Title

Presentation

Ambarella, Inc. beats earnings expectations. Reported EPS is $-0.26, expectations were $-0.32.

Operator: Thank you for standing by. Welcome to Ambarella’s First Quarter Fiscal Year 2025 Earnings Call. [Operator Instructions] As a reminder, today’s program is being recorded. And now I would like to introduce your host for today’s program Mr. Louis Gerhardy, Vice President, Corporate Development and Investor Relations. Please go ahead, sir.

Louis Gerhardy: Thank you, Jonathan, and good afternoon. Thank you for joining our first quarter fiscal 2025 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 first quarter and fiscal 2025. 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 filed with the SEC. Access to our first quarter fiscal 2025 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. Fermi will now provide a business update for the quarter. And John will review the financial results and outlook, and we will be available for your questions after that.

Fermi?

Fermi Wang: Thank you, Louis, and good afternoon. Thank you all for joining our call today. Our Q1 results were 1% above the midpoint of our guidance range, with revenue increasing 6% sequentially. As expected, both auto and IoT revenue increased sequentially, and the AI products were about two-thirds of our total revenue. As previously discussed, our customers are in the midst of recovering from a cyclical inventory correction, and the favorable impact from this is expected to carry into the second quarter. We continue to expect our fiscal ‘25 revenue to grow year-over-year, driven by both the cyclical tailwinds and the secular growth in our AI portfolio. The combination of this cyclical and the secular forces is expected to enable our AI inference revenue to grow more than 30% in fiscal 2025.

Zooming out for a minute, the significant capacity being added to the AI training network infrastructure globally both help for the ultimate deployment of AI inference at edge where we participate in the market. The deployment of AI inference at edge enables end-users to more practically take advantage of so many different AI breakthroughs. As focused on AI and the edge of networks increase, we see AI inferencing proliferating in multiple areas, and we believe we are well positioned to take advantage of this. In fact, we are already in the early stage of demonstrating how it may play out for us. In Q1, for example, our customer engagement includes our first passenger vehicle wins for our 5-nanometer CV3-AD family of AI central domain controllers.

We added another CV3-AD win in the commercial vehicle market, secured multiple enterprise class AI inferencing wins, and even in other IoT cameras, we are reporting additional wins for our 5nm CV5 AI process. In the midst of this great change, our opportunity and the challenge are to develop AI technology and products that not only are extremely efficient for edge deployment, but also flexible enough to execute a very wide range of AI workload across all disparate applications. We are already in mass production with our AI products for video-intensive CNN networks, such as detection, classification, fusion, planning, stitching, mapping, tracking, framing, auto-editing, and neural network image signal processing. Now our third generation of AI technology integrated into our CV3-AD and CV7 series of SoC can support transformer networks for a variety of generative AI applications.

I would now like to describe customer engagements that can offer some indication how it can play out for us. As we have made significant investment into our CV3-AD family of automotive AI domain controllers. And we expect the CV3-AD family to be a major revenue driver. So we are pleased to announce our first CV3-AD family wins in the passenger vehicle market, which complements our ongoing wins with the CV3-AD family in the commercial vehicle market. In April, during the Beijing Auto Show, we reached a strategic collaboration agreement with the battery electrical vehicle company in China. This company will use our CV3-AD AI domain controllers in new passenger vehicle models. This is an important development for us in several regards. First, major by the number of EV delivering calendar 2023, this OEM is considered one of the top five new EV companies in China.

While most of the OEM deliveries were in China last year, the company has an impressive plan for globalization of its business. Second, Chinese automotive OEMs are aggressively and successfully adopting next-generation technology into their vehicles, which aligns with our strategy to intersect the safety and autonomy domain with next-generation technology, in particular Level 2+. For example, to improve accuracy, many OEMs in China have aggressively adopted the BEV former AI framework for 3D perception tasks in its autonomous driving software stack. And this high-performance framework can leverage to a high degree the unique capability in our CV3-AD AI inference processors, including the ability to process transformers at a low power. Third, the efficiency and the scalability of our CV3-AD family portfolio is also a major factor in the collaboration with Ambarella, as the OEM can reuse this software on low, mid, and high end vehicles.

