Please welcome Chief Legal Officer, Alan Prescott. Welcome. Welcome, everybody. Good afternoon. I'm Alan Prescott, and it's my pleasure to introduce you to Luminar's first ever Luminar Day. I think it's gonna be a great opportunity today for you to hear about our business, our great current and upcoming near-term products, and our deep, deep leadership bench. We've got a really terrific speaker lineup that's gonna be coming up from both inside the company and some of the powerhouses of auto tech. We have an agenda so long, they all don't fit there. There'll be additional content on manufacturing and industrialization. After we get through this, after the close of market, we'll be releasing our earnings results, and then Thomas Fenimore is gonna take the stage here, and he's gonna go over the financials. For those who are still here, after about 5:00 P.M., we'll be taking live demonstrations at our long-range testing facility. When I say demonstrations, you don't have to be in front of the car, you can be in the car. I think you'll have a lot of fun with it and really see some of the real dramatic improvement we can make. For those who aren't here in person, online, we'll be posting the webcast and the presentation after the close of the event. I hope after today, I hope you'll be as excited about Luminar as I am. I've been with Luminar about 2 years. I was formerly the general counsel at Tesla. I came here because I see in Tesla a lot... I see in Luminar a lot of what I saw in Tesla. Which is a young company that hadn't made it to scale with some great product that's gonna do great things and make a lot of money along the way. Here at Luminar, I hope you're gonna find what I do, which is we have a tremendous opportunity to make really, really dramatic improvements in safety for people today. real cars that people are driving in today and not robotaxis in the future. Along the way, we can be wildly financially successful. With that, I would now like to introduce you to Dieter Zetsche, the chairman of Mercedes-Benz, and, former chairman of Mercedes-Benz and a Luminar advisory board member. My name is Dieter Zetsche. I'm the former chairman of the management board of Mercedes-Benz. Looking at the development of the automotive industry, the last 5 to 10 years probably has seen the most change ever. This is driven by 3 major trends. 1 is electrification, the 2nd one is autonomous driving, and the 3rd one is digitalization. Luminar definitely is in a very special spot in this regard. Many suppliers thought that talking about autonomous driving is all about robotaxis. In reality, for the industry, it's much more important to go for other systems. That means assistance systems in the different levels from 2 to 5. Luminar has an absolutely leading position that starts with the hardware, where the lidar of Luminar is absolutely second to none. It goes on with the software, where Luminar has understood to embed the lidar into an overall software system, which basically can provide for a full autonomous driving system or an assistance system towards autonomous driving by itself. Beyond that, Luminar understood early on that it makes a lot of sense to go for the development together with OEMs. Luminar is almost the only supplier who does exactly that. Taking all that together, I think Luminar has a fantastic opportunity to support the automotive industry in following this transformation successfully and being a very important partner to the major OEMs. After more than four decades in the automotive industry, we, especially at Mercedes, have always dreamed of a world where there are no accidents anymore, or at least no harm to the passengers. This was a dream. Now it's about to become reality based on this fantastic technology which is now becoming available, not the least based on what Luminar has developed, this very powerful lidar and all the algorithms which allow us to really detect the danger before it occurs and ultimately save the life of the passenger. This is, I think, the most important development beyond electrification of the automotive industry, because it really makes the car an absolutely positive thing all around. Please welcome Founder and CEO of Luminar, Austin Russell. All right. Well, thank you, Dieter. What a legend. That's awesome. Well, I appreciate everyone coming out here, and this is so great to see a full crowd all around. Wow. Great to have you guys here. Thanks again for making all the trip. Happy to be hosting this at our new grand opening for our headquarter building in Orlando, Florida. Here we are. Like I said, we've got a packed agenda today, but start to be able to go through this. Wanna be able to give a little bit of an overview in setting the stage as we dive a little bit deeper into today in the presentation. Kicking it off, wanna be able to just take a step back and just as a reminder of the holistic problem that we're solving here and what we're going for. I think it's really just shocking to see, to be able to take in how big of a holistic problem the vehicle accidents are generally with causing over 1.3 million fatalities annually. If you actually add that up statistically, you know, even with all of us here, it's about on average, you know, 1 in 100 of us will tragically lose our life in an accident. Statistically, at least one person in this room will die as a result of a vehicle fatality. Very real problem. When it comes to accidents, fortunately, most of them are not fatal, but it doesn't change that it can be incredibly negatively impactful, of course, with the average person, even in the U.S., for example, experiencing four collisions as a driver over the course of their life. That causes ultimately over 50 million injuries globally from vehicle accidents. That probably adds up to explain why $1 trillion will be spent per year to auto insurance companies by 2027. It's, it's sort of mind-blowing to think about. I think it's actually on the order of around $750 billion today. We're gonna talk a little bit more about the implication of insurance and what Luminar's plans are holistically with some news from an insurance standpoint. I think this is one aspect of the holistic journey that's very underappreciated and just how impactful this is. I mean, it's literally like, you know what? You know, over 1% of like global GDP, you know, is spent because our cars aren't able to prevent us from getting into accidents. That's these are the second-order opportunities and effects of what can happen when you substantially change vehicle safety. You would think that despite all of these advancements in assisted driving systems and new technologies on vehicles that we're seeing over the course of the past decade, that there would be a dramatic reduction in the vehicle fatalities holistically as well as per capita. The challenge is that, you know, what we've seen in terms of the real-world data is that that actually hasn't happened at all. In fact, not only has it not gone down, it's not even stayed flat. It's actually gone up of all things, which is extremely counterintuitive and almost shocking to be able to say the least. I think when it comes down to it, what's clear is that there's two things that are happening. One is assisted driving systems that are out there today aren't able to have an improved impact, you know, for first from a safety perspective. It's not a panacea that solves vehicle accidents altogether. It only solves a small fraction and a portion of holistic vehicle accidents. The second part of it is that I think as time has progressed, people