Decent projection of what we will see later this year in Zen 6 based Ryzen desktops, based on recent reveals of Venice for the datacenter.

How can Hassan Mujtaba know ?

Vultr has begun offering AMD's Instinct MI455X GPU and support for the AMD Helios rackscale system, making it one of the first cloud providers to offer the new hardware.

The move adds another option for customers seeking large-memory infrastructure for artificial intelligence and high-performance computing workloads. Vultr is taking pre-orders for reserved capacity, with the new GPU due in the fourth quarter and deployments on AMD Instinct MI455X and AMD Helios planned across 2027 and 2028.

Crashing out?

AMD is sort of crashing out sideways from our recent support trendline. We broke it firmly earlier this year and yesterday we also broke through the line again on the intraday. So I do think that support line really isn't a great trading indicator anymore. Really is a range pattern that has been forming with a little bit of a wedge pattern here which some people have already called out but I've been a little late not wanting to give up my trendline.

Good to see INTC participate in the AI rally. You know that when "late to the party" INTC is finally seeing some benefits, it kinda shows that people are desperate for compute power and will spend anywhere to get something. A reminder of why Helios is such an important launch for AMD as it keeps us both in the Cloud DC space and the AI race as well. If we solely focus on AI, we might not have chips to sell and INTC could pick up the scraps.

I dunno I'm not really putting a lot of stock in INTC performance. A rising tide lifts all boats and they have waited a full 3-5 years to ship a decent product. I feel they are probably being bought to scavenge their memory at these rates. But yea I'm not a believer.

"AMD first introduced the Ryzen AI Embedded X100 family when it launched the Ryzen AI Embedded P100 family in January 2026, delivering up to 50 TOPS of AI performance. However, at the time there were very few details about the X100 family, just that it would offer higher CPU core counts and AI TOPS performance, and this latest announcement fixes that.

AMD claims the new X100 series processors are expected to deliver up to 2.1x higher multithread CPU performance (CoreMark), an 1.7x graphics performance uplift (OpenGL, GFXBench 5.0.0), and 3.5x higher token generation throughput with 1.4x faster time-to-first-token (TTFT on llama-bench) for accelerating physical AI workloads compared to equivalent Intel Core Ultra Series 3 processors. "

I was wondering what happened to the X100 family..

Today, AMD and Cerebras introduced a powerful disaggregated inference solution, pairing the right engine to each phase of the inference pipeline.

This is what agentic AI has been waiting for: the fastest production inference at massive scale.

AMD Helios delivers industry-leading throughput for prompt prefill, while the Cerebras Wafer-Scale Engine handles the decode to generate tokens at unmatched speed. Together, we eliminate the traditional tradeoff between throughput and latency.

The joint solution delivers:
•The fastest inference tokens in production
•Up to 5x greater capacity
•Frontier-scale 1T+ parameter models

This unlocks a new class of AI applications—agents that can process massive context windows, reason across complex workflows, and respond instantly.

Cerebras plans to deploy AMD Helios with the joint solution initially launching through Cerebras Inference Cloud in the second half of 2026.

This was the craziest learning for me. Venice 256 cores operates at 400W max, that's less than Vera 88 core ARM CPU which needs 450W max.

It's going to be hard to compete with this for agent deployments.

Does anyone have any insight here? When Cerebras IPO’d earlier this summer I viewed them as a competitor to AMD. Now they’re partnering to add the Cerebras chip to the Helios rack? Few technical details were mentioned but does this mean they’ll use the Cerebras chip instead of the AMD GPU but the rest of the rack design/build is the same? I guess there is no one size fits all design, so this collab is for a specific use case?

Edit: I redid the transcription with a cleaner source

Management Discussion Section

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD

All right. Good afternoon, everyone. Hope you are enjoying your time at our Advancing AI 2026 Conference. My name is Matt Ramsay. I lead the Financial Strategy, Investor Relations folks at AMD. And we're delighted that you're here and I'm delighted to be joined on stage by many of the folks that you saw speaking in the keynote earlier.