In April, we added another CV3-AD family win in the commercial vehicle market with the announcement of a strategic collaboration with SANY Corporation. SANY is one of the world’s largest engineering machinery manufacturers, providing heavy-duty commercial vehicles to the global market. SANY intent to leverage Ambarella’s CV3-AD family of automotive AI domain controllers to develop advanced automated driving solutions on its next-generation commercial and special-purpose vehicles. The companies will collaborate on the joint development and promotion of high-performance and highly integrated automated driving solutions with SANY’s goal of achieving the start of production for at least one model by calendar year 2025. At the Beijing Auto Show in April, Tier1 Neusoft Reach announced a strategic partnership with Ambarella.

The companies plan to expand on their existing relationship to jointly promote and explore AI-based product technology and market development in areas including autonomous driving and driver monitoring. Neusoft’s third-generation forward-facing intelligent camera X-Cube 3.0 is powered by Ambarella’s CV22 AI Vision SoC to target level 2 plus autonomy levels and has already been mass-produced and deployed by automotive OEMs. We are pleased to announce that Seeing Machines, the leading provider of driver monitoring systems software, selected our CV25 for its own aftermarket system for commercial vehicles. The Guardian Generation 3 meets the European Commission’s general safety regulation for drowsiness detection, a requirement for all the new cars, vans, trucks, and buses across Europe.

And in April, at the ISC West security exhibition, we successfully demonstrated the latest generated AI technology running region language model, VLM, on our N1 and the CV72 SoCs. Our demonstration includes using the multi-model VLMs to search video recording to detect objects defined by packs and provide near instantaneous results without the need for training specifically for that object. This capability opens up a whole new range of AI-based search capability for enterprise cameras and primus-based AI systems. Our third-generation AI inference technology includes specific support needed to efficiently run these new classes of networks. During the ISC West, we also announced and demonstrated our new 5 nanometer CV75 AI SoC, which provides the performance required to run the latest VLMs, as well as AI-based IQ enhancement.

This capability very efficiently run this cutting-edge AI technologies is highly sought after for cost and the power-constrained AI cameras used in enterprise, smart city, retail stores, robotic access control, and AI-based consumer devices. At the Enterprise Connect Conference in March, Poly, a leading global provider of workplace collaboration solutions, and the wholly -owned units HP, launched its Studio E360. This center of a table system utilizes a single 5 nanometer CV5 for four 8 megapixel cameras with AI inferences processing, choosing the optimal framing angle for in-room participants. And also in Korea, the Korea activity for our AI SoCs remain high, with the leading security camera maker, Hanwha, introduce new AI model base on our CV22 and the CV2 AI SoCs. And IDES introduce CV25 -based models, and the C-Pro introduce dual-sensor AI camera based on CV22.

In the other IoT market, we are pleased to see our 5 nanometer CV5 AI inference processor being utilized in another consumer cameras to significantly improve both image quality and to automate certain user interface functions. Insta360 introduced its X4 action camera in April with dual-sensor for 360-degree 8k capture. In conclusion, I mentioned last quarter our goals are to restore revenue growth and profitability while continue to drive our strategic R&D priorities. Q1 represented a step in the right direction, most skillfully highlighted by our first passenger vehicle win for the CV3-AD family by the expanding breadth of CV customer engagement stands out, and we expect this to build a growth foundation upon with multiple AI applications can drive revenue growth and result in positive earning leverage for shareholders.

The further commercialization and the monetization of our technology and the product is of utmost importance to us, and I am excited about the opportunity before us and what we will achieve in the years ahead. With that, John will now discuss the Q1 results and outlook in more detail.

John Young : Thank you, Fermi. I will now review the financial highlights for the first quarter fiscal year 2025, ending April 30, 2024. I will also provide a financial outlook for our second quarter of fiscal year 2025, ending July 31, 2024. I will 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 expense, along with acquisition-related costs, adjusted for the impact of taxes. For fiscal Q1, revenue was $54.5 million, 1% above the midpoint of our prior guidance range, up 6% from the prior quarter, and down 12% year-over-year. Non-GAAP gross margin for fiscal Q1 was 63.4% above the high end of our prior guidance range by 0.4%.