are continuing to become, you know, more and more distracted. Maybe there's an argument people are driving worse and worse, not totally clear. I think the data speaks for itself, that this is not a problem that's gonna be solved on its own and it's headed in the wrong direction. By the way, even the past couple of years, same thing. No precipitous drop and continued this trend. Vehicles equipped with these, you know, current camera, radar-based assisted driving systems, if you take, like, the specific, for example, pedestrian scenario, they don't end up working the vast majority of times in the scenarios where you end up needing it most. I think this is important to know because it's also not just about the people that are in the vehicles that are affected by these things, but also, you know, as it's called in the industry, vulnerable road users or pedestrians, and bicyclists and other folks that can tragically lose their lives from vehicle accidents as well. The other hard part is that where the biggest challenge is generally for higher speed scenarios, but the higher speed scenarios are usually the ones that end up causing the fatalities in the first place. This is a problem that needs to be solved, and we need a step change in technology to make this happen. If you take a look at it, what I'm saying here is nothing fundamentally new around autonomous vehicles holistically and the efforts from the industry and what everybody wanted to make happen from the beginning. Maybe a little bit more color on the significance and severity and the trends over this over the course of the past decade that I think is surprising. At the most fundamental level, you take a look at where the autonomous vehicle industry was. The question is sort of what happened? There was all this grand vision. If you take a look at the original presentations from, you know, companies that were trying to be able to create driverless vehicles, you know what, 5, 10 years ago, that the whole point was to be able to save lives. You know, it all comes back to saving lives. The challenge is that replacing drivers is very, very hard. You know, as you know, Al and Dieter and other folks have mentioned there, our whole vision from the beginning was always about enhancing the driver, not replacing the driver. That was the big bet because replacing the driver is very, very hard. You have to cover exponentially, you know, orders of magnitude more edge cases that can be extremely challenging, even with, you know, the best lidar and even with Luminar lidar in the vehicle. That does not make it a solved problem. It's still very, very hard, even with those capabilities that make it theoretically possible. The thing is, our whole goal is realizing this and taking it out of R&D and bringing it into production vehicles. That's where you see the transition from cars that look like that to cars that look like this into consumers' hands. Again, we're all about enhancing the driver, not replacing the driver. That's the most important part. You know, with tens of millions of, you know, consumer vehicles shipped annually, representing $ trillions per year in sales, this is an existing established market. Isn't going anywhere for that matter. This is something that is a massive opportunity for us to be able to directly address, of course, in addition to the trucking market. What does that lead up to is our holistic vision. I've said this before, when we first launched this vision at, not this past CES, but the prior CES, laying out what we're gonna do and everything of what this company leads up to over the next 100 years. That's the opportunity to save as many as 100 million lives and 100 trillion hours out on the road over the next 100 years. I think this is something that everyone in Luminar is just incredibly passionate about. You know, everyone from, you know, all the way from our customers, of course, to our suppliers, and importantly, you know, the investor audience that we have here as well. Like I said, it's just incredible having you guys along for this journey, and we're all a part of this to be able to make this vision happen. I think this is, of course, in addition to, as Al mentioned, making a ton of money, what probably one of the most philanthropic things that we could try to do for humanity and society generally, just in terms of the implications of what this can mean. That mission is what drives everyone at Luminar to make this happen. That all sounds grandiose and everything. Okay, like, what's the tangible reality? There is a master plan to achieve this in four easy steps. Just kidding, they're not easy. The first step for this part of this, number one, is creating the world's best lidar for production cars and trucks. That's what we spent the better part of the past decade doing, and that's exactly what we've done. We actually. That's a, that's a check. Great to be able to have that. We're now, of course, with Iris, we developed this for series production consumer vehicles, and we hit start of production in the fourth quarter of last year. Step two, launch and enable the safest and most advanced cars and trucks on the road, starting with high-end models. Basically, like flagship vehicles for these automakers. That's generally what we've been on. That's what people have planned us into initially and originally. I think that we have generally been incredibly successful at positioning Luminar as a, you know, desirable feature and capability for consumers generally when working with premium and luxury automakers. Of course, it's not you're never gonna get to where we need to go to save that many lives or build a $1 trillion business at the end of the day by, you know, just sticking to flagship vehicle models. The important part here is that you can start to move towards mainstream vehicle models by launching and enabling proactive safety and highway autonomy systems on those vehicles. That is the transformation that we're starting to go through now. You know, our recent announcement last week with Mercedes-Benz, I think is perfectly exemplified of that, of something where, you know, we can move from a single vehicle model to now, in their words, increasing that by more than an order of magnitude to be able to enable this vast opportunity ahead and moving towards, you know, mainstream vehicles. Of course, it's not just them. You know, Mercedes, you could argue that any Mercedes vehicle is a great vehicle. When we start to have partners like everyone from, you know, Nissan to SAIC, in China, you start to see that vision for how that opportunity is ahead when people are saying they wanna be able to standardize this across their lineup by the end of the decade. That's a critical part for the next step. That's what we're going through in the throes of and in the transition of right now. For step two, for that matter, we will be, you know, I think checking that box over the course of the next year as we begin launching on these flagship vehicle models, starting with folks like Volvo and Polestar, then ultimately to, you know, the other automakers that we've talked about historically. Mercedes, of course, too. The last step is to democratize advanced safety for everyone. I think that ultimately we see Luminar as something that should be a fundamental right, not just an option to all drivers out on the road, given how vast of a problem this is and how important this is. That said, I think that there continues to be additional significant opportunity for monetizing the upside for comfort features in addition to