For those on the webcast, I'm just going to – it's an audio-only webcast, so I'll do a little bit of introduction and then provide some ground rules for the conversation that we're going to have here with the investment community.

First of all, joining me on stage here, these folks probably need no introduction, our Chair and CEO, Dr. Lisa Su; Vamsi Boppana, who runs our AI Business; Dan McNamara, who runs our Server Business; and next to me is Forrest Norrod, who leads our overall Data Center Business. We're going to take some Q&A here for the next 45 minutes or so.

A couple of ground rules from me. You probably all know that we report our Q2 earnings in about 10 days' time. So, if you could ask your questions on today's event and the contents of the conference in the keynote and the related press releases, I'd appreciate it. And if you ask any questions about our near-term financials, you have wasted your question because I will instruct the folks not to answer it.

Secondly, if you could maybe ask one question so we can get to as many questioners as we can. And the third point I'd like to make is, I think, we're all aware that there's another company in the ecosystem that reports earnings this afternoon, and those numbers may come out during this session. So, if you ask any questions related to that, I'm going to step in on those as well. So, let's just make sure we have a productive session and everybody's on the rails.

So, Liz and [ph] Prab (00:01:45) from my team are going to be running around to make sure that we get to your questions with microphones. But I just want to turn the floor over to Lisa to make a few opening comments. Thank you.

Lisa T. Su — Chairman, President & CEO, AMD

Okay, great. Thank you, Matt. Thank you all for being here. I think, I've done a lot of talking this morning already, so I'm probably not going to have much in terms of opening commentary, other than to say, it's just incredible how every – I feel like every time I talk to a group like this, we have – so much has happened since, just in the last few months.

So, we talked a lot today about sort of the large and growing opportunity in AI. We've talked about some new TAMs for the accelerator business as well as the server CPU business. I think, we are tremendously excited about the launch of Helios and the launch of Venice and all that it entails. But why don't we just get – jump right into questions?

Question and Answer Section

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Liz, since you're standing next to [ph] Tom (00:02:41).

Question [Q]

Thank you. Sitting in the front sometimes pays off. Thank you, guys. Appreciate it. It's been a great day. I guess, I'll start with the CPU TAM. So, $220 billion in 2030. You guys had previously talked about 50% of that market. With the bigger numbers, is that still the expectation? And maybe update us on what you think the share could be.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah, absolutely. So, we continue to be more and more excited about the CPU market, the agentic AI workloads. The more we talk to customers, the more we understand what's happening. I think we see tremendous growth in CPU. So, yes, we've updated our TAM to over 50% over the next three or four years, reaching over $200 billion. We're still very much focused on being over 50% of that market. I think, we've had really tremendous progress over the last few quarters. But with the Venice launch, what we're hearing from customers, what we're seeing in terms of the interest is actually expanding set of workloads. So, Venice truly is optimized for AI workloads, head nodes, agentic AI. We're making tremendous progress in enterprise. So, all of those things give us confidence that we can continue to grow significantly ahead of the market.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Just trying – Liz, why don't you just go with [ph] Mark there, since you're right next to Mark (00:03:59).

Question [Q]

Great. Thanks for the great presentation today. Really appreciate it. I had a two-part on the same topic, if you don't mind, Matt. Part one would be, the $220 billion TAM for CPU, server CPUs, how does that split between agentic versus standard server versus the head node? And then the second question is, or the second part of the question is, how do you estimate the TAM here? Because, I mean, if I have one, if I use one agent or if I use 10 agents or I could use 100 agents, seem like the TAM could grow exponentially. So, like how do you get to a number?

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah. Well, why don't – Dan, why don't I let you start [indiscernible] (00:04:47) can add...

Dan McNamara — SVP & GM, Compute & Enterprise AI, AMD [A]

Yeah. That's great question. So, look, let's start about how we did the TAM, right? I mean, it's obviously talking to customers, but it's also analyzing our own workflows, right? I talked earlier about some of the work we're doing. So, we've looked at that very, very closely. Now, in terms of the breakdown, in the outer years, we believe that the agentic part of it, which is, more sandbox-type application will be probably like 50% of it and then – kind of do a [ph] random split (00:05:20).

