Good afternoon, everyone. We'll get started with the next fireside chat. We're very happy to have Astera Labs here with us, relatively recent IPO. We have the CEO, Jitendra Mohan, as well as Nick Aberle, the Treasurer and Head of Investor Relations. So, gentlemen, probably Jitendra, Astera is a recent IPO, hypergrowth story, AI connectivity, tons of exciting stuff, but might be new to some folks. We'll dive into, you know, product types and all of that later, so you don't have to go into that answering the first question. But just talk a little bit about the market opportunity you saw and how Astera fits into it and addresses it. Absolutely. Thank you, Rob. Thank you so much, first of all, for the opportunity, and thank you all for joining us here, sacrificing the sunshine outside, you know, for this room. So thank you. We started Astera Labs six years ago, a little over six years ago, so we've been sort of, you know, in the business for six years, and when we started Astera, it was with a very simple premise. What we wanted to do was to connect all of the GPUs together to solve models that were growing in complexity even back six years ago. That they will reach a trillion parameters was not something that we had predicted, but our basic premise was, "Hey, look, the model complexity is increasing. You will need to interconnect many, many GPUs, you know, hundreds, thousands, tens of thousands, and now we see hundreds of thousands of GPUs together." We didn't wanna be the company that created the GPUs or the AI accelerators. You know, several folks were doing a bang-up job already, but we did want to be the one to connect them all, and that's really what we have done over the last five years. If you look at how these GPU clusters operate, they're trying to solve these immense problems. In order to do that, they need to collaborate with each other. In order to do that, they need to talk to each other at very, very high data rates, and that's the problem that Astera is trying to solve. We have our connectivity products that solve the problem of getting data in and out of the GPUs, and what you find with modern clusters is typically about three different bottlenecks. Data bottleneck, getting data in and out, network bottleneck, to kinda connect these big, large clusters together, and memory bottleneck. These are the problems that we are trying to solve, and you know, the culmination of all of these is the GPUs are the clusters are only utilized about 50% at best, sometimes even less than that, and that's a huge problem for the industry that we are trying to help our customers solve, deploy these complex clusters into their data centers. Over the last five years, we've released three different product families, as well as our COSMOS Software Suite, and together we call this our intelligent connectivity platform. So we have our Aries retimers. That's probably the one that's most famous for PCI Express. That solves the data connectivity bottleneck. We have our Taurus smart cable modules. It does for Ethernet what Aries did for PCI Express. That solves the network bottleneck. And then we have our Leo CXL memory expansion products, and that addresses the memory bottleneck when it comes to general-purpose compute as well as AI. And of course, we are not sitting idle. We are working on many new products. We introduced our Aries smart cable modules recently that expand the reach of PCI Express to seven meters, and working on new product families as well. And actually, maybe if I make just one more comment there. What has happened over the last five years is this is, you know, very unique. I've been in this industry thirty years. It's very unique, what we've managed to accomplish is to really become a trusted partner to our customers, whether they are the AI platform providers who are innovating at, you know, super rapid pace, NVIDIA said they are, they're gonna be introducing new, you know, families every year, or the hyperscalers. They come to us now and say, "Look, we are planning to deploy our next generation of ASIC accelerator or a third-party GPU. Here are the connectivity solutions we need, and Astera, you guys can do chips, you guys can do hardware, you guys can do software. Here, build this solution for us." And that is very, very unique to us. And not only have we deployed the hardware, which we are very proud of, but also our COSMOS software. And for those of you new to Astera, what COSMOS software does, it really harnesses the power that we have built into our hardware solution, whether it is for performance, diagnostics, observability, you know, fixing issues that might come up, and enables that our hyperscaler customers to use the COSMOS software into their own operating stack. So they use this COSMOS software to customize the solution, optimize the performance, have debug features, have diagnostics features. Effectively, our chips have becomes the eyes and ears of the connectivity infrastructure with the COSMOS software. So very proud of what we've been able to do. You know, the culmination of all of the hardware and the software are the results that we've delivered. We've had two quarters as a public company now. Last quarter, we delivered $77 million in revenue, 78% gross