Marvell Technology, Inc. (MRVL) Earnings Call Transcript & Summary

Good morning, everyone, and welcome to Marvell's Investor Day. The entire team is super excited to share our story with you today. Before we get started, let me walk through our schedule and some housekeeping items. On the scheduled side, we'll kick things off with eminent CEO, Matt Murphy, and then transition the presentations from the members of the executive team. And then Dan Durn, our CFO, will wrap things up before we open it for Q&A. We will have a break after Sandeep's presentation. Now let me handle a couple of housekeeping items. . Let me first explain the syntax around our fiscal and calendar years and then our revenue reporting. In today's presentation, we'll be referring to fiscal years whenever we refer to financial data in calendar years, for market data. As most of you know, our fiscal year is basically 1 year ahead of the calendar year. So for example, our fiscal year 2026 actually started in February of calendar 2025 and ended in January of '26. Now moving on to the revenue side. We report our consolidated revenue broken out in 2 end markets: data center and communications and other, nothing new there for you all. To provide additional context during these presentations, we'll be giving you revenue and addressable market trends by the 3 businesses within data center as well, Interconnect, switch and storage and custom. These align directly with the framework that we've been using for the last few years. So there's no category changes needed in your models whatsoever. Now on to some of the forward-looking statements. I'd like to draw your attention to the forward-looking statements. As a reminder, today's presentations contain projections and other forward-looking statements regarding future events and financial performance. Such statements are predictions and subject to risks and uncertainties, which could cause actual results to differ materially. Please consider the risk factors in our SEC filings, which could potentially affect our business and financial performance. These filings are available from the SEC and on our website. Finally, during this presentation, we will be mentioning certain non-GAAP financial measures. Reconciliations to GAAP are available on our website. To that point, all of the presentations you're going to see today will be posted on the Investor Relations website as well later today. With that, we're super excited to see you all here. Let's get started with a brief video. [Presentation]

Please welcome to the stage, Marvell, Chairman and Chief Executive Officer, Matt Murphy.

Good morning, everybody. All right. All right. Good morning, everybody. Here you go. I'm fired up to be here today, are you? Come on. All right. So welcome to Marvell's 2026 Investor Day. It's great to be back in New York and have so many of you with us today. And I have great memories of the last time we were all here, which was about 2.5 years ago. And I remember having lunch afterwards and sitting with a bunch of you, and one of you spoke very fondly of this hotel, you have gotten married here. And another investor at lunch said to me, "You know, Matt, good call on the location at the Pierre, the Pierre is a bull market hotel. And look, I agree from April 2024 to now, it's definitely been a bull market for semiconductors. Hasn't it? Excited to be back here today to show you what the next phase of Marvell looks like. All right. Blast from the past. Let's go back in time. This photo is from Marvell's first ever Investor Day in 2017, and that's me there on stage and a number of you were there. In fact, I can recognize many of you just from the backs of your heads. You could probably find yourself. And by the way, I'm not sure who this young guy is on stage, but he's pretty handsome, isn't he? This is what 10 years as a public company CEO will do to you, okay? But still -- I'm still ticking. I remember the first question I got at that Investor Day after we finished and Chris Rolland from Susquehanna who I think is here today, stood up and very seriously asked me, first question has said, what company is this? Is this Marvell? And there was a reason he asked that question because at that time, Marvell had never communicated ever to Wall Street what its mission or vision was where the company was going. And the company had gone public in 2000, by the way. So most people back then thought of Marvell as a consumer electronics company, right, selling into smartphones, tablets, other digital devices. But look at what we were talking about back then, look at my slide, the explosion of data and bandwidth demand, compute moving towards the data, end-to-end security, the need for power efficiency, this was in March 2017, and we were already talking about the data center, data infrastructure and where we believe the industry was going. Now before Marvell, I spent 22 years at Maxim Integrated Products, which is one of the leading analog semiconductor companies. And one of the great things about the analog business is you get exposure to virtually every end market and every major technology trend. The one third thing I learned from that experience was that the market that you sell into is what matters. It's not just about having the best chip or the best part, the best widget, it's your end market exposure and then your long-term sustainable competitive advantage within that market, that's what matters. So actually, when I came to Marvell, I had a strong point of view about where the semiconductor industry was going and where I wanted to take the company. And that point of view I had was centered on data infrastructure in the cloud even though at that time, most of Marvell's revenue was tied to consumer. Back then, less than 10% of our revenue was actually in data center. And that's what led us to develop Marvell's mission statement. Here it is. So we wrote this in January 2017, about 6 months after I became CEO. In nearly 10 years later, this mission has not changed. It's exactly the same words from January 2017. Now this might seem like motherhood and apple pie today, make high-performance chips that move data, store data, process data, compute, networking and storage, all those types of trends. But I could tell you, 10 years ago, this was unique. There was a category back then called data infrastructure. The whole semiconductor market was defined very differently back then. Remember, recently, I was in a meeting with one of our senior fellows as a long-time Marvell employee big engineering group, and he said, "I remember when Matt first presented this mission statement to us when we were sitting around at Marvell. And I'd already been at Marvell for 15 years, and I remember sitting there watching him and thinking, I don't know what he's talking about. Now -- and then he stood up and said, now 10 years later, I see it, we have actually all the pieces now, moving data, storing data, processing data, all the key elements. We didn't have those back then, and we do now. So that was the vision. And over the past decade at each of our Investor Days, and we've had a bunch of them, we've continued to share our point of view about where we believe the industry was going. So let me show you a few examples. In 2018, 8 years ago, we were talking about AI as a major driver of this center and now a volve across both training and inference. So a long time ago. This is pre-ChatGPT, pre big AI wave. 2020, we were talking about the shift from application-specific workloads to data-centric workloads, with functions like networking, security and storage increasingly moving into dedicated infrastructure silicon. 2021, we broadened that to the era of cloud optimized silicon. This was 5 years ago. And we said that compute, storage, networking, security and optics were all becoming increasingly purpose-built. And if you look at what we were describing back then, those were really the building blocks of what we call today XPU attach before we even had a name for it. In 2024, when we were here in New York at the Pierre, we talked about how front-end and back-end networks were required for AI, and how optical connectivity would be a major driver of the next wave of AI infrastructure. And then finally, the summer, in June, we showed you the breadth of our Cumsilicon capabilities. including the emerging opportunity we call XPU attach and why we believe custom was going to be a major and much larger part of AI infrastructure. So throughout this journey, we've had a pretty consistent point of view where the industry was going, and we've aggressive -- we've invested aggressively ahead of these transitions. But you can have a vision. You can see the shifts, but that is not enough. We had to build this company and the capability to capitalize on the opportunity. So what do we do? The mission in 2017 became the guiding principle for how me and the team allocated capital and architected Marvell over the last decade. In some areas, we invested in strong technology and expertise that we already had inside Marvell. We had a very talented team when I joined in engineering. In other areas, though, we pursued very strategic and quite frankly, very ambitious M&A to add critical capabilities and domain expertise in a number of new important areas where we didn't have that capability. At the same time, though, we didn't just buy things. We narrowed our focus through divestitures, which created significant shareholder value. We received premium multiples for these businesses that we sold, and it allowed us to continue to hone our focus on the data center. But I've got to tell you the real value of the acquisitions we made and those capabilities that we then gained, those came after those teams were inside Marvell and then part of our platform. [Audio Gap] grown our custom business essentially from scratch over the last 5 years. And last year, it was about a $1.5 billion business. Along the way, we've set some pretty aggressive targets, including on this stage back in April 2024. And last year, we told you we expected custom revenue to more than double in FY '28, putting us on half to more than $10 billion in FY '29. We Today, that business is on track against that plan. And based on the opportunity we're seeing, we're raising our FY '29 outlook for this business. We now expect custom revenue in FY '29 to more than triple from FY '28, reaching more than $12 billion and putting us well above our prior $10 billion target. Now this update to our expectation is primarily driven by the rapidly expanding XPU attach opportunity we see in front of us, including the strategic agreement that we announced in August. The XPU attach opportunity continues to expand every day. And more importantly, this is not a single customer, and it is not a single socket. We're seeing a broad set of product wins across multiple customers and multiple programs. spanning all the areas I just mentioned. That's what gives us confidence to raise the outlook from more than doubling to more than tripling. Thought you digest that one for a second. All right. So let's take a step back and look at the market opportunity. By 2030, we expect total data center CapEx to reach roughly $3 trillion, growing at about a 35% compound annual rate starting from calendar '25 to calendar '30. And importantly, that assumes that the current rate of CapEx growth moderates over that period, moving closer to historical levels in the outer years. As you guys all know, we're growing faster right now than the 35%. So in our model, we expect some normal deceleration to a more normal base case in the outer years. Now within that, accelerated compute represents roughly $1.6 trillion of TAM opportunity. And within that infrastructure, we see approximately $385 billion of data center TAM addressable by Marvell. And when you add in the opportunity and the rest of our business in communications and other, that represents another approximately $15 billion. So when you put it all together, we see an approximately $400 billion total addressable market, all in for Marvell by 2030. And that market that we're addressing is growing at a 45% compounded rate from 2025 to 2030. So it's growing faster than CapEx. And to put that in perspective, just so everybody knows, there's a lot of big TAM numbers out there these days. But for us, the last time we laid out the TAM for the company, it was less than $100 billion. So this is a 4x increase to our TAM opportunity that's occurred. That's how fast the market is moving for us. And the growth, though, which is a good thing, is not concentrated in just one part of the business. So let me dive deeper and show you what's underneath the $400 billion. All right. There's a lot of numbers up here, so let me take -- just give you a minute to absorb them, but I'm going to start at the top and work my way down on the TAM. So in interconnect, we see the TAM growing at roughly 65% annually, reaching approximately $65 billion by 2030. And as scale-out continues to grow and new opportunities emerge in scale up and scale across. In switching and storage, we see the TAM growing at roughly 40% annually, reaching approximately $85 billion. Now this is driven by continued growth in scale-out switching and then the new emergence of scale-up switching. In custom, the market is expanding dramatically. We see the TAM growing at roughly 55% annually, reaching approximately $235 billion by 2030, driven by the growth in XPUs and then the layering in and emergence of XPU attach on top. And Communications another adds an approximately $15 billion. So put it all together, you get the $400 billion TAM I showed you, growing at 45% annually through 2030. So look, these are all very healthy growth rates, but I want to point out interconnect stands out at roughly 65% compounded growth over the period. So as I said earlier, when you look at where the growth is coming from in the industry, it's connectivity. Now this breadth gives us the confidence in the overall growth potential of the company even if the exact mix over time evolves and changes. Now let's look at what all of this means for our revenue outlook. In FY '26, as I said, Marvell generated $8.2 billion in revenue, and this year, we expect approximately $12 billion, so that would be 47% year-over-year growth looks great. We're excited about that. On our August earnings call, we raised our outlook to approximately $18 billion. That represents 50% year-over-year growth, showing that even as the company gets significantly larger, our growth rate is actually accelerating. Now today, we're raising that outlook again. We expect approximately $20 billion in total company revenue in FY '28, representing about 67% year-over-year growth. And then within that, we expect data center revenue to grow approximately 80%. Now when we raised our FY '28 outlook in August, that increase was driven by interconnect, scale-up optics and switching. The additional $2 billion of growth we're seeing for next year is being driven by the same trends. Scale-out optics continues to accelerate, scale-up optics continues to grow, and our switching portfolio is firing on all cylinders. So once again, it's connectivity leading the race. Okay. Now I'm going to put this $20 billion in context for [indiscernible]. So if you take a step back, when we were here in April 2024 on stage at the Pierre. The prior year, we had just printed $2.2 billion in data center revenue, which is our FY '24. At the time, we told you we believe we could grow our data center business to $15 billion by FY '29. That was going to be 7x growth in 5 years. And I think people had a hard time wrapping their head around it. And I know it was ambitious. I got it. It was ambitious. A year ago, in June, we had our custom AI event, and we just -- we basically said, look, the opportunity is developing faster than we thought. So at that time, we were raised our FY '29's data center revenue from $15 billion to approximately $18 billion. In other words, the target we had said a year earlier was already moving higher. Okay. Now I'm going to show you where we are today. With the $20 billion in total company revenue we outlined for FY '28, approximately $18 billion is going to come from data center. That means we now expect to reach the $18 billion data center target we set for FY '29 almost a full year early. Now that would represent roughly a 70% compounded annual growth for our data center business over that period from FY '24 to FY '28. Okay. So stepping back for a second. So we've put some ambitious targets in front of you over the last few years, and the Marvell team has executed. We've gone from $2.2 billion in data center revenue in FY '24 and we've got a plan to go to $18 billion next year. We're hitting our goals, and we're doing so earlier than planned. So with that perspective in mind, let me now show you how we're thinking about the opportunity from here as we forward. So for our purposes of our Investor Day, we're going to set our growth plan starting with FY '26 last year and outlined the opportunity through FY '31. This matches the TAM framework I showed you earlier, from CY '25 to CY '30. Okay. So in F '26 of the $8.2 billion, $6.1 billion was data center. And I showed you just now the plan to get to $18 billion in data center revenue in fiscal '28 with $20 billion total company revenue. So during that period, FY '26 to '28, that's about 70% growth in our data center business, compounded. And if you remember, that's about the same growth that we were looking at from FY '24 to FY '28. So basically, we've been growing pretty existently since calendar '23 in our data center business. Now for FY '31, we have a bottoms-up plan that I'm going to walk you through shortly. This is not just topped down. I'm going to walk you through the bottoms up in just a moment. But let's start at a high level. Looking forward from FY '28, if you assume the $20 billion total revenue plan and you roll up by customer and product and design win and you layer it up, we see a path to continue growing our data center revenue at roughly 70% annually through FY '31, despite the moderating CapEx assumptions. But look, it's a dynamic market. So today, for our -- when we talk about our revenue goals, we're going to give you ranges okay? And so for the -- at the top level, we're going to put a range starting at 55% at the low end. So taking that 55% to 70% growth range, that implies data center revenue of approximately $67.5 billion to $87.5 billion in FY '31. Now if you add in $2.5 billion for comms and other, you get a range of $70 billion to $90 billion in revenue for Marvell in FY '31. I'll let you digest that for just a second. I understand. The absolute numbers are large, but the growth rates are at or below what we're already delivering today. So those numbers in mind, let's take a step back and look at the company as a whole. $8.2 billion in revenue last year in FY '26, plan to deliver $70 billion to $90 billion in 5 years, $80 billion at the midpoint. That would represent 10x growth over a 5-year period and 55% to 60% compounded annual growth over the same period. Now that's the growth framework behind the long-term outlook that we're setting today. These are very strong growth plans, but what gives us conviction is not the top down view. This is a bottoms-up plan, and we have a history of delivering at these growth rates. All of this is grounded in business we have today. our customer positions and the opportunities that are already right in front of us. So let me now walk you through what underpins the bottoms up. Here we go. Okay. So I'm going to walk you through one by one, each business and what gives us conviction in our outlook. So let's start with Interconnect. Scale out has been an incredibly strong business for us. And in the last few years, that business has been roughly doubling each year. In this model, we actually assume that, that growth rate moderates over time. At the same time, though, I want to say keep in mind, we're just beginning our transition to 1.6T in volume in the market, and we have 3.2T ahead of us. And on top of that, scale out, which you're going to hear from Russ on, has a very, very strong future. And in scale across, we already have a very strong position with new use cases for that market that we're going to hear about. And scale up optics, which is part of this, that's all in front of us. We have virtually no revenue in this area today with strong growth beginning next year, and we already have significant traction. So on interconnect, what we're assuming is actually pretty straightforward, maintain our positions and scale out and scale across in a very high-growth TAM market and then execute on the scale-up opportunity in front of us. That's what we've got to do. We execute that plan that gets to $37.5 billion at the midpoint in FY '31. Now let's look at switching and storage. Storage is already a $1 billion-plus business, and we assume it continues to grow at a double-digit rate. In scale-out switching, as I said earlier, we're going to be well north of $1 billion next year, with our 51.2T product just ramping in its first full year of production and our 100T product still in front of us. Now based on the customers and programs we already have we see scale-out switching becoming a multibillion-dollar business over time. Then on top of that is an entirely new opportunity in scale out scale switching. We already have deep multiple deep customer engagements in this area today. And as they materialize, those are going to provide another meaningful layer of growth in our switching business. So when you put those pieces together, we see line of sight to approximately $10 billion in switching and storage revenue at the midpoint. Okay. Now there's custom. And custom might be the simplest of all of them. I just showed you that we expect this business will reach more than $12 billion in FY '29. Our existing XPU programs are on track, and we're assuming that those programs ramp into that plan and continue to grow at a normal rate from there. On top of that, though, is the rapidly expanding XPU attach opportunity, supported by the design wins in our strategic customer agreements. And just to be clear, we've taken a very pragmatic view in judging the total opportunity covered by the large agreement we recently disclosed. So if you start with more than $12 billion in FY '29, the growth we're assuming from FY '29 through FY '31, is roughly in line with the market. We think it's a very reasonable assumption given the programs and the customer positions we have today. And that gets us to approximately $30 billion at the midpoint in FY '31. By FY '31, we expect custom at that time to be much more balanced between XPU and XPU attached sockets with no single socket concentration. Finally, in comms and other, we are assuming that we just maintain our position with very modest growth over the period. So that gets us to approximately $2.5 billion at the midpoint. So when you put all of that together, that's the bottoms-up case behind our $70 billion to $90 billion FY '31 target. And when you look at the assumptions behind each of these businesses, I think they're very reasonable. These are businesses that we have today, customer positions we already have and opportunities that are in flight and in execution that are going to -- and the opportunities are continuing to develop. We feel very good about our ability to get there. It's pretty exciting, isn't it? It's exciting. Thank you. I'm excited. We're excited you're going to hear about it today. Okay. So I'm going to wrap it up here and bring it all together for you. And this is why invest in Marvell. I've given you a lot of big numbers today. So let me just take a moment and recap the ones I want you to remember. By calendar, we see approximately $400 billion of total addressable market for Marvell. That's up 4x from the last time we updated you. In FY '28, next year, we expect approximately $20 billion in total company revenue, up from the $18 billion outlook we gave you in August, driven by connectivity. In custom, we expect FY '29 revenue to more than triple, reaching more than $12 billion, putting us well above our prior target. Looking out to FY '31, we see a path to $70 billion to $90 billion in annual revenue with $80 billion at the midpoint. And as you'll see throughout the day, we're positioned as an ideal partner for all these hyperdata center customers with deep, trusted relationship and years and years of working together. They look today at Marvell as their primary connectivity partner, and we're deeply embedded across their entire architecture. So although the overall data center market by design, concentrated among these hyperscale customers, Marvell has built an incredibly diverse business with hundreds of products being delivered across this customer base and no single socket controlling our destiny. So when you see that kind of revenue growth, you're probably already doing the math. In fact, I see a lot of heads down in the audience on your PCs, look up, stay with me, hold on, we're almost there because of what you're doing, and you're probably wondering is, well, what's the earnings power for such a company of such scale. I'm not going to give you that now. I'm not going to do it. We have a new CFO at Marvell. He's outstanding, and his name is Dan Durn. He's been with us since June, but I've known him for a very long time. This is Dan's first Investor Day with Marvell, and I certainly don't want to steal a thunder. Dan is going to come back later and show you what this growth can mean for Marvell's earnings power, put it in the context of the overall financial model, gross margin, operating margin, EPS, the whole 9 yards. So for now, I've given everybody the revenue as a starting point. Okay. Before I wrap up, I want to recognize the Marvell team that makes all of this possible. None of what I've shared with you today happens without the incredible work and commitment of our employees all around the world. And for everyone at Marvell watching and listening today, thank you. I've been at Marvell for a little over 10 years now, and I've never been more excited and fared up about where this company is headed. We have an incredible team, the right technology, deep trusted relationships with the most important significant customers in the industry and relationships that we've built over many, many years. And we have an opportunity we're looking at in front of us. that is larger than anything we've ever seen before. I truly believe the best is still in front of us. So thank you so much, everybody, for joining us today, and I'll talk to you guys later during the Q&A. Thank you.