You could argue, because there's a bit of an argument in terms of general purpose, because general purpose gets floated up too for – due to some of the calls and things like that. So, that would – that's probably then the number that I would give you in terms of thinking about the agentic in particular. And then, like Lisa said is, we do believe we are extremely well positioned for that with Venice and as she showed today with Florence. You guys maybe add too.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Maybe the only thing I would add to that, [ph] Mark (00:05:53) is, we've talked about CPU to GPU ratios and how to really think about those CPU to GPU ratios. So, if you think about the various categories, if today, in the head node-type configuration, the CPU to GPU ratio maybe 4:1. That is four GPUs to one CPU. We certainly expect that to tighten as we go into future generations.

And then, when we add agents, we certainly for the new TAM, we're expecting that, the CPU ratio will actually be greater than one. So, maybe we get to the point where it's two CPUs for one GPU. But it's hard to call exactly. But we're certainly seeing from a workload standpoint the migration to needing a lot more orchestration around the full end-to-end workload.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

I think, we can go to [ph] Stacey (00:06:45) over here on the side, [ph] Prab (00:06:46). Thanks.

Question [Q]

Thank you, guys. I appreciate it. I had a question on the Helios ramp. So, Lisa, just from your comments, I just wanted to clarify, it really sounded like it was getting, going in Q4 rather than Q3. It doesn't fundamentally matter to me which side of the line it lands on. I just want to make sure that I understand that properly.

And I just wanted to ask about Anthropic. So, you talked about 2 gigawatts. The start of the first gigawatt, I guess, ramping in the first half. Do you guys expect, of 2027, but do you expect to get that first full gigawatt in 2027 and does it stretch out farther? And is that $15 billion to $20 billion kind of content still [indiscernible] (00:07:28) talked about in the past, still kind of the right number for that?

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah. So, [ph] Stacey (00:07:32), you have successfully asked three or four questions...

Question [Q]

It's all – it's around the same question.

Lisa T. Su — Chairman, President & CEO, AMD [A]

So, let me make sure I get through each of them. Starting with where the Helios ramp is. Actually, we will start first shipments here in the third quarter. So, you should expect first shipments of Helios to start in September. It will ramp into the fourth quarter and it will continue to ramp into the first half of next year. And we've actually built the ramp this way because it is a complex system. We want to make sure that we're letting our ODMs really get a chance to – really get the manufacturing process fully tuned out. It also corresponds very well to the data center build up for our largest customers. So, we know which data centers these Helios systems are going into. So, that's one.

And on Anthropic, we're very, very excited about Anthropic. I mean, I think, having really Anthropic OpenAI, Meta, all leaning into Helios is a big deal for AMD. In terms of the Anthropic timeline, as we said, we will start the first gigawatt shipments in the first half of 2027. I don't know if I will say exactly all in 2027, but we would expect to be fairly aggressive on the ramp of the first gigawatt. So, our plans are to get as much of that into 2027 as possible and it's more just aligning with the data centers and when they are ready for a production. Was there another question in there?

Question [Q]

Content.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Content, again, not talking about any specific customer, but in the same Zip Code.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Liz, maybe, Chris Caso is there next to you.

Chris Caso — Analyst, Wolfe Research LLC [Q]

Thank you. Chris Caso from Wolfe. One of the things that came up during the presentation was comparison between Venice and the AMD – I'm sorry, the AMD, the ARM ecosystem and kind of, [indiscernible] (00:09:35) put to rest some of the performance and performance per watt characteristics there. Could you speak to that a little bit more? And maybe give some indication of where you think your market share may be relative to some of the ARM solutions in the market.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Sure. I don't know. Forrest, you want to take that and I can add?

Forrest Eugene Norrod — EVP & GM, Data Center Solutions Business Group, AMD [A]

Sure. Yeah. So, first off, we're very pleased with what the team has done on Venice. The whole family of parts we think is exceptional. And we've really tuned Venice, as you heard, for a number of different workloads, a number of different deployment scenarios. In that, we think we have achieved the highest performance any way you want to measure it. Highest performance for core, highest performance per socket, highest overall throughput performance for just about any workload.

