Rambus Inc. (RMBS) Earnings Call Transcript & Summary

All right. Good afternoon, everybody. Thank you for being here. I am Marco Lagos, I'm Morgan Stanley's head of U.S. semiconductor investment banking. And I am thrilled to be here with Luc Seraphin, CEO of Rambus, this afternoon. Just to read a quick disclosure here. For important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative.

So with that, Luc, thank you for being here. Great to have you. Why don't we start sort of high level? And I'm going to take it easy on you given the crazy 48 hours of travel you've had, which is symbolic of all the great client and customer interaction you're having. So let's start at the top. So framing the business just in general, what is Rambus today? But the question really is, I think a lot of investors think about Rambus primarily as an IP company. That is -- IP licensing company. How would you describe Rambus today? And what has changed the most meaningfully in the last, call it, 3 to 5 years?

Yes. For some people, Rambus is known as an IP company, and that's understandable. We still have a very strong and very enduring IP portfolio, which is foundational to our business. But we are not only an IP company. Today, we are really a system-relevant semiconductor company that offers complex chips, chipsets, but also system solutions to the data center memory subsystems, basically. So we've shifted the company over the last 2 to 3 years from being essentially an IP company to becoming a semiconductor company that offers complete system solutions for data centers and AI.

Wonderful. So just kind of touching on that though, talk a little bit about the economic model, product revenue, royalties and IP. How do those things all sort of interact? And why is that mix strategically attractive?

So we have an interesting business model. Intentionally, by the way. On one hand, we have our IP business that brings cash flows, that brings longevity because we have long-term agreements. And that brings us reach in terms of the number of customers that we touch and the number of platforms that we touch with that IP business. And we combine this with a product business, a semiconductor product business that brings growth to the company, that brings customer intimacy, that business. And that brings also relevance into the memory subsystems for AI. And the combination of the two is quite unique in the semiconductor industry, but it's a very balanced business model that allows us to invest in innovation. That high cash flows that we get from our IP business allows us to reinvest into products in a market that keeps accelerating in terms of the type of platforms that we have to roll out to our customers.

So it's not just the sort of the magnitude of the cash flow, it's the predictability of it that lets you sort of plan ahead as well?

Yes. The magnitude of predictability, those two aspects allow us to go through cycles while continuing to invest in new products and new solutions.

You've now mentioned AI and data center a couple of times. I'm assuming that's the market that you guys are most focused on today? Or is that -- or is it different than that?

This is certainly the focus of the company today. We are going through a memory supercycle in AI. And it's not only a question of having more bandwidth. It's a question of having the right level of power. It's a question of reliability of the systems. It's a question of interoperability of the systems. So it requires a lot of the investment, deep understanding of those systems and intimate relationship with customers. And that's where we position the company today. We certainly address other markets with our IP business, but the focus is really data centers and AI infrastructure.

Wonderful. So with that in mind, right -- and this is directly related. Why don't you tell the audience a little bit about the Rambus DNA? So what is the heritage of the company and why is it right place, right company, right time?

So our DNA is really memory subsystems. And it's not about simply providing chips for the memory subsystems in AI infrastructure, it's understanding how memory interacts with the system. And we've been doing this for the last 30 years. It's -- we understand memory subsystems really, really well. And as I said earlier, it's about how do we see those systems evolve in terms of bandwidth, in terms of power management, in terms of reliability and in terms of interoperability between the different chips. It's not something that is easy to reproduce. We typically develop solutions ahead of the market, several years ahead of the market, several years before they actually ramp in the market. We work closely with our customers. We work closely with the standard organizations. So we have a pretty good view of where our road map is going. But that system understanding of how memories operate in a data center is really, really our DNA. And what we've realized over the last few years is that memory subsystems have become a critical point of success in AI infrastructure. It's actually a bottleneck, and resolving that bottleneck is what we know how to do.

Excellent. So as it relates to -- obviously, memory is going through a supercycle. I think we've seen some -- just amazing performance from all the traditional memory players in general. How are you positioned for sort of the key memory architectures for AI and data center? So just to name 3 -- and you can talk about more if you'd like or just keep it to these -- but DRAM, high-bandwidth memory, SRAM and the next-generation CXL-type stuff.