that, when it comes to autonomous capabilities, software, services, and talk a little bit more today on the insurance front. There you go, four steps. One significant bit of news here is when you add everything up is that Luminar is now planned into over 20 production vehicle models and variants across the globe for major automakers. This goes to show how we're making that leap, you know, from that second step from what we're talking about into that third step and starting to go much more mainstream. This is no longer something, like I said, that's just meant as a novelty for a flagship vehicle. This is something that is exponentially accelerating and becoming more and more widespread. It's funny, even when we added all the different models and everything that we've had, even I was surprised by the end of the day of just taking a step back of what we've been able to achieve. Again, a huge congrats to the team across the board, in helping enable this and make this happen. Of course, we have to be able to continue and execute, and that's what a lot of the speakers that we have here today, as part of our team and our leadership, will be speaking to in how we're making this happen and how we're delivering on this. The important part is the OEMs are there, the business is there, the contracts are there, the people are there, the execution is there. We have everything set up for success. Of course, it's clear how this transitions into, you know, a multi-billion dollar order book, you know, for us as a company. It's not just about future promise. I think all of this, as these models get phased in, at, you know, different years throughout the next handful of years and throughout this decade, Luminar is very uniquely positioned to be able to deliver real revenue, scalable profits, and exponential growth, you know, from our multi-billion dollar order book over both the near term and the long term. I think, you know, frankly, have the biggest opportunity to be, you know, the first profitable company holistically, in this space and industry, or maybe even just autonomous vehicles generally for that matter, by delivering real product into real cars. We transitioned from just thinking that, you know, before when we were going public, a single vehicle model up to these 20 different vehicle models. That's driving now what I think is really kicking into high gear this year as an inflection point. That order book starts translating into revenue. That transition is enabling us to expect triple-digit revenue growth every year for the next handful of years and continuing to exponentially accelerate. Tom will be speaking more to specific details on, you know, financial guidance and what we're looking ahead for. You know, when you guys know the laws of exponentials there too, it's you start getting to some pretty massive numbers when you're at these breakneck growth rates holistically as this translates across the board from, like I said, order book into revenue. Transitioning a little bit to industrialization and execution at a global scale, wanna be able to talk a little bit more about how we're making that happen and also how we're supporting this to be able to execute on these programs, scale accordingly, and give a little bit more insight and a couple of updates on those fronts. Just taking a step back, over the past handful of years, Luminar has developed a truly global footprint, and this is a very important part in establishing ourselves among the automotive ecosystem. In significant part because, you know, automakers are very geographically diversified. It's very, very, you know, industry specific, you know, in this world of automakers. We are able to successfully execute and support customers from across the globe, and I think never more exemplified by us constantly, and the leadership that we have constantly traveling around the world, to make this successful. When it comes down to it, I wanna be able to speak a little bit more to Mexico and specifically this new high volume automated factory that we have that will ultimately be coming online in the not too distant future for in Monterrey, Mexico. Also talking a little bit about the team composition. I think one thing that's important to note that's just very unique to Luminar is we have this combination of both deep technology experience and at the same time deep automotive experience. We've sort of architected the company from the beginning to be able to be at a merger of both of these worlds. I think this is sort of exemplified in a very unique way, probably more than anything, that we've sort of defined ourselves as a sort of new class of automotive technology company that has the opportunity to work and partner directly with automakers to see through this technology into the real world, into consumers' hands, and build a huge scalable business out of it. Normally, you know, technology companies have to work very closely with, or license a product to a tier one or a legacy automotive tier one supplier to be able to have any shot at being able to theoretically get put into a car. The problem is that you don't end up controlling your own destiny, you don't end up controlling your own product. It's not clear that there's any viable path or solution with that approach to be able to make a great experience for or a great product generally for the end user. We're leveraging, you know, I think we have like a millennia of man-years worth of talent, you know, that we have even in the lidar systems domain and optical systems domain as well, and technology generally as well as software with automotive and that talent base. Moving to Monterrey, Mexico. We're happy to be able to say that we now have the majority of our new production lines of installed as part of this capacity plan and as part of this new factory build-out that we've been doing to be able to scale up from our more manual, lower volume facility in Mexico to this dedicated high volume facility that we're doing the build-out of. This is where we get to start seeing all these huge industrialization efforts pay off from both a product standpoint as well as an automation standpoint in this new factory. We'll have Debbie Pappas and Jeff Giese will be able to speak more detail to this later on. The important part is that this factory is now expected to be able to come online ahead of our prior guidance for the second half of the year that we previously guided to. Now, we expect it to come online in Q2. Throughout the course of the rest of the year, we'll be focused on the validation and qualification of the facility to be able to prepare for global series production vehicle launches, including Volvo for their start of production. Taking a step back, I think it's important to be able to take a look at, you know, the end-to-end automotive vertical and ecosystem here. The important distinction with Luminar and everything that we have today is that we're operating literally all the way from the semiconductor level, the chip level up through the stack. the optical transceiver, building out the lidar system, being able to produce this in series production and working closely with our contract manufacturing partners to make that successful and happen. The software stack, of course, for what it takes from a base software standpoint as well as the advanced software layers that we're developing on top of this. OEM partners, again, working directly with them to make this successful. Consumers, being able to get consumer recognition of Luminar and the benefits for that. That's obviously what