Thank you for standing by, and welcome to Ambarella's Second Quarter Fiscal Year 2027 Earnings Call. At this time, all participants are in listen only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you will need to press star one one on your telephone. If your question has been answered and you would like to remove yourself from the queue, simply press star one one again. As a reminder, today's program is being recorded. Now I would like to introduce your host for today's program, Louis Gerhardy, Vice President, Corporate Development. Please go ahead, sir. Thank you, Jonathan, and good afternoon. Thank you for joining our second quarter fiscal year 2027 financial results conference call. On the call with me today is Dr. Fermi Wang, President and CEO, and John Young, CFO. The primary purpose of today's call is to provide you with information regarding the results for our second quarter of fiscal year 2027. The discussion today and the responses to your questions will contain forward-looking statements regarding our projected financial results, financial prospects, market growth, and demand for our solutions, among other things. These statements are based on currently available information and subject to risks, uncertainties, and assumptions. Should any of these risks or uncertainties materialize, or should our assumptions prove to be incorrect, our actual results could differ materially from these forward-looking statements. We are under no obligation to update these statements. These risks, uncertainties, and assumptions, as well as other information on potential risk factors that could affect our financial results, are more fully described in the documents we file with the SEC. Access to our second quarter fiscal year 2027 results, press release, transcripts, historical results, SEC filings, and a replay of today's call can be found on the investor relations page of our website. The content of today's call, as well as the materials posted on our website, are Ambarella's property and cannot be reproduced or transcribed without our prior written consent. Before starting the call, we hope to see you at one of the following investor events that we have scheduled in our third quarter. First, on September 8, we will host a DNB bus tour at our offices in Santa Clara. September 9, we will be at Citi's 2026 Global TMT conference in New York. September 15, we will participate in Piper Sandler's Growth Frontier Conference in Nashville. September 16, we will host Sanford Bernstein's 8th Annual West Coast Semiconductor Bus Tour. During the week of October 4, we will have a European NDR with cities to be determined. Also available to investors during the third fiscal quarter will be our booth and presentations at the AI Infra Summit in Santa Clara on September 15- 17. We hope to see you there, where we will lead the Physical AI track with a number of Edge AI and robotics demos, in our exhibit area. Fermi is now going to provide a business update for the quarter. John will review the financial results and outlook, and then the three of us are available for your questions. Fermi? Thank you, Louis, and good afternoon. Thank you for joining our call today. Driven by a new record level of Edge AI revenue, we reported a fiscal Q2 revenue slightly above the midpoint of our guidance with non-GAAP EPS of $0.18, and with guidance for seasonal fiscal Q3. By product, we are in the midst of a very steep revenue ramp with our 5-nanometer CV75 and the CV72 AI SoCs, and by market, we have sequential growth in both IoT and auto, with automotive revenue driven by commercial vehicles. The market is increasingly recognizing the strategic value of Edge AI, as well as our Edge AI and the Physical AI platform leadership. We continue to make significant progress with the expansion of our Edge AI platform leadership, including new go-to market strategies and engineering and market development for a number of new higher value SoCs, some of which extend our reach into entirely new markets. We remain optimistic about the long-term secular growth opportunities in the Edge AI market, and our R&D priorities are aligned with both the Physical AI markets that represent a vast majority of our total revenue today, as well as the robotic and the edge infrastructure markets that are in the early stages of developing. Altogether, our technology products and new go-to markets, combined with the significant secular growth in Edge AI, are increasing our five-year serviceable market forecast today. Before I reveal our new market forecast, I would like to step back and discuss the market environment we are in. Demand signals for the application of Edge AI remain strong. At the same time, it is obvious that memory vendors and the entire supply chains are prioritizing AI data center demand, which is resulting in rising supply chain costs for everyone. Surging memory price and the scarcity of supply are impacting the entire industry. Related to this, we are providing significant assistance to customers who are attempting to create a wide variety of workarounds to the memory situation. Ambarella itself is also facing rising supply chain costs, and we plan to pass this cost to our customer to maintain our long-term gross margin target of a 59%-62%. Returning to our rolling five-year serviceable market update, I would like to