margins. We delivered $0.13 EPS, non-GAAP, so clearly, you know, focusing on building new products, servicing our customers, and delivering great results, and we are just getting started. Thank you for that overview. Let's - before we get into some of the specific product types, to the extent you were prescient enough to see some of these connectivity needs in the AI market, at least directionally true, where do you think we are in the AI cycle overall? The sustainability of it, the need for a digestion period or not seems to be a very active debate. From your perspective, where are we? I can say definitely we are early in the AI cycle, so we are not seeing any signs of slowdown. However, I will say that with any new technology, especially one that's evolving as rapidly as, you know, AI is, whether it's, you know, third-party GPUs, merchant GPUs, or the ASIC accelerators, there will be ups and downs. There will be, you know, periods of very rapid growth, and there will be some periods of, you know, maybe not so rapid growth, my crystal ball is not much different from yours. I can't really predict when these happen, but what we are focused on is what we can do. So we are working heads down to make sure that our customers can deploy all of this technology in the fastest possible manner. Whether the market is going up or the market is going down, our job is really to make sure we deliver results and outsize results in whatever the market conditions will be. One other evolution amongst many in the AI market is the type of processor to accomplish that. You mentioned about kind of the ASIC side of things. Does Astera care if it's a GPU or an ASIC? No, not to the first order. Our content varies from platform to platform, whether it's, you know, GPU by one AI provider versus GPU by another AI platform provider, or ASIC, the content will vary. But we are in the business of connecting all different type of GPUs and accelerators. And by the way, NIC devices, storage devices, what have you. Whatever it takes to build a complex AI server and deploy it, we are in it to connect them. The difference sometimes comes in which part of the system we play in. Typically, for some of the GPUs, you know, let's take NVIDIA as an example. They use NVLink to cluster the GPUs together. That's a closed standard. It's a proprietary standard. We don't play there. If you look at the ecosystem outside of NVIDIA, companies would typically use either PCI Express or Ethernet or, you know, derivatives of these protocols to cluster their AI accelerators, ASICs, or their GPUs together, and that's an additional opportunity for us, and typically, our content is even higher in those platforms than it is in some of the other ones, so at the high level, it doesn't matter, but based on which one will ramp when, our content may vary. So we'll get into more aspects of the question I'm about to ask when we get into retimers themselves, but how much customization do you see of these platforms, where the delta in your content matters more by what the CSPs choose to do and the topologies and architectures they choose, rather than, you know, it's an ASIC, is it GPU, is it NVIDIA, is it AMD, et cetera? Yeah, great question. So I think first thing I would say is no two CSPs are alike. They're all trying to solve the same problem of enabling and deploying AI and making it available to their customers, but everybody does it differently, and each one is big enough that they can demand a custom solution for to suit their needs. Whether it is, you know, power delivery, cooling, how they monetize the solution that they are about to deploy, what software infrastructure they have put in terms of the smart NICs that they are using, so what we have learned is no two clouds are the same, and they're all big enough to require customization of the solution. What it means to us, though, is, you know, we can't be the ones producing a specific solution for each cloud vendor. That's, that's just not very practical. So the approach that we have taken is to, you know, build our products from the ground up with a software-first architecture, where we have a lot of microcontrollers, that that run all of the protocol features and make our products really what it is. And by using these, the software that runs on these microcontrollers, what we call COSMOS, we are able to customize our solution to the requirements of each and every hyperscaler. And so you will see that the, the solution we give to CSP one or CSP two is based on the same product, but customized to their application. So let's talk about the retimer business, your Aries product line. It's still, you know, 85%-90% of your revenue, I think, this year, growing a couple hundred percent. So very, very powerful growth and impressive growth. For this audience, please explain what does a retimer do, and what's the sort of content that people should think about in a typical AI server? So, so for the record, I've been building retimers for more than a decade. So sometimes I get too much into the nitty-gritty. So let me, let me try to give an analogy that I, I used once, you know, earlier in the year. What the retimer is able to do, what the retimer's purpose is to, to, enable communication between two