Please welcome, President and Chief Operating Officer, Chris Koopmans.

Good morning. It's great to be here with all of you today talking about this massive opportunity in front of us. past summer, also marked my 10-year anniversary of Marvell, and I've had a blast. But I'm here to tell you that our best opportunity our most exciting times are in front of us. We spent all these years building this platform and this company for this moment. And I'm going to talk about how we've been doing that and how we've been planning to scale this company. I'll talk about it along these 3 pillars. I'll start off talking about our customers. Where are we focused and how do we win? I'll talk about our core engineering in our system, however we set up the scale to deliver for our customers. And I'll talk about the relationships in securing longer capacity in the supply chain. Let's start with our customers and where we see the overall TAM going. Last year at our custom AI event, I showed that analysts were forecasting about $1 trillion in total data center CapEx by calendar 2028. And that was showing basically a modest 20% growth CAGR from going forward after a really strong growth year in 2025. I remember when we put the $1 trillion up there, we kind of stuck in my mouth, I was at $1 trillion, like that's a lot of money. Is this a little bit crazy? And then you fast-forward 1.5 years, and it wasn't cracy at all, actually. We had 2025 over $700 million. And now we're hitting over $1 trillion this year already. Clearly, this is a fast-moving market and one that's hard to forecast, and it's growing faster than anybody expected. As Matt said, analysts are now forecasting over $3 trillion by calendar and that's after a much faster '25, '26 and even '27, we're still expecting CapEx to moderate over time to about 20% after that. And this is the CapEx envelope that all of the numbers we've shared with you today, okay? The total market, the $400 billion TAM, all the revenue targets, that's the assumption of the total data center CapEx. So if you look inside that data center CapEx, the top 10 or so hyperscale customers are actually driving over 60% of that last year. And as large as they are, they're actually expected to grow their spend even faster than the overall TAM, reaching more than 70% out in calendar '30. That's astounding. If you do the math, that means that these type of companies are 200-plus billion TAMs each. And if you look within that, the top 4 U.S. hyperscalers alone were more than half of total data center CapEx last year. So you can see that any customer strategy in this market really needs to be hyper-focused on those companies. And it's not just the largest economic opportunity. These are the technology leaders in the world. And so any -- the focus that we put on them will pay dividends throughout the rest of our customer base. In fact, we have architected this company to be the perfect partner to the hyperscalers. They're large and sophisticated operators. They've been designing and deploying complex infrastructure for decades. They actually define what it means to operate at scale. And they've seen in the real world how these workloads interact with the underlying architecture and they have a point of view for how to optimize that architecture for the future in evolving workloads. What they need is a broad portfolio of connectivity technologies to stitch it all together. And at every hop in every distance, Marvell has a full portfolio of capabilities. Our teams are able to sit together and make bandwidth, reach, power and manufacturing scale trade-off decisions and literally co-architect future cloud data centers. So at Marvell, we are laser focused on these top 10 hyperscalers. In fact, within that top 10, we can hit the vast majority of the goals that Matt laid out with the top 4 U.S. hyperscalers alone. We aren't counting on some major new customer win or a new home run design win. We need to focus on this finite set of customers and execute. So we've been doing this for a decade now. And our typical customer journey starts off with an off-the-shelf system, a branded storage switch optical module with Marvell silicon inside. This is how these hyperscalers get experience operating networks with Marvell chips. The next step is often to build a custom system with Marvell standard silicon inside, optimized for their overall network design. Next, they will often ask for a custom feature or maybe they want to put some of their IP in an otherwise standard chip, adding their secret sauce and adapting it to their own network topology. The last step is a full custom engagement where all the IP that they've been using in those standard products for all those years is brought to market in a fully custom piece of silicon designed for that customer. But we're not selling custom silicon to customers who aren't also other parts of our platform. We're not an ASIC vendor. Give us a call if you want a custom -- we're not a back-end services company with layout engineers hanging around. We're not a manufacturing company. I call us if you need some wafers. We are a connectivity leader building deep partnerships with the large hyperscalers in the world. So in the end, this is a full platform engagement, merchant all the way through custom. I took a look at that fiscal '31 forecast that Matt was talking about, and I broke it down by product and by customer, we're talking about hundreds of products across this hyperscale base, just the top 10. If I look to the top 4, more than 35 sockets, millions of dollars each to deliver that forecast. This is an incredibly diverse hyperscale data center engagement. So at Marvell, we are really good at building these strategic engagements. We've actually publicly disclosed strategic agreements with 3 of the 5 largest companies in the world by market cap. Each of these agreements is totally unique and tailored to the individual situation built on top of years of collaboration. Our first announcement was with AWS in 2024. It was a 5-year agreement covering custom AI products and a broad swath of networking and continuity products, including switching data center interconnect and optics. Last year, we had our co-packaged optics technology to the agreement after our Celestial AI acquisition. Earlier this year, we announced a strategic agreement with NVIDIA. This, again, was a very broad and very strategic agreement covering optics and photonics, scale-up network with NVLink Fusion and AI RAM. Most recently, the announcement was with Google. And this outlined a total of $120 billion opportunity over 6.5 years for custom products attached to the TPU ecosystem. That's in addition and separate from all the connectivity business that we do together today. All these partnerships are multiyear, multi-product, multigenerational in nature, and they're all on track in execution and delivering value for both parties. These agreements are a natural evolution of our partnership. Usually, when we've already been working together for years at or nearing $1 billion a year in business together with rapidly expanding design win funnel. That's typically when these sorts of discussions start. How do we move towards a win-win partnership, aligning interests on both sides. So we are very strategic with how we approach these agreements. Now let's talk about how strategically we approached scaling our engineering systems and organization in the company. We have been preparing for this growth for a long time. We've been consistently investing in R&D ahead of our revenue growth. Just take an example, look at fiscal '24, where Matt mentioned that we had done $2.2 billion in data center revenue. We spent $1.5 billion in R&D that same year, the vast majority of which was into the data center end market, which means we were investing well north of 50% of our revenue back into R&D to drive Marvell's growth. And it's worked. If you take last quarter, fiscal Q2 of 2027 and you annualize it, we quadrupled our revenue in data center to $8.7 billion. So we are consistently investing heavily in our R&D to drive Marvell's growth. And we're making these investments in strategic R&D centers around the world. We're not just hiring from our competitors. These are very unique skill sets, very hard to hire people. So we're doing it right. We're building a long-term talent pipeline at Marvel. We're partnering with the local universities in each of those countries where we have these R&D centers set up. We're partnering with specific professors, and we're funding their research in things like optics in analog mixed signal design. We're partnering with -- we're also helping to influence the curriculum to make sure that the talent comes out with the right skills that Marvell needs. And we're funding scholarships, more than 200 students are funded by Marvell scholarships every single year across more than 50 universities around the world. And that brings us to our internship program, which we started in a decade, growing in every year. It's now more than 500 students annually, the vast majority of which convert to full-time Marvell employees over time. Put it all together, Marvell has become a premier destination for talent. A company people actively seek out and want to come and work for. And recruiting talent is only half the story. When they come to Marvell, we arm them with the best tool set in the semiconductor industry. We have embraced and adopted AI tools throughout our design flows. We've deployed an ever-increasing pool of agents for common tasks, automating design, simulate, fixed loops. And we've built homegrown tools such as the Marvell design assistant. This is the proprietary homegrown tool that we built in-house with our own data and our own decades of experience designing chips. We launched it over 2 years ago and has grown dramatically since. It now found -- becomes the foundation of Marvell's AI-native workflow. And the results are dramatic. We now see engineers with 5 years of experience delivering the results that it used to take an engineer with 15 years' experience on a traditional tool set. And it's not just making engineers more productive sooner that's happening. We're actually accelerating and shrinking the overall design cycle. We're shrinking the time from concept to shipping silicon allowing us to iterate more quickly on designs, find issues early and adapt quickly. This is really important in the age of ever-shrinking hyperscale design cycles. And none of this would be possible if we just kept doing it the way we always had. And that includes moving to the cloud. One of the advantages of working with the largest cloud operators in the world as we see how differentiated and performance their technology stack is. So we went all in early in announcing our first deal with AWS in 2023 to move our EBA into the cloud. We invested ahead of the curve when it wasn't the obvious choice. In fact, my IT team told me at the time, Chris, this is going to be more expensive if we do it this way. But I knew where Marvell was going wasn't going to scale without the cloud. So we've worked closely with our entire tool set, all of our EDA vendors and our cloud to optimize the complete flow and move it all into the cloud. Today, more than 80% of our total compute infrastructure is in the cloud. So may be wondering how does this matter? And does this actually help? Let me give you an example. Last year, we won a design win that we didn't have service provision for. Within 60 days, we had 30,000 new cores and over a petabyte of data provision and engineers productive and working in the cloud. 90 days later, that was up to 70,000 cores. I can't even imagine how this would have been possible if I had people running around looking for servers and data center space to deploy it today. completely impossible. And by the way, that same chip, we were able to tape out in less than 9 months. It's in the fab today, it will be delivered it to our customers next year. Now let's talk about our supply chain, a critical part of Marvell scaling journey. Everything I said about focusing on fewer customers plays out 10x in the supply chain. It's all about trust. These companies are buying buildings, hiring engineers and buying equipment for products that are going to be delivered 5 years from now. So they need to trust you. They need to know you're going to be there. They need to know your demand is real. So our strategy is to focus on a small number of critical suppliers who are the best in the world at what they do. These relationships often go back to the founders of these companies. When I took over operations in early 2021, Matt and I went on a sales campaign. We can see where all this was going. So we built relationships deep into the supply chain, not just foundry, but substrates, packaging, you name it. We need a complete set of relationships all the way through. And we told them our story, where do all these chips fit? Why are they critical why should they bet on infrastructure at a time that they were seeing unprecedented demand from stay-at-home-driven consumer end markets. We show them how diverse our platform is, how when anyone wins, Marvell wins. Because these suppliers are very sophisticated. They're very experienced in this market. They've been burned many times, and they're really wary of the 1-chip moonshot customer. So these trusted relationships are also built on a track record of doing what we said we were going to do year in and year out. So we made the decision again to give our suppliers a 5-year forecast. 5 years, like who does that? But that's what you have to do today. You can't just show up and say, how many wafers can I get next year? You needed to tell them 5 years ago, how many wafers you were going to need. So in order to do that, we invested in a world-class data-driven business intelligence platform. have every piece of data at my fingertips today, every customer's forecast. What are the products? How has it evolved over the last 8 quarters? What are all the pieces in the supply chain? How much capacity have we reserved? This isn't just an MRP feed. At Marvell, we have architectural insights across the stack. We know what's going on. So we build this forecast. I review it with Matt and the Board every year, and we give these suppliers an early look, and we've been doing it now for 5 years. so they can see how we've performed over that period. That fiscal '31 forecast of $70 billion to $90 billion that Matt put up, that might have been a surprise to some of you, not to our suppliers, Matt and I have visited these CEOs, shown them our forecasts, asked them if they could get us there, shook hands and we are now hand in hand to deliver those results. And the very last step is a capital investment for capacity reservation. This isn't where you start. You can't just show up with the checkbook and say, how much capacity can I get? They'll just tell you to go away. You needed to have build a trust, shown them that you have a track record. And then yes, we are investing ahead of our growth to reserve the capacity. This is to cement the relationship and put skin in the game for our forecast. This is how you build a supply chain that can grow at the rates we have been growing and will continue to grow at. As you can see, at Marvell, we are not short-term thinkers. We are building for the long term. We have deep trusted relationships with the largest customers in the world. We've built a talent pipeline and tools to feed our growth and keep the company scaling. We have a supply chain that we've built based on trust with the critical suppliers. We are the best in the world at what they do. My team and I are ready to deliver that $70 billion to $90 billion that Matt laid out. We've grown the company 4x in the last 6 years. We got all the demand and the supply I need to hit the $20 billion next year. We can certainly ForEx from that with the wind at our back. We don't need any new home run design wins or any new sockets. We have what we need today. We need to execute, deliver them to market and put them into production. And I'm here to tell you that my team and I are going to deliver that forecast. Thank you.