we've been making a big push for and already is starting to gain huge traction, and will only be accelerating as OEMs start launching vehicles with Luminar on a global scale over the course of the coming year. At the same time, insurance. That's something we wanna talk a little bit more about. At the same time, we have some news on the semiconductor front with the creation of a Luminar Semiconductor entity with leveraging all of Luminar's expertise and subsidiaries in the semiconductor world more generally, which I think is maybe an underappreciated aspect of Luminar and something that we have continued huge growth opportunities in, more generally as part of a core engine of what powers us. Literally end-to-end, that's our opportunity, that's our TAM, that's our ecosystem. People may see us as a lidar company, which is true in some ways as part of the foundations for what we've had. There is a lot to this story holistically when it comes to a transformation as a solutions company. That's exactly what we've done. We can speak a little bit more in monetizing the ecosystem, but one of the things that I think is gonna be critical to that, and the thing that we wanna talk about today, is insurance. We've established a new exclusive partnership with Swiss Re, a leading provider of global reinsurance, and I think actually the second-largest in the world, to be able to better quantify the benefits of Luminar's lidar and the benefits for proactive safety and highway assistant autonomy capabilities for vehicles to be able to translate those safety savings into real numbers that they can provide to insurance companies globally. At the same time, we have an opportunity and actually will be launching a Luminar Insurance product ourselves, to be able to capitalize on that opportunity by already off the bat, underwriting some additional cost reduction for consumers, understanding that even a tiny difference in safety makes a massive difference in economics. We have an opportunity to capture upside in that trillion-dollar market. It's not something that you'd think about or expect, the economics are actually shocking when it comes down to this and the second order effects of what Luminar can enable. What's on the table is we have, the average cost of auto insurance in the U.S. is about $1,750 per year. If you add that up over the course of a 12-year vehicle lifespan, which is the average lifespan, that ends up being over $20,000. I mean, just think about it. That's like a material portion of the overall cost of the car. All of that is just going towards, you know, or at least the vast majority is going towards the overall notion that vehicles will not actually prevent accidents in the first place. It's because vehicle accidents happen, it's because collisions happen. That's the whole point of insurance. If you imagine a scenario where, you know, Luminar comes in, we're disrupting the industry. Even just take a base case, you know, of what, for example, Volvo and their safety engineers, which I think are generally conservative said, you know, have the opportunity to improve safety and collisions right off the bat at 20%. We think we can. Ultimately, the theoretical limit is up to 7 times improvement in safety, even at 20% of these numbers is massive. What ends up happening is that the technology, even despite the notion that we're being adopted for the benefits and the features and the savings capability, life-saving capabilities today, the technology will ultimately end up paying for itself and potentially even multiple times over along the way. We look forward to being able to see that realized in the industry, as well as having the opportunity to capture some of that upside ourselves. Enough about me talking. We have an incredible lineup of guest speakers here today, from across the board in the industry. Some of the best figures of industry have fortunately been able to take a moment and take some time to be able to actually speak on behalf of the vision for what they have and how Luminar is transforming that holistically for their company and beyond. Fantastic lineup. We're gonna go through a little bit more detail. Not all of these will be here with me, but this is across the board for the company. So first up, we have Volvo. Jim Rowan, the CEO of Volvo, be able to come on, say a word. Around five years ago, we launched the Volvo Cars Technology Fund. Its mission was simple: invest in early high potential technology startups with the hope that those firms would help us accelerate our own technology development. Luminar was one of the first companies that we invested in in June 2018. It was a company with promising technology for the future, led by people that we believed in. Now, five years later, our partnership with Luminar is stronger than ever. Lidar will come as standard on the new Volvo EX90, our new all electric SUV. That means for the first time, a global production car is equipped with high performance lidar and the related software. Together, they enable a new generation of smart and safe Volvo cars that sets a new bar for our industry. Lidar's ability to detect objects up to 250 meters away in the glare of bright sunlight as well as in complete darkness, makes a big difference as we look to take safety to the next level. We see lidar as an icon of 21st century safety automotive, just like a three-point seat belt was in the last century. It can be groundbreaking. With its centimeter-level accuracy and high resolution, it can estimate shape and size of objects, map the geometry of the road ahead, and even estimate the size of speed bumps and potholes ahead. All of this detail is instantly processed by Volvo's new core compute technology, allowing the car to act accordingly. In other words, an important step forward in our journey towards even safer cars and the safe introduction of autonomous drive technology. Our partnership with Luminar is a great example of our approach to developing new technologies. Luminar embedded technology is one more reason to look forward to our next generation of Volvo Cars. Stay tuned. Awesome. Thank you, Jim. That was awesome. What a fantastic partnership more generally and awesome be able to see what a difference it'll make for you and your customers. All right. Next up, we have Daimler Truck, the world's largest producer of commercial vehicles. The CEO of Daimler Truck is here to be able to say a word about the state of the industry and Luminar. Hello, everyone. everyone. My name is Martin Daum, I am the CEO of Daimler Truck. Daimler Truck is the world's leading truck manufacturer. In 2022, we sold 520,000 vehicles, we have a strong presence in all regions. In North America, for example, we are the clear market leader with our Freightliner and Western Star brands. We do not want to lead our industry only today, we also want to lead it tomorrow. That is to say, we aim to lead the technology transformation towards zero emission and automation. We are fully committed to autonomous trucking because we see huge potential in this technology. There's more safety, more efficiency, and a very attractive business case. We aim to launch autonomous trucks by the end of this decade. To achieve this, the right technology, of course, is crucial. An autonomous truck must be able to recognize its environment in a reliable way. This cannot be done just by cameras. We therefore focus on a combination of lidar, radar, and camera technology. Lidar's capability of long distance perception is key to make autonomous trucking work. There's no doubt that Luminar is