entities. It could be a CPU or it could be a GPU, it could be a CPU to a NIC or GPU to a NIC or what have you. The retimer is kind of like, maybe the analogy is to use a relay race. So if you are gonna be running a sprint, you can run very fast for a hundred meters and kind of, you know, finish that in record time. But if somebody asks you to run a sprint over a marathon distance, that's not possible. So what you do, or one of the things that you can do is, you know, look at the analogy of a relay race. You run, you sprint hundred meters, pass the baton to somebody else, run another hundred meters, and you can complete the whole marathon that way. And this is really what a retimer does. When you launch a signal at a very high rate, it gets corrupted, it gets kind of tired much sooner. And so you put a retimer. What the retimer will do is to recover that signal, understand what the message is, and retransmit a completely fresh copy of the message. And now you can go another distance, and once the message gets corrupted, you can put another retimer there. And so you might even see multiple retimers in a link. So Aries family does this for PCI Express, and PCI Express, for those of you who may not know, is really the nervous system of an AI server. All of the different peripherals have evolved to connect to each other over PCI Express. So we see this running around everywhere, and that's where our retimers get used. And our Taurus family does the same thing for Ethernet, for connectivity between accelerators or sometimes from a server to the top of the rack switch, et cetera. So people have talked about the need for a retimer potentially lessening as some of the AI architectures are going more systems approach. You know, the GB family from NVIDIA, AMD just bought ZT Systems, so they're gonna try to go down the systems route. Mm-hmm. Talk about the role of retimers in these new kind of more system approach, from not your direct customers- Sure. but part of the supply chain. Yeah, no, very, very good question. The need for retimer is actually driven by the need to connect multiple GPUs and accelerators together. So long as you have a cluster that is hundreds, thousands of, you know, these accelerators connecting together at increasing speeds, you will need the retimers. Where they go will keep changing based upon the unique architecture. So you mentioned Grace Blackwell. In the Grace Blackwell architecture, the CPU and the GPU are right next to each other. You don't need any retimer to go in between. The signals are, you know, easily able to make their way from the CPU to the GPU. But what about the NIC? Who is gonna drive data into this combination of Grace and Blackwell? The data has to come over the network, that is connected through a NIC. So now you need to go from this combination of Grace Blackwell to the NIC. That is over PCI Express. Well, you may argue that, "Hey, I can bring the NIC close to this combination as well." Now you don't need any connectivity, any retimers between the NIC and the Grace Blackwell. Well, then the NIC has to go to the top of the rack switch. So it's like a balloon. You push in one side, it's just gonna pop in the other side. So long as we have new platforms coming up, which are driving the data rates higher and higher, just like Blackwell platform does, from PCI Express Gen 5 to Gen 6, Ethernet is going from 100 Gbps per lane to 200 Gbps per lane, the need for the retimer-type products will continue. Now, exactly where they go, who's buying them, is it the AI platform provider or the CSP? All of that changes, but the need is there. So investors seem to try to make it a black-and-white discussion, an either/or, but yours is the mix will be different, the use case will be different, what you're connecting will be different, but the need for it will persist. Absolutely. And so how do you differentiate in retimers versus the competition? You talked a little bit about the COSMOS software side of things, but just talk about, you know, it's a standard PCIe. How do you or Astera differentiate versus what, you know, Marvell reports after the close tonight? You have the guys from Broadcom coming at that market, too. What makes Astera special? You said something, let me answer that first, and then I will answer the competitive question as well, which is investors like to see it black and white. So, you know, maybe, if I may, kind of help understand the situation. What the mix of products will be, how exactly Grace Blackwell or Blackwell gets deployed, or for that matter, other products get deployed, that's not really our call to make, you know? And NVIDIA is gonna do what they will do, CSPs will choose to deploy it one way or the other. But where we do have visibility is into what designs we have won, what backlog we have. And this one I can say with confidence, that with the Blackwell family, we have a backlog in place, where we are gonna be selling our different product families, including the Grace Blackwell. Where our content on per system basis is going up from kind of hundreds of dollars, if you look at a Hopper generation, a HGX board, to a rack-level solution, where we are, you know, in tens of thousands of dollars of Astera content. Blackwell is