Please welcome, President Data Center Group, Sandeep Bharathi.

Good morning, everyone. I'm very excited and delighted to be here today. Every dollar that gets spent in the next 5 years by the AI hyperscale data centers and our customers will run into the same 4 constraints or was, bandwidth, latency, power or energy efficiency and data center reach or the distance data has to travel. So before I get into that, let me tell you and for the next 15 minutes, why Marvell is best positioned to solve those barriers and those challenges. But I wanted to give you my origin story. Eight years ago, Matt invited me to dinner exactly 8 years ago. And he laid out his vision for how he's going to transform Marvell to be a data infrastructure company. This was even before AI. He told me and threw me a gauntlet at how I have an opportunity to transform the product strategy, technology, execution and build the team to take it to the next level. I signed up to the challenge, and that's when my journey at Marvell began in February of 2019. So in 2020, if we go back to the Investor Day, I presented a 3-pronged pillar based on process architecture and design to transform Marvell to be the leading silicon provider for data infrastructure. And let's go through this. On the process side, we had to pivot because Marvell was historically a process fast follower. We were on technologies, 1 generation or 2 generations behind, but implementing products such that it was already energy-efficient but a fast follower. It had architecture to do WiFi and storage products about 200 square millimeters, but we had to pivot the team and the technologies to do reticle size chips, then came design and analog mixed signal IP that needed to be for the data infrastructure market had to be high-speed, high-bandwidth surveys. We already had 28 gig and 56 gig, but that had to transition to higher data rates more like 100 gig, 200 gig at advanced nodes. And let's see where we ended in 2026. And I'll go from the top process technology. This was a very important challenge. Matt wanted me to get a team to the next node. We were on 12- and 16-nanometer and this was a company betting moment where we skip 7-nanometer and went to 5-nanometer. This is very difficult to do. And not only did we do this successfully in the years 2020 and 2021, we continued with leading-edge process in first in node with all the IP shuttles with our foundry partners at 3-nanometer at 2-nanometer, and we are already on 1.4 nanometer or 14 angstroms. And not only that, we have transitioned from less than 50% A0 to production. What is A0 to production mean? A0 to production means you need to get it right the first time, measure twice, cut once, but we measure many times and the masks get cut once, so we deliver time to market to the customers. Again, next is from an architecture standpoint, we wanted to deliver radical size dies. The ones that will and they were going to talk to you about. 200 Square millimeters and the reticle size die is about 856 to 858. This is defined by the lithography limits and process technology that we can do today. And I'm here to say we have industry first monolithic 1000 switch. Nobody has that. Dave will talk all about it. And we have about greater than 10 products at square millimeters and beyond shipping in volume and production. And Will is going to talk about his XPU and expertise where we have accomplished that. So we have completely transitioned for not only on process technology, but also architecture. And when you take a look at these large dies, why is it hard? It's hard because, let's say, you have a 856 square millimeters. You may get maybe 30 or 40 dies and you need to get it first time right, because you need to have the methodology and the team to execute flawlessly to ensure that they account for defect density, signal integrity and many other laws of physics in the silicon to optimize these architectures and get it first time right. Now let's talk about design. We were best-in-class IP portfolio, but fast follower, but we had to invest significantly in our technology to get leading-edge IP at 28 gig, 56 gig, 100 gig, 200 gig and 400 gig SerDes. And just in ECOC and OFC, we have demonstrated in silicon. This is just not theory. It is actually done in multiple process technologies, and we have industry's best in class sees at all these data rates. So we have delivered and proven at every step, and this is foundational for Marvell. Now let's talk about what is AI token economics. In the building of the data centers you get into the same barriers that I talked about, bandwidth, latency, energy efficiency or power and distance or reach. And what everybody is optimizing for total cost of ownership is really about delivering the maximum tokens per dollar per megawatt but you also want to have the performance or the interactivity of the user. Whenever a query served, you need responses immediately on the tokens, whether it is on research on LLM or even other applications that people are interacting with LLM. So what happens here is AI is no longer a silicon problem, it is a system architecture and the data center connectivity challenge that Matt talked about. Now in order to increase performance, we need to take a look at all the constraints and let me talk about the walls that you will run into, starting with the first one, the memory one. The best way to think about it is an example of the human brain. The plasticity of the human brain gives immediate access to memory with the compute, it's so intertwined. Let's say, for short-term memory, you will remember what you had for Brexit today. are from long-term memory, you will know what you studied in your universities. So in an ideal world, you want infinite memory, uniform latency and a very high bandwidth interaction. Now how is that achieved in the real world. In the real world, the memory wall is because of the hierarchy of memory that exists in the compute architectures and system architectures. XPU has a distance chasm to get the HBM memory or when you have a pool of accelerators or excuse, they need to access not only HBM, but tools of DRAM. So memory wall is a real bottleneck for performance for AI infrastructure scaling. And how is Marvell positioned to take advantage of that is memory wall as a shared resource, we have multiple technologies that Will is going to talk about in his section, we have controllers that can spread and reduce the latency or memory access. Compute Express Link technologies in our Structura family for memory expansion and pooling, again, bringing memory as close to the compute as possible. Photonics interconnects for memory disaggregation and Dave will talk to you all about those applications. And not only that, influencing accelerators and the performance needs very high density, highly capable SRAMs very close to silicon, and Will, will go into further details about that. So re-architecting systems using all these technologies is what Marvell is excellent at, bringing memory closure to scale up fabric from forever from all the history that we have had with these products. Now let's take a look at the next wall. It is the reach on the copper wall Matt went into considerable detail on this, but what I'm here to tell you is the copper wall is extending all the way from clusters of AI compute to coming to rack and tray. The reason is, today, if you want to transfer or transmission, a large amount of data movement, the short line of silicon and the tray is physically bound. And in order to get maximum amount of data transmission with the highest bandwidth, you need to get optics into the system, into the scale of frac because today, scale-up represents greater than 85% of the data center traffic. So optics scale-up optics is here and now. So solving the scale of bottleneck is the biggest gain we can do. Dave is going to talk about the scale of optics and cross scale out and scale across. Xi and Russ are going to go into further more detail. Now let's take a look at how Marvell is positioned to bring scale-up optics into this system, we are integrating silicon photonics onto the silicon, onto the substrate to enable the scale-up optics revolution. If you just take a look at the entire gamut of technologies we have at our disposal, we were already leaders in different modulation schemes. Optical modulation schemes are very important for getting the reach, bandwidth distance and the energy efficiency that every application needs. It's very different. It's not a one size fits all. So you have Mark vendor modulation for distance is greater than 20 kilometers plus. Not only that, for within the silicon if you want different modulation for highest energy efficiency, you have micro ring modulators, different modulation scheme. Then Dave is going to talk about the photonic fabric and the electro-absorption modulation, different modulation scheme. And scale in interconnects have newer micrometer technologies like micro LED and micro cells. Xi is going to talk all about it. So what is this actually telling you that is telling you is data movement challenges for those constraints require multiple technologies. So this is the core bet Marvell is making. And we have the industry's largest optical talent. Chris went into how we have enabled talent and building these teams, and this was just a decade in the making. So we have the most brilliant optical engineers, making all these technologies happen at scale proven in silicon. Now let's take a look at the common technology foundation that we are enabling across all these products. I've already talked about how Photonics is a key piece of our Marvel competence. Not only that, you have advanced node in process, analog mixed signal, advanced packaging to solve every reach because ultimately, to solve those constraints, it is not just about compute. It is about connectivity because if the connectivity is not solved, then intelligence or access to compute means it's stranded compute and lose intelligence, not usable intelligence. So let's take a look at what are we doing on the process technology. It is going beyond CMOS. Obviously, we talk about nanometers, but nanometers itself doesn't solve the problem. It is the table stakes to play in the market. However, we also have advances a silicon germanium indium phosphide to implement and produce highly capable TIAs and drivers. Xi is going to talk all about how this is a key core part of its portfolio. Silicon photonics. This is where scale across is being enabled, including distances from 2 kilometers to 1,000 kilometers. Russ is going to talk all about it. Advanced material science research, thin film lithium niobate. We work with advanced foundries across the board to bring technologies of the future. And this is here and now. Five years later, we are taking a look at what it's going to be for high-bandwidth, energy-efficient applications. It's plasmonic, that is also being invested in today so that we can have products 3 to 5 years out. So this is about technology enablement even before products are released 3 to 5 years out. So we are fully integrated, process agnostic, foundry ready and future proof. Now analog mixed signal is the heart of the data movement challenge. Why? Because high bandwidth and low latency requires SerDes. And SerDes is a very critical technology. And if you take a look at what we have today, we have demonstrated and shipped SerDes high-speed, whether it is optical or electrical at 100 gig, 200 gig and 400 gig has already been enabled in products which will be shipping in volume next year. That's 8x growth in detrade in 6 years. And SerDes is just not the only technology that is important for delivering on our products. For XPU and XPU attach because they're more than 8 or 10 does inside the package, you need highly capable die-to-die interfaces, and you might have heard Pico jewels per bit as a currency for high energy efficiency, we have advanced die-to-die interfaces to enable the communication and the data movement between these dies. And bringing it all together at the architecture level, you use these SerDes so that there is important constraints to be understood at the system level or the trail level or the package level when we have to connect XPU attached devices to the XPU that requires advanced system level, simulation and technologies that we already have built and enabled and shipped in volume. So Marvell SerDes leadership and advanced mixed signal is in here now proven in volume for every reach. Let's take a look at the most important technology that's also in not only compute but also high-density switches. It's our packaging innovation. I talked about many of this in our June 2025 event. In the past, you had 2D packages, single die, very simple to do. then it went to 2, 2.5D wherein you have multiple dies on chip on wafer on substrate or any other silicon interposer material. But now where we are seeing this move to is integrating die on die, meaning bringing advanced memory on a logical die or multiple logical dies on a package, Graben 8, possibly 10 to 12 all the innovations that are important in packaging is critical because these substrates are greater than 100-millimeter on the site going to 150 millimeters on the site. And some of the samples Dave is going to show you not only that, because of the copper wall, optics scaling comes into the package, we also innovate on core packaged optics. So it's full integration and codesign to scale in volume. And these are the capabilities that you need in every single product that we ship. So I have talked about a multitude of technologies. It's easy to say, well, we have CMOS. It's easy for a company to say, well, we are excellent at silicon germanium or we are excellent at silicon photonics. But what I'm here to tell you is it requires just not one technology. It requires advances in packaging, all the capabilities in foundry analog mixed signal all under one roof, and that's how we are well positioned to capitalize on the opportunities that Matt talked about. This is foundational, and this is technology at its very best and bleeding edge. Industry-leading core technology across all these domains means it's process and packaging, IP and architecture and system-level solutions. And you will hear the details from all my colleagues, Will, Dave, Russ and Xi. Now it's proven execution and deployed at scale. And to put it all together, let me start by saying, toconomics is just physics. I know when it's just physics, physics doesn't negotiate with strategy. The company that solves the physics problem of bandwidth, latency, reach and power is the one that is best positioned to go after the opportunity that Matt outlined today. And I'm here to tell you that the team that we have built at Marvel is exceptional at it. Marvell is trusted and undisputed leading solution provider. Are you all fired up. Okay. Thank you.

