Mobileye Global Inc. (MBLY) Earnings Call Transcript & Summary

Okay. Great. Thank you, everybody. My name is Mark Delaney, and I have the pleasure of covering Mobileye for Goldman Sachs. With me today is Dan Galves, the Chief Communications Officer. Thank you very much for joining.

Thanks, Mark. Thanks for having me.

I thought to kick things off, maybe it would help to level set everyone on the key products and the rough pricing per product. A lot of our discussion, I think we'll get into some of the offerings and ASP opportunities. So level set people, if you could, please, around the base ADAS product, the rough price, what's SuperVision, what's Chauffeur, et cetera.

Yes. So I mean the core revenue driver of the business today is base ADAS, where we go to market with a single chip with our software on top that supports a front-facing camera system. Typically, we're getting about $49, $50 per chip on average at a 70% gross margin. That's -- those numbers have been pretty stable for quite a while. The next step up is what we're calling surround ADAS. So this is a system that's intended to kind of meet the late decade regulatory drivers that we're seeing to kind of develop in the U.S. and Europe, where regulations and standards are really stepping up significantly. We don't have any design wins for this business yet, but it's a single EyeQ6 High chip supporting 6 cameras around the vehicle, anywhere from 2 to 5 radars. This chip can handle the processing for all of those sensors and kind of the pricing is going to be in the $175 to $200 per chip range, again, kind of similar 70% gross margin. SuperVision is a significant step up because this is a system that supports point A to point B driving. So basically put your address into the system and the car will drive you there with as little kind of human input as possible, but you need to keep your eyes on the road because it's a single sensor system, it's camera only. We support this with 2 EyeQ6 High chips that support -- that processes all the cameras, integrates the mapping, includes the decision-making software. It's anywhere from $1,200 to $1,500 per unit, but this is a little bit different. We're selling the chips on a domain controller. So the gross margin is a little bit lower kind of in the 45 -- 40% to 45% range because there's a lot of third-party components within that -- third-party hardware within that system. The next step up is it's basically the SuperVision system plus a second perception system based on radars and LiDARs. This is called Chauffeur. This supports eyes-off driving on specific -- in specific situations, certainly highways at high speed. You add a third EyeQ6 High chip and the price goes up to kind of the $2,500 to $3,000 range. And then we have what we call Drive, which is a complete self-driving system for robotaxis. This is a really -- it's a very different business because you're generating revenue per mile instead of revenue per car as the operator of these robotaxis. So you're really kind of supporting the elimination of a human driver, which is very expensive, generates a lot of cost savings. So we're selling this for significantly higher prices. So I won't get into specifics on that one, but in the tens of thousands of dollars.

Very helpful. In terms of developing your product set, AI is one of the key technologies needed to develop the algorithms for partially and fully autonomous driving. Mobileye put some work and blogs out there around your views of the best way to develop this. You call it the compound AI systems approach. Maybe talk about what you're doing with AI development, how that maybe compares and is similar or different versus an end-to-end approach.

Yes. So I mean this is -- it's a complicated question, and it's one that I think that requires a lot of education. There's a lot of noise around it that is as usual, it's more complicated than people make it out to be. I think the first thing I would say is that this idea of end-to-end pure AI, data in, controls out versus kind of a rules-based system is a false dichotomy. I think no one is really doing either. Like everything, the truth is in the middle. And I think what compound AI systems means is essentially you are incorporating transformer-based end-to-end AI architectures inside of an engineered system. And you may have kind of other systems within that, that create efficiency or more accuracy within the overall network. And I think that, that's basically like if you kind of look at the research and the latest talk from OpenAI and Google and other researchers, this is kind of large language models have moved beyond pure end-to-end AI and move towards compound AI. And I think the reason is because like if everyone was using kind of the same approach and everyone has the same access to the same data like the Internet, you're not going to be able to create any differentiation. It's really in the engineering that creates the differentiation. And it's kind of the same for automotive. And automotive is even more kind of challenging because it's an area where safety is paramount. You're not going to die from making the wrong prompt in ChatGPT, but you could easily die if a car makes a mistake. So I think this calls for a significant amount of engineering and kind of fallback systems within the overall system, and that's really our approach. And I'll give you an example. So we very much believe in kind of the value of new architectural approaches like transformers. And for our EyeQ6-based system, the core vehicle detection and many of the other detection and perception engines are based on transformer-based kind of end-to-end approaches. And it's very helpful because in a convolutional neural network approach, you're actually analyzing each different object in the image separately and then you have to stitch them together and then you have to eliminate overlap and there's a lot of steps to it, and it's not as accurate, whereas in a transformer-based system, you're analyzing the entire image as one. So it creates a much more efficient approach. But if you encounter an object that's not in the data set, the system could easily just ignore it and run into it. Thankfully, for us, we have legacy techniques based on geometry that essentially are saying, if an object has size and mass, I don't care what it is. I want to avoid it. So having those 2 different approaches within the vehicle detection part of the computer vision system creates redundancies, creates areas where different engines fail in different ways. And we see that as kind of the most efficient way to get to the high performance requirements needed for these systems.