one of the key players in the lidar industry. We therefore decided to partner with Luminar, and we even invested in the company. We did so together with our partner subsidiary, Torc Robotics. Torc's autonomous fleet is equipped with Luminar technology. This technology is part of our sensor suite, and it is providing us with a reliable basis for the development of the autonomous driver. Let me conclude by saying how glad I am to see so much interest in autonomous trucking. I'm sure it will be the next big thing, and at Daimler Truck, we are all in to make it a reality. With that, I wish you a very successful Luminar Day. Thank you so much for your attention. Awesome. Well, thank you, Martin, there too. That's fantastic. Yeah, I think the whole commercial trucking space is there's huge opportunities ahead, and I think also one underappreciated aspect of what's possible. I mean, it's just as important to talk about, you know, collisions with consumer cars, collisions with big rigs are, you know, that much more impactful when it comes down to it. Okay. Next up, we have Polestar and Thomas, their CEO. Good role. Hi, I'm Thomas Ingenlath, CEO of Polestar, a global pure play EV brand with a clear mission: to improve society by accelerating the shift towards sustainable mobility. Our core pillars are design, technology, and sustainability. Our ambition is to create electric performance cars that push the boundaries of the automotive industry at large. Since day 1, we embraced collaborating with industry leaders who are experts in their field. That includes Luminar. Today, Luminar supplies the lidar for Polestar 3, the SUV for the electric age that we launched last October and have now opened for orders with lidar. This significantly enhances the car's advanced driver assistance systems to create a superb assisted driving experience, but it also supports the future of autonomous driving as that technology continues to evolve. In January, we announced an expansion of our partnership, taking our relationship to the next level. The partnership now includes scope to work on integration of lidar in our future cars, starting with Polestar 5, which we plan to launch in 2024. We are pioneers, and so is Luminar. Luminar and Polestar have developed a close relationship and a dialogue about future integration of lidar as a design driven and beautiful piece of innovative tech. As different as our companies may be, we feel strongly aligned in spirit and ambition as young and upcoming leaders in the electric automotive future. We look forward to combining our R&D and product design expertise with Luminar's spearheading innovation. We believe that Luminar is at the forefront of long-range lidar, and our closer collaboration will allow for greater innovation in our cars to come. Fantastic. Awesome. Thank you, Thomas, there. What a great partnership. All right. Yeah. Polestar is, for those that don't know, is a leader in the new EV revolution there, and is already producing what, you know, tens of thousands and, you know, what soon to be hundreds of thousands of, you know, electric vehicles out there and excited to be implemented across vehicles in their next generation lineup. Next up, we have Mercedes. Hot off the heels of the recent, substantially expanded deal announcement that we have with Mercedes, I would like to be able to welcome Markus, the CTO and on the board of management of Mercedes-Benz. Hello, ladies and gentlemen. My name is Markus Schäfer, I'm Chief Technology Officer responsible for development and procurement at Mercedes-Benz. I'm sure most of you have already heard by now, I'm happy to repeat the good news. Mercedes-Benz has found a valued partner in Luminar. Luminar's lidar sensors are helping us to enable Level 3 conditionally automated driving at our next generation Mercedes-Benz models. Lidar allows us to build an additionally redundancy in sensing modalities, braking, steering, and the power supply. By using the best-in-class lidar technology from Luminar, we can achieve high range even for the smallest items with low reflectivity in the infrared spectrum. This will help ensure both high Mercedes-Benz safety standards and customer satisfaction. Customers will benefit from Level 3 automated driving at higher speeds. We aim up to 130 km per hour or around 80 mi per hour at our ultimate stage. Functionality is likely to include automatic lane change and highway to highway transfer. We intend to roll out these features worldwide. We are glad to have found a great partner in Luminar and look forward to the amazing achievements we can accomplish together. Fantastic. Thank you, Markus. I think all of these just go to show again the exemplified transformation between Luminar as a company holistically from what we were From a consideration of a commodity supplier or even a supplier generally, if you notice when these companies are talking, not only is it, you know, at the highest level and at the strategic level for the overall business for these automakers, but also, you know, speaking about us as a partner. That's the most important aspect for how we can successfully collaborate, deploy these systems, scale, and work with that whole truly vertical ecosystem that we talked about earlier. A word on the product that we have for Mercedes, which is gonna be a next generation of Iris. The quick history, and we'll have others talk it through a little more, back in, you know what, 2016, 2017, we originally launched out of stealth mode with this lidar sensor called Model G. Took us a lot of letters to get to G in the first place there in the previous five years, as you could probably figure alphabetically, you know, ultimately transitioned to Hydra. Hydra is what sort of established us in the industry and supplying it to autonomous test and development vehicles and initially automakers to be able to have the first look at what Luminar's technology is, the first, you know, scalable semiconductors and chips in the product and, you know, showing breakthrough performance in something that can be manufacturable. Iris, of course, is our first series production product. That's what we developed over the course of years for automakers to be able to enable it into series production consumer vehicles. What's next is what we are now launching is Iris+. Iris+ is the next generation of product in this, you know, Iris lidar family that significantly builds upon what we did initially with Iris and furthering the holistic capabilities of the product. What you're seeing in terms of benefits from that, right off the bat, you're gonna have as much as three times the performance of what Iris had. That's a combination of both range, resolution for the product. The key is being able to see resolution at range for even those hard to see use cases like the things that Markus Schäfer, the Mercedes-Benz CTO, was talking about that uniquely and only Luminar can fulfill. That, of course, translates to further improved safety in terms of covering even more types of scenarios for the vehicle. It has a 20% slimmer profile as well to be able to further provide seamless integration with automakers from an implementation and aesthetic standpoint, and an opportunity to be able to improve upon that by likely as much as another 20%, in addition to that product from better integration modalities and capabilities that sort of integrated in partnership with these different automakers on the different vehicle models. Lastly, this translates into a highly manufacturable product. You know, we're expecting, Iris+, to be as much as