remind you of our methodology. Our SAM for any given year is based on the products we expect to have available for production in that year, overlaid on the total available market projections from a number of third parties research firms. So our five-year SAM captures any revenue-generating products announced or unannounced on our roadmap in the next five years. Our prior five-year rolling SAM was announced in May 2025 and projected a five-year fiscal year 2026 to fiscal year 2031 compounded annual growth rate of about 18%, with also representing a slightly higher proportion over the terminal year. Our new five-year rolling SAM from $8.5 billion in fiscal year 2027 to $22.9 billion in fiscal year 2032 represents a CAGR of about 20%, with IoT markets now representing about 70% of the terminal year. While there are several factors behind the strong growth and underlying mix change, I will focus on the most important change. In the last year, it has become clear that operational efficiency or the ability of an enterprise to generate more revenue and/or to reduce expenses is likely to be a key driver of our emerging edge infrastructure business. Operational efficiency at the edge refers to the use of open-weight and distilled models running on on-premise inferencing hardware, in contrast to the large frontier models that run in the cloud. Benefits of this approach include reduced latency, data protection, privacy, lower bandwidth cost, and higher reliability. Target markets include security, retail, lodging, logistics, healthcare, and more. The on-premise operational efficiency use case has emerged with growing expectations for sustainable high-volume inferencing, and increasingly for agentic AI and the Physical AI application that can perceive, reason, and ultimately act in the physical world. The key question has become: Who can help the enterprise lower the cost per useful AI influencing outcome? This is where Ambarella's superior performance per watt portfolio kicks in, providing the efficient edge intelligence needed to enable this next-generation agentic and the Physical AI workload at scale. With this perspective, in the last year, we have several new products in development targeting on-premise hardware or what is commonly called edge infrastructure. As you know, we already have our N1-655 AI SoC in the market, and we have additional unannounced AI SoCs in development. We also are implementing a standalone AI accelerator product line targeting the edge infrastructure market. Together, this new age infrastructure products, both AI SoCs and standalone AI accelerators, represent the single most important reason for the upward revisions in our SAM. Before I introduce our first standalone AI accelerator, allow me to be clear about our terminology. We define the Edge AI SoC as one integrating all of the accelerated computing functions into a single chip: camera perception, AI accelerators, CPUs, encoding, and so on. We define an AI accelerator as an AI processor that is not camera-specific and it targets a wide variety of digital or physical modalities. We believe this type of multimodality is critical for edge infrastructure applications that target operational efficiency. While not formally announced, I would like to preview one of the new AI accelerators that will anchor this new product category for us with another well-defined, well-performed product already behind it. We refer to this new AI accelerator as X7. This SoC is sampling now and expected to land initial design wins in edge infrastructure applications where it can serve as an AI co-processor for host processors such as ARM or x86. Together with our new product thrust, expanded market reach, and the SAM, we expect our revenue growth to be supported with two incremental go-to-market strategies. First is the multistep establishment of indirect sales channel, and the second is a semi-custom chip strategy, both of which will augment our existing direct sales efforts. As a reminder, virtually all our revenue is generated by our direct sales teams, and today I am excited to announce two material partnership agreements to develop our indirect sales channel. Combined, these two partnerships plan to drive a significant amount of incremental revenue over the next seven years through customers who have largely been unserved by us so far. First, today we announce Ambarella's strategy to partner with Capgemini, designed to help enterprise adopt Edge AI and Physical AI solutions faster by reducing the complexity of moving from evaluation to scalable deployment. By combining Ambarella's power efficient AI software and platforms with Capgemini's global engineering, system integration, and industry expertise, the partnership aims to help customers improve operational efficiency, enhance real-time decision-making, and deploy intelligent systems in physical world environments with greater speed, scalability, and confidence. In our second partnership to develop our indirect channel, today we also announced a seven-year agreement with Macnica, a leading global technical distributor. Macnica will support both Ambarella's Physical AI and the new edge infrastructure products by developing and supporting an independent software vendor ecosystems, including onboarding, technical integration support, and joint go-to-market programs. With