Maybe we can talk then around where you stand on some of the feature capabilities. So SuperVision is your hands-off but eyes on product, highway driving, but driver needs to pay attention at all times. That works on the highway today, you already ship it. You hope to roll that out to work in city streets. Where does that stand?

Yes. Good question. So I think that in China is where the SuperVision system is in production on the road in kind of automaker vehicles with ZEEKR and a couple of other brands. We launched the software a little bit more than a year ago where we kind of enabled the software a little bit more than a year ago in 2 different cities for highway only, and now it's operating in 160 different cities, highway only. For urban, our view is that high-definition mapping is extremely important to create kind of certainty around different intersections, where the crosswalks are, which traffic light is relevant to which direction, yield patterns, yield rules. All of this can be included in a high-definition map and would take a lot of the pressure off the perception system. So our competitors, which are primarily kind of self-developing auto OEMs that have done their own software are also only on highway and have not been able to kind of operate in urban settings. And we kind of attribute this to lack of mapping and the high-definition mapping in China is very expensive because it's done manually with kind of LiDAR equipped vehicles. Our kind of Crowdsourced mapping called REM, we see as kind of the trigger to create that kind of certainty in the urban areas, but we have some challenges in China with lack of vehicles, harvesting REM. So bottom line answer is we have not delivered kind of the urban software yet in China. I think a collaboration agreement that we announced with ZEEKR last quarter is intended to work towards unlocking those kind of roadblocks, very difficult data restrictions in China. So -- and lack of vehicles, this is the intent of this collaboration is to kind of progress towards a more robust REM map. What I need to say, though, also is in U.S. and Europe, we already have maps that are kind of covering more than 90% of roads in U.S. and Europe. So when we launch systems with SuperVision in the U.S. and Europe, we see it as a much kind of faster ramp-up and including urban streets as well.

Okay. And then within China, though, more work to do and no time frame that you can share as to when you think that will be done?

The target is by the end of the year. So we're hoping to get to that.

Okay. And then the next level up is Chauffeur, which would be eyes off. And so on a highway, maybe the driver can look at their phone and also have their hands off the wheel. When do you think you'll be able to ship that type of a product?

So I think the main Chauffeur activity is with Audi, which the target launch date is late 2026. So I think it's kind of the perfect partner to have because we'll collaborate on this with Audi, kind of very kind of robust validation processes. They'll rely on the other work with the VW Group for SuperVision because it's really kind of a scalable compute platform. So we can really focus on the radar LiDAR perception system as well as kind of validating the system. So we still feel like we're on track for late 2026 launch of Chauffeur in Europe, likely the U.S. as well. And I think that, that we'll be able to take advantage of the fact that those REM maps are already available in those areas. So it should be a pretty fast ramp-up phase.

So then the VW Group wins you have are for vehicles not just to be sold in Europe, but also into the U.S., if I heard you correctly?

For sure. And there's a plan for China as well. So it's -- they're intended to be global vehicles sold globally. That's another reason why kind of the collaborations in China are very important because we want to have kind of the landscape in place to support those Western customers in China as well as Chinese OEMs.

And I think your VW Group win is a lot broader than just the Audi Chauffeur agreement. You alluded to you have SuperVision as well. So as I think about the U.S. market, maybe help me better understand when we may see vehicles with SuperVision on the road and Chauffeur on the roads here in the U.S.