Ladies and gentlemen, at this time, we would like to pause for a 15-minute intermission. Kindly return to your seats within 15 minutes. Thank you. [Break]

Please welcome, Senior Vice President and General Manager, Connectivity business, Xi Wang.

Good morning, everyone. Welcome from the break. Matt said, Marvell is a connectivity first of the company. I'm thrilled to be here to talk about connectivity first. Just like Matt and Chris, this year marks my 10-year anniversary at Marvell, although that 10 years, I spent 5 years at [indiscernible] before the acquisition. Today, I want to show you what we actually mean when we say Marvell is a connectivity first company. and why that position is becoming more critical as AI infrastructure skills. Let's start with what connectivity first look like in practice. Marvell has the broadest end-to-end connectivity portfolio. We organized our portfolio into 4 categories: scale across, scale out, scale up and scale in. And together, they cover every distance that AI signal has to travel. That is everything from 1,000 kilometer between data centers down to 10-centimeter inside the package. At each of these distance, Marvell has a solution, coherent module and DSPs for the longest rich PAM, TiA drivers and AECs for data center. ACC, MPO and the CPO for the RAC. And today, I'm also going to share more about what we are doing with optical I/O chiplet using next-generation lessors as we bring optics inside the package. No other companies cover this entire stack. Our competitors may try a piece of it for Marvell offer all of it. That is the breast exactly will let us support our customers' architecture with whatever implementation they go with next. In my presentation, I will focus on scale-out as well as scale in. Russ will talk about scale across and Dave will talk about scale up. Before we talk about the product and business, I want to take a moment to show you the complete connectivity technology portfolio we have built over the past 30 years. As a connectivity first company, we have placed dedicated focus into being the first to solve tomorrow's AI infrastructure challenges. We build the best franchise in SB analog with expertise spanning across all compound semiconductors. We developed our analog IP that is tailored to the specific requirement interfacing optics. We built our DSP portfolio with advanced CMOS from the very beginning. We developed deep expertise in DSP algorithm supporting both PAM and coherent modulations and also with a variety of IPC options. We also developed photonics in-house as well as forging partnership with optical component vendors in the ecosystem. We work with a wide range of optics from silicon [indiscernible] to macro, micro VCSELs and plus manics. The result is a technology portfolio that span every single aspect of connectivity, not by chance, not because of one product, it is 30 years in the making. I am very excited to be in this market. Personally, I earn my PhD in BE and optics with a focus on plasmonics. I also spent years on his big analog with LEDs and VCSELs. I develop datacom solutions before I joined the Marvell. It's exciting to be able to bring all this technology together to support the market we are in today. There is one aspect of this enabling technology portfolio that does not get enough attention, the TIA and the driver. If you take a look inside the optical module, high-speed analog sit right at the boundary between the optical domain and electricity. The job of the TIA and the driver is to convert electrical signal and optic signal and back again. The performance is everything here. noise, linearity and power. If you get wrong, the holding suffers, you also have to do it at high speed generation after generation, using certain innovation because, as you know, analog does not scale with process. This is not a single product category each generation will support a wide range of optics, which has a different requirement. The market is also going to expand to support emerging form factors like NPLs and CPLs. This is a component category where Marvell has built quietly with the industry-leading performance and it is foundational to everything else we do in optical interconnect. Marvell has a long history here. On the product side, we have led the industry since the 40-gig generation that is where [indiscernible] got it started. Today, we are at 1.6T generation, shipping in high volume, leading our competitor by 2 years and continuing. On the technology side, we have invested across multiple process nodes across a wide range of compound semiconductor developed together with our foundry partners. Because different upticks again require different requirements on the bandwidth, [indiscernible] and [indiscernible]. That multi-foundry multiprocess leadership combined with our capacity investment is what keeps us ahead. All of the technology developed fully in-house support our flagship PSP portfolio. We have been leading since inception of PAM4 with a fully codesigned DSP driver TIA solution. We have been leading at 200 gig, 400 gig, 800 gig and 1.6T. 800 gig is the workhorse of AI today. It is what powering all the AI models that you are using right now. There is a strong continued demand from the market on our 800-gig solutions. This is what helped us to drive this business to multibillion dollar annually. We are leading at 1.6T. First to sample, first to 3-nanometer, first to 3-nanometer in volume shipment. Marvell is the powerhouse here. We are in the middle of the fastest round of 800 gig and 1.6T. Interconnect is accretable to AI and the way we engage with the customer has evolved very along with it. 10 years ago, it's very simple. You get a spec from standard body and view to it. However, early on, we realized that model wasn't sustainable for the market where it's heading. So Marvell established a multigenerational codesign model, working directly with the cloud customers, system integrators and optical component vendor in the ecosystem to build it together, years ahead of deployment. The result is a solution that is aligned to the customers' architectural need from day 1 and ready to run when the moment is needed. This is even more important in [indiscernible] AI era, where GPU and XPU refreshes occur every 12 to 18 months. Fast forward to today and our approach to 1.6T reflects just how much AI workload has diversified, training, inference, networking, security. So rather than one solution, we are executing on multiple Optima 1.6T product in parallel, each purposely built. Ara being the foundation, AraT optimized for power, for introducing TRO optics, AraX for link robustness, AraM for security visibilty and Petra for flexible network development. Hyperscaler customers need this multiple optimized solution so they can have the optionality and the flexibility to deploy their network and compute. Our market has outgrown our [indiscernible] feed approach. Long on our base product for each generation is sufficient to support this market. We expanded our portfolio to support it. We have the pole engineering resources to deliver all of them to our customers' time line. They invest and they scale. Looking ahead, the jump to 3.2T brings a new set of demand. Even as hypescaler are deploying 1.6, we are already working on the next step. Double the benefits at a much larger scale, more robust more power efficient and still in the pluggable transceiver form factor, our customers know how to deploy. We started working on this requirement more than 2 years ago. Marvell was first to show a live demonstration of 400 gig per PAM4 in 3-nanometer at OFC 2025. But working with our customer, we learn something important. 3-nanometer alone wasn't the optimal answer and PAM4 modulation has limited. It's very simple physics. PAM4 has propelled the industry for more than a decade, but at 400 gig per name, the reach maps out a rough 500-meter to 1 kilometer. Most of scale our interconnect today runs 300 to 500 meters, but larger deployment require reach up to 2 kilometers, and that caused for a more advanced modulation scheme. Our answer is company right, where Marvell is first. It bridges PAM4 optics with traditional long-rage coherent technologies with a balanced approach to power and cost, giving customers the best of those work without forcing a trade-off. We don't just talk about it. We showed that 3 weeks ago at the ECOC European Conference of Optical Communication Marvell demonstrated industry first 2-nanometer technology live, low power, 2-nanometer 3.2T solution with 400 gig per land. 3.2T coherent for data center and campus rich with balanced power and cost. We started this journey years ago. As a matter of fact, we are in volume production and shipment of our first-generation 1.6T coherent light with open update for campus application. We are bringing Coherent into the term. And our 2-nanometer approach reflects our long-term understanding of the technology and the market and the uniqueness of Marvell to support both time for an Coherent right. This is the same platform leadership story extended. We built our DSP, TIA and driver technology with our own leadership IP, and it is what carried us from 200 gig through 1.6T. Where we are first to ship 3-nanometer involvement. At 3.2T, we are leading with 2-nanometer comparing and 2-nanometer 400-gig PAM, and the road map continues on to 6.4T. We have the technology depth and breadth and we developed it years ahead of when the market is needed. Scale is the largest revenue driver from our rail interconnect business today and continues to be strong in the future. Now let me talk about what we are doing to bring optics into the package, which is what we call scale in. Why is this important? [indiscernible] continue to scale interface between chip-to-chip and chip to memory will become the bottleneck. At the same time, the die-size are increasingly getting bigger. So not only the speed is getting faster, it is also need to transmit longer, in some cases, meters. Traditional interface shown on the lifeline side is built upon electrical service. Electrical die to die service has been a workhorse, but it does not scale to what is coming next. We could meet the bandwidth requirement by increasingly speed over time. However, the distance has this limitation. Together with our customer, we identified a solution to it designed to replace traditional service for all future generations. We take next-generation life source technology. Micro ID and the micro VCSEL and integrate them directly into the package on the silicon with optical SerDes. This breakthrough is the life source or the laser itself. It is the integration, the system-level design and advanced packaging that make it over all based on high volume component that is ready to scale for on-chip interconnect. This level of integration takes actual ordinary engineering. We are already working with customers who are looking to bring this solution into their system. Over time, this could be yet another multibillion-dollar business for Marvell. So let me bring that together. Marvell has built a strong position across 3 things: technology, deeper customer engagement and scale. These are not 3 separate threats. There are one connected advantages. In scale out, this is our most established business and existing leadership position with new design in coming continue to drive growth. Our DSP revenue has already go into multibillion annually, and our analog business is rapidly headed towards $1 billion plus annually. We see strong growth continuing in scale our demand with data center, the double -- data double generation to generation accompanied by an increased content for Marvell. In addition, we are seeing new opportunities opening up for scale up with our TIA and drivers with significant revenue ramping next year. As a result, I expect the DSP and analog business that I manage to remain the largest contributor to an overall interconnect revenue, which is in aggregate we expect to reach approximately $37 million in IFRS 31 at the midpoint of our forecast. Across all 3, the investment we are making today in technology, the customer codesign and the manufacturing scale on what let us keep us leading at every hub, every distance and average generation. Thank you.