Non-GAAP operating expense was $46.7 million, approximately $2.6 million higher than the prior quarter and $800,000 lower than the midpoint of our prior guidance range of $46 million to $49 million, driven by continued expense management and the timing of spending between quarters. We remain on track to our internal product development milestones. Q1 net interest and other income was $2.3 million. Q1 non-GAAP tax provision was approximately $607,000. We reported a non-GAAP net loss of $10.5 million or a $0.26 loss per diluted share. Now we’ll turn to our balance sheet and cash flow. Fiscal Q1 cash and marketable securities decreased $16.6 million from the prior quarter to $203.3 million. Receivables days of sales outstanding increased from 44 days in the prior quarter to 47 days.

While days of inventory decreased from 131 days to 123 days. Inventory dollars declined 2% sequentially and declined 31% from a year ago. Operating cash outflow was $15 million for the quarter. Capital expenditures for tangible and intangible assets were $1.1 million. We had two logistics and ODM companies representing 10% or more of our revenue in Q1. WT Microelectronics, a fulfillment partner in Taiwan that ships to multiple customers in Asia, came in at 62% of revenue for the first quarter. Chicony, an ODM who manufactures for multiple end customers, was 13% of revenue for the quarter. I’ll now discuss the outlook for the second quarter of fiscal year 2025. We remain confident our business is continuing to recover from the cyclical correction led by our AI inference products.

For fiscal Q2, we estimate our total revenue will be in the range of $60 million to $64 million. We expect sequential growth in both IoT and Auto. We expect fiscal Q2 non-GAAP gross margin to be in the range of 62.5% to 64%. We expect non-GAAP OpEx in the second quarter to be in the range of $47.5 million to $49.5 million, with the increase compared to Q1 driven by increased headcount and engineering-related expense, including our first 2-nanometer SoC project. We estimate net interest income to be approximately $1.8 million, our non-GAAP tax expense to be approximately $600,000, and our diluted share count to be approximately 41.1 million shares. Ambarella will be participating in Bank of America’s Global Technology Conference on Wednesday, June 5th in San Francisco, Mizuho’s Technology Conference on June 12th in New York City, and Rosenblatt’s Virtual Age of AI Conference on June 13th.

We hope to see you at one of these events. Please contact us for more details. Thank you for joining our call today and with that, I will turn the call over to the operator for questions.

Operator: [Operator Instructions] And our first question for today comes from the line of Christopher Rolland from Susquehanna.

Christopher Rolland: Hey, guys. Can you hear me? Great. Thanks for the question. You brought up VLMs on the call. Just wanted to know a little bit more about that application. Does that increase your TAM overall? Is this additive to what you’re doing in, for example, LLMs? How should we think about that? Thanks.

Fermi Wang: Right. So, we start talking about LLMs and start demoing our CES this year. And then we continue to watch the potential application that we can use with our solution for our customers. And we identify vision language model, which is really a large language model that can respond to text for search different objects or using that to describe different video things. And we have a live demo. In fact, we welcome you to call, a lower set up live demo for you how the vision language model used in our current enterprise customers or other potential customer in that space. So this definitely is a brand new application that we identified by the market and the customer and we’re engaging with our current customer, particularly on the enterprise and security camera market and they show extremely interest on this product because you can imagine that this is really a model that can replace the people who use to monitor the different cameras in a control center and you can use a large language model not to give you early warning but also have a using tags to do a search of different objects without really training for those objects and I think that’s a really a breakthrough for enterprise side and we expect that some of our customers will kick off projects with us with the VLMs in the near future and we can use both N1 as well as CV72 for that product.

Christopher Rolland: Great, thanks Fermi. And then on the auto opportunity making some progress here sounds like on the Chinese EV side of things perhaps you can talk about the pipeline kind of how you see it expanding engagement of late here that you’re seeing and whether you think there’s going to be more to come and whether any of these could actually be implementing your software as well? Thanks.