twice the efficiency of Iris from a manufacturing capacity and as well as capital efficiency standpoint for launching the product. That translates through design for manufacturability and better scalability into millions of Iris+ product that will be deployed across consumer vehicles, globally, in the second half of the decade or by, you know, 2027. It's noted that, Iris+ will first become available for consumer vehicle production models as well as truck production models, for start of production beginning in 2025. If you actually zoom out and take a look, holistically, we've been able to leverage all the benefits of what the Iris architecture has, but upgrading each of the individual, you know, components, both at the semiconductor level, as well as at the subsystem level, to be able to further enhance the performance and be able to improve the overall efficiency and capabilities of this for maximum safety and scalability of the product across vehicle lines. We're not even stopping at Iris+. Given this is sort of the first opportunity that we've had where we've even talked about product roadmap capabilities and think of first opportunity, well, I think as a public company that Tom will talk about long-term models and capabilities as well, I wanna be able to give a little bit more insight in terms of what's beyond. In January, we acquired the lidar division of Seagate Technology. Seagate is the largest producer of hard drives and data storage solutions globally, which what they produce like tens of millions of these hard drive systems on an annualized basis. There's actually a interesting and surprising amount of similarity from a components and supply chain perspective for what Seagate's done from a complex optical and optoelectronic systems perspective, as well as what's possible on a lidar. This deal included the assets of this, including IP and specific IP that was developed over a period of years and exclusively licensing other IP that Seagate has developed over decades of time. This will be leveraged to substantially enhance our development effort for the next generation of lidar, even beyond Iris+, that will enable an additional step function in terms of capabilities and cost downs that will allow this to go from, you know, call it millions of vehicles that Iris+ is on to tens of millions of vehicles. With that, like I said, a huge thank you for all being here today. There's a lot more throughout what we have in terms of the presentations that our various members of leadership will be giving, and excited to be able to hand this off to Aaron Jefferson, our Vice President of Product Management. Thank you, everyone. Hi, I'm Aaron Jefferson. I'm happy to be here today. Thank you for that warm welcome. I'm here to talk to you today about our product strategy and our product roadmap. Austin mentioned a lot about safety. Safety is where I spent most of my career, and it's really the foundation of why we're here today. If we take a look at our markets, you know, our goal is really to deliver 1 singular product, 1 singular SKU into all of our different markets, consumer vehicle being the key market that gives us the volume, gives us the scale, gives us the learning to be able to provide reliable, robust, solutions into that market and then scale across into trucking, into robotaxi, into the adjacent market. So we utilize these really to grow ourselves and understand exactly what technology is needed. There's varying requirements across these four different markets, ironically, our solution is very robust, whether it's vibration, whether it's EMC, magnetic interference, our solution is scalable across all of these, and we're able to really focus on that solution for the market and then deliver them to all of our consumer base. We've talked about Iris as the foundation. It's the reason we're here. It's the wonderful work of the likes of Jason Eichenholz, and Dr. Weed, and Austin, of course. Iris is that foundation, and as an organization, Luminar quickly recognized that you just can't deliver that Iris lidar. You have to understand what that data is, what it provides, and how to understand that data and deliver the understanding to the vehicle so that you can control the vehicle in the right way. Perception is essentially taking all that point cloud data, that sensing data, and making sense out of the way you and I do when we drive. Is this car gonna pull over? Is it slowing down? Is it speeding up? It does this without all of the drowsiness and people trying to read and do all the other crazy things people do when they drive. We utilize artificial intelligence and machine learning, which Dr. Weed will get into, and Dr. Annie Guan will talk about as well, to basically have a scene understanding and try to give that information to the vehicle so that it knows exactly what to do. From there, we purchased a company called Civil Maps last year. Mapping comes into play not only for autonomy in terms of localization, understanding where you are, where everything is around you, such that you can better control the vehicle, but it also allows you to update maps to understand when an intersection has changed from a, from a four-stop to a roundabout. You can understand that detection. You can understand that change. You can detect it, basically collect that change and then deliver that change to mapping companies, to our partners, as well as our customers and our OEM providers. Again, that is a new area of space. You look at our product software offering, it is just a very complementary piece that helps with our perception software, but also helps shore up our product offering as we grow into the stack. Then Sentinel is essentially taking all that information and deciding when to brake the vehicle, when to steer the vehicle, and being able to understand and basically deliver that control. We want the capability to be able to deliver this full stack solution to our customers. Also, for me as a product person, I want the ability of our team to be able to understand what our lidar can deliver, how good our perception is, such that we're not dependent on any of our customers to relinquish this into the, into the market before we can say, "Hey, we can achieve this." What we've shown at CES is proactive safety. We've shown highway autonomy. We can show the capability of our lidar without waiting on something to enter into production. That gives us a very powerful message in terms of our capability, and again, to be able to demonstrate, not on a PowerPoint, but what you'll see later today at the test facility, what really can be achieved with vehicles. We achieved our Sentinel Beta solution, which was improved proactive safety. When we talk about proactive safety, we're talking about, you look at Euro NCAP today and crossing scenarios and cyclists and pedestrians, there's a lot that comes with that. That's still limited. That's still in the daytime. That's still under a certain miles per hour. Our goal is really to deliver on the increased speed, being able to detect objects, small objects, and to be able to control the vehicle in a very safe way and deliver the performance necessary to increase the, to increase the safety, but deliver those numbers that Austin mentioned earlier in terms of the number of deaths and the number of accidents. Here's what we demonstrated at CES and what you'll see a bit later. This is a two-year-old on a body car. Again, we have the ability to detect this and basically stop the vehicle. The last scene that you saw where you come from a curve and that small child