great for us. You know, we love it. The visibility we have is not based on a guessing game, but based on the backlog and pre-production shipments that we have done. And the same thing is actually applicable to even greater extent with ASIC platforms, where, as we discussed earlier, we have even greater content. Now, to come to the competitive question. Contrary to what you guys might have heard, we were not the first ones out of the gate with the retimer solution. When we first got our retimer solution out was July of 2019. There were already three or four other, you know, companies that were trying to also execute on a retimer solution. You know, fortunately for us, based because of the architecture that we have, we survived, all the other companies are gone. And the reason for that is rooted in the architecture and our understanding of the problem. Most of the companies are building the retimer to solve the retiming problem that we just described. Signal doesn't go from here to here, and so you need a retimer in between. We did that, other companies did that as well. But what we also realized is the deployment complexity is going to be rather large. These clusters are very complex, and the customers will have a lot of need for deep diagnostics, ability to understand what is going on with their clusters. We built a lot of these diagnostics features in, and as I mentioned, enabled it over COSMOS. What we're able to do with COSMOS is when a problem arose in the field, and there were many, by the way, not just for us, but for our competitors as well, we were able to find out what the problem is in a matter of days and solve it in another few days. Given a week, we figure out one problem, and we are on to the solving the next one. We were able to iterate very, very quickly, which our competitors were not able to do. So that is what got us into this leadership position. Now, you may say, "Look, the new competitors know what you're doing," and we have certainly talked about it openly, and they can copy that architecture. You know, sometimes, imitation is the best form of flattery. So even if they do that, though, over the last three, four years, we have learned a lot by being in the trenches, by understanding in this PCI Express, you know, standard, what works, what does not work. Thousands of pages of spec, everybody implemented just slightly differently. With our COSMOS software, we can, you know, solve these problems that arise in the field, understand what those are, what are the workarounds needed, put that back into COSMOS. So over time, COSMOS has become very rich, and any new entrant will have to spend that soak time. I mean, there is no shortcuts to experience. They'll have to spend the soak time to get not only their hardware up to par, but also their software up to par, and then convince a CSP that they should deploy yet another software standard into their operating stacks. So, you know, over time, it will happen. Meanwhile, if you look at the reality of the situation, PCI Express Gen 5 is already done, right? The designs are already won, et cetera. PCI Express Gen 6 is very close to getting there. NVIDIA has mentioned that they're gonna start shipping in Q4, Q1, and so on. If somebody is not ready with their PCI Express Gen 6 solution, they will again find themselves kind of, you know, going after a much smaller piece of the pie. So going from Gen 5 to Gen 6, in and of itself, doesn't really change the core value that Astera can bring relative to the competition? It not only does it not change the core value, it actually strengthens the proposition that we have. Where COSMOS is already deployed, for our CSPs, the easiest upgrade path is to simply go from Aries Gen 5 to Aries Gen 6. It is fully backward compatible. They know the device, they know how to use it, the software is already there, everything just works. So in many ways, I would say that when we go from PCIe Gen Five to Gen Six, and our customers have said this, this is our business to lose. So long as we keep providing good parts, we keep supporting our customers, this is our business. Does the retimer itself come up as a, you know, area that they're trying to squeeze that cost out of the equation? You mentioned earlier that the GPU utilization can be as low as 50% at times. It seems like enhancing that would be a much better TCO move than focusing on getting rid of retimers, but am I correct in that? Absolutely. And first of all, in any pricing negotiation, nobody should walk away happy. Everybody should have some level of unhappiness in the pricing discussion. But when a design in actually happens for these retimer-type products, pricing is not the first thing we talk about, it's not the second thing we talk about, probably the third or the fourth thing. First, decision point is always: Are you able to make my infrastructure work? Which is to say, do you have the right performance? Can you make the signals run, you know, point A to point B at the right speeds that I want? That's one. Because if you don't have it, then you don't have a product. Second one, which is absolutely important, is how robust is that link? That's where we have spent, you know, all of the last three, four, five years in improving the