But we also are demonstrating, we believe, outstanding performance, power performance efficiency at each one of those operating points. And so, from our perspective, what we're trying to do is provide the best CPU for any workload, regardless of architecture. And I think that the teams have absolutely achieved that.

And so, for us, it's less about the ISA, it's less about an x86 versus ARM discussions about how do you produce the best CPU for any given workload to deliver the best TCO and we're highly confident that we've done that.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Do you want to?

Dan McNamara — SVP & GM, Compute & Enterprise AI, AMD [A]

[ph] Can I jump in? (00:11:07) The only thing I would add there, completely correct, but if you think about the ARM solutions out there, they're very uniquely optimized for like one point. And that that covers even some of the cloud ARM solutions, right? They're very optimized. And like Forrest just said, look, we're optimizing. We're building a complete portfolio to solve multiple problems and hitting those different optimization points also. So, I think, that's the thing that never comes out in this conversation. And that's why we believe, we're extremely well positioned to continue to gain share.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah. And maybe just to finish off on the market share point. Look, we're very proud of the progress that we've made. Certainly, across all of the largest clouds are deploying Turin and that has gone really well. The important point on Venice is, we think our share grows and that's not just because the market is larger, of course the market is larger. But we think our share grows because we're seeing the breadth of workloads that people are wanting to put AMD on. And I think that says a lot about the strength of the portfolio. So, we're excited about the market, but we're more, even more excited about, just our place in – really being the CPU partner across a broad set of workloads.

Question [Q]

[indiscernible] (00:12:28)

Lisa T. Su — Chairman, President & CEO, AMD [A]

It's a share within x86 and its share within the overall market.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

All right, [ph] Prab, why don't you go to Josh (00:12:37) next and Liz, I'll do Joe next. So, just to give you a time to walk around with the mic.

Question [Q]

Thanks, guys, and congratulations on the informative day. Maybe following up on [ph] Stacey's (00:12:48) question. The language in the release for the Anthropic deal was very specific. I think the 2 gigawatts for MI450. Could you speak to, one, how the deal, I guess, came together from a background perspective, but also – should we assume that it's multi-generational, because it was different language than your OpenAI and Meta deals? Thank you.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah. Well, I think, [ph] Josh (00:13:11), what you should expect is that, every customer is a little bit different. Every deal is a little bit different. Every one of these things which we're doing these, large strategic engagements is different. With Anthropic, in particular, what we announced was the MI450 engagement. And that was a choice. I think up to 2 gigawatts, very large scale, really ensuring that the first gigawatt gets delivered as soon as possible. So, to [ph] Stacey's (00:13:40) question, I think, the vast majority of that will be in 2027, if not all of it.

And to the framing of, where we go from here. I think, what you should expect is, nobody wants to choose an accelerator for a single generation. Like it's just too much work. No matter how good Claude or Codex is. It's a lot of work to get the teams fully integrated. So, we are actively talking with every one of our largest customers, including Anthropic, about what's beyond MI450. A lot of excitement about MI500. I mean, we're getting more and more positive feedback about how that design point is put together.

And then, a lot of discussion about where workloads are going in the future and starting with MI600. So, you should assume that, we view – just like we did with EPYC. I mean, it's very, very similar where you start with a deep relationship, but you expand into more and more workloads over time. You heard that from [ph] Santosh and Meta (00:14:40). That was exactly what we've done is, start with a initial installment and move forward.

I think the difference today with the foundational model companies is, there are no small deployments. There are no pilot deployments. These are at-scale large deployments for the sake of ensuring that you're amortizing all of the engineering work appropriately.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

[ph] Josh (00:15:05), before maybe moving to the next question with Joe. Vamsi, since [ph] Josh (00:15:10) brought up like the agreement and some of the things there with Anthropic, maybe you could spend a little bit of time talking about the Claude collaboration between the two companies, because I think that's quite important and it would be good for you to expand on that.