Fermi Wang: Right. so first of all, I definitely believe they will be more to come and I also believe that the first design win is really show off that our program we have been talking about our strengths which is we can run really transformer most advanced network very efficiently in low power and also have a scalable architecture that can really address using a sense software to address from low end to the high-end vehicles and also that the power consumption that were much lower than our competitors give significant advantages in the design win, so that really is the reason we won but also I think it’s important to point it out that it’s just like an EV market Chinese EV automakers are really aggressive by pushing technology envelope and that for one of them adopting our Level 2+ solution will help us for other potential OEM design win that we are bidding on.

Operator: Our next question comes from the line of Ethan Patashnik from T.D.

Unidentified Analyst: Yes, hi, everybody. This is Ethan Patashnik on for Matt Ramsey. Congrats on the great results. I wanted to ask is the passenger vehicle win you guys discussed tonight likely to get CV3 to the tipping point with regards to wins and other OEMs. Are there other OEMs waiting to see maybe another one kind of go first maybe if you guys could discuss those dynamics?

Fermi Wang: Right. So, first of all, I think the lifetime value of this design win is meaningful and also material for us and also that they are very aggressive, the target MP date is the end of ‘25 or early ‘26 and that will help us to really take our CV3-AD platform into production therefore provide a mature solution to other companies who is considering our current solution. so I definitely believe that not only this design win is help to our pipeline but also going to be a major help for us to secure our design wins in the near future.

Unidentified Analyst: Okay, understood. And as my follow-up, you guys gave it a lot of good information around the AI inference opportunity with the revenue expected to kind of grow 30%. I think you guys said in fiscal ‘25 and you called out some progress I think was enterprise applications. I was wondering how these — how the early stages of this opportunity are playing out? What sort of impact some of the announcements you guys made at CES, I think it was the N1 SoC and the Cooper Development platform, what’s kind of driving that, how is the roadmap progressing? Any early feedback and any additional insight would be helpful.

Fermi Wang: Right. So just a maybe refresh our GenAI strategy, we definitely intend to leverage our current existing third generation AI inference engine into a GenAI and the LLM. And we demo the, like you said, CES N1 with Lava demo, and then at the ISC West, we demo with VLM running on both N1 and CV7. So our strategy for current generation has become very clear. First of all, we’re going to focus on edge application, both for edge camera as well as edge servers. Two, we’ll focus on the workload that we can — really can take advantage of our current silicon. And so that’s really enterprise market, as well as some adjacent market that can use those Lava model, as well as VLM models. And we think, we continue to believe that our opportunity for GenAI revenues in 2026, we are not only demoing, we’re assembling N1 and the CV72 to our key customers who are interested in GenAI application.

So that’s our first generation and also, as you can see, I think John mentioned that we’re investing on two nanometer process nodes. You can think that’s a preparation for our next generation GenAI solution. Although we didn’t talk about our plan for that yet, we are trying to work on that. But we believe that with our second two nanometer technology development, they will significantly help us on the technology side for our roadmap.

Operator: And our next question comes from the line of Joe Moore from Morgan Stanley.

Joe Moore: Great. Thank you. In terms of the passenger car win in China, can you talk about, I think you mentioned it as an L2+, if I heard you right, type of opportunity. Can you describe how many cameras per car and what capabilities you could offer there?

Fermi Wang: Yes. So first of all, it is an L2 + car. And because they have different models, it’s anywhere from 7 to 10 cameras plus 5 radars configuration. And it’s designed to do it from the highway level to city levels of autonomous driving.

Joe Moore: Great. Thank you for that. And then was this customer, I know you have a probability weighted funnel, was this customer somebody that you had anticipated had some probability within that funnel?

Fermi Wang: Yes. And now I think with the next funnel discussion, they should be in the one category instead of the probability category.

Operator: And our next question comes from the line of Kevin Cassidy from Rosenblatt Securities.

Kevin Cassidy: Thanks. And congratulations on the great results and the design win momentum. And maybe Fermi, maybe you hinted, I was going to ask more questions about the two nanometer process technology. Do you have a timeline for when you’d have first silicon, and are you staying with Samsung, or will this be with TSMC?