robustness of these links through the hardware that we've developed and the COSMOS software. It is absolutely critical that these links remain up at the highest speed all the time. What you don't want is, I have a GPU that's running at PCIe Gen 5, but every so often it's dropping packets. Like we discussed earlier, the whole GPU cluster will run at the speed of the slowest GPU. The hyperscalers, data center operators pay very close attention to the health of their system, and that's what we really enable with the products that we have. Robustness is number two. After that, you get into other kind of ancillary things, including pricing. So the last question on the retimer side, before moving on to the other two sides of the business. Some of those potential competitors, aspiring competitors, also have an ASIC business. Mm-hmm. They also have big networking businesses. So to the extent, you know, you have to understand what the processors are gonna do, understand what the networking is gonna do, and kind of the way you outlined it before, do they have a distinct advantage in that they would be able to bundle and have a better shot at getting into the retimer market? Not for the type of customers that we are talking about. The hyperscalers that we are talking about are big enough. They have kind of enough muscle to kind of not fall prey to some of these bundling techniques and so on. If you look at technically, is there an advantage because they are building the ASIC versus, you know, maybe they're also able to build retimers and such? I would say there is not that much, because just the very nature of retimers is that it needs to talk to one device on one side and a different device on the other side. So the fact that you're able to talk to perhaps your own device on one side is only part of the equation. You need to be able to work, interoperate with, you know, ten different types of, you know, processor class devices, maybe fifty different types of endpoint type devices. And that's what we have done over the last three, four years, is to build a very healthy interoperability lab where we do this testing, figure out what's working, what's not working, and fold that back into our COSMOS software. That's what the ASIC guys will have to do as well, and I would argue that we are better prepared for it because of our history than some of the ASIC guys. Let's pivot over to Taurus, the AEC product. How are you guys at Astera differentiating versus some of the competition, the Credo and Marvell that are either in or soon to be entering that market as well? Yeah. So for Taurus products are a little bit different from Aries. They are doing the same thing in that they are both retimers. Aries are PCIe. Taurus is for Ethernet, but the form factor in which we are selling is different, and that's also what differentiates us from the competition. Aries is sold mostly in the chip form factor, although most recently we also introduced the Aries Smart Cable Modules. Taurus, on the other hand, is sold as Taurus Smart Cable Modules, which get assembled as part of an Active Electrical Cable. So the difference between what we do versus what, say, somebody like a Credo does, is Credo says, you know, "In order to solve this problem of reach, I'm gonna give my customer the whole cable end to end." And there are some certain advantages to this, one of which is speed, right? They were able to come to the market sooner with their solution. But if you look at it from a customer standpoint, what they have to do now is they get to qualify one cable from, say, a company like Credo, but then in order to make their supply chain diversity work, they need to qualify another solution from somebody else and then maybe another solution. That's what they're used to, two or three different cable suppliers. So we chose to do it differently, partly because, you know, we are not experts in cables, and I would argue maybe even Credo is not experts in cable. The cable expertise resides with companies like Molex and TE and Amphenol and so on. So we work very collaboratively with them. We design the electronics, the paddle card, as it is called, where the retimer chip resides and a few other ancillary components reside, and we sell that to the cable vendor. So now Molex or TE or Amphenol, what have you, they can build the active cable and put all of the R&D dollars that they spend on cable development, inventory management, put all of that to work and supply a full Active Electrical Cable to the end customer, which might be a hyperscaler. Now, if you look at it from a hyperscaler perspective, they get to qualify this only once. Because we work directly with the hyperscaler for every component that goes on this paddle card. Every piece of software is to the specification of the hyperscaler and customized for the hyperscalers, by the way. Security requirements, software requirement, f irmware requirement, link robustness requirements, all of them are part of the hyperscaler specifications. So they get to qualify this once, and as and when there are problems in the field, they know who to go to, which is, in this case, would be Astera, because we are the ones who are providing the electronics. So fundamentally different business