the same time, they need to start to think about how they can accommodate AI adoption in enterprise. They are facing the challenges of running out of power in the space. If you look at our Gen 4 family of processors, we literally can provide the same compute with 45% less servers. What that means is if they adopt AMD's solution versus our competitors, they actually can save CapEx almost by half upfront. And then in addition, the operational cost, that will be 40% less. So when you look at the TCO benefit we can offer plus we have been investing in go-to-market. We have been -- have more feet on the street to talk to enterprise customers and show them the TCO benefit they have. So we do see the acceleration of our effort is paying off. We talked about American Express, Shell, STMicro, some of the larger enterprise customers shifting to AMD solutions. So that's just the beginning. We do think in second half, with the demand improvement and our continued share gain in enterprise market will also help us. Of course, as you know, we are very excited by the Turin launch, which is our Gen 5 Silver processors. It will extend the TCO benefit compared to Gen 4, so we're very excited about it. Of course, the revenue ramp-up probably is more in 2025. But the momentum, when we look at our competitive positioning, how we can provide the best TCO for customers, we feel pretty good about the second half.

Similar question that I asked on data center, but now focused on the client PC, right? You drove better than seasonal shipments in Q1, guided for slightly better seasonal shipment dynamics in Q2. Full year, I think we and consensus have your client business up about 25%. What metrics are you monitoring that gives the team confidence that PC client business will drive strong growth relative to the overall TAM growth?

Yes. Yes. I appreciate your comment. It's true that when you look at the first half, our PC client business are performing really well. We are gaining share. And primarily, they are driven by our most recent generation of processors, Ryzen 8000. When I look at our Q1 performance on the desktop side, we had strong year-over-year double-digit growth. On the mobile side, we actually almost doubled the revenue from the Ryzen 8000 processors. So the way to think about it is we actually were the first here to introduce NPU inside of a PC. The AI PC people talk about is with the Ryzen 7040, and we're also the first to introduce NPU inside the desktop. That's the 8000 series. So the technology and product leadership, that have helped us drive the significant demand. I think AMD has always been using this strategy is to drive the top line revenue growth through product technology leadership. And the team has been executing extremely well. And then in the second half, I think we're going to launch our next-generation AI PC, Strix. You're going to hear about it in the coming weeks. It's a very exciting product and very competitive to power the AI applications in the PC market. We do believe AI PC is a very significant inflection point. It will potentially help the refresh of the PC market. And so overall, to come to your question, it's we think generation-over-generation technology and product leadership will help us both on the commercial side and the consumer side to continue to gain share.

Perfect. We did talk a little bit about the traction and announcements today at Microsoft Build relative to the MI300. But let's talk a little bit more about AI and accelerated compute, right? Your team is executing extremely well, fastest product ramp in the history of the company, $1 billion in cumulative revenues just over the past 2 quarters. You've taken your MI300 calendar '24 revenue targets from greater than $2 billion to greater than $3.5 billion to greater than $4 billion. Near term, the team has said that there's supply constrain, right? It seems like demand is rising much faster than expectations. But Lisa said that off of the $4 billion revenue target for this year, that the team has supply commitments to drive revenues significantly above that amount, right? Is that still the case? And is GPU revenue upside from here just purely dependent on customer conversions from eval to qual to deployment?

Yes. First is the MI300 ramp is really unprecedented. If you think about it, we launched the MI300 December 6 last year. And since then, as you mentioned, in less than 2 quarters, we actually passed $1 billion revenue. And we also guided Q2 significantly increase and each quarter sequentially for the rest for the year. And we updated to like $4 billion -- more than $4 billion in revenue for this year based on what we have qualified on backlog or the orders at the point when we did our earnings announcement. So we have more than 100 customer engagement ongoing right now. Lisa talked about the different customers and the different stage of engagement from a POC to qualification, lab, production to ramp. So all those customers -- the customer list include, of course, Microsoft, Meta, Oracle, those hyperscale customers, but we also have a broad set of enterprise customers we are working with. Overall, if you look at the AI accelerated demand, it continue to exceed everybody's expectations. I think there are more demand for GPUs, and our team is working very hard with our customers to continue to go through those kind of process to scale our customer, to make sure they ramp into the production. So we do have more than $4 billion supply secured, especially in second half. We are absolutely working hard to continue to drive the customers and help customers to ramp into production.

Your data center GPU competitor has laid out a multiyear road map, increased cadence of new products and also more finely segmented out their product line, right? I think we and investors are wondering when the AMD team is going to provide us more visibility on their road maps. And I think Lisa said that we should see new products being introduced towards the latter part of this year. Is that still on track?