this ecosystem in place, Ambarella solutions can be offered as individual components or as a complete bundle for multiple Edge AI vertical markets, including video analytics, smart city, edge computing platforms, robotics, industrial IoT, intelligent transportation systems, retail, analytics, security, and surveillances. I want to emphasize the importance of the indirect channel to serve small and mid-size customers and highly fragmented markets like robotics. However, the indirect channel is also critical to support our more complex AI SoC targeting the edge infrastructure where a broad network of partners is vital for our long-term success. Meaningful revenue is expected in 2-3 years and will grow as we introduce new products for the market. Our second incremental go-to market is our semi-custom opportunity, which can enable us to gain more share in existing markets and switch into new markets. We have our first semi-custom project underway, the 2 nanometer CV AI SoC, which is expected to generate first production revenue in fiscal 2028. We are in discussion with other companies for additional semi-custom chip projects. Our representative customer engagement this quarter once again demonstrates Ambarella's extending traction across a broad set of applications: robotics, automotive, security, trail cameras, and smart video intercoms. With the CV72-based quadruped, robots validate Ambarella's high-resolution, high multi-camera Edge AI capabilities in robotics. A major S&P 100 communication equipment company announced an AI-based enterprise video intercom, further extending our reach in the emerging access control market. We landed another win with [Motorola] for AI trail cameras and a win with Canon, Suprema, i-PRO, and Secpro further strengthen our AI monitoring pipeline with CV75, CV72, CV5 wins using our own AI ISP software. Through tier 1s, we have two in-cabin vehicle wins with tier 1s in China, one for driver monitors and the other for more complex camera monitoring systems used in Audi and VW vehicles. The breadth of these wins and the wide variety of corresponding AI workloads highlight the programmability and flexibility in both our AI SoCs and our Cooper development platform. This ease of use is facilitating the onboarding and expansion of indirect sales channels. Very few competitors can offer this type of proven platform with more than 50 million Edge AI SoCs shipped. In conclusion, I remain very excited about the overall growth opportunity of the Edge AI market and our company's specific growth drivers putting us in a unique position to benefit. Ambarella is expanding beyond low-power AI SoC to deliver the complete foundation for Physical AI, and we are becoming a full stack Physical AI platform provider. With that, I will now turn it to John. Thank you, Fermi. I'll now review the financial highlights for the second quarter fiscal year 2027, ending July 31, 2026. I will also provide a financial outlook for our third quarter of fiscal year 2027, ending October 31, 2026. I'll be discussing non-GAAP results and ask that you refer to today's press release for a detailed reconciliation of GAAP to non-GAAP results. For non-GAAP reporting, we have eliminated stock-based compensation and acquisition-related expenses adjusted for the impact of taxes. In addition, this quarter, as described in our Q1 fiscal 2027 10-Q filing as a subsequent event, we recognized a $9 million reduction in our GAAP research and development expense due to the cancellation of a customer's development project. We do not expect any impact on our non-GAAP outlook from this development. For fiscal Q2, revenue was $108.1 million, slightly above the midpoint of our prior guidance range of $105 million- $111 million. Up 7.7% from the prior quarter and up 13.2% year- over- year. Automotive revenue established a new revenue record on continued strength as the commercial vehicle adoption of AI remains strong and auto revenue slightly outpaced the growth in our IoT business. Our enterprise-driven businesses outperformed our consumer-led businesses. Non-GAAP gross margin for fiscal Q2 was 59.3%, below the midpoint of our prior guidance range of 59%- 60.5%. Non-GAAP operating expense in Q2 was $57.4 million, slightly below the midpoint of our prior guidance range of $56 million- $59 million. Q2 net interest and other income was $1.8 million. Q2 non-GAAP tax provision was approximately $344,000. We reported Q2 non-GAAP net profit of $8.2 million or $0.18 per diluted share. Now I'll turn to our balance sheet and cash flow. Fiscal Q2 cash and marketable securities were $272.3 million, decreasing $5.5 million from the prior quarter, but increasing $11.1 million from the same quarter a year ago. The sequential decrease in cash and marketable securities was primarily due to higher payments for IP licenses. Receivables days sales outstanding decreased from 35 to 32 days. While inventory dollars declined 4% sequentially, the days of inventory increased from 145 days- 157 days. Operating cash outflow was $260,000 for the quarter. Capital expenditures for tangible and intangible assets were $6.8 million for the quarter. Free cash outflow was $7.1 million for the quarter. During the second quarter of fiscal year 2027, we did not repurchase shares of our stock. During the second fiscal quarter, Ambarella's board of