model. We certainly believe in our business model, but time will tell who is more successful. How should investors think about the growth trajectory of this business? It's relatively new to you very, very small as a percentage of sales, but starting to grow pretty rapidly. So just talk about the targets and the slope of the growth that you would expect. Maybe I'll start and then Nick can add. So like you said correctly, the business is just starting to bloom. We have some of the Taurus products selling in lower volumes for the last couple of quarters for 200G node, which is a fairly niche application. Later this year, we'll have 400 gig that is going to ramp, and I would argue that's also a niche application. For some of these AI clusters, where the cable thickness needs to be small and so on, you know, we are addressing those with our Taurus 2 product family. Later this year, in 2025, as data rates shift from 400G per cable to 800 G per cable and 100G per lane, that is where we see a lot more deployment of Active Electrical Cables. We will see this will go from being a niche application to a broad base, where most hyperscalers are going to add Active Electrical Cable solutions. Yeah, I mean, so the only thing I would add is, you know, when you talk about our guidance into Q3, we guided to roughly $20 million of incremental revenue quarter over quarter. A meaningful piece of that is driven by Taurus. And the exciting piece of that is it's not just one program going into one application. It's actually, programs that are ramping on the general purpose side, and programs ramping on the AI side. And even on the AI side, it's going to be connecting and scaling out, both, internal ASIC platforms and, third-party GPU platforms. So I, expecting a pretty nice growth rate. We had the partial quarter in Q3, so there'll be some ramp in Q4. But these things take multiple quarters to kinda get to volume production and full mature run rate, so I think it's going to be a pretty nice driver for us. Does the kind of accelerator/GPU versus CPU crowding out effect, AI servers versus general purpose servers, does that matter much within this business for you? Because it seems like, you know, it'll target both sides of that equation. Okay, go ahead. So, yeah, I mean, so there are opportunities on both sides. I think the good thing for us is we play on both sides of the equation. We approach the market with various applications, whether it's going to be a straight cable, a Y cable, or a crossover X cable. So we're really there to support whatever the customer is trying to accomplish. And, you know, again, kinda just going back to the kind of core premise as speeds continue to increase, these distances continue to get harder to traverse with good fidelity with the signal. So those attach rates will go up. We're seeing that happen in 400G, and then we'll really start to see it happen on 800G. As those speeds go up, is there the risk that there's even more intelligence added to the ends higher level of processing that would be beyond what you're targeting? You know, when people start to do some of the PAM4 side of things. We are already doing PAM4. The Taurus product that we have does 800G PAM4. So, I mean, contrary to some belief out there, these are DSP chips. They have DSP in them. You know, case in point is, we took the DSP, we took the flexibility of our COSMOS architecture, and we drove PCI Express over optics. Right, so we are doing what a traditional optical DSP would do. So these are all very smart and heavy-duty DSP chips already. Got it, so the final of the three segments that you've talked about is the CXL business, the Leo business. That one is a little bit more nascent, and so versus the other two, where the market's big and people are more or less arguing about, you know, the growth rate of an existing market and the share you take, this one, it's a little bit more nebulous as to the size of the market itself. So explain what CXL is going to mean as a market and where Astera plays in it, if you could, please. Yeah, perfect. So CXL, for those of you who don't know, is a new standard that's written on top of PCI Express, and among other things, it allows a CPU or a GPU to access memory over a CXL link. So this was something that was introduced in 2019, and we've been working very, very closely even before CXL became an open standard, so we really believe in CXL. What we have been able to do over the last year is actually demonstrate the problem that we are solving with CXL, using Intel's Emerald Rapids CPU and equivalent CPUs from AMD as well, where we can see application-level performance speed up 50% because of the additional memory bandwidth and the additional memory capacity that's available. Same thing goes for database applications themselves. So the ROI is clearly there, and we have very clearly demonstrated. But as you say, this is still a nascent market, for two reasons. One is the CXL-capable CPUs got delayed. So what was supposed to happen, the Sapphire Rapids generation, is now happening with the Granite Rapids and Turin generation and the equivalent CPUs from ARM. As these CPUs get deployed in 2025, we will see this product family ramped as well. The other factor, frankly, is