Fermi Wang: Right. So these two nanometers will be Samsung’s two nanometer, and we plan to take about second half of next year and get ready to go into production in 2026.

Kevin Cassidy: Okay, great. And maybe just to follow-up on Joe’s question, you mentioned that it’s 7 to 10 cameras plus radar. Is that your radar in the design?

Fermi Wang: We haven’t talked about that yet.

Kevin Cassidy: Okay. All right, maybe I’ll go to an easier question with just your backlog visibility, if you’re saying you’re going to see growth in fiscal year 2025, can you talk about your backlog visibility?

Fermi Wang: Yes. Our backlog visibility is getting much better than before. In fact, that’s the reason we feel comfortable that with the street’s consensus of $250 million revenue forecast this year, and our lead times are really in the 24 weeks, and that tells us that we still have a clear visibility to mid of Q4, reminding you that our Q4 is to January. So we see clear booking for Q3 and Q4, that’s why we continue to feel comfortable with our guidance.

Kevin Cassidy: Okay, great. Thank you.

Fermi Wang: However, let me add one more sentence. I think that while we are comfortable with the $250 million consensus level, we believe there is a seasonality in Q4, so I think that’s something we should consider while we see the visibility, we definitely believe that we’re going to continue to see the trend Q2 to Q3 growth, but from Q3 to Q4, just like the normal seasonality before the COVID, we should have a seasonality in there.

Operator: And our next question comes from the line of Quinn Bolton from Needham and Company.

Nick Doyle : Hey, this is Nick Doyle on Quinn. And thanks for taking our questions. Maybe just zooming out a little bit, could you give us a pulse on the Chinese auto market overall? How do you see current EV demand and supply? And then you mentioned two CV3 wins in the passenger and commercial markets. Can you size those opportunities at all? Thanks.

Fermi Wang: Right. So, first of all, we don’t play on the EV market. We play on the autonomous driving market. But they are very much correlated. I think what happened in EV is that Chinese automaker continue to aggressively push the technology envelope on the EV side. We see the same trend on the autonomous driving technology side. I think, for example, that almost all the RPQ that we’re building in China, all of them require most advanced network like BEV former, very L2+, C-level autonomous. All of that is really showing me that they are very aggressive — Chinese automaker is very aggressive to push the technology envelope. And we believe that play to our strength. And we believe that we can take advantage of that. Although that EV market shows some slowness in terms of total market size, but I think that from the EV market point of view, we still believe that the growth is continuing to be there.

And we expect that majority of the EV cars will have a level 2, level 2+ system in the coming years, near term.

Nick Doyle : Okay. The margins, the gross margins were a bit of a bright spot in the quarter and guide. Could you expand on what’s driving that? Thanks.

John Young: Yes, so essentially, it’s mix. We had a little bit higher contribution than we had forecast for customer NRE projects that came through in the quarter as the main driver.

Operator: And our next question comes from the line of Tore Svanberg from Stifel.

Jeremy Kwan: Yes. This is Jeremy calling for Tore. And let me add my congrats on the growing CV3 design win. Maybe a quick follow-up on the gross margin in the NREs. Is the NREs something that is kind of like an ongoing project or sustainable in terms of contribution over the longer term? Just want to see the impact against your gross margins for the next 12 to 18 months. So that’s my first question.

John Young: Okay. So, yes, we did — it is a project that will be ongoing in the near future. Our long-term model, though, is 59 to 62 for gross margins. I think there may be a temporary blip-up for this quarter, next quarter potentially, as we’ve guided. But I think that if you’re thinking about long-term modeling, I wouldn’t see this as a new norm necessarily.

Jeremy Kwan: Got it. And I guess in terms of this passenger vehicle design win, can you give us a little bit more detail in terms of like how many car models are impacted, if there’s a way to kind of weigh it in terms of how many of the new vehicles are likely to see this incorporated? And also, I understand, the ASPs, even an L2+, can have a pretty wide range, maybe 40 at the low end, 200 at the higher end. Can you give us a ballpark where this fits in terms of the design win and the ASP size? Thank you.