directors authorized a new $50 million repurchase program valid through June 30, 2027. The repurchase program does not obligate the company to acquire any particular amount of ordinary shares, and it may be suspended at any time at the company's discretion. WT Microelectronics, a logistics partner in Taiwan that ships to multiple customers in Asia, was 60.2% of revenue for the second quarter. Hakuto, a logistics and distribution partner in Japan, was 11% of revenue in the quarter. I'll now discuss the outlook for the third quarter of fiscal year 2027. We are anticipating favorable seasonality in our fiscal third quarter, with revenue in the range of $115 million- $124 million, or $119.5 million at the midpoint. At the midpoint, we expect our growth to be led by Physical AI demand from the IoT market. We expect fiscal Q3 non-GAAP gross margin to be in the range of 59%-60%. We expect non-GAAP OpEx in the third quarter to be in the range of $56.5 million- $59.5 million. We estimate net interest and other income to be approximately $1.9 million, our non-GAAP tax expense to be approximately $700,000, and our diluted share count is expected to be approximately 44.9 million shares. Thank you for joining our call today. With that, I'll turn the call over to the operator for questions. Certainly. Ladies and gentlemen, we ask that you please limit yourselves to one question and one follow-up. Our first question for today comes from the line of Christopher Rolland from Susquehanna. Your question please. Hi, this is Dylan Olivier on for Christopher Rolland. Thanks for taking my question. It's nice to see your roadmap expanding, and I know that you announced this X7 accelerator. I was hoping to hear a little bit more about this new chip. Is this a chip that you can bundle with your existing N1 portfolio, or does this address a different part of the stack? Thank you. Yes, Chris. For the X7, this chip is an accelerator which can be bundled with any host, including our own chip. In fact, that's our customer using a certain part number, and when they feel they need to have more AI performance for certain workloads, the X7 gives them the flexibility to upgrade the product without redesigning the board. This accelerator definitely is a way to design that. But in addition to supporting our own SoCs, any other CPU like ARM or Intel chip, Intel CPUs, we can also bundle X7 with that as AI accelerator. Great. Thanks. Appreciate this. For my second question, I wanted to ask about the Physical AI and humanoid opportunity. Is this responsible at all for this increase in SAM? Are there any new engagements or new designs that you can point us to? Thank you. Yeah. So definitely that's a big part of that. In the last earning call, we talked about 15 design wins for the robots, including for roughly $100 million. Although we can't give you another breakdown, I can say that we add more design wins to that pipeline and the higher revenue target. From that point of view, we continue to make progress. But in addition to robots, I also think that edge infrastructure and also enterprise security as well as portable video are all the reasons that we are increasing our SAM number. Yeah. Dylan, Fermi mentioned a quadruped robotic dog, the CV72 chip this quarter. So continue to add onto the robotics wins we've described before. Thank you. Our next question comes from the line of Joe Moore from Morgan Stanley. Your question please. Yeah, thank you. I wonder if, first, in terms of the broader ecosystem, you talked about some of the challenges of memory. What does that mean for your business, do you think? Is there a risk of pull forwards or things like that because people are trying to get ahead of memory price increases? Is there pressure on you? Just what are you seeing from that memory impact from your customers? Right. We continue to monitor this situation very closely by talking to customer all the time. For Q3, we are comfortable with the guidance we provide today. In Q4, we continue to talk to customer to make sure our customer, we can secure enough memory for Q4 business. That definitely is an uncertainty that we are dealing with. Okay, that's helpful. Thank you. Then in terms of opening up to a broader ecosystem, distribution partners, things like that, I think you made the comment about that would take a couple of years to inflect. I guess, I would sort of think that those customers would act a lot more quickly, and that pipeline could build a lot more quickly than what you had seen previously in automotive. Just what was the comment that I maybe misunderstand there? Then, what is the timeline to start to see traction from that kind of broader ecosystem? Right. When I say 2- 3 years, we talk about meaningful revenues. I agree with you that we, in fact, we already start seeing a small amount of designing which can generate revenue next year. But when we talk about meaningful revenue that will have impact to our revenue forecast, I think that will take 2- 3 years. In fact, when we talk to both Capgemini and Macnica, in fact, the range of revenue we are expecting from this collaboration is a half a billion dollars with each one of them. From that point of view, we definitely looking forward to gradually ramp up the revenue for the next couple years and start seeing meaningful revenue behind that. Great. Thank