Please welcome, Senior Vice President and General Manager, Data Center Interconnect business, Russ Esmacher.

Good morning, everyone. I'm Russ Esmacher, the data center interconnect business at Marvell, the connectivity first led company. Simply put, my business interconnects data centers, the highest bandwidth and the highest speeds over optical funding. Now there's been a lot of 10th anniversaries from Marvell today from Chris, Matt, Xi, this is also my 10th anniversary, my 10th month anniversary here at Marvell. If you're not -- see a lot of familiar faces out there. I've been this industry for almost 30 years. I started with my graduate work in electro-optics and high-speed optics and then progressing to some of the largest IP and optical OEMs in the market, including Cisco, Nokia and most recently, Infinera. I could not be more excited today to be at Marvell and lead and have the privilege to lead the most experienced, coherent, pluggable team in the market. So let's hop right in. Marvell has connections for AI infrastructure at all distances. We've heard she describe our advance in our leadership and scale out and scale in and Dave will cover next scale up. And I'm here to talk to you today about scale across. Now this market is very dynamic and data center interconnect is changing. So let's jump in to scale across. Now DCI market has a lot of really positive tailwinds today. First, power efficiency. We heard Sandeep mention this in his talk. It has been a transition over the last 10 years from boxes to pluggables to interconnect data centers. This is nothing new to Marvell, partnering closely with our hyperscaler customers we pioneered and invented this market a decade ago. Data center densification. We're all very familiar data centers are trying to find more power, more locations. This is densifying the network full of data centers. What does this mean? More fibers, more connectivity, and it's actually shrinking the distance between the data centers, providing more opportunities for the application of coherent pluggables, another very strong tailwind. Third, line system density, millions of kilometers of fiber are going in annually into the network, easy to be lit by optical line systems. There's been tremendous innovation here in the last 2 or 3 years that are allowing this type of high density to accept all of the bandwidth generated from coherent pluggables another third strong driver for coherent pleasable in the market. Now a strong these 3 tailwinds are is a fourth one that has come on very strong in the last 2 years. And this is scale across. This is redefining the data center interconnect market. This is the direct connection of AI clusters to each other from distances from maybe 10 kilometers on a campus, all the way up to 1,000 kilometers. However, the bandwidth here is not the same as traditional DCI disconnecting data centers is 15x ex the bandwidth. And we're going to jump into this and the impact this is having on the pace of innovation required to deliver such a massive amount of bandwidth in such a short period of time. Again, very strong tailwinds into this market. Now as I mentioned earlier, Marvell led the pleasable transition a decade ago, moving from boxes to smaller boxes moving into pluggables, this move from boxes to pluggables provides a 75% TCO reduction for hyperscalers. And each generation of closable provides a 50% power reduction per generation. As we can see here, there is significant power savings and power efficiency, but we can also look that time frames are increasing. The pace of innovation is pulling the DSPs forward. And this requires an extremely strong technical and deep customer partnership to deliver these. And so we used to have 4 years between generations. It's now down to 2. We used to be able to have 1 DSP for each generation. Now it's multiple. Now let's jump a little bit further into scale across in the AI clusters. We had 15x the bandwidth. What this does to the market is very profound. Not only is it more bandwidth, it drives the unit capacity of pluggables way up. I'll give you an example. This year, the total addressable market in units program pluggables is right under $1 million. Now versus Xi's business, this is a relatively small unit. But for coherent optics, this is a very large number. By calendar '30, our FY '31, the demand for coherent pluggables between data centers grows to over 3 million units. This is an extremely steep ramp. However, this is perfectly aligned to Marvell's strength as a semiconductor powerhouse and an at-scale optics provider. We are ready to meet this steep ramp and continue to lead and innovate for our customers. Now this is also pulling forward the pace of innovation with regards to speed. It feels like we just got to 1.6T because we just did. But now 3.2 is required. We must continue to invest and keep the pace of innovation rolling. Now Marvell is also unique in another regard. We have 2 distinct paths to market. Number one, our coherent module business. And we've been in this for a decade. And this allows us to partner very closely with hyperscalers to deliver these modules based on performance and power and speed and security to them. However, there is a very broad market, and we are the leading merchant coherent DSP provider in the market. And this allows us to address all of the accelerating demand, whether it's from hyperscalers, neo scalers or carriers between these 2 very distinct and unique paths. Now let's look inside a little bit deeper into the hero module. And I will tell you, these modules, they look innocent enough. Very small fit in your pocket, I will tell you, these run at the highest bandwidth highest speeds across every technology Marvell provides today. So all the advancements that Sandeep mentioned, that Xi mentioned are inside of these modules. Marvell is a powerhouse year because everything you see in blue is designed from the ground up by Marvell. Now let's talk a little bit about that laser that's in there. We co-design and codevelop this laser with the leading laser manufacturers in the world who can provide us high quality, high reliability and highest volume. Now we're also very fortunate and I feel privileged to lead the largest coherent team in the market. We have the largest and most experienced DSP team in the world. They've been working on this since 2006. So they're in their 20th year now. Second, leveraging Marvell's powerhouse advanced SerDes that Sandeep walked us through. Third, we have the best fastest and deepest converters to convert the analog to digital and digital analog back into the DSP. And last but not certainly not least, the most experienced and deepest photonics team to do the high package integration of the optics to the electronics. They've been working on this also for more than 20 years. Now putting all these technologies together is crucial. But I will tell you one of the most difficult pieces with this high-speed, high-bandwidth optics is the high-volume manufacturability. And this is where Marvell excels. And I've been in lots of different optics companies. I can say with hard confidence this is a superpower for Marvell that allows us to deliver units at volume to meet that steep ramp. Today, Marvell has more than 1 million coherent modules and service, over 15 billion field hours. We've been in this business since that we started it. We continue to innovate and lead today. So for me, when I look at all these core competencies, deep technical, this was a very compelling reason. I feel very privileged to lead this team and have joined Marvell. Now multigenerational scale across requires leadership from a long time. We got into this business at 100 gig ZR about 10 years ago. We've been innovative with our customers and brought 400 gig ZR to market. Then we have 800 gig ZR. And we partnered with our customers, and they said we would like you to place please put encryption and higher performance in 800 gig, we need this now. So we've built another DSP for them. We had these new features inside of it. And as you can see, as we go to 1.6T, multiple DSPs are required whether it's for campus, metro, long haul, these are optimized for performance, power and distance. And 3.2T is under development as we speak. This requires not only more DSPs, but much like 1.6T new materials. Sandeep mentioned 1.6T required thin-film years later, I'm excited to work on lithium niobate again. But now plasmonic is here. This requires higher bandwidth, lower power, shorter modulators, and we are making the investments in this technology to ensure that it's ready when needed for 3.2T and will also be with 14 Angstrom DSPs. Marvell is the leader at 2-nanometer technology. And we didn't do on 2 new DSPs, new modules. We demonstrated these publicly for the first time 2 weeks ago at the European Conference of Optical Communications in Spain. And I'll say in our industry, this is rare to be able to deliver 2 DSPs at the same time. And I would contend it's been the first time it's been done in the industry that own leading node in the market, 2 simultaneous coherent DSPs were built, brought up, demonstrated both our technology and our partners as a leading merchant at the same time. This is the pace of innovation that our customers are counting on Marvell to continue to deliver, and I'm very, very proud of the team who executed this flawlessly with the first tape out on the first shuttle in January. But like Xi said, demonstrating it is where it's important. Having modules, having a little samples, it's great, showing it to our customers on time, first time right is what they count on us for. And this is the live demonstrations in our booth and then our partners boost publicly at the European conference. So again, thank you to the team who is able to deliver this first for our customers. Now bringing this all together, in summary, I could not be more excited about the tailwind in this business and the team we've assembled over decades to continue to deliver for our customers. Again, we have very strong tailwinds. We see our TAM expanding rapidly, both in units and revenue. In addition, we are shipping to the top 5 hyperscalers today. We are deeply embedded with design with them and making sure we deliver the right technology at the right time with the right features. As a result, we are on track to drive revenue from business from roughly $500 million in fiscal '26 to safely over $1 billion in fiscal '28 with a clear path to multiple inserting the subsequent financial years in the strategic period FY '29 through '31. I'd like to thank our customers, our partners and the Marvell team for continuing to deliver innovation at scale and on time for our customers. Thank you.

Please welcome, Executive Vice President and General Manager, Data Center Networking business, Dave Lazovsky.