Well, Polestar 4 should be the first SuperVision-equipped vehicle to be sold in the U.S. They are not delivering cars yet because the car is produced in China. So it's subject to 100% tariff right now. The intent by Polestar, which has kind of always been the intent, is to produce the car in Korea starting next year. They'd be able to get around the tariffs that way. So I would say by middle of next year, you should be able to drive a car with SuperVision equipped. And then I think the Porsche and Audi, VW Group vehicles start to launch first half of '26 with SuperVision. It should be pretty concurrent Europe and the U.S.

Okay. As we think about that mid-next year, Polestar 4 timing, do you think SuperVision software and mapping is ready to actually allow for the features?

I think it's always kind of a combination of us and the automaker, right? So I think that -- I don't think you're going to see too many vehicles really ever launch and have kind of the software for the kind of the full suite of capabilities available right at once. So I would expect that Polestar has a bit of a validation process after the vehicle launches, but I don't think it should take too much time.

Okay. Robotaxis have been very topical. We're in San Francisco, lots of Waymos, Tesla has got its robotaxi event planned for October. On your last earnings call, you talked about some incremental interest in Mobileye Drive, which is the Mobileye robotaxi solution. So maybe talk a bit more on the interest Mobileye is seeing in the Drive platform. And any sense on timing of when we could see Mobileye Drive equipped robotaxis on road somewhere?

Yes. I mean robotaxis have been a crazy roller coaster for like the last 10 years. And I think just as kind of the cruise negative news peaked, and I think that's died down a lot, Waymo has made, I think, a ton of progress with adding cities and removing drivers. And I think it's very encouraging to the whole industry to see that. And yes, we kind of have experienced the same or similar level of kind of renewed interest. I think from -- our plan basically is to try to put together vehicle platforms that are purpose-built for that business, like so shuttles that have multiple seats and are configured a bit differently that are engineered to integrate our self-driving system. So pre-engineered for where all the sensors are going to go, like where the compute is going to go, kind of integrated APIs that can be used by whoever the network operator is, visualizations for the customers, like there's so many different aspects to this business that need to be in place. You really need like a vehicle development partner to work alongside you. And so we have Volkswagen Commercial Vehicles. We have a company called Holon, which is a division of Benteler that just raised a significant amount of capital for this specific business a few months ago. Those are 2 main ones. Then we also have Verne, which is a division of Rimac that's creating more of like a smaller shuttles. And so we have a good set of vehicle partners that have been working with us for the last few years to kind of integrate these systems. And then we're the provider of the self-driving system, and then you need to connect the demand side. And the demand side is probably best served by a transportation network company like Uber or Lyft, but also like public transit operators. So we have an engagement with Deutsche Bahn that's supported by specific German states, that are looking to replace fixed route buses with on-demand autonomous shuttles. We have a relationship with Ruter, which is kind of the public transit operator of Norway that is kind of very eager to reduce congestion in Oslo and other cities in Norway. Beep, which is kind of another sort of public transit operator in the U.S. So we're kind of creating this ecosystem. And so what I would say in terms of progress is the Deutsche Bahn testing activities, the Hollow Ruter testing activities and the VW commercial vehicle testing activities, which are in Austin and Germany are all targeted for closed loop testing starting by the end of this year. So that would be essentially a group of people that have signed up to be users of this service. So we think Waymo is the leader here. There's a -- it's a different technology approach. We don't see it necessarily as scalable, but very kind of impressed by their performance, and we feel like we're right there.

Okay. That's helpful. One of the sensor technologies that Mobileye uses for Level 3 and robotaxi vehicles and the road map is LiDAR. You had some news out recently around a change in your LiDAR development program. You've been working on a next-gen LiDAR in-house. You've made a change going forward. Maybe talk a bit more on what you plan to do in terms of sensors and then the financial implications?