you. Thank you. Our next question comes from the line of Tore Svanberg from Stifel. Your question, please. Yes. Thank you, and congratulations on the Macnica and Capgemini partnerships. I am curious on those, Fermi. What are some of the early use cases that those two partners are going to be helping you with? Maybe you can call out some markets or applications. How should I think about that in the context of your Cooper platform? Are they going to be working with you on Cooper? Are they going to be providing some of their own software? Just curious how that is going to play out. Thank you. Right. Let me answer the second question first. Yes, both of them will use Cooper. In fact, that is a key driver for them to select to work with us because they see a very mature software platform they can immediately tag along and start building around it, generating infrastructure for their own product line. So that our mature AI SoC, as well as a mature Cooper software platform, is the probably most critical engineering aspect that we offer to our partners. Go back to the potential market that we are talking about. In fact, there are multiple of them. In fact, when I talked to Macnica CEO, in that meeting, they are highlighting that they have already started winning design wins with our solution on drones, on retail channels, and also manufacturing. So that is definitely, you can see that it is really a large market. However, most of the design win is small and segmented at beginning, but if they can ramp up to larger volume of business, that will take time. But we already start seeing our partners start talking about different applications. Hey Tore, it is Louis. They can work together as well. As Fermi said, Macnica can serve small to mid-size markets that oftentimes are very fragmented. But really for Capgemini, it is large enterprise customers, and you can look at who they have talked about before. Those are the type of customers we would really go after with them. So they are very complementary to each other. Very good. As my follow-up on the edge infrastructure market, this is obviously a completely new area. It sounds like that is the sort of biggest contributor to your increased SAM. I am just curious, who is going to be some of your partners there? Are these going to be your end customers sort of building their own infrastructure, or is there going to be like an intermediary company that is building it? Is it going to be the traditional server guys? Just curious how that is all going to play out. Thank you. Well, I think obviously we're going to continue to talk to some of the larger customers directly, but at the same time, we're counting on Capgemini and Macnica to help us to penetrate this because they're already in that market. They're already selling solution to the existing AGI customer with their existing solution. So working with them will help us to ramp up our revenue much faster than just we talking to direct customer directly. Makes sense. Thank you. Thank you. Our next question comes from the line of Quinn Bolton from Needham & Company. Your question, please. Hey, guys. Thanks for taking my question. I just wanted to ask longer term on the Macnica and Capgemini partnerships. Does that change the long-term gross margin target? I assume that there's probably some allocation of revenue that would be attributed to those partners, so I'm wondering if that has any gross margin implications as that indirect channel ramps. Right. Today, I think our long-term gross margin is still 59%-62%. We are definitely trying to continue to watch, because we just started ramping up this business. If there is any change, we will definitely inform our investors. But today, for us, after we talk to Capgemini and Macnica, we do not feel there is any need to change that target today. Yeah. Thanks, Fermi. I guess just a clarification on the $9 million charge for the project that was canceled. Was that a semi-custom project that was canceled? Does that have any impact on your expected revenue timeline for the semi-custom business? Yeah, thanks, Quinn. It is not one of the semi-custom opportunities that we talked about. It was a development project with, I guess you could say an automotive customer, auto autonomy customer. We have been negotiating the termination of that for quite some time. In Q2, we finalized the agreement. Understood. Thank you. Thank you. Thank you. And our next question comes from the line of Kevin Cassidy from Rosenblatt Securities. Your question, please. Yeah, thanks for taking my question. Going back to the shortage on the memory side, and you've got near-term visibility, but I'm wondering on the designs. I know a lot of your customers or the market out there is probably dominated by a GPU-based embedded product. It uses much more DRAM than yours would. Are you seeing any additional interest because you're more efficient with DRAM content? Well, yes. First of all, the memory situation is dire for everybody, but some of our competitor who has more money to buy more memories. However, any customer who comes to us for the Edge AI or Physical AI, they probably only use GPU for their first generation product, and they understand. So the memory cost is just one reason, but more importantly, it's power efficiency and other reasons. But the memory cost definitely is a driver