Good morning. I'm Dave Lazovsky, the EVP and GM of the Data Center Networking Group. I joined Marvell in February of this year. with the acquisition of Celestial AI. I was formerly the founder and CEO of Celestial AI. So this is my first Marvell Investor Day, and I couldn't be happier to be here. I'm excited about the opportunity here before us. I'm thrilled by the magnitude of the opera team with both scale up switching and in optics. I feel that Marvell is layering strength on strength with our inorganic growth strategy. As you heard from Matt, we have invested as a company over $40 billion over the course of the last 10 years in innovative technologies and in leading teams. And my business group is the beneficiary in large part for a lot of those investments. So I'm excited about the position that we're in and couldn't be happier to be a part of Marvell right now. So let's dive into the data center networking business group. The group is comprised of 3 different business units, cloud optics that you just heard from Russ, that includes pluggable data center transceivers and DCI and then switching and integrated optics. Switching includes both scale up and scale out and integrated optics is NPO and CPO. I'm going to focus my talk on these 2 areas of integrated optics and switching. Let's start with switching. So as Matt mentioned, we have an established and growing business in Ethernet switches based on our Terralynx platform. We expect that business, driven in large part by the ramp right now in 51T switches to exceed north of $1 billion and significantly so next fiscal year. In addition to that, what we're most excited about is a new flagship product that we have recently released which is based on much of the technology that Sandeep introduced in his talk earlier today. This is our Teralynx T-100 product. And this it introduces multiple leading-edge disruptive technology capabilities, including it is the first and only monolithic full reticle-limited die that is operating at a full 100 terabits per second of bandwidth. How we've achieved this is, as Sandeep pointed out, Marvell has the world's leading 200-gig and 400-gig SerDes. We have 512, 200-gig SerDes in a single reticle-limited die in this device. Why does that matter? Well, it matters because if it's a uniform monolithic device, that means that the latency of this device is significantly lower than a multi-die multi-module package. Our latency is leading edge. We're on the order of 20% or more, lower latency and in fact, lower power than any leading competitor in this space. And why that matters is because we can use this device uniquely to serve both scale out applications for conventional Ethernet as well as scale up this emerging market that is taking off right now. So we're thrilled about the opportunity for the 100T net switch, and we expect the 100T switch as a product in and of itself to layer on incremental multiple billions of dollars of annual revenue in the coming years. So a huge opportunity from this switch alone. But right behind that, we have a series of additional Ethernet-based switch solutions. That includes the 200G switch. It includes the 400G switch, and we have ESUN, Ethernet scale-up network solutions that include an E115,115T Ethernet optimized for scale up, similarly 230 and 460 in the pipeline. So a broad suite of Ethernet-based switches and ESUN based solutions for scale up and scale out. In addition to that, Marvell is developing for our customers UA-Link-based switches. We're building now, and we'll be releasing next year a UA Link U115 switch that is being deployed at one of the industry's leading hyperscalers. And right behind that, we have the U115 -- excuse me, the 30 and 60 switch, a broad portfolio, the industry's broadest portfolio of scale-up and scale-out switch technologies we have within Marvell, excited about this opportunity, a growth engine for the company going forward. And the opportunity extends also to not just UAL based protocols and Ethernet or ESUN-based protocols. But as you -- as Matt mentioned, we have partnered earlier this year with NVIDIA, and we now offer NVLink based protocol solutions for our customers. So we have the ability to craft solutions for all of our customers for scale up and scale out to meet their requirements on an application-by-application basis and on a customer-by-customer basis. So let's discuss -- what I'll do is I'll go into much more detail on scale up. You heard from Xi and you heard from Russ scale -- the scale across, scale out and scale end markets. I'm going to dive in to a detail not just talking about the products and technologies but about the application drivers at the artificial intelligence workload level that are driving requirements for the next wave of data center infrastructure, specifically and scale up. We feel that scale up is going to drive a tremendous opportunity for the company. It's an inflection point. And it's an inflection point, in particular, with this transition from copper to optical interconnectivity that Marvell is so well positioned to lead. So let's begin with the workloads. The workloads that we've been addressing as an industry over the course of the last several years, began with the ability to train multitrillion parameter models. And this is hard, right? So it puts a lot of pressure on all of the resources on compute, on memory, a lot of network intensity. But over the course of the last couple of years, 2 years ago, specifically, there is a new wave of inference-based models, which are our inference time compute. And what that did is it introduced a set of requirements for higher capacity bandwidth, higher capacity, high bandwidth memory and it introduced the need for scale up networks to increase the amount of memory semantic interconnectivity within the scale of domain, XPU to XPU connectivity. Those workloads were driven by OpenAI o3 and o1, for example, an DeepSeek-R1 that was released a couple of years ago. And then more recently, you see this push toward mixture of experts and longer context-based workloads. This was the result of a very important innovation that took place in June of 2023, about 3 years ago at Berkeley. And UC Berkeley, a group introduced an open source inference engine called vLLM and one of the important innovations inside of vLLM was KV cache. And KV cache has now proliferated rapidly through the industry, and it's enabling much more efficient utilization of memory. So I'm going to spend some time in this talk talking about the impact that KV cache is having on the data center infrastructure that we're building with all of our hyperscale customers. But all of these innovations have come together and a shift at the same time has taken place. A shift from a training centric environment for data center infrastructure to an increasingly inference centric infrastructure. Today, about 60% of total data center infrastructure is inference. And as you all know, inference is the return on that ROA equation. Training is the investment. So we're seeing not just an increase in inference. We're seeing an increase in efficient infants. So what that has done in turn is drive a significant increase in the operating profitability, the operating performance -- operating profits of the cloud service providers. Three years ago, there were some cloud service providers that had operating profits in mid-single digits. Today, almost all of them are seeing operating margins that are approaching 40%. And the math is working. The flywheel is spinning. Those profits are being reinvested in data center infrastructure. The $1.6 trillion of CapEx that you just heard from Chris, that's being invested this year. going to $3 trillion as we exit the decade. It's the largest infrastructure investment in the history of humanity. And the fact is it's justified because these are profitable workloads. So that investment is taking place across compute, across memory, across networking and across connectivity, the market is coming to us. We're extraordinarily well positioned from where we sit right now at Marvell. So let's dive into specifically what's happening within reasoning models and why we care about with this group of researchers that UC Berkeley did 3 years ago. But we don't really care so much about that as much as we do about the utilization, the efficient utilization of memory. What we care about is how the model is building the context token by token. So again, this group introduced the concept of KV cache. So what is KV cache? KV cache is the storing of key and value rather than requiring the need to recompute that stuff. So you have the information available and high-speed memory so that it makes the interaction in reasoning models rapid, for recompute, humans are inherently impatient right? So the problem, though, is that the amount of KV cache is not unlimited. So it puts a lot of intensity on memory capacity on memory bandwidth, and it puts a lot of intensity on the network latency. But at some point, you exceed the amount of available KV cache in the system. And at that point, 1 of 2 things happens. You either need to reload from a different location in the memory hierarchy, those key in value parameters or you have to go back and recompute them. And in both cases, you have to make room in the KV cache for the new key value indices and you have to inject or information to make room for it, which can potentially result in hallucinations. So in all cases, this reloading and recomputing results and inefficiencies. It drives higher marine latency. It drives a need for memory and compute transactions, overall, a negative impact on the efficiency of these systems. So ideally, we have systems that have -- and ideally, incident amount of KV cache, high-speed memory that's available that can be addressed by any XPU. The problem is it is not infinite. The KV cache is finite. So how we're addressing this issue is at the system level. We're addressing it first with maximizing the amount of high-speed SRAM on the chip we then increase the amount of high-bandwidth memory in the package, right? So if you look, for example, at state-of-the-art GPUs today, Rubin from NVIDIA, Rubin has roughly 300 gigabytes of memory capacity in the package. The problem is that, that 300 gigabytes is orders of magnitude too small to deal with today's advanced AI models. So that has driven NVIDIA and the rest of the hyperscalers to build systems that interconnect multiple SPUs together in a memory semantic scale-up domain. In the case of NVIDIA, they use NVLink and you switch. Now there's 72 interconnected XPUs inside of that rack. The problem is that the memory requirements are initial. They're continuing to grow, and they're spilling over what will fit in the rock. The industry needs multi-rack scale-up domains, growing to 512, 576 and beyond. So how do you get there? And what are the challenges, right? So some of the challenges are, today, 100% of all interconnected XPUs inside of all racks are copper, all of it. That is both the challenge and the opportunity for Marvell. So why is that? So why not just take that and extend it to a multi-rack domain? Well, the problem is that the data rates that we're running at, which are 200, 224 gigabits per second, they're going by the way to 448 gigabits per second. But at 200 gigabits per second, the reach that you've got is 2.5 meters. It forces you inside the rack, right? So the only way to overcome this limitation within the scale of domain is optics rather than fighting the laws of physics, knowing that moving information over copper electronically, you're dealing with electronics and unfortunately, electronics have mass. The beautiful thing about optics is that they have no resting mass right? So it gives us the ability to leverage physics. You use it to our advantage that are trying to fight the laws of physics. It gives us the ability to increase fully connected scale-up domains with optics. Larger numbers of directly interconnected XPUs is sharing the same memory with extremely high bandwidth and with extremely low latency. But the bar is high. It's very different, right, than a scale-out network. If you think about it, the XPU on the left here has to be able to operate, do a load store transaction and address the XPU on the right, the memory in that XPU and pull it across the network. And ideally, it is operating as if it's the same performance in terms of bandwidth and latency as the memory on the package. That is challenging, right? Because HBM has very high bandwidth. It's tens of terabits per second now. HBM 4 has about 16 terabits per second of bandwidth. And you do not want the network to be the bottleneck for memory transaction. You also want to be able to minimize latency. Again, the latency for these applications and reasoning translates directly to revenue for our customers. The latency out of the package is less than 100 nanoseconds latency going over a scale-out network, if you had to use a scale-out network for this would be hundreds of times greater than the local memory latency. So what you really need is the latency down around 200 nanoseconds. Really, really fast memory transactions also with low power. Sandeep pointed out earlier that the amount of data traffic going across scale-up networks is 85% of total data center data traffic, 85% of it. Only 15% is scale out. What that means is that if you can reduce power here, even a few picojules per bit, you can repurpose that energy that's being used to move information and use it to compute information or tokens can be generated. Tokens aren't generated moving information. So the options that we've got for addressing this set of challenges are, unfortunately, not pluggables. As you just heard from Xi, the leading-edge pluggables are going from 1.6T to 3.2. It's an order of magnitude, lower in terms of bandwidth. The power is not there. The latency is not there. They're not designed for these applications. This application requires integrated optics. It requires NPO and CPO. The good thing about the circumstance though for Marvell is that the market's just come to us because we have a full suite, as Xi pointed out, of optical technologies that we have built over the course of the last 25 years with the best team on the planet building these technologies. And they -- we bucket them in 3 categories. They're the category of working with module providers in the way that we have with plugables with supporting and providing these module providers and the overall optics ecosystem with drivers and teams, which we're doing today. And then we have 2 categories of fully integrated, what we call light engines. One of those categories we call Fast Pipe, which are 200 gigabit per second going to 400 gigabit per second per lane in optics. And the other, we call Flat Pipe. Flat Pipe optics are designed specifically for scale-up networking, much lower latency, much lower power. We have 2 flavors of flat pipe, One is based on industry standards that are emerging now. OCI MSA, big set of acronyms that sends for optical compute interconnect, multi-supplier agreement. That's basically the industry converging around ESUN based optical scale up networks and they've landed there. So it's a set of optics that the industry has standardized on or is working on standardizing on, we have that as an option. The other is the technology we developed it, Celestial AI photonic fabric, which is fully optimized again, ideally for scale up networks where we've got strong customer demand. We put checks in the win column as it relates to customer demand across all 3 of these categories. We're winning in delivering drivers and ties to module providers today. We have won a major socket recently, and we're winning multiple sockets in fast pipe optics. And we have won sockets, including the world's leading hyperscalers in flat pipe as well. So let's double-click on this and take a look at the level of complexity of these devices, right? What's in here, right? So in the case of the fast pipe light engines here's our 200, 400G. You see we're able to leverage things like our optical DSPs and the range of optical DSPs that we've got that are fully timed or transmit retimed optics. And then if you blow open the light engine, you can see a lot of the innovation that Marvell again has developed over the course of the last 25 years in advanced drivers and teas, including silicon germanium. And then we have, again, tapping into the know-how that we've got in silicon photonics with [indiscernible] and parameters. So -- and all of the optics and packaging and scale that you heard from Russ and Xi, leveraging all of that in an NPO form factor. So a large opportunity, fast-piobjects, excited about that opportunity. On the flat pipe side, very similar other than the fact that this technology has been designed from the ground up for this application, scale up. And what we've done is if you -- the light engine is far more integrated, right? It's a deeper level of integration in the optics. So all of the discrete components are now fully integrated in an advanced ASIC. This is the drivers, the teas, the controllers and most importantly, analog SerDes. These systems are designed to eliminate the need for digital signal processors. We're using analog equalization. And by eliminating the DSP, you take the largest power contributor and the largest area contributor out of the equation, game changing as it relates to performance, game changing as it relates to latency. The ultimate optimal solutions. By the way, that fast pipe, the flat pipe is applicable for both, I'll jump back because it's important. It's applicable for both MR-based silicon photonics as well as EAM or electrooptiulator based photonics sharing the same control electronics, the same advanced ASICs. So this is where we brought the teams together from all that horsepower power that's come from Marvell over the last 25 years with our team from Celestial AI. So now form factor. Some customers are interested in PO-based form factor, some are interested in CPO. From our standpoint, the answer is yes, right? We're agnostic. If a customer's operational priorities, our field replaceability of the optics, they're worried about last radius of a failure or if they want reconfigurability use an NPO, plug it into the Board. And if there's a concern, you swap it out, not a problem. For those customers, on the other hand, that are looking for the ultimate in performance, the lowest latency, the lowest power we're offering today and we have customers deploying co-pack shopping. So this is the deepest level of integration, which provides the most superior performance for scale up network solutions. We are we have developed both and we are in the process of deploying both. So again, Marvell is in a position where we don't have to force our customers to make a choice, we can embrace them. And in fact, that's how we do it. So if you think about how all of this technology comes together and how we work with customers, our customers are operating with us as an extension of their own teams. We're engaging with them to understand what their requirements are for developing, architecting and developing the right scale-up network across the entire link from the XPU interface going -- in some cases, going from copper to the right optical IO, determining what is the right physical layer, what optics do they want to run? What is the right logical there, what protocol do they want to run to the switch, all of it. And these things are highly integrated and highly interdependent, right? So most of these programs that we have with the large hyperscalers in the world have started years ago. So we're working with them to develop solutions for scale up networking that takes time to get developed and implement and deploy it, right? And it enables us to design and optimize for linked performance, including power, latency, bandwidth, it enables us to accelerate time to market and time to first token generation with them, and it also helps them derisk the operation of these devices by leveraging things like telemetry. So they can see the stability and the resiliency of their links and employ things like security to ensure that in the world of agentic AI, their links are fully secure. So these are examples of how we're working together using the leading-edge technology that Marvell has brought together to address these rapidly evolving architectures in scale of networking. Now what I'm about to show you is how we are adding new capabilities and tools to the toolbox to help our customers disrupt this. meaning help them craft system architectures that can provide next-level capabilities for dealing with things like KV cache sizes. The ability to decouple memory scaling, high speed, high capacity, high bandwidth memory scaling from compute. So what you're looking at right here is what we call the photonic fabric memory module. These modules, 8 to 16 of them are integrated in a photonic fabric memory appliance. And what it does is it provides the first time really in history, the ability to decouple memory scaling from compute. The only sockets that are currently available for HBM today reside 1.5 millimeters away from an XPU or a GPU. So what that means is that our customers are forced to use their GPUs as the world's most expensive memory controller. This technology changes that. It changes fundamentally the economics of memory. And we're excited about where we stand with this. This is a product that we taped out earlier this year. It's been brought up now, and we'll be sampling with multiple customers as we move into next year. So very excited about this opportunity. So in closing, I'd like you to take away 3 primary things from what I covered. The first is that we have an established scale out switching business. All of our business in switching today, all of it is scale out. Now that business is growing is doubling year-over-year, this year and will double -- more than double again year-over-year next to a well over $1 billion annual run rate. and that will grow to a multibillion dollar annual run rate in scale up switching -- scale out -- excuse me, switching alone. In addition to that, we are leading and enabling this new emerging market segment of scale up switching. And there, we have significant, significant customer traction. We expect scale up to layer in an additional multibillion dollar annual recurring revenue opportunity for Marvell. And in addition to that, we have scale of optics. And what's interesting about scale up optics is the fact that there is significant Marvell content. It's -- there's a significant component for a few reasons: one, because the bandwidths are so high. The other because you saw the level of content in these highly integrated devices like the fast pipe and the flat pipe light engine, a lot of content. So the -- if you think about it in terms of the dollar content for scale of optics per XPU. You should think about this in the context of on the order of thousands of dollars of scale-up optics per XPU,right? So it's large, valuable technology. But it's bigger than that. The optics are required on both sides of the link and our customers, in large part, are looking for comprehensive end-to-end solutions. The objects are required on both the XPU side as well as the switch side of these links. So we're excited about the magnitude of what the scale of optics market segment brings to Marvell and the fact that this market has just come to us. So with that, we are in the right place at the right time with the right technology, and we've got the right trusted team to execute. So with that, I'd like to say, thank you.