So we actually play in all of these areas one way or another. On the product side, obviously, we focus on DDR module solutions or chips for those modules. And we see growth there not only in terms of continuing to grow our market share, but we grow the content on those modules. And those modules are going to become more complex going forward. So we do have several vectors of growth on the DDR side of the business. We also interact with other customers with our IP business with our HBM IP, our PCIe IP. So anyone in the semiconductor industry who wants to develop a solution for AI infrastructure has a possibility of using our IP. That's really interesting for us, that IP business in HBM and PCIe, more security because we deal with semiconductor companies that build chips that are going to be in the market in 2 to 3 years from now, but it gives us a very good insight of the trends that are happening in those markets.

That's excellent. And so as we think about sort of customer interaction, right? Traditionally, you could look at -- and I'm able to talk about this more, but it's obviously SK Hynix, Samsung, Micron, the storage players, that's been traditionally where you guys have had the most kind of interaction success. How are you thinking about sort of the pull side of things with the hyperscalers and working with them and interacting with them?

That's a very dynamic market. It's a market that is accelerating. So historically, you're correct. Our main interactions were with the 3 memory vendors and with Intel and AMD because that interface chip that we develop sits between the memory modules and the processors. So they have to be validated by both the memory vendors and by the processor vendors. What has happened over the last 2 years is that the hyperscalers have increased demands on the performance of those systems. They are actually pushing the market to move faster. So we have interactions with them. They are also proposing novel solutions that we have to look at. So our interaction with the ecosystem has changed. We're not only dealing with the memory vendors and the x86 processor vendors, we're also dealing with anyone who develops processes based on ARM cores, for example. And we interact with our customers' customers, namely the hyperscalers. So this is a very deep ecosystem interaction that we are in today.

And again, you get an early look at all that stuff just given the development?

Yes, we look at it early. We also take a leading role in JEDEC, which sets the standards for this. Because all of these products, whether they are ARM-based, x86-based, whether they're using different types of modules, they all have to work together. So it's important for the industry to define those standards, and we do play a critical role in this standard setting to make sure that we participate in the definition of the road map. And that gives, I would say, durability in our revenue outlook because we know what we need to develop ahead of time. We actually participate to the definition of that. And that gives our team a very clear road map into what they need to do in the next few years.

Got it. So just the last question on sort of the memory part of it, right? You're talking about durability of the revenue over time, part of it being driven by the stickiness of your relationship over longer periods of time and understanding things well ahead of when they're coming to market. I would say, in memory, the things -- in memory architecture in general, the things that matter are reliability and performance probably over cost, right? And if that's -- if you agree or disagree with that, first of all? Second of all, if you agree with that, how does that dynamic benefit Rambus?

So reliability in a memory subsystem for a -- in a data center is not an option. I mean, not being reliable is not an option. If you have an issue with that chip that sits between the memory and the processor, then you have a system down or the workload doesn't work. So the cost to our customers and customers' customers is unacceptable. So reliability is very, very important. Therefore, our customers pay attention to the trust that we have developed over the years. They pay attention to the validation process, the quality that we put into those products more than they care about cost. So that gives us a longer-term, sticky relationship with the ecosystem. And that gives us also a way of maintaining price at a reasonable level. Because cost is important. But I would say that's less important than the quality, reliability of the system. And the ability to develop this generation of products generation after generation at a faster pace, that's really what's important for those customers.

Okay. So shifting away from -- a little bit and wading into AI data centers. And you talked about system, so system complexity. That's obviously a big part of the structural growth story for the company. So one thing we've seen is AI is driving incredible innovation as far as the architectures for memory, right? What has surprised you the most about how quickly those requirements are evolving?

Actually, what has surprised me is how fast it has evolved over the last few years. The -- I would say over the last 2 years, we had to double the pace of rollout of our products. We had to expand our product portfolio. And we also have to look at all the innovations that people are coming up with in terms of memory subsystems. And that plays at the center of what we do. So we actually like that dynamic that is happening now. It's putting a strain on our development teams. They have to work faster, they have to work better. But it also gives us a lot of opportunities in terms of the type of products that we can develop for the future. And that gives us also some immunity against the cycles because these requirements are always going to be here. The requirements for bandwidth, the requirements for low power, the requirement for reliability, the system understanding are always going to be relevant going forward. And that plays at the center of what we do. But the pace of change has been amazing over the last couple of years.

Right. So I'm going to pivot just a second away from sort of the main path here and just talk about your decision-making, how you manage the company. Obviously, a lot of opportunities you could be [ speeding ] and thinking about. You're talking about the change and the pace of the change and how that benefits you. How do you think about where to allocate time, dollars, personnel? How do you make that decision?