for people to start considering what's the more efficient way to do the product. So I agree with you that almost all the customers who come to talk to us is because our power efficiency solution and the lower cost solution than what they're using. Okay. And maybe along the same lines as with the AI accelerator, you would be competing against a GPU that uses a lot of memory also. What is the memory architecture inside your X7? Well, in fact, we need a much smaller footprint. For example, we only need 4 megabytes memory for the accelerator running large language models. Just to show you. More importantly, as an accelerator, the power envelope you have to fit in is anywhere between 4 to 5 watts in the current design. All of the power efficiency, memory size, and also cost is really helping us to penetrate this market right now. Okay, great. Thank you. Thank you. Our next question comes from the line of Suji Des ilva from Roth Capital. Your question, please. Hi, Fermi, John, Louis. Just a clarification for me on the X7 chip. Is that competing really only with edge GPUs, or is it other AI specialty chips, or how should we think about the competitive landscape for this new offering? Right now, in addition to NVIDIA and Qualcomm having similar products in this market space, there are probably 50 startup companies doing similar chips. It is a crowd space. However, at the end, it is really about the power efficiency, because I just talk about to run a certain workload, you have to have a mature, not only a power efficient solution, but a mature hardware and software, which I think we are one of the very few that can do that today. Okay. That is helpful for me. My other question is, you are talking about customization now, projects. I am just wondering what precipitated the demand from the customers or your push to provide customization. What is newer versus your standard product history now that is driving the need for that or your desire to do that? I think you are talking about optimization for the memory situation. Is that correct? Or you said semi-custom. For semi-custom. Semi-custom. I apologize. Yeah. For semi-custom customer, in fact, we basically allow our customer give us a spec, and we build on the spec. However, when we negotiate a spec with a customer, we need to make sure that we can sell the spec to somebody else. For the semi-custom chip, we pretty much build a purpose chip for the one customer, which they benefit from this, but at the same time, we can sell the chip to others that are not competing with the key customer. That's the business model and how it works on the engineering side. Okay. We'll try to offer as much of our own IP in those semi-custom chips as possible. For example, we have our own IP for the AI accelerator, the NPU for all the perception capabilities, including the ISP and encoder, the CPUs. All of those functional blocks are available for a customer to develop a semi-custom or custom chip with. Sure. Okay, great. Thanks, guys. Thank you. Our next question comes from the line of Liam Farr from Bank of America. Your question, please. Hi. Yes, thank you for taking my question. Is there a way to frame how much memory cost inflation you're absorbing this quarter, either in basis points or maybe what gross margin would have been without any memory cost inflation? Is a passback above 60% feasible while memory prices stay elevated, or does that require pricing to come down? Thank you. Right. First of all, the memory price doesn't impact our gross margin. It really only has a potential to impact how many chips our customer can buy. Memory cost, because we don't buy memory and we don't resell memory, the memory price has no impact to our gross margin. I think that answers your question. But the real question for us is how that memory cost can, because our customer needs to increase the price, whether that will reduce the total volume they can sell and therefore reduce the total ordering to us. That's something we need to continue to observe. In Q2 and Q3, we see little impact on our revenue because of memory situation. We continue to watch for the Q4. Thank you. I guess for my follow-up, Q3 is guided up 10.5%, roughly sequential versus 13.5% last year. How much of this next quarter is normal seasonality versus just underlying end demand strength? Given you flagged Q4 memory supply, obviously changing the demand picture, how should we think about Q4 seasonality and whether the full year 10%-15% is still reasonable for the full year for the guide? Thank you. Right. I think the outcome this year is still a little uncertain because of the memory constraint that you talk about. Like I said, we continue to talk to our customer for that to monitor how that impacts our performance in Q4. Barring for any memory impact to our revenue, I think that you should expect the Q4 as a regular seasonality. Thank you. Our next question comes from the line of Gus Richard from Northland. Your question, please. Yes, thanks for taking the question. Robotics architecture is looking an awful lot like an autonomous car in terms of what it needs to do. I am just wondering, you have a domain controller for autos and you have the CV products. Are you seeing any traction in domain controllers? Any clarification on where you are seeing the strength? Is some of this coming out of