Fermi Wang: Right. So, first of all, this, currently this OEM has, only a portion of the model has level 2+ in there but I do believe just like any other Chinese OEM we talked to they want to move to level 2+ to all their models because they view that as a huge differentiation so I think we expect when we go into production with this customer all of the car they ship it will have a level some kind of level 2+ solution there, as we talk about in the past in our low-end to a high-end ship it can go anywhere from $50 to $400 and the midpoint is $100 plus to $100 million that’s the range we’re looking at from ASP point of view and we’ll start addressing more, well we have — we can disclose more with our customer. In terms of the size of this true opportunity I really think that it’s, we talk about the significant I think, is north of $100 million easily for the first design win, but we think that we can achieve more if we can continue to at work with our customer getting more models and more other components into their car.

Jeremy Kwan: Thank you, Permi. I’m sorry, I didn’t quite catch how much, how many million was for the first design win.

Fermi Wang: I said, north of $100 million.

Jeremy Kwan: North of $100 million. North, got it. Thank you.

Operator: And our next question comes from the line of David O ‘Connor from BNP Paribas.

David O ‘Connor: Great. Thanks for taking my question, guys. Maybe just going back to the seasonality in Q4, just looking back there, pretty cool, whatever you talked about, seems to be down like 15%, 20% Q-on-Q. Is that kind of the type of ballpark or zip code we should be thinking of for that Q4 seasonality, or is it a bit more new to the lack of the secular trends that you’re seeing? That’s my first question.

John Young: Yes, so I think it’s relatively difficult for us to give crisp visibility out into Q4. But I think, if you’re thinking about the full year guidance of, or I should say the consensus of $250 million, I think that’s definitely reasonable at this point. We don’t have any issue with that. I think, though, the number of the percentages you’re talking about are within reason.

Fermi Wang: Well, we have seen this kind of a seasonality before COVID time. And I think when our — after the COVID time, after all the inventory correction is done, I think we’re back to the normal seasonality. And with the downturn, we haven’t provided guidance at Q4, but I think if you look at the past history, that would be probably, if you look at the pattern, it will be similar to the seasonality we’ve seen before. Majority of that is in the IoT side, but a little bit on the auto side.

David O ‘Connor: Okay, got it. That’s helpful. Thanks, guys. And then maybe just a follow-on on the CV3 win with the EV passenger vehicle. And just to clarify, I mean, this is separate to the Conti-Bosch agreement. Does it have anything to do with that? And can you update us as well, just on the status of those agreements, wherever they stand at the moment?

Fermi Wang: Yes. First of all, this design win has nothing to do with Conti or Bosch. This Chinese guy is really using a Chinese supply chain. And in terms of Conti, I would say that we continue to have very strong collaboration both on the SoC and the software side. And also, we continue to make progress moving toward our first SoC project that we talked about probably a year ago. And that target MP time is currently at 27. We continue to make great progress on that. And also, we actively building on RFI RFQs with Conti on this. So with the Bosch side, also we don’t have software development collaboration, but we do have working with them on the RFI RFQs bidding on some of the European design wins.

Operator: And our next question comes from the line of Richard Shannon from Craig-Hallium Capital.

Richard Shannon: Hi, guys. Thanks for taking my questions. Maybe touching on your comments about AI inference growing 30% or more this year, maybe give us a sense here of how much this is weighted towards IoT versus automotive, and then any kind of general sense here of how much this unit versus ASP driven. And then it seems like you do the basic math using the fiscal 25% that seems like AI would probably get a little over 70% sales this year. Is that a decent math on that?

Fermi Wang: I think your math is correct. And let me give you more color. I think first of all, we have a lot of design wins on the CV5 and CV72. In particular, CV5, we talked about that the production, getting into production this year, and we talked about that we’re going to ship one million units of CV5 this year, and consider that ASP is around $35 plus minus, and that really helped us to get an ASP chump as well as revenue growth. So that’s one side of CV growth. The other side of CV growth is that we believe CV72, we’re getting into production with enterprise IoT, and that’s another one. And however, I also want to point out that even in automotive, we continue to ship, for example, just another design win with a Neusoft on the ADAS side with CV22, and as well as a few other designs we had with automotive. So I think both IoT and the auto will continue to have a CV growth in there, but I think IoT is probably more.