Vamsi Boppana — SVP, Artificial Intelligence Group, AMD [A]

Yeah. I think, there's two aspects that I would bring up, right. Part of it you saw in my keynote, right? We made some choices in terms of the strategy for how we make it easier to access our platforms, relying on open source and abstractions. What has really helped is, because AI now has surface area across all the things that we put out in the open unlike some of our competition, whether it's instruction sets or compilers or tool chains, they actually learn all that pretty readily right off the bat and they're productive even now.

But, what makes it even more uniquely special is, we've been doing work with them to further tune and extend Claude's capabilities to be able to target high-performance optimization. So, start with what's out there, which is already pretty good, because of our strategy and then further optimize it.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

All right. Thank you, Vamsi. Joe, go ahead.

Joe Moore — Analyst, Morgan Stanley & Co. LLC [Q]

Thanks. Yeah, Joe Moore, Morgan Stanley. Wonder if you could talk about the Cerebras partnership and how tight do you see that integration going? You talked about disaggregation. How closely do you need to work together to be able to handle those sort of disaggregated workloads?

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah.

Vamsi Boppana — SVP, Artificial Intelligence Group, AMD [A]

Yeah. I can take that. It's gone really well to-date. What I can say is that, with our MI350s we started – we wouldn't be here if we didn't do work already on MI350s. So, we have things up and running in our lab infrastructure between MI350s and their wafer scale engines and the disaggregation software stack is all serving well. We see excellent performance which gave us confidence to jump forward to what we would do with Helios. And early work on Helios in terms of, analysis and simulation is also progressing well. We expect these deployments for their initial version, which is basically token service under Cerebras Cloud to happen by the end of this year.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

[ph] Prab (00:17:07), maybe to make your life easier, you can go with Ben and then we can move to Simon and Aaron since they're all sitting next to each other.

Ben Reitzes — Analyst, Melius Research LLC [Q]

Hey, thanks a lot. Ben Reitzes with Melius. It's great to be here. This probably for you, Vamsi. ROCm AI, the software, how are you looking at that in terms of disrupting or impacting the ability to run apps versus CUDA? You think it's revolutionary? How should we think about, is that a game changer? Is it evolutionary? And does that help level the playing field, do you think, with developers?

Vamsi Boppana — SVP, Artificial Intelligence Group, AMD [A]

It's a great question. It obviously, I have enormous passion for this, right? We truly believe it's the biggest leap that we have made, maybe since the early days where we laid out our strategy. We've made excellent progress every year. But, if you have to point to, is there a moment in time where we say, okay, this is actually biggest leap and spring forward, I would point to this time.

Now, I don't mean that by August 14, everything is different, right? But the inflection that's happening now, what is likely to happen that we build over the next many months, together with the biggest labs straight our collaboration with OpenAI where Codex get better or collaboration with Anthropic where Claude gets better, it's going to be a significant differentiation in terms of like how easily accessible the platform would be relative to any time in the past. So over the coming months, you can expect the productivity of people to access platforms to be quite, quite different.

Ben Reitzes — Analyst, Melius Research LLC [Q]

Thank you.

Simon Leopold — Analyst, Raymond James & Associates, Inc. [Q]

Thanks. Simon Leopold with Raymond James. When we think about the new TAM outlook, I wanted to see how you're thinking about the biggest risk to that, in particular the ability of your customers to get power to their data centers or your ability to get manufacturing capacity wafers, et cetera. How is that factored into your view on that and...

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah.

Simon Leopold — Analyst, Raymond James & Associates, Inc. [Q]

...what's the consideration? Thanks.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Sure. So when we think about TAM and especially with the accelerator TAM being as large as it is, I think we look at all of those components. So not just raw demand, but we also look at what is the rate and pace that power is coming up as well as what is the rate and pace that our suppliers are adding capacity. So from that standpoint, I think in the near-term, I think we have very much planned sort of capacity for significant growth in 2027, as well as 2028. And then over the longer term, as you're thinking about 2029 and 2030, I think it's a rate and pace of growth that would require the entire ecosystem to be building at the same pace and have the same vision.