If you look at the history of Rambus, one of the first things we did a few years ago is to actually stop the activities that were not related to the memory subsystems in data center or AI infrastructure. And that was, in retrospect, a very good move because of the acceleration that is happening in the AI infrastructure. So the first decision is to decide what not to do, and we did that. Then when we look at what we want to do. We want to invest in products that have the potential to grow in the market and where we have the potential to take a leadership position. And as a first approximation, what we're doing is we are developing products for every module solution that either goes into an AI infrastructure or data center or in the client system. And what you've seen over the last past years, couple of years is product announcements in that direction. We announced power management chip for the data center. We announced power management chip for the client space. And we also announced companion -- other companion chips for these two. And all of these chips are defined by JEDEC. Again, that gives us the confidence that they are going to be adopted by the market at large. So that's how we make decisions. In terms of prioritizing those decisions, time to market is really, really important. The validation process for these products is critical. And it's a long process. So you want to be first in market with the new products. So what we look at is what are the products that are so critical in terms of time to market, and we give those products the priority. So we decide what not to do. We decide to focus on standard products that are approved by JEDEC or defined by JEDEC, and we prioritize the product where we can be first to market.

Wonderful. So getting the train back on track here with the system conversation. Where do you see the biggest increase in content per system over the next several years?

Content per system, when the market moved from DDR4 to DDR5, we had an expansion of the content because some of the functions that were sitting on the motherboard in the DDR4 generation of products had to move to the module itself. So instead of having a buffer chip only in the DDR4 generation, we have a buffer chip and what we call companion chips. So there's a content expansion just in a standard module. Going forward, the market is going to adopt what we call MRDIMM. And MRDIMMs are module solutions that double the capacity and double the bandwidth of systems. That also multiply the content by a factor of 3 to 4. Because at those speed and those capacity, you need to add a lot of more chips than you currently have on a standard DIMM. So that's a very nice, I would say, growth vector for us. And as I said earlier, we're also addressing the client market. Because in the client market, some of the challenges that we found today or we have found in the data center, we're going to find them in the client systems as well. As speeds go up and memory capacity goes up, some of the functions that we had to perform in the data center has to be performed in the client systems as well. So that's how we see the expansion. More chips on the current DIMMs, MRDIMMs, that is going to increase the content quite substantially. And introduction of similar types of chips in the client system.

Wonderful. So if we're talking about what's coming next, right, which newer products or technology should investors pay attention to that aren't really fully reflected in sort of your guide and your financials today?

Well, today, most of our revenue is coming from the licensing business and from the product business. Product business is actually today, the largest business in the company and the fastest growing business. What is not reflected in our numbers yet fully in terms of potential growth is precisely MRDIMMs because it's going to be introduced to the market towards the end of the year, it's going to be in full swing next year. The client systems as well. So all of these new products that we have developed over the last 2 years that are actually in validation process in the ecosystem as we speak are not reflected in the short-term, really in a meaningful way, revenues. But they are going to contribute to the growth in the longer run.

Okay. Then how do you -- as you think about products and newer products again -- and this is back to the management questions, just as a core strength of the company. How do you balance investing ahead of the curve, right, versus waiting for the standards and the platforms to fully form?

Well, that's an iterative process, if you wish. We do talk to customers and partners, the customers or the memory vendors, the partners or the processor vendors. And we talk to the hyperscalers as well. And with them, we have a view of what they wish their road map to look like. We also are part of the JEDEC standard organization. And that's where we also -- with the other members of JEDEC, define products. So that's how we define the products, and that's how we prioritize our products. Then, as I said earlier, in terms of timing of rollout of the product, it's really about being first to market with the most complex products. If you look at the history of our product introduction for the DDR5 cycle, for example, the first product we introduced is what we call the RCD product, the clock recovery product on the module because it's the most difficult product to design. It's the longest product to validate in the market. So it was important for us to be first with that. We came with companionships later, and we did this on purpose because we didn't want to miss the transition from DDR4 to DDR5. And we didn't miss that transition. When we moved from DDR4 to DDR5, we went from a 20%, 25% market share to 40% plus market share today. So that was the right decision. We then introduced our companion chips. And in the companion chips, we invested heavily, in particular, in the power management chip because we believe this is something that is critical to the performance of the system after the RCD chip. And it was important for us to build the team so that we have the know-how internally. And we've introduced our first products. And with these first products, we have very strong and positive customer feedback, especially in the high end. So that's what we do. We pick the things that are difficult to make that are really relevant for our customers. We want to try to be first with those. That's how we develop our road map.