Please welcome, Executive Vice President and General Manager, Custom Cloud Solutions business, Will Chu.

All right. Good morning. My name is Will Chu. I've been with Marvell for 9 years, and I lead our custom business. At last year's custom AI investor event, I talked about how Marvell was becoming a leader in custom solutions. I thought my team was pretty busy then. It turns out we were just getting started. Since then, our traction and opportunity have grown dramatically. We've increased our fiscal '29 revenue outlook from more than $10 billion to more than $12 billion, and we're on a path to approximately $30 billion by fiscal '31 at the midpoint of our long-term target range. Today I'm super excited to show you what's driving that growth. Okay. Let me start with how we build the custom business from the ground up. Very early on, we saw that hyperscalers were going to need significantly more custom solutions. We recognize that Marvell already had the core IP to address this market and world-class engineering teams with 30 years experience in storage and custom ASICs, 25 years in networking, compute and security. We also had decades of experience taking the core IP from our merchant products to create semi-custom and full custom solutions. My mission has been to integrate these teams with our core AI is and build a custom solutions leader. We are focused on XPUs and a diverse set of XPU attached solutions and on customers that leverages Marvell's entire technology platform. Our strategy is working. At last year's custom AI investor event, I talked about the 18 sockets we had already won. Since then, we've continued with many more designs and with multiple multigenerational wins across the top 4 hyperscalers along with early wins with many others. That continued momentum is what's driving our strong revenue growth. Let's start with XPUs. Hyperscalers were initially interested in custom XPUs. So that's where we started. Our initial XPUs were already complex devices. One to 2 [indiscernible] with integrated HBM, using 2.5D packaging technology. Today, our XPU business is on track. We've already shipped in high volume, and we're executing very well across all our programs. Looking forward, XPU complexity will continue to increase as hyperscale is pushed for more performance. We see more compute dies, more HBM and stand-alone copper IO chiplets, all integrated using 3.5D packaging. By the N+2 generation, we expect even more compute and HBMs and that these XPUs will approach the copper wall and need to integrate optical IO. This is why at our Custom AI investor event last year, we highlighted the critical technologies you see here. Our deep investment in connectivity IP is another big differentiator and positions us extremely well as XPU architectures continue to scale. Hyperscalers need a partner like Marvell that already has a track record of taking complex XPUs into high-volume production and leading NPO and CPO technology, as Dave highlighted. We are focused on customers that leverage our complete end-to-end portfolio of XPUs with our IO chiplets, optics and networking. That combination of connectivity leadership and XPU experience sets Marvell up to be a big winner as AI architectures scale. And our close partnership with NVIDIA further expands that platform. NVIDIA and Marvell are jointly engaged with customers on NVLink Fusion solutions, combining Marvell's custom XPUs and NVIDIA's scale-up connectivity and rack scale infrastructure. Now our opportunity extends beyond the XPU, and there are a number of exciting XPU attach opportunities I'd like to discuss next. The XPU opportunity really evolved from the traditional data center market. The market established -- well-established ecosystem of merchant solutions using standard interfaces like PCIe to support x86 CPUs. Marvell participated in that market for many years. We developed networking, processing, security, storage and memory products and ship millions to the hyperscalers, millions of units to the hyperscalers. As the industry transition to AI, hyperscalers initially leveraged those merchant solutions. But as XPUs became more complex, they needed increasingly optimized solutions around the XPU. We saw this trend early and proactively engaged our hyperscaler customers to address these new requirements. Marvell was a natural partner. We had the underlying IP, product expertise, customer credibility and the experience of turning our merchant IP into semi-custom solutions. Now what makes XPU attached very attractive for Marvell is that these sockets are very sticky. They can persist across multiple generations of XPU. They heavily leverage Marvell's IP and expertise, and they extend our reach across the entire infrastructure for AI even with non-Marvell-XPUs. Let me walk you through a few of them, starting with NICs. In the traditional data center, a vast majority of the market were merchant NICs. Foundational NICs are the most prevalent. There are smart NICs with integrated CPUs and I/O speeds are typically 100 gig or less. Marvell had shipped NICs for decades and millions of parts into production. Marvell invented the SmartNIC back in 2005 and has been in production for over 20 years now. There are a few merchant NICs on the market today, but all hyperscalers have or are moving to custom because standard NICs lack either the optimization or the performance they need. Hypersalers are looking for a specific mix of I/O speed, bandwidth and configuration. They need optimized data paths, accelerators as well as custom networking protocols and integrated CPUs dimensions just right for their applications. All of these requirements tied directly to how efficiently data moves across our network to support their specific workloads. Marvell is a trusted partner for hyperscale to solve these challenges. We have leading SerDes IP at 100 gig, 200 gig, 400 gig, decades of experience with NICs, high-performance data path compute and acceleration. We also have the capability to design very complex custom solutions. For example, our latest NIC is greater than 400-millimeter square to give you a sense. We are doing really well here. We have design wins with multiple hyperscalers across multiple generations that are ramping oriented execution. Now let's take a look at memory. In traditional data centers, workloads were compute bound, not memory backed and having memory directly attached to the CPU was generally sufficient. CXL was originally developed for traditional data center applications, not AI. We at Marvell had early investments in CXL, but this market developed slowly. AI changed everything. Workloads like inference and KV Cash are memory hungry and latency sensitive, driving higher memory capacity and bandwidth for both CPUs and XPUs. This surging memory demand, of course, has created a memory shortage. Very early on, we saw the memory wall challenged and worked closely with a leading hyperscaler to define a differentiated solution, leveraging our early investments in CXL. Today, Marvell is a leader in memory expansion and near-memory compute with the broadest portfolio of high-performance solutions in 5-nanometer. Our early design wins are ramping at multiple hyperscalers. And with multiple multi-generational programs in execution. Our Structera X products support DDR5 and DDR4 memory recycling, industry-leading memory capacity and compression to extend the capacity further. Our Structera A products brings compute close to memory to accelerate memory-intensive workloads like LLM and offload the CPU. We also have a broad ecosystem across memory, CPU and GPU providers. This is a memory adding card developed with a leading memory vendor. And the opportunity is expanding beyond CPUs. XPUs need more memory capacity and bandwidth as well. We're now developing custom memory expanders that connects directly to the XPU, at very high speeds using our high-speed SerDes IP, giving the XPUs direct attach to expanded memory. This creates a very exciting new growth vector for our memory expansion business. And with that, I'll move to storage. Historically, the storage controller market had many merchant solutions, often bundled by the flash vendors with their NAND. There are also merchant accelerators that offload storage and data management functions from the CPU. Again, Marvell brings decades of storage experience with millions of Bravera SSD controllers and accelerators shipped across multiple generations. Looking ahead, hyperscalers want to control their storage, firmer and software, so they can leverage their investment across multiple generations of SSDs and multiple NAND suppliers without being tied to a specific drive vendor. AI workloads also rely on flash now to continuously feed data to the XPUs, making storage offload performance increasingly important. This plays directly to our storage heritage. We leverage our merchant technology to build a leading portfolio of semi-custom 5-nanometer SSD controllers and storage accelerators. For hyperscale is developing do-it-yourself SSDs our multi-vendor controller delivers high performance and custom features while giving them full control of their software. For storage accelerators, we optimized our merchant technology for an initial hyperscaler and have already secured design wins beyond that initial engagement. Our accelerators increased storage throughput and provide confidential compute and virtualization offload, freeing up the CPU. Now I also see storage requirements continuing to increase, and they're doubling -- they're roughly doubling generation over generation. This is creating a strong tailwind for our custom storage business. Now I'd like to discuss a couple of emerging XPU attach opportunities that we've never talked about before. The first is a new class of AI infrastructure management silicon. We talked before about NICs, memory and storage. Today, we're introducing an entirely new XPU attached category, driven by a fundamental change in AI infrastructure. In traditional data centers, BMCs monitor the health of a relatively simple server, typically 1 to 2 CPUs. These servers have approximately 150 sensors generating relatively small amounts of data, so the processing and I/O requirements are pretty modest and the impact of a failing server are also relatively contained, typically 1 to 2 CPUs. AI changes this dramatically. AI servers are some of the most complex servers ever created with more than 1,500 sensors and generating hundreds of megabytes of data per day. Just managing this complexity requires 1,000x more performance. And the impact of failure is much, much greater. A single XPU failure can disrupt the work of thousands of XPUs. And traditional BMCs weren't designed for this. AI infrastructure needs an entirely new level of performance processing and I/O performance. Okay, at Marvell, we recognize this challenge early and proactively engage with multiple hyperscalers to develop a new infrastructure management solution. They needed a much more powerful multi-core processor to monitor the servers, their servers and switches across their AI infrastructure. We already had deep relationships with these customers and a long history of delivering infrastructure class processors. So we partnered closely with them and developed an optimized solution, leveraging our OCTEON technology, proven 5-nanometer IP and experience in high reliable, mission-critical applications. The Marvell semi-custom processor delivers the 1,000x increase in performance needed for these AI infrastructure management workloads. Today, we have programs with multiple hyperscalers, creating an attractive XPU attached growth opportunity ahead of us. Now let's move on to another emerging XPU attach opportunity. The next opportunity is inference acceleration. And this is an exciting emerging category that could significantly expand the XPU TAM. Inference, as you all know, is growing rapidly and architectures are evolving to deliver significantly more performance. One of those changes is the use of specialized inference accelerators to attach to the XPU to offload specific workloads. These are highly complex, large devices that require the most advanced process nodes. This represents another significant silicon opportunity around the and Marvell was already investing in the technologies needed to address it. That includes our high-speed SerDes and die-to-die connectivity with a path to optics. Our SRAM technology, which can deliver 17x more bandwidth at 2/3 lower standby power than standard solutions and advanced 3.5D packaging technology integrating 3D stacked memory and/or logic die to enable even more performance together. These technologies allow us optimize inference accelerators for performance, bandwidth and power. We believe inference accelerators can become a significant new XPU attached market, and we're already engaged with multiple customers. Marvell has the core technologies to win here. Okay. So let's summarize. We're engaged with all the major hyperscalers. Since last year's Custom AI investor event, we've deepened our customer relationships and have won additional multigenerational designs. All of our XPU programs are on track and XPU attach has become a big multiplier to our opportunity. Standard products are moving to high performance and more complex semi custom solutions for nicks, memory and storage. New attached categories emerging, including AI infrastructure management and inference acceleration. As AI performance scales and XPU complexity grows, we see higher attach rates and higher ASPs, significantly expanding our opportunity. You can imagine 1 to 2 sockets attaching to each XPU with ASPs around $1,000. You guys are going to write all that down. Do the math, and you can see how each of these attached categories can represent a $1 billion opportunity with some reaching several billions. So as these programs ramp, we're building a large and increasingly balanced custom business across both XPU and XPU attach. Okay. I'm very pleased with how quickly our custom business is growing and diversifying. As XPU attach ramps, it will drive greater balance between XPU and XPU attach. We were on track our custom revenue to more than triple from fiscal '28 to more than $12 billion in fiscal '29, well above our prior fiscal '29 target of more than $10 billion. Looking further ahead, I am personally very confident in our ability to grow custom to approximately $30 billion in fiscal '31 at the midpoint of our long-term target range. My confidence is driven by the momentum I discussed today across all the Tier 1 hyperscalers in both XPU and a diverse set of XPU attached programs. As you heard from Matt, we don't need new wins to achieve our target. We are in full control of our destiny. We have the customers, the team the technology platform and the programs in place to deliver on the tremendous custom opportunity ahead of us. So like I said at the beginning, we're going to be pretty busy. And we're just getting started. Thank you.

Please welcome Executive Vice President and Chief Financial Officer, Dan Durn.