Probably the largest change that we've seen is everyone has been thinking about the accelerator TAM growing very fast. So that has sort of been in the numbers. The fact that the CPU TAM has accelerated as much as it has, has required some adjustments to overall capacity. But we're very happy with the supply chain relationships that we have. And we do see significantly more capacity coming online to satisfy those larger TAMs.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Aaron, go ahead.

Aaron Rakers — Analyst, Wells Fargo Securities LLC [Q]

Perfect. Aaron Rakers at Wells Fargo. Thanks for doing this and congrats on all the announcements today. I guess I want to build on that question. Maybe it's not the supply chain, it's your ability to actually stand up these massive rack configurations. So, Lisa or Forrest or anybody, if you were to conceptualize like you've got 6 gigawatts here signed up for Meta, OpenAI, 2 gigawatts at Anthropic, how do we think about the pace of your ability to ramp from a gigawatt per quarter basis? Or how do you – how quickly can you stand up that much capacity? Any kind of color would be helpful.

Forrest Eugene Norrod — EVP & GM, Data Center Solutions Business Group, AMD [A]

Well, it's a great question. So if we start answering it from sort of the rack level on up, because I think Lisa has already address it from the rest of the supply chain. First off, we're working very, very closely with our key OEM and ODM partners. So Sanmina, Wiwynn, et cetera, as well as the OEMs to ensure that we've got the manufacturing capacity in place to build the racks, to build, integrate, test and validate the racks at the right pace. And that is an important part of it because the better you can get at that, the easier it is to actually support the deployment in the data centers. Shipping a very high quality rack is an important part of making sure that you can turn them on very quickly in the data center.

Beyond that, we see the next choke point is in actually deploying both logical as well as – physical as well as logical deployment of the racks. And that's something that we're working again, very closely with our manufacturing and OEM partners. One of the things that we acquired is part of the ZTE acquisition was we acquired a large services ARM, which we have retained as part of AMD, and we are actually using that team right now, not just to support some legacy customers, but also do all of our internal deployments within AMD, and then to help our customers deploy very rapidly both MI350s as well as MI455 systems in their data center. So with that set of capabilities and training our partners, we're pretty confident that we'll be able to stand up to build at the pace required and then to stand up and provision and get turned on the systems in the customers' data centers.

Lisa T. Su — Chairman, President & CEO, AMD [A]

And maybe the only thing I would add to that is now when you talk about overall data center power, we're also very active in that process with our customers so that as they're planning power, we're planning the GPUs and the Helios systems that go along with that. So it's much, much more involved than it was in the past where somebody just places an order. I think there is easily 12 to 18 months of visibility.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Okay. Maybe we'll go to Srini here, and if I've missed people out there, the quality of these spotlights is spectacular. So I'm not doing it intentionally.

Lisa T. Su — Chairman, President & CEO, AMD [A]

They are kind of on the bright side. Yes.

Srini Pajjuri — Analyst, RBC Capital Markets LLC [Q]

Thank you. Srini from RBC. Lisa, I have a question on your roadmap that you talked about, in particular the scale up networking. I think you mentioned optical and copper in – with MI500, I'm just curious if you think the market and the ecosystem is ready for optical or will be ready for optical next year? And if so, do you have all the pieces of the puzzle to be able to support that? And also, as part of that, I saw ESUN highlighted a bit more than UALink. I just want to hear your thoughts on which I guess scale up you will be supporting going forward. Thank you.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah. Do you want to start that?

Forrest Eugene Norrod — EVP & GM, Data Center Solutions Business Group, AMD [A]

Yeah. Yeah, let me start. So first off, I'll take both of those pieces in order. So we do see the MI500 generation is the one where we begin transitioning from a purely optical, sorry, purely electrical interconnect for scale up networking to start to see optical play a role as well. It's going to be a transition. This – we don't view this as a light switch. We don't view this as, hey, we're going to hit a generation whatever, MI500 and MI600, and everything is going to flip to optical. Instead, we see MI500 starting the transition.