is coming from behind a vehicle, that's a real scenario that no car on the market today will stop for, okay? The nice thing about this is it doesn't matter if, you know, this technology is really the first technology that has to be future-proof. When I first started working on this, I won't speak to my age, but when I first started working on this, there were no electric scooters on roads where people were driving by. It doesn't matter if you're on a scooter or if you're on a Jetson hovercraft, it doesn't matter. Our sensor is gonna detect that, and it's gonna stop the vehicle no matter the scenario, which is really nice. Next, you go from a simple safety scenario such as this to driving on highways. What we're gonna show is a lower speed, 40 mile per hour, small object detection. Imagine you're utilizing systems today. You're taking all this input. You're understanding that Super Cruise systems are out there, Autopilot systems are out there, and you're driving 80 miles on a highway, and now you're hands-free, and there's a tire or a real wheel in the center of the road, and you might damage your car. You might cause a huge pileup. You could do all kinds of things. It's important to be able to detect those small objects, and that's the direction that the industry is going, and that's how we build our roadmap to, again, increase that performance. Here you're going to see stopping for a tire. Broad daylight. You're going to see it at night. Again, if you're driving on the highway at high speeds, let's just say you have a broken headlight, you still want your car to be as safe as possible. The fact that lidar can detect these things and perform in advance of causing an issue is very key for us. Again, we talked about perception. I won't go deep into it, but one of the nice things about lidar is you get the best scene context that's available in 3D. If you think about camera's really good at understanding the scene. Lidar is good at understanding the scene, but also understanding where everything is distance-wise and position and how that changes over time. Where systems fail today is understanding that, and they don't have to cross-check with other sensors. Within this singular component, we have a complete understanding of the scene. We understand road edge, lanes, free space, objects moving, whether it's pedestrians, cyclists, or vehicles, and we know where we are, and then we're able to basically control the vehicle. Again, this perception software is able to think like you and I even better and make good decisions for the vehicle. Like I said, Dr. Annie Guan will talk about how we do that and why that's important. Next is HD Maps. We mentioned that we purchased the company. What we did at CES was we were driving around in Vegas, and we were able to essentially see, our vehicle drive around, collect data, and build maps real-time. As I mentioned before, the goal of this is really to deliver the functionality such that as you drive around, you're collecting data, you're taking all the necessary data to be able to deliver functionality to the vehicle to better position yourselves in the lane, as well as provide updates. Now imagine we have 1 million of these vehicles on the road between North America and Europe and globally. Essentially, we can map the world with the precise data that you need to be able to provide those updates and again, making driving safer. The only sensing that can really give you the granularity and precision data that you need is lidar. Here, you think about what systems are today. Hands-off, you wanna be able to be comfortable. You wanna take that safety guard down, put your hands down on your lap, relax, and trust that your vehicle is gonna be able to perform correctly. Our job is to make sure that we're doing safe implementation of our lidar and our software systems so that you have that comfort level, and you feel safe, and that the consumer market feels safe to purchase and to drive those vehicles. Next, I'll talk about our lidar roadmap. Again, you know, we talk a lot about execution today and making sure that we're successful in how we deliver this technology into SAIC already, Volvo and Mercedes in the future. Just as important is our roadmap. We have to maintain our competitive advantage from performance and technical standpoint, but we also have to make sure that we address size, cost, power, and we get this thing to the point where it can go in any segment vehicle at any price point, again, to deliver the safety that Austin talked about. SOP in 2022 last year with SAIC for Iris. Later this year, we expect to go into production with Volvo. We talked about Iris+ for Mercedes, which will be in the next generation platforms by mid-decade. Then our next generation development, which is key, and we'll hear more about that from our advanced team, from Tanner and others, is taking our key technologies and really driving the market. Another advantage of our organization is the component group you'll hear from Mike and others later, where we have these key components that really give us the differentiation for our product. With those together, we're not waiting on the supply base to come up with new technology. We're driving that new technology. We are basically setting our own destiny and delivering the performance necessary to keep our advantage, to get size down, cost down, maintain our performance or improve upon our performance. That's really exciting in terms of being at an organization that can really drive and deliver that. It's a huge differentiator that Austin mentioned, gets overlooked, but we're gonna emphasize that more and more as we go forward. Iris, again, the first 3D automotive-grade lidar to enable highway speed autonomy. You heard Markus Schäfer mention 130 kph, 80 miles per hour. To be able to do that, there's no system on the road that can do that today. One of the bigger topics was really around getting the lidar accepted into the roof line. Designers of vehicles are some of the most difficult individuals to convince that technology needs to be in a particular place. You know, that design is their baby. They're very eccentric. What we've been able to do is allow the data to speak for why you want that vantage point. You wanna be able to detect lanes, objects, free space. You wanna see as much of the road as possible. The same way we are in position in the vehicle, you want that lidar there as well. That is a huge paradigm shift, if you will. We saw some of this in China, but in terms of Volvo really being the one to accept it, all of our customers now, we have fewer and fewer discussions around where to put the lidar, and now it's about how do we integrate and how do we maximize performance. That's the direction we needed to head in. You have Iris+. Austin mentioned 40, 20% smaller or slimmer. You'd be amazed at how many, how much a few millimeters makes a huge difference in terms of fuel economy and importance at an OEM, but we're delivering that today, we're able to see further small objects. Again, increasing that performance for higher capability, higher speed capability, and safer implementation, also designing such that we have higher levels of production capacity. Again, as we go from generation to generation, we expect to go from hundreds of thousands of these sensors to millions of these sensors. The manufacturability aspect of that is extremely important. Having the capability we have in-house, working with our design teams, our teams sitting closely together and working together is key for us to deliver that. Lastly