just the growth in AI. People had a finite, you know, infrastructure budget, and all of that got sucked into AI. So as people start to now, you know, refresh the servers from the two-generation-old Ice Lake servers to now Granite Rapids servers and equivalent for AMD, you'll start to see more money going into general-purpose compute, which helps deploy the CXL family. How does the competitive landscape differ in this market versus your other two? Actually, the competitive mode is even stronger than any of the other ones. Excuse me, and the reason for that is the following. It is, you know, a little bit more nuanced. People talk about CXL all the time, and absolutely, CXL is necessary to enable this application. You connect to the CPU or even the GPU over CXL. But I would say that the real knowledge is in the memory side. So on the other side of this product, which by the way, is CPU, CXL connects to a memory expander device like our Leo, and then there is DDR5 DIMMs on the other side. For those of you who know DIMMs, know that DIMMs will fail. The memory will fail, it is matter of time. It's very well understood in the industry. And how people deal with memory failures is very different. Intel will have a different approach, AMD has a different approach, ARM CPUs have a different approach. Hyperscalers have a religion around how they manage memory. And what we have done is we've learned over the last eighteen months what this religion is, what needs to be done for each CPU platform and each hyperscaler, and again, built that into COSMOS. And that is really driving a very strong competitive differentiation compared to anybody else that's out there. And how do you think the key killer app for the technology is gonna be more on the expansion or the pooling side of things? And how does the timeline differ between those? Yeah, I think, CXL is very much one of the crawl, walk, run type of situations. We believe that memory expansion for general purpose compute is where it'll start. That will be the first volume deployment of CXL, and we know this because we have hyperscalers who are doing rack-level deployments now to pipeline the system in preparation for the mass deployment with the new CPUs. So that's where it'll start. Also because we are able to do this without requiring any software changes from the application. So we can bring the goodness of CXL with zero software changes from application. So that's where we'd get started. Now, over time, people will be able to customize these applications and then drive additional performance gains for database applications. I think that's where it'll go next for expansion. Eventually, when you have CXL 3.0 and CPUs that are capable of CXL 3.0, which is probably 2026, 2027 timeframe, is when we'll start to see CXL memory pooling applications. It'll be great news for us. We can actually support pooling now. It'll be additional content, not just Leo, but also the retimer products. But in order to make that happen, you do need software changes, so I'm not really holding my breath, to be honest with you. So the key metrics there are hopefully the CPU vendors are on time with their general purpose server CPUs. That's right. The Turin and the Granite and the Diamond after that. Correct. Great. Yeah. In the last minute or two, let's talk, wrap things up with a little bit of the financial side of things. The company is already significantly profitable, which is quite amazing at this stage in your life, but ironically, Nick and Mike, on the CFO side, spend a decent amount of time explaining why your gross margins have to come down from that scarily high 70s to maybe 70% over time. Just talk a little bit about how are they as high as they are, and what drives them down to, you know, a still ridiculously impressive 70%? Yeah, I mean, so I mean, clearly, the gross margin, where it stands today, is a testament to the value that we deliver to the customers, and as Jitendra had talked about earlier, you know, COSMOS is a big piece of that. When you're giving them the capability of managing their fleets in a proactive way and saving money on, you know, these huge investments they're making, there's a lot of value in that, so we're able to capture that. So looking out over time, as, you know, as we've been saying, product mix really will be the biggest driver to the gross margin trajectory over time. Today, a vast majority of the revenue is driven by silicon only or, you know, standalone silicon shipments. But we do have some pretty compelling opportunities here to grow the business through hardware-based solutions as well, whether it be with the Aries SCM product portfolio or the Taurus SCM product portfolio. So those naturally carry a little bit of a lower gross margin. So as those blend into the mix over time, you'll see the margins start to come down. We have a long-term margin target of 70%. We guided to 75% for Q3, and to the extent that that mix kind of moves more towards hardware, you'll start to see it glide down towards 70% over time. Gotcha. Guys, we are exactly on time. Thank you so much for joining us here in beautiful Dana Point and explaining the impressive Astera story to us. Okay. Thank you so much. We are just getting started here. Thank you.