Yes. So we -- as of a few years ago, we started developing 2 different sensors internally. One is an imaging radar and one is an FMCW LiDAR, which is essentially like a next-generation type of LiDAR as compared to the current LiDAR, which is called time-of-flight. The imaging radar is very strategic to us because we see the potential for this sensor to create LiDAR-like output. So give you basically as much resolution, as much range as LiDAR does, and it's really all about cost. So if we can essentially reduce the number of LiDARs that are needed on a robotaxi or an eyes-off vehicle by using imaging radar, which is significantly lower cost than LiDAR, then that creates a more scalable, lower cost system in general. The imaging radar is on track. It's hitting all the performance targets, and it launches into production second half of next year. The FMCW LiDAR was a little bit of a hedge, what if the imaging radar doesn't really turn out, what if our technology road map requires a more sophisticated LiDAR than time of flight. We only saw 1 or 2 developers or 1 or 2 groups developing FMCW LiDAR. So what if we don't have access to that. So it was a bit of a hedge. We're now at the point where R&D on the LiDAR needs to start moving to the production phase, which leads to a ramp-up of expenses. Because of significant progress on the computer vision side, significant progress on the imaging radar side and also like very kind of steep price declines on time-of-flight LiDAR, we just don't see a scenario where we need this anymore. And so didn't see kind of the value of continuing to invest. But we still plan to use LiDAR on the Chauffeur and drive systems for sure. We just plan to use third-party LiDAR, which we are already planning to use for the kind of the first generation.

I think there were some expense savings in the press release you put out.

Yes. So this -- our kind of adjusted operating expenses, which excludes stock-based comp, are around $940 million this year is -- that's what's incorporated into our guidance. $55 million of that is related to the LiDAR activity. So that's a cost that we will not need to repeat next year.

Okay. I wanted to talk about the competitive environment, including potential future design wins. On the last earnings call, the company talked about for its advanced products, so SuperVision and Chauffeur, you've either got wins already or you're in advanced discussions with 14 global OEMs, and those 14 OEMs represent over half of global auto production. Anything you can share around how those engagements are going and what it might take to get new wins for Advanced Products?

I think continuing to make progress, right? And no change in terms of kind of the direction, kind of the engagement or the time line of what we expected as of a month ago when we talked about that. And there's really been no change, I would say, for the last 4 or 5 months, the expectation is that 4 or 5 of these kind of new SuperVision engagements are targeted for decisions by the end of the year. what are the chances that all of them come to decision and there's no delays, probably fairly low. But I think with that many opportunities, there's a good likelihood that we get decisions on some of them. There's also 4 RFQs for surround ADAS that also -- some have a chance to be announced in the near term. So I think from a business development perspective, like we continue to see more opportunities than we ever have in the past and it's of build on each other. I think it's like the Volkswagen announcement led to reach outs from some of their competitors. I think that there's a couple of these kind of new deals that are very kind of influential mass market OEMs that would lead to greater urgency with others in that group. So we feel really good about kind of the opportunities in front of us. Like we don't have full control of when they're announced or when they're completed, but we're not seeing any roadblocks right now.

Okay. And just to make sure I understood those comments properly. So 4 to 5 awards slated to be decided in the second half of the year, that's specifically around SuperVision and Chauffeur.

Correct.

But some of those may slip that somewhat out of your control when...

Yes. And that's what we've kind of always thought. But I think that kind of -- I think that investors are kind of rightfully looking for that kind of next proof point on the advanced products. And I think that there's consistently a lot of noise in the automotive market, like whether it's kind of production headwinds or kind of lower EV penetration that means less investment required. And so I think that there's a lot of noise around kind of what the automakers are going to do. But we continue to see the same level of kind of eagerness, progress, engagement. And these are the kind of things that are not -- it's not like you're having a check-in call like once every couple of weeks. There's real demo work, validation work, physical testing of the products, roles and responsibilities, legal, commercial, technical agreements. So there's a lot of work to do, but we feel like we're on track.

Okay. DXP has been part of your offering and potential value proposition that OEMs may want to use Mobileye for these advanced products. Maybe talk about how DXP is being received.

Yes. So DXP is -- well, at a higher level, like the one thing that our automaker customers are unwilling to compromise is having some level of control over the driving experience of the vehicle, right? They don't want to have a turnkey system that is the same as everyone else that has no chance for them to differentiate. And so early on, that led them to feel like they needed to control the software, the entire system. But we've been kind of arguing or advocating that there's a middle ground and DXP is our way to kind of find and enable that middle ground by creating an API where the automaker can take core technologies like computer vision perception and mapping that the consumer is never going to see. They just want to know that it works. But then be able to fine-tune things that are visible to the consumer, like how aggressively are you kind of cutting in front of cars on the highway or in a roundabout or how -- what the braking profile is in front of a stop sign or do you stop like right at the stop sign or a little bit ahead of it, in front of it. All of these things are the things that the automakers want to control and DXP has kind of found the sweet spot of how to do that without putting too much responsibility onto the automakers, developers, which creates risk.

