Marvell Technology, Inc. Common Stock The Six Five Summit: AI Unleashed 2026
Review the key takeaways and the transcript of this earnings call.
- Marvell has pivoted over the last ten years to focus on the data infrastructure market, which now accounts for over 80% of its revenue, up from less than 10% a decade ago.
- Marvell's data center business currently generates over $2 billion in quarterly revenue, with AI-related revenue expected to be $200 million in 2023 and $400 million in 2024.
- Marvell acquired Inphi in 2021 and Celestial AI in late 2023, enhancing its silicon photonics and optical connectivity capabilities, which are critical for scaling AI infrastructure.
- Marvell offers a broad portfolio including DSP-based optics, silicon germanium broadband analog components, silicon photonics, and custom silicon solutions, enabling connectivity within racks, across pods, and between data centers.
- Marvell has developed memory expansion technology based on the CXL standard, which has seen accelerated adoption due to AI workloads and memory shortages, positioning it as a multi-billion dollar business segment.
- Marvell's custom silicon business, originating from a 2019 acquisition, has grown significantly with multiple custom CPU and XPU attach designs deployed across major hyperscalers, with NVIDIA investing $2 billion in Marvell earlier in 2023.
- Marvell emphasizes coexistence of custom and merchant silicon, with custom silicon penetration in data centers expected to exceed 25% of units.
- Connectivity is identified as the next major bottleneck in AI infrastructure after compute and memory, with Marvell well-positioned to address this through integrated solutions.
- Marvell's CEO Matt Murphy describes the AI infrastructure market as still in the early innings, with significant technological advancements and scaling of GPU clusters yet to come.
- The company has a unified executive leadership overseeing silicon photonics, DCI modules, and switching platforms to drive end-to-end AI infrastructure solutions.
- Marvell's AI-related design wins span multiple hyperscalers and include custom silicon, memory expansion, and connectivity products, reflecting a comprehensive approach to AI infrastructure.
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Transcript
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We are kicking off with Matt Murphy from Marvell on where AI silicon is heading, then across four tracks: connected intelligent edge and networks, AI devices, enterprise AI software and agents, sustainability. We are going to hear how AI is moving out of the data center and into the network, the endpoint, and the application layer. Pat, you've been beating the drum on this for a year. Compute, it's being solved. You could say maybe it's been solved. It made NVIDIA a $5 trillion company. Memory, it's being solved. The memory wall remains, but we're making progress there. Connectivity is the new bottleneck. Jensen literally crashed Matt Murphy's Computex keynote to call Marvell the next trillion-dollar company. So frame day 2 for us. What does it mean when the wire between the chips, what connects the chips, becomes every bit as important as the chips themselves?
Yeah. So Daniel, this really is running historically as we've seen before, right? When you lose the capability, let's say, in one rack of data center equipment, you've maxed out the compute, either the power, you have to go elsewhere, right? You can build it up inside the rack, you can build it outside the rack, and that's really what Marvell is doing here. Not only is it intelligently connecting things inside the rack and then between racks, but also between data centers. And that's how you get this distributed computing that we need for training and, by the way, inference. As we'll also hear in day 2, we're distributing also on devices and onto the edge as well, kind of playing out historically like you would expect.
Absolutely. We've only touched on the power of physical AI, robotics, autonomy, but of course, today we're going to get a little bit more on that. And then, of course, we're even going to have the energy conversation in our sustainability track.
Yeah, looking forward to that.
All right. Well, let's everybody welcome Matt Murphy to the stage.
Let's get into it. Welcome to The Six Five Summit 2026.
It is AI Unleashed. It is day 2. I'm Patrick Moorhead, joined by my bestie, Daniel Newman. Today, we're kicking off things by talking about X infrastructure behind the next phase of AI and discussing what will it take to keep pace with the scale of the build-out. We're joined by Matt Murphy, CEO of Marvell. Matt, welcome to Six Five. You've been on the show before.
Hey, thanks, Pat. Great to be here.
Hi, Dan. Hey, Matt. It's been a minute, but you're a wily veteran of the show, so it's great to have you back here.
You kind of heard Pat in the setup. Look, it's all the things, and if you look at Marvell's, your M&A and your building over the last few years, it seems like you were kind of playing all the right cards. As we keep talking about where is the constraint, and you guys are playing in all of them.
Yeah. But look, let's start at a high level.
We are in the middle of the largest infrastructure build-out in history. Probably the largest technological revolution that any three of us young men will experience in our lifetime. From where you sit in the ecosystem, right in the middle of the action, curious, what is your overall observations of this transformation that's going on, and do you think people are actually underestimating this even still, as big as this is getting?
Yeah. Well, again, great to be here, and I think a couple of things to think about. I think the first is we've been on basically a 10-year journey here at Marvell. We made a pivot to what we called the data infrastructure market, which we kind of named 10 years ago. That really didn't exist as a sort of a semiconductor end market. But the belief we had basically was that all these millions and millions and billions of units of devices that had shipped and had created data, were going to create a whole bunch of data that was going to need to get sorted through and monetized and ultimately transmitted and moved around and stored. And at that time, the advent of cloud computing and data center technology was really taking off. So that's where we pivoted the company.
It was less than 10% of our revenue back then, and it'll be 80-plus percent of our revenue, not in the too near future, and the company has grown over 5x over that period. So it's not a new thing for us. But I think to your point, the AI application became kind of the killer app of data infrastructure. And while it feels like we're at the top here or can it keep going, I think we've all felt that way since ChatGPT dropped back in the end of 2022. So from our standpoint and what I see in the market, being in this business day in and day out, we are still at the very, very early stages of the deployments.
And even more importantly, I think the very early stages of really having, as a broad ecosystem, the technology required to truly scale AI to the levels it needs to, and we can talk about that. But Pat referred to it at the beginning. You had the compute, and that got all the attention, and it was sort of like who can make the best GPU and XPU and custom ASIC, and we could talk about all that, and processor. And then the memory and the storage has really been sort of a pronounced super cycle, if you will, that has been sort of unprecedented in the last year or so.
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