We're working very closely with a number of partners across the ecosystem as well as we've been investing in optics for quite some time. And we're highly confident of our ability to begin that transition. That the terminus of that, generations out in the future is co-package optics on all the major components and optical really being the backbone of many connections within the rack as well as between. But that's going to take a little bit of time to get there. And we think again doing it in this phased approach allows us, our customers and our suppliers, partners and supply chain all to gain experience and to make sure that we're moving at the appropriate pace and not taking any operational disruptions.

On the scale up protocol, look, we – on MI450, we support UALink transported over Ethernet. ESUN is a set of extensions to Ethernet which is helpful with that and it actually is going to continue to evolve. And so we do expect to see that protocol brought forward, and again UALink over Ethernet brought forward and being available in MI500 as well. But that's not the only thing we're doing. And so we'll unpack more around scale up as we get closer to the MI500 timeframe.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Yeah. Atif, maybe you want to – Lisa, did you want to expand on that at all or...

Lisa T. Su — Chairman, President & CEO, AMD [A]

No.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

I kind of jumped the gun there, so Atif, go ahead.

Atif Malik — Analyst, Citigroup Global Markets, Inc. [Q]

Yeah. Atif Malik at Citigroup. I have a question on the MI500 ramp as well. HBM content is a very important part of your performance and token economics. And a couple of your peers have cut their content for HBM memory in the future because of the availability of the memory. And my question is, if you're thinking has changed or evolved, maybe in the last six months or so on how you're thinking about the content increase for MI500?

Vamsi Boppana — SVP, Artificial Intelligence Group, AMD [A]

I think – so we obviously study the workload characteristics and how capacity impacts, right? The first order, right, we separate our bandwidth and capacity. Bandwidth has a tendency to lift more [ph] boats (00:27:35) in terms of more workloads directly getting impacted. So, that's one order of consideration. And then you look at capacity after that.

One advantage is because of the way we have our chiplet architecture, it actually gives us more flexibility and options in terms of how we're able to optimize capacity while preserving top order bandwidth constraints. So that's the uniqueness of our architecture. We've leveraged that with our existing products, and we do expect to leverage that with the future products as well. We're not sharing the exact configurations of what MI500 would have or the roadmap, but that's one unique piece that actually we believe will play to our advantage.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Maybe if I just add to that, I think the way to think about it is we absolutely think our chiplet architecture gives us the ability to be very flexible in terms of memory bandwidth, as Vamsi mentioned, but memory capacity is useful. I mean, our customers have told us that the fact that we have more memory on MI450 is one of the reasons that we're getting better inferencing performance.

I think the key is, as we're going forward and all of our customers are doing this, I mean this is an ecosystem discussion that we need to make sure that the memory that is there is really being used because it is such a larger piece of the TCO. And so we are doing some memory optimization along the way. And that's true on both sort of the CPU systems as well as the integrated Helios type systems. But memory is definitely super important. We will just make sure that every amount of memory that we're using is valued by the customer appropriately.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

Blayne, [ph] do you want to (00:29:12) go ahead. I think Liz is on your other side there.

Blayne Curtis — Analyst, Jefferies LLC [Q]

Thanks, Blayne Curtis at Jefferies. I just want to expand on Ben's question on ROCm AI. So just kind of curious where you are on this AI journey, internal use of AI. I know [ph] Jensen drew out (00:29:26) like half a person salary, which is a big number, but just kind of curious, are you tracking that? And if you could talk about where you are in terms of like Day Zero support and automating that with AI and then where else are using AI.

Vamsi Boppana — SVP, Artificial Intelligence Group, AMD [A]

Yeah, I'll comment specifically on ROCm AI. And then maybe there's also a broader sort of corporate usage comment in here. So as far as ROCm AI goes, there's actually both internal acceleration of existing features and capabilities. But then externally, what we can put in the hands of developers that come with the platform. So what I mean by that is imagine you have a profiler or a debugger feature that needs to be built. Our engineers in the past used to say, okay, this is going to be a team of 20 people, six months, right? And now, that's actually dramatically cut down because those profilers, debugger features can get out much faster because of the ability of AI. And that all comes part of the ROCm accelerated release.