China? Right. First of all, you are 100% right that a lot of robot design system architecture looks just like the autonomous driving car, which I totally agree. However, I think the robotic market situation really reminds me autonomous driving seven years ago, when at that time, all of the automotive customer in trying to just using individual modules and put a solution together and start demoing and selling the first generation product. I think this is how we act with the current robots. We see a lot of customers are rushing out their first generation product by putting individual components together to demo their capabilities. However, we do believe that integration path of the robotic will be very similar to what happened to the autonomous driving car. It is, there will be people going to buy perception system, but down the road, people want to buy domain controller. We do see both opportunities today, but I will say majority of our customer today is asking for perception modules, perception solution, but on their roadmap, they want to have a way they can buy a domain controller in the long run. I think we have a complete roadmap. We can sell just perception system to a customer today. In fact, people want to buy brain, domain controller, for the brain of the robots. We have the solution too. Our plan is we are going to continue to develop solution for both so that we can cover the total space of robotic. Got it. If I think about, again, robots, cars are 2D and robots are 3D, and I'm just wondering is one of the limitations of penetration training, and can you help your customers train robots? I'm thinking about humanoid, but go ahead, sorry. Right. In terms of training, it's really about how to collect data. One thing we help our customer is we build a platform for people to collect data easily, and also we provide a platform that, and providing a service to help people to label those data automatically. So people can use our system to, reference design to collect data. In fact, some of the, I would say the, people doing mapping, generating the map, city mapping, are using our system to collect data. Also we are providing service to some of our automotive customer that we can, using our tools to auto labeling all of the data they generated. Those are two things we can help to provide assistance on the training side. Got it. Thanks so much. Thank you. Thank you. Our final question for today comes from the line of Martin Yang from Oppenheimer. Your question, please. Hi, thank you for taking the question. Fermi, you sized the potential revenue from Capgemini and Macnica pretty similarly, but they face different variety of customers. Can you talk about the methodology you applied and those dollar figures? Is it similar methodology or a very different approach to size those potential markets? Go ahead. Hi, this is [Maneet] just jumping in there. I think both Fermi and Louis were commenting earlier about how complementary they were, right? I think one, on the Macnica side, I think Louis has commented, it is large scale, medium large kind of customers we have not addressed in the past. So think of them as a large volume play where we have typically directly engaged with high volume customers. These will start aggregating a whole bunch of small mid-size customers that we did not have access to in the past. So it is a volume play, and I think Fermi already indicated that we are starting to see some small design wins come through with these distribution. Then if you think about Capgemini, it is more of a value play. I think Louis indicated before, these are large enterprises and customers who will bring complex solutions, deploy at scale to enterprises. The modeling is on both slightly different. One, it is distribution channels, reseller scaling with small design wins, so building up small volume. The other ones are large customers and logos, which have much larger opportunity deals, but complex opportunities. On both sides, the modeling is done on value versus volume. I think the earlier question was also you should see different timelines on this. We do expect faster timelines on the distribution side and more longer timelines on the more larger, complex opportunities. But the modeling has been built out for seven years of how this will come to fruition. Of course, some of them are new to our products, so initial ramp-up, market making, pilot opportunities is what we are allowing for. But we will keep you updated as we start winning some large deals and meaningful revenue as Fermi pointed out, in future quarters. Great. Thank you, Maneet. I have a follow-up on X7. Is that accelerator chip primarily targeting for as a channel product or there is no distinction between for channel, for direct? There is no distinction. In fact, I am expecting that both Capgemini and Macnica will do product reference design for that and targeting different customers. Thank you, Fermi. That is it for me. Thank you. Thank you. This does conclude the question and answer session of today's program. I would like to hand the program back to Dr. Fermi Wang for any further remarks. Thank all of you for joining our call today. I hope to see you and talk to you next time. Thank you, ladies and gentlemen, for your participation in today's conference. This does conclude the program. You may now disconnect. Good day.