Richard Shannon: OK, perfect. That’s helpful, Fermi. Follow up question here on a different topic, and that of kind of China-US geopolitics here, obviously in the context of a couple of nice wins here with your CV3-AD domain controller going into China. Just wondering if there’s any change in the kind of the undercurrent of geopolitics that might make it a little bit more of a headwind to continue to do well there. Just want to get a general sense here if there’s been any real change there.

Fermi Wang: No, I don’t think there’s any meaningful change in the last three months. I think geopolitical situation continues to be an issue that we need to watch and deal with. I think that we talk about the Chinese market, Chinese customers really want to make sure they use local components. But however, I think with the advantage we have, especially for customers who are focusing on the export business, they also need to use silicon from outside China. So I think that’s kind of a balanced view we have right now, and that haven’t changed. We haven’t seen any new regulation from any regulation to change this AI limitations.

Operator: Our next question comes from the line of Kevin Garrigan from WestPark Capital.

Kevin Garrigan: Yes, great, thanks for taking my questions, and let me echo my congrats on the strong results. Fermi, on automotive side, I know you noted that you’re more focused on autonomous driving and the market is pushing more towards EVs, but are you seeing combustion engine opportunities and are any kind of automotive OEMs backtracking from originally thinking about developing EVs to maybe giving you opportunities in combustion engine or hybrid vehicles as well?

Fermi Wang: Absolutely. I don’t think the AD is exclusively for EV at all. I think we continue to see RFQs for combustion engine cars and also hybrid cars. So I won’t say that’s exclusive, but just that first design win, it just happened to be a pure EV company. And that also shows you that all the EV companies trying to find possible differentiations other than just the battery life, but also adding AD capabilities is one way they can differentiate. So I think that this AD application will go to all kinds of cars, including both EV as well as combustion engines.

Kevin Garrigan: Okay, perfect, sorry, that makes a ton of sense. And then going after Richard’s previous questions, you noted in your prepared remarks, AI inferences proliferating in multiple areas and your AI revenue would grow at 30% this year. You have a bunch of design win in the pipeline. Is the AI inference market kind of taking off as quickly or not as quickly as you originally were kind of thinking? And is it developing into as large of an opportunity as you had imagined?

Fermi Wang: Well, for the IoT side, I think we do think that enterprise IoT is growing as fast as we expected because I’m surprised on the other IoT space. But I think that one thing that really didn’t grow as much as we expected is automotive. We have been invested heavily on CV3-AD market and we got the first design win. I think there’s a lot thing for us to work on to make sure that we can continue to take advantage of our investment in AI inference engine in automotive markets.

Operator: And our next question is a follow-up from the line of Tore Svanberg from Stifel.

Jeremy Kwan: Hi, yes, this is Jeremy again. Just a housekeeping question. Did you provide the split between auto and IoT? And if you could just refresh us on what those splits were for the last couple quarters?

Fermi Wang: You’re talking about revenue split between auto and IoT. Is that a question?

Jeremy Kwan: Yes, that’s right.

Fermi Wang: Yes, so if you look at last year, I think IoT was roughly two-thirds of total revenue and auto is one-third and if you look at inside IoT enterprise securities to continue to be the largest portion and the last year consumer IoT and other IoT roughly the same size. But if you look at a growth this year, I think that inside IoT enterprise and auto side IoT is growing faster and auto also, we expect a growth this year.

Operator: Thank you. This does conclude the question and answer session of today’s program I’d like to hand the program back to Dr. Fermi Wang for any further remarks.

Fermi Wang: Thank you everybody for joining us today. And I’m looking forward to see you talk to you in a conference call next time. Thank you.

John Young: Thank you.

Operator: Thank you, ladies and gentlemen for your participation in today’s conference. This does conclude the program. You may now disconnect. Good day.