And if they're going through the work of doing some coding themselves and using DXP, why not just go all in-house?

Yes, because I think it's too hard. It's too expensive. Like I think the last thing that the OEMs want right now is to invest in a program that doesn't have a high probability of success. And I think that they've already spent time in trying to do in-house development. They've been down that road. It's very expensive. I mean XPeng just announced or just disclosed that they spent $0.5 billion a year on ADAS software engineering. This was disclosed yesterday. So I think that they're kind of past that point of kind of wanting to do everything themselves, but are looking for ways to be able to tweak the driving experience and also ways to make sure that if there is an issue that they can identify the root cause. And this gets back to kind of the CAIS discussion, which is pure end-to-end kind of data in controls out, it's really a black box. So if there is a problem, your solution is to try to identify kind of what was happening in the environment and then generate more data, whether synthetically or real-world data and then retrain the network and hope it fixes it basically. That's not going to satisfy regulators. That's not going to be a good answer to an automaker's customer. So that's the other thing that I think that is sort of a deal breaker if you can't provide.

Okay. Mobileye is assuming in guidance that it becomes optional rather than standard fit in the future for ZEEKR with SuperVision. Can you give us a sense of how much of your SuperVision shipments the last few years were to ZEEKR? And how impactful going forward will this change to be optional on your shipments?

I think it's definitely impactful. So just to level set, so the ZEEKR 1 is the main -- has been the main volume driver of SuperVision volume and accounted for around 45,000 to 50,000 units in the first half out of the 70,000 that we shipped. And every ZEEKR 1 produced had the SuperVision system. ZEEKR for the last 5 years has been developing their own kind of internal system that's similar to SuperVision, and they have it on a car called ZEEKR 7 that they've been producing for the last 1.5 years or so. They made the decision in August to kind of split the ZEEKR 1 volume between their own system and SuperVision. And unfortunately, for us, like we're going to have kind of the minority of the volume because it's only on -- it's on the lowest price version of the car because it's significantly lower cost than their system. But we're estimating that it will be about 20% to 30% of kind of the going-forward volume. That was incorporated into our second half guidance as of the Q2 earnings call. So this is not anything that's going to drive a change to volume, but it does create kind of a lower run rate of volume to start next year. So yes, it's -- I think it's -- from the ZEEKR perspective, it's -- there's a lot of investment that they're making into this software. They're proud of it. There's marketing positives in China to say that you're in control of software and you're using NVIDIA processors and you have LiDARs on your car. So I think that there was a lot of reasons for them to do it, not to mention that they really need to kind of spread the R&D across more volume, which the ZEEKR 7 was not generating that much volume. So I think it's something that we're fine with, obviously, but we also see opportunities to continue to collaborate with ZEEKR, like I was talking about earlier in kind of like productizing REM in China, like that could be a big differentiator for Mobileye. But I think we've kind of realized that we do need help from a partner. We've used partners in the past, but not very sophisticated ones. So I think this could be helpful not just to generate more business with ZEEKR, but to generate more business with other Chinese automakers.

This year, Mobileye expects to ship advanced products for about 120,000 vehicles and incorporating some of those factors that we just discussed. Any directional views as we think about advanced product shipments in '25 and '26 that you can help us with?

I think it's too early to really start talking about specific numbers. I think that what we have is kind of likely incremental volume from Polestar 4 next year, likely incremental volume from FAW next year. And then kind of the big change to the business happens when the Western OEMs start to launch like Porsche and Audi in 2026. And then the RFQs that we're pursuing for other SuperVision customers are targeted for 2027 launches and could be very meaningful, could make today's business, today's SuperVision business look extremely small, any one of them.

Great. Well, Dan, really appreciate you coming again this year. Appreciate all your time, and thanks so much.

Thanks, Mark. Really appreciate it. Thanks.