Hi, everyone. Good morning. Thank you all for coming today. I'm Dan Durn, Chief Financial Officer, and I've been at Marvell a little more than 3 months. From a career perspective, I got my start in the military. I'm absolutely honored to have worn the uniform of my country for a dozen years. Subsequent to my time in the military I spent a little more than 2.5 decades in and around the semiconductor industry. First, as an investment banker with Goldman Sachs in their merger department covering semiconductor companies, then in private equity investing in semiconductor companies, and now in the last 15 years in operating roles as a CFO, leading finance organizations. Before diving into the financial model, I want to share how excited I am about the opportunity we have in front of us. Marvell, we're at a unique inflection. We believe we're on the cusp of increasing the magnitude of our revenue by a factor of 10, and that's going from $8 billion to $80 billion of revenue at the midpoint of our long-term model and doing it in a very short period of time. And it's all predicated. It's all predicated on a vision, one that was laid out 10 years ago by Matt and the team, and it hasn't changed. A decade later, it is the exact same vision. So what has changed? We've taken that vision, that North Star for the company and a point of view of where our end markets are going. And we've backed it up. We backed it up with conviction and a decade of investment. We've invested tens of billions of dollars to bring this vision to life. And now we're purpose built. We are purpose-built for this moment. We're intersecting the largest wave of infrastructure investment in human history. And we're doing it with critically enabling IP and foundational technology and it's IP and technology that directly addresses strikes right at the heart of the single biggest rate limiter in data center performance today, and that's connectivity. How do you efficiently move, store, process and secure data? How do you do it at an absolutely massive scale and power efficiently? We, Marvell -- we're built for this moment, and it's been a decade in the making. And as CFO, I take comfort in the underlying drivers of growth. And you heard it from Matt and the team today, the drivers of growth, they're diverse. They're diverse across products, customers, technologies and multiple generations of design wins. And we've got many shots on goal, and no mega socket is needed to deliver on our long-term targets. I can't think of a better time to be at Marvell. With that, let's dive into the financials. Before looking forward, let's do a quick recap of how Marvell has performed relative to its long-term targets that we put forward a handful of years ago at our last Investor Day. I think it's important context setting and forms the foundation of our journey ahead. At the time, in 2021, we laid out 3 key priorities and Marvell has delivered on each. Revenue, we delivered a 23% compound annual growth rate from FY '21 to FY '26, exceeding the high end of our target long-term revenue growth of 15% to 20%. On earnings, we delivered strong operating leverage. Our non-GAAP operating income growing at a 32% compound annual growth rate, nicely outgrowing revenue over this time period. Finally, capital allocation. We've invested heavily in growth, $8 billion of organic R&D investment, and we've complemented it with $11 billion of inorganic investments all while returning about $4 billion to shareholders via dividends and share repurchase. So to recap, we've invested in growth. We've returned capital to shareholders all while maintaining a strong and flexible balance sheet. With that behind us, I know you're here to focus on the next 5 years. So let's jump into that. What have you heard today? First, we see a huge revenue opportunity in the next 5 years, and it's largely coming from our focus on connectivity and compute for our hyperscaler customers. We've got a massive $400 billion TAM in calendar year 2030. And that's a greater than 4x increase from the last TAM we provided. And it's growing at a 45% compound annual growth rate even when factoring in a moderation in data center CapEx, which we have growing at a 35% CAGR over this same time period. So we window back out. Data center CapEx, 35% CAGR. Our opportunity or TAM 45% CAGR. Our revenue growth, 55% to 60% CAGR. Second, we purpose built a vast array of connectivity and custom technologies to address the massive TAM that we see. That includes our leadership positions in DSP and optics, our analog mixed signal capabilities, our silicon and packaging technologies. These capabilities -- these capabilities are foundational to our success. They're truly differentiated and they're truly world-class. Third, combination of this massive TAM, our key differentiated technologies, that positions us to accelerate our revenue growth in the years ahead. Now let's put some numbers around this. Going forward, we remain focused on the same 3 metrics: driving strong revenue growth, delivering earnings leverage, growing cash flow. And I'll dive deeper into each of these in the subsequent slides, but I just want to share a few quick highlights. Revenue, we expect the revenue CAGR to be roughly 55% to 60%, which is significantly faster than the growth of data center CapEx and our opportunity, our TAM. On earnings, we expect to grow earnings meaningfully faster than revenue and deliver operating leverage and do it at scale. Finally, we expect to generate strong and growing cash flow that gives us positive optionality for capital allocation in the years ahead. Now let's double-click into each of these individual pieces of the 3 focus areas we just talked about. So Matt and Chris showed some of this earlier today. They highlighted in a forecast $400 billion TAM for Marvell in calendar year 2030. And as you know, that is the equivalent of our fiscal year 2031. Within that opportunity, we believe Marvell can grow our revenue from $8 billion last year to $80 billion of revenue at the midpoint of our long-term model in FY '31. We expect the communications and other business to grow at the same low single-digit rate that we've discussed in the past. So no change. But as you can see, our data center business, this is the primary driver of the growth with a 65% CAGR at the midpoint of our long-term model in the coming years. So let's dig a bit deeper into the data center. Consistent with the data center splits that we've highlighted in the past, we see strong growth across all 3 pillars of our data center business in the years ahead; interconnect, custom, switching and storage. For interconnect, with the move to optical connectivity supercharging growth, we forecast a revenue CAGR of about 65% at the midpoint, driven by scale out, scale up and scale across. For switching and storage, we see a revenue CAGR of about 45%, with our switching business expected to grow even faster. And that's driven by scale out and scale up. Finally, custom. We see a revenue CAGR of approximately 80% at the midpoint, and that's driven by both strong acceleration of our XPU business, and strong acceleration of our differentiated and sticky portfolio of XPU attach products. Taking a step back, the key takeaway, all 3 pillars of our data center business, they've got strong growth in the years ahead. We have 3 large, diversified, high-growth engines that are powering our data center business. So next question. How does this revenue growth translate into earnings? As we've said for many years, Marvell's gross margin, that's mix dependent. Custom silicon carrying a relatively lower gross margin but has an attractive operating margin due to customer-funded NRE and scale of the business. Merchant silicon on the other hand, has a relatively higher gross margin but also has a higher R&D profile. So the net of this dynamic, both custom and merchant, yield attractive operating margins despite the variations that they have from a gross margin perspective. We expect to grow operating expenses at roughly half the rate of revenue growth. And that will deliver nice operating leverage as well as a sizable upside to the operating margin in the years to come. Netting this out, we remain committed to growing earnings at a rate that's nicely above our revenue growth between now and FY '31. So based on this combination of significant revenue growth and strong operating discipline and execution, we're going to deliver a structural increase in the cash flow generative capabilities of Marvell and our priorities for this significant increase in cash generation. We're going to remain oriented towards growth. We're going to continue to fuel the growth of company, and that's going to be both through organic investments and inorganic investments. And we're committed to returning greater than 50% of our free cash flow on average over time, and that's all while maintaining a strong and flexible balance sheet. So let's summarize all of this in a single table. Our new long-term target model, FY '31. We expect to deliver revenue of $70 billion to $90 billion, and that's driven by a diverse set of customers, products, multigenerational design wins, and that's across all 3 pillars of the data center business. We expect a gross margin of 56% to 59% with the range being mix dependent, and that's consistent with what we've shared in the past. It's also important to keep in mind this mix dependence. It acts somewhat like a hedge. The low end of the gross margin range, it likely requires a significant upside to the base case revenue forecast for our custom silicon business. Conversely, if connectivity revenue nicely outperforms, our gross margin will likely trend towards the upper end of the 56% to 59% range. So the mix dependence acts as a bit of a hedge. We expect an operating margin of 44% to 46% as OpEx grows at roughly half the rate of revenue. And taking a step back, putting that in context, our new operating margin target is 6 points higher than the prior long-term target we put forward a handful of years ago. This significant increase in profitability as a result of the increased scale and differentiated positioning we have as a company. We expect a tax rate of 15% and a free cash flow margin of greater than 36% over time. And I know that you guys all took a stab at what the earnings power of the company is a couple of hours ago, when Matt previewed and laid some bread crumbs. So to demystify it with these assumptions baked in, confirm that you guys got it right, which I'm sure you did, here's the math. Combination of these metrics imply a non-GAAP EPS of greater than $30 a share in FY '31, at the midpoint. So when I window back out, when I think about the earnings power of this company and how to frame that, I think of $30 in '30, greater than $30 of EPS in calendar 2030, which again is the equivalent of our FY '31. So greater than $30 of EPS in calendar 2030, $30 in '30. So let me bring you back to a slide from the end of Matt's presentation. Why invest in Marvell? You heard about the technology. You heard from the team, we talked about the large market opportunity. There's 5 numbers I want you to walk away with from this room. $400 billion TAM, calendar year '30, massive and growing. $20 billion, revenue guidance for FY '28, $2 billion higher than our prior guidance. $12 billion-plus custom revenue target, FY '29 up from $10 billion plus. $70 billion to $90 billion, revenue target FY '31, bill bottoms up with a conservative view on data center CapEx. Last $30 and '30, earnings power, long-term model, greater than $30 of non-GAAP EPS in FY '31, $30 in '30. We have Marvell. We've worked hard to earn the trust of our largest partners. Similarly, we appreciate the trust you, our investors place in us. On behalf of the entire Marvell management team wanted to express appreciation and say thank you. With that, let me welcome the rest of the team back up, and let's kick off the Q&A. Thank you.

[indiscernible] the Q&A, but before we do that, I think, Matt, just wanted to kick it off with one comment.

Yes. Anyway, it's great to see everybody. We'll do a Q&A and then we'll have lunch. But before I do that, I actually want to give just a special recognition for a moment of a very important person here who has supported you guys tirelessly for really almost 2 decades, and that's Ashish Saran. Ashish joined me in 2018, and Marvell was not in the place that we are today. He was very brave to take this on with me. And they say being a CEO is a lonely job and it is. And I think one of the few roles and people that understands that implicitly always is the Head of Investor Relations. And so in my darkest times and deepest criticism and things just not going the way we want it because, look, it hasn't been all open to the right for the last 10 years. Although if you look at it, it's pretty good, right? And the 300, not bad. But along the way, Ashish, you and I had a roller coaster. And I just want to have everybody -- Ashish, stand up, please. Give Ashish Saran a round of applause. He is retiring soon but we're keeping him on the payroll for a little bit longer because we just can't seem to let them go. Anyway, with that, why don't we kick off, Ross, and we can moderate the Q&A.

Raise your hands, wait for the mic to get to you, so those on the webcast can listen. And I've been in your seat, so please listen to this last thing. One question. Not 5-part questions, one question. All right. First ask, Vivek.

My question has to do with your custom opportunities. So to cover that perhaps how much [indiscernible] are they? And then maybe look at the forecast, if you gave the $30 billion [indiscernible]?

Yes, sure. Yes, that's a great question, Vivek. I think first, the way to think of it is, fundamentally, these programs that we're executing on are all proprietary sole source. It's Marvell IP and technology, especially when you get to the more complex products and on XPU attach, it actually starts with Marvell at the core. And in some cases, it's our entire design. It's what you call build-to-spec, which means we basically get a specification of the customer, we work with them and we deliver it to them. And on the magnitude of the opportunity, when you go out to 2030 calendar fiscal '31 and you're looking the $30 billion, what I said is, I think the mix, we still don't know exactly, but think of it as largely balanced, right, between the existing XPU programs we have coming and then XPU-attach. And I could see that tilting one way or the other. I think it depends on how some of these programs take off. But with respect to the XPU attach and the large strategic agreement that we announced in August, the way that we've got that modeled right now in fiscal '31 is very pragmatic and judged. So don't think of this as the max case when you built your model on what the value of that warrant is. As usual, the way I do it is, I'm not conservative, and I'm not aggressive. I'm pragmatic. I use most probable outcome and we start from there. And then as we build over time, we adjust, right? We adjust our update. So that comprehends not the full value of the warrant, but some portion of it that, in our view, is a very appropriate judge view for this time. So what that means is you've got to a very healthy set of other sockets coming in because as Will talked about, we had 18 of these already won like a year ago we've layered in more and they're across all the different hyperscalers across all those different technologies. So it really will be a very diversified, rich business when you get to custom in 2030. And it's actually a great way to play custom because you're not rolling the dice on one giant socket and hoping and seeing what happens. We've developed quite a portfolio here. And I think that's going to serve us well as we go through the next few years. Next question.

Let me go to Tim.

And I'll direct traffic on these. So ask the question, and I'll farm it out.

So Matt, one, the emerging theme is sort of powered shell and whether there's going to be enough power [indiscernible] for all these XPUs. And Jensen would say that there will be enough for his product, but there won't be enough for anybody else's. So I don't know how much does that? I know that you're being very conservative in your XPU model for fiscal '31. But like how do you think about that? Like when you're talking to hyperscale CEOs, is this something that's like coming up?

No, not in the context of our XPU programs, our custom business are, quite frankly, anything to do with our current revenue. The way we have our CapEx, I think to set aside land power and shell, just take a step back, if you look at our model, which is 35% CapEx growth over our period from fiscal '26 to fiscal '31, that's not a linear CapEx. So right now, it's growing like 70% or more, right? And so we anticipate at the tail end of this, it's probably growing more like 20%. So we think we've built in our model just a lot of cushion for the AI business to kind of digest over time. If CapEx does better, actually, we'll do better but we don't see that as any kind of constraint or any kind of customer discussion at this time. And remember, we're across all the fleets and all the different customers, and we sell to everybody and we sell the systems, not only custom-based systems, but obviously, our broad-based business connects to every GPU, XPU accelerator on the planet. So not an issue for us. Next question.

Let's go to Tom.

For the interconnect TAM, I was curious if you guys could break that down a little bit further into calendar year '30. I think it was $38 billion. Is that more DSP share, more DSP volume, NPO, CPO? Any kind of breakdown that you could give us. Because that's obviously a really large number and where you see the most growth?