So when I think about sort of -- you obviously -- you talked about choosing what not to do and then thinking about the things you want to tackle and how you're going to tackle them being sort of critical parts of the strategy. You mentioned power management a couple of times, right? That has not traditionally been an area where Rambus is focused as developing a sort of specific product. It's happening now, right? Obviously, competition is robust in that ecosystem with a lot of traditional players out there. How is Rambus well suited to compete and succeed in power? And how much would you say the growth and the future of the direction of the company depend on the ability to succeed in that specific vector?

Yes. Power management is different than power management on a module. A module environment is a very stringent environment in terms of thermal requirements in a server, in terms of space and in terms of how precise this power management, this power delivery has to be. So it's more than being able to do power management at large. It's about being able to do power management for this type of memory subsystems. And the power management chip interacts with the other chips on the module. So the understanding of how the system works is also very, very important. So we do understand modules. We do understand the interoperability of chips on the module. We understand the ecosystem because these are the same customers with the same validation processes. And we have invested in power management several years ago. We were silent about it. We have built the teams. And the first power management chip that we have released to the market have had -- we were not the first. We came into a market where you had incumbents there. But we've been designing by all of our customers, especially on the high-end side.

So would you say that the way you've tackled power management is purpose-driven, as opposed to reverse engineering with a product that already existed?

Absolutely. It's purpose-driven. This is also an area where we work with JEDEC and the industry. But AI infrastructure will require more bandwidth, more capacity, and this is not going to stop. And on the same type of form factor. So the system requirements are going to become more and more complex. And having the ability to understand power management in that environment, clock recovery in that environment, system interaction in that environment is really, really critical. And I think that as the infrastructure for AI continues to evolve and improve, it's going to play on those strengths of ours.

Yes. So I think it's clear. Connectivity, memory, power. You mentioned clock. Timing is a little bit of a dark art. How do you see that evolving for Rambus? And how do you think you'll be playing that market?

Timing?

Timing, yes.

The RCD chip is actually a timing chip. And the challenge with these chips is you have memory signals at very high speed traveling very close to each other. So there's a lot of cross noise and these type of things. And that's why on our earnings call, we talk about signal integrity. The key here is to be able to deliver clean signals between the memory and the processor in a very noisy environment and at a higher and higher speed. So that's signal integrity. That's actually timing technology. So in the future, there will be timing requirements. The first adjacent markets that we are addressing, as we said earlier, is the client system. In client systems, we're going to have faster and faster signals traveling on very -- lines that are very close to each other. That's going to create noise. We will have to clean those signals. This is really a -- not as much as engineering work. And that's why it's very difficult to reproduce. This is things that we have learned over decades of work in that specific area.

Terrific. All right. So a little bit of a hypothetical. You're looking out 2 to 3 years in the future. What would you make Rambus -- what would make Rambus look meaningfully different than it does today?

Well, I think we'll continue to have a broader portfolio of products. That's certainly something that is clear. I think we're going to have deeper relationships with our customers and the hyperscalers in terms of defining what's going to be required for next generation of AI. These are two areas that are absolutely clear for us. There's certainly the capability for us to expand our know-how in signal integrity into the other markets or our know-how in power integrity into other markets. That's where we see the growth vectors above and beyond what's driven by the AI infrastructure. But the AI infrastructure offers tremendous growth potential for us already.

Great. All right. Well, look, I can't hand it off to the audience or without talking a little bit about your financial model. It's attractive. Rambus generates substantial free cash flow, right? Why don't we talk about some of your metrics and your performance and free cash flow. Anything that you're particularly keen for the audience and the investors to understand?

So yes, we generate strong cash flows just because of the structure of our business, the combination of the IP business and the product business. And our #1 priority is always to reinvest into products that are going to continue to fuel profitable growth into the business. And this has been the case over the last couple of years. As I said, the road map has accelerated. The pace of that road map has been doubling over the last few years. And the breadth of our product offering has been expanding as well. So our #1 priority is to reinvest into our business so that we can continue to grow and to keep our leadership position there. Then we look at M&A. Of course, that's always a vector, whether it is to expand or accelerate our growth, but also in terms of bringing the right resources internally. And as I said, we are specialized in power integrity, signal integrity, and it's important to have the right resources to continue to fuel that engine. And finally, we have a -- we are returning cash flow to our investors on a regular basis. Say, 40% to 50% of our cash flow is being returned to our shareholders on average. We pick the right time to do this. But we are able to balance these 3 vectors.