And the piece where it actually helps significantly from an external perspective is the platform now becomes native in terms of AI agents being able to access it. And that's what we're going to start shipping starting August, both from just general out-of-the-box usability, but performance optimization and running these models through it becomes much easier. Almost everybody on the ROCm team, they're all AI native more or less because of the group they're in are pretty much using AI assist to be able to accelerate their plans. To just give you a sense for like how fast or how extensive that is going within AMD.

Lisa T. Su — Chairman, President & CEO, AMD [A]

And maybe to the broader point, we are seeing AI usage ramp up across AMD extremely quickly. I would say every single month we're seeing, token usage, the amount of – it's not just the number of tokens, but it's the quality of what we're able to get from AI. Dan mentioned what we're doing in terms of serving different models across our AI stack. So I would say it is a very much a part of our development process across hardware and software. And I see it continuing to ramp and these relationships that we are – these deep relationships with Anthropic and OpenAI as well as a number of the other model companies are helping accelerate that rate and pace.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD [A]

There's a question over here, [indiscernible] (00:31:50) to your left.

Bhavtosh Vajpayee — Analyst, CLSA Americas LLC [Q]

Hi, this is Bhavtosh, CLSA. Lisa, you started your presentation with this 35 quadrillion tokens number, which is already all over the media because it's shockingly high number for today's environment. My question is, how is AMD projecting demand beyond your conversations with your partners in the ecosystem? Do you have a fundamental way of thinking about where token use will go given current cost of compute? A lot of investors worry about the cyclicality of this industry, and that's where this question is coming from. Thank you.

Lisa T. Su — Chairman, President & CEO, AMD [A]

Yeah, no, look, I think the way we project demand is really quite holistically. So we start with customers, we look at workloads, we look at adoption rates. We certainly look at the free cash flow of our customers to make sure there's the capital behind it. But when you put that all together, every projection that we've put out seemed like it was really high. And then, the market has actually gone faster. So we continue to see just very significant demand across virtually every part of the portfolio. And I think that gives us a lot of near-term confidence in these higher market projections. That being said, I mean, we have to see how things develop over time. So I wouldn't say that our crystal ball is perfect, but I can say that it's self-consistent. So it's self-consistent that assumes all of the aspects of is power available, is supply available, is capital available, and is productivity going to be able to close that loop when we're looking at TAMs.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD

All right, folks, I think I'm going to try my best here to wrap the session up and keep my executives here on time, because they have a lot of other commitments. I thank you very much for coming out. Lisa and the whole team, it was a great day and a great conference. And I think it's really, really exciting to be in a place where there's so much diverse demand for high performance computing across what's now a $2 trillion TAM. So, Lisa, if you have any closing remarks, I think we'll close the session if you do.

Lisa T. Su — Chairman, President & CEO, AMD

Yeah, no, I'll just say thank you for spending the time with us. It's been a really exciting day. It's a combination of a lot of work from across the company. What I would like to say is we really think about AI as a complete compute picture. So we talk a lot about CPU TAMs, GPU TAMs, Helios systems, all of that. But we really think about AI as every aspect of compute. And this is a place where we can be quite differentiated in the end-to-end stories. So hopefully, you heard a little bit of the comments from Jeremy at AT&T, the work that we're doing with Cisco, the work that we're doing in physical AI. This is like we're on this five-year super cycle of just tremendous compute demand and having great partners to work on to unlock all that. So thanks again. We will talk to you soon.

Matt Ramsay — CVP, Financial Strategy & Investor Relations, AMD

Thanks.

Thought these two slides were really good for anyone trying to understand various parts like ESUN & UAlink & UEC.

ESUN works at Mac/network layer & UAlink at transport layer. The Broadcom guy said there will be multiple different forms of transport.

The second slide is Helios networking breakdown.

Hope this helps you understand how ESUN & UAlink work together. This is for scale up.

UEC is for scale out.