is our next generation lidar. You know, one of my jobs here is to take all these different inputs. What is Mercedes like? What is GM like? Whatever customer, the consumer market, and bring all those requirements in and say, "Okay, what's gonna be the best product for the market? How do we work with our R&D teams, get all of these inputs?" We have to make something that is scalable, that meets the, say, mass market customers as well as the premium customers, delivers the functionality. We will not sacrifice our performance and dumb down our product just to be another me too. It really is important that we have that technical advantage, but also address the size, cost, power, such that this is easily adaptable into all of our customers. That's really what we focus on for our next generation product. Next up will be Dr. Weed to come and talk about, dive a little bit deeper into the technology, why Luminar, our competitive advantage, and a little bit about our software. Safety is not a privilege. It is supposed to be standard, and we're working toward that. Thank you for your time today. All right. All right, again, thanks, everybody, for the attention today. I had the opportunity to start the pivot into peeling the onion back. We've talked a lot about the what that Luminar is doing, and we'll start talking a bit more about the how. I'm gonna set a little bit context, particularly focused on differentiation. Obviously, as an investor, this is rather important. There's a lot of folks out there selling lidar. When it comes to differentiation, there's 2 things that may be non-obvious. This is what Luminar focuses on. We're not gonna get buried in the details of specific sensor specifications, though we'll show some proof points of where this all leads up. There's 2 areas in which we differentiate, and it's important, and it's very deliberate. We set out to future-proof our customers' vehicles. This has already been mentioned, and I'll show some detail into what this really means, how we future-proof their vehicles. We're also on the mission to get this tech into every car on the road. This means we need to cut down, flatten all the barriers of adoption, not just high-end luxury cars, but also vehicles that anybody can afford out on the road. What do you mean by future-proofing? From a sensing perspective, this means we have to be able to do more than what the vehicle needs to do on the day it drives off the lot. This has been mentioned, and it's gonna be a continuingly important message into the automotive space in the future. You've heard some of the leaders of the biggest automakers in the planet start to talk about this. How Luminar does this is by delivering sensing technology that can detect, track objects at significantly longer ranges, enabling much higher speeds of operation. We can do this while simultaneously understanding the threat assessment level of these objects. This is this idea of a contextual detection. Where is the thing I'm detecting? Is it actually a threat? How is it moving? All of this information is really important to be able to know, is there a thing? Do I care, as a car? How can I plan around it? Thirdly, we need to be able to make this technology, this data stream, be available in all conditions: sunlight, setting sun, nighttime, shadows, as well as in inclement weather. Of course, any sensor, including the human eye, is gonna degrade as weather gets worse and worse and worse, but we need to allow that sensor data to be still available and give as much capability to the vehicle as possible in all these conditions, 'cause it's when you need it the most. How a lot of this comes together, we show an example. It was mentioned, this tire in the road. You'll probably see this increasingly, you know, present in the broader landscape because at the end of the day, as we move to autonomy, everything that could cause harm to the vehicle or disrupt the drive becomes collision-relevant. Even the tire on the road, a brick. We need to be able to think about these things, and it's a good case of how a lot of this comes together. We'll show here is in the data example. Our Luminar car is highlighted in green. It's gonna be driving to the left, and we show an aerial top-down view of data. Highlighted in red here is the tire on the road that we are driving up on and doing a stopping scenario for. This is a very small object, right? In this data stream, it's called an occupancy grid. We're basically looking and mapping the data, in 3D and looking down on it from above, and we can understand, where the road surface is, kinda subtract that out and highlight anything that is collision-relevant in front of the vehicle. That's why it's black in front of the vehicle and kind of there's objects and barriers off to the, you know, up and below, to the left and right of the vehicle. We can kind of see how the environment is in front of us, so we can make sure that regardless of who's in control of the vehicle, whether it be a person or an automated system, we know not to hit things. That's really, really important as subtle as it seems. We need to be able to do this at significantly longer and longer ranges, the faster the vehicle wants to go. What you see here, a little bit of nerdiness we can dive into. The white curve that sweeps through here and makes a function of detection range versus vehicle speed, specifically safe vehicle speed, is from a third-party estimation This from UNECE. There's some references you can look up later. It's actually a really interesting report that assesses how far away you need to know where something is to be able to safely handle it. We can map against this how far away we can see things and then figure out how fast we can safely drive. If the goal is 130 KPH, again, 80-85 miles an hour, we need to be up above 150-160 meters. It's quite far, particularly when you start caring about things like a tire. Cars are easy. Pedestrians are actually really pretty easy too for lidar, but small, still collision related things are what's difficult, and that's where our differentiation comes. It's unlikely that even the best of our customers are gonna hit the road on day 1 unlocking 130 KPH. They're gonna build to it. We need to allow them that opportunity to build to it. The sensor can't be the linchpin. I should say, it can't be the limiting factor. The software needs to be proven, validated, and developed, and we need to give them that roadmap. While the rest of the lidar landscape is really kind of hitting up against this kind of wall that exists in capability of legacy technologies, we give this huge roadmap, and that's really a big point of differentiation in our customers' eyes. It gives them the ability to provide their consumers a more long-term experience where the vehicle is better every day it is out on the road, as opposed to today, where the best day is when it leaves the lot. You don't have to take my word for it, you know, take our word for it. We have pretty fantastic partners. I'm gonna show some remarks here, from a customer or partner that couldn't be more aligned to our mission, at Nissan. They've done extensive work validating and benchmarking what's necessary to achieve the same things we're talking about as proactive safety within their platform. Nissan is committed to realizing a zero-accident society with innovative technology. Our vision is to reduce the number of deaths from accidents involving Nissan vehicles to virtually zero. In order to realize this capability, we need to develop ground truth perception by not only using