Wonderful. A few minutes left. I wanted to see if anybody in the audience have any questions? We've got one right here up front.

I have one question. So compared to the CXL, I think Rambus is more preferred for the MRDIMM to expand the memory, right? So -- but right now, there's -- some hyperscalers, they have traction -- some traction to use CXL to disaggregate the HBM and the story -- sorry, the memory as computing. So my question is firstly, like I remember in your previous quarter calls, you said that you -- Rambus will be -- invest more in the MRDIMM compared to CXL. So this thing will change it or not? Will you think about to develop any kind of CXL controller in the future is the first question. The second question is like -- since the hyperscaler is thinking about to use CXL to disaggregate the HBM to the GPUs or ASIC, will this impact Rambus HBM IP business?

I think there were two questions there.

Two questions, yes.

First is -- the first question was around CXL and MRDIMM. The initial idea about using CXL for memory expansion is -- was the following. If you take a processor in a data center, the processor has a limited number of memory channels. And the AI workloads require a lot of memory. So very quickly, you saturate those memory channels. And once the memory channels are saturated with memory and you need more memory, then the only way to do that is to have another processor with memory, and that's not economically...

Is that the memory wall that people talk about?

This is the memory wall that people talk about. But the -- so one idea was to use the CXL interface to actually add memory. That -- this is where it started. And at Rambus, we play in CXL in two ways. One, we have a CXL IP controller that as part of our silicon IP business, that we sell to whoever wants to develop a chip in the semiconductor industry that has a CXL interface. The second way we play in CXL is we have developed our own CXL chip, CXL controller chip, but we've not commercialized that chip. And the reason is that CXL defines an interface, it does not define a chip. It's not like JEDEC. And what we see in the market is people who have a CXL controller chip, these are custom chips. The Customer A has a flavor of a CXL controller, Customer B has another flavor, Customer C has another flavor. And for us, the business model didn't really make sense if we had to develop a chip per customer. This is -- it's -- the market in aggregate is an interesting market, but it's a very fragmented market. But if we want to talk about memory expansion, then the MRDIMM solution is a more elegant solution. Because you just remove a DIMM from a memory channel and you plug an MRDIMM instead and you double the capacity and double the bandwidth with the same software infrastructure and with solutions that are being developed by JEDEC. So that has been adopted across the industry and across customers. So that's one reason. So we still play in CXL, but we've limited our play in providing IP, silicon IP to anyone who wants to develop one of those custom chips for this aggregation, whether it's for HBM disaggregation or DRAM.

Okay. Perfect. Anybody, any other questions from the audience? Okay. If not, I do have one. I know. Yes, I do have one. Back -- we started with the big picture, let's close with the big picture, right? So if an investor puts their money to work on Rambus and they checked back in on that investment in 5 years, what do you hope that they will say that the company got right?

What I would say -- I'd like them to say that we understood how the memory subsystem evolved. We anticipated that, and we invested early with conviction into these new memory subsystems. I hope they would say that we could balance our investments in a way that prioritize products where we have strength. And I hope they would say that we have become a very strong player in the development of AI infrastructure because memory is critical to AI infrastructure.

Perfect. Look at that, almost perfect timing there. Thank you very much, Luc. Appreciate your time today. Thanks, everybody. Oh, we've got one more question in the back of the audience. Sorry about that.

Sorry to keep everyone here. Can you help us think through DIMM growth? Like there's a lot of moving parts on server growth and DIMMs per channel. And just what you guys view the DIMM growth market as and how you should perform in that? And then just a second question for MRDIMM, just how we should think about the mix of that in the ecosystem in like '27, '28?

Yes. So for the DIMM growth, what we quoted, there are several factors entering the DIMM growth is the server growth. We quoted in the last call, the 8% growth from Gartner, which is on the high end when you look at these analysts. But we believe the DIMM growth can be higher than that. There are several factors coming into it. One is the number of memory channels per CPU. It moved from 8 to 12, it's going to go to 16. So that increased the DIMM growth. You have to balance that with the capacity on each one of the DIMMs because it can increase capacity just by increasing the capacity on 1 DIMM, not only adding DIMMs. And you have to balance also traditional servers versus AI servers. But all in all, we believe the DIMM growth is going to be higher than this 8% that we quote. It's probably going to be double digit, but that's something we continue to track on a regular basis.

Okay. All right. Well, unfortunately, we are out of time. So thanks very much again. I appreciate it. Thank you.