Yes. I think, Harlan, I will highlight first how AMD got where we are today. If you think about the AMD since Lisa and Mark Papermaster joined the company, has been trying to build a high-performance compute company, so not only we have been investing in CPU. And on GPU side, we have been investing in GPU for many, many years since the ATI days. And if you look at our GPU road map, we have been investing in GPU from MI100, 250, 200 to today. So the approach has always been multi-generational multiyear road map from AMD's perspective. And the MI300X ramp, the success software side and hardware side is really a reflection of long-term investments that we have been making. So I think from our perspective, that background and backdrop is really important. And when we work with our customers, both companies are investing significant results. So you should expect the customer relationship is about market generation, and we actually get a very significant feedback from our customers about not only MI300X, the next generation and the generation after next. The other thing I would say is AMD has been doing the chiplet architecture for a long time, literally almost 10 years. The success of our server CPU road map, it's because generation over generation, it's about chiplet design. That really gives us a lot of flexibility to expand our road map and accelerate our road map. That also help us. We tend to be more conservative from announcing road map perspective, but you should expect us to have a very competitive road map. I think stay tuned, and we will have a preview of our road map in the coming weeks.

Okay. Perfect. I feel like part of the expansion in your data center GPU business outlook this year has been 2 dynamics. First, unlocking better supply availability. But secondly, faster time to production conversion by your customers as they migrate their software stacks over to your platform, right? Thanks to several new iterations of your ROCm software framework. What is the AMD team doing here to continue to sort of close the gap on software, AI frameworks and just accelerated compute ecosystem development?

Yes. Great question. Software is so important in this market. The ROCm software AMD has been investing initially, it's in HPC market. So when you look at MI100, 250 and MI300A, it's ROCm software. Between the MI300A and the ROCm, we are powering the most advanced, the frontier model in the hyper HPC market. So last 2 years, we have made a significant investment and progress in the ROCm to support AI. That has been tremendous, and the ROCm 6.1 actually expanded our support for broad library models, tools and also ecosystem. That has been the reason a lot of the models, if you are writing based on open-source framework, you actually can run your model out of the box using MI300. And that's also why with Microsoft, we can work together closely to really co-optimize the performance to the point to be the best price performance MI300 machine. So the importance for us to move forward is to continue to scale because we have more than 100 customers. We have a broad set of different workload. We need to scale our model with open-source ecosystem. That had been evolving very quickly. And also, secondly, is we do have the approach at the AMD's end-to-end AI. So the ROCm as a single-software platform will support the AI PC, the GPUs and eventually, the edge side for AI applications and the server CPUs and also multi-generation GPU road map. So from that perspective, broadening the support and the deepening the support are what we are doing. And as you can see, we not only invest organically. We also did some small acquisitions to really expand our software capabilities.

Great. Why don't we see if there are any questions in the audience? If you have any questions, raise your hand. We have one right up here. While we're -- it's going to take some time. So why do -- before he asks a question, let me ask my next question is, when we talk about AI compute silicon and hardware, it's typically focused on cloud and hyperscalers, right? But interestingly enough, right, a majority of customer-specific and proprietary data actually resides on-prem. Your enterprise customers would like to keep the proprietary data on-prem, run their AI workloads on-prem. The team is actually starting to prime the enterprise markets with MI300. You announced a plethora of OEM server partnerships recently. What's the strategy for targeting the enterprise markets? And how is this sort of modulating your sort of future product portfolio?

Yes, we actually -- if you look at the over 100 customers we have engagement right now, there are a lot of enterprise customers. The approach we are taking is not only we want to make our hyperscale cloud customers successful, we also want to seed our enterprise customers because we do think AI is going to be everywhere. And you're absolutely right. When we talk to our enterprise customers, they do start to think about that question is, do I do it on-premise? Do I send it to cloud? So that is a strategic approach they have to think through. And typically, they will come to us basically saying, how should they deploy AI? I think we are uniquely positioned. It's because on the server side, we are working with our customers. We are helping them with how they deploy servers, so it become like a significant leverage for us. And then frankly, on the commercial PC side, right, so AI PC, the server side and the GPU side, that's part of our go-to-market model right now is we actually can leverage that to work with the enterprise customer across our different platforms. And of course, ROCm software is really important because ROCm is open source by nature. And the customers, if they can write their model based on the open-source framework, it actually saves them more money. And then from a TCO perspective, that's what we're really trying to approach. It's consistently try to provide our customers the best TCO. We do think that's something we can continue to drive the engagement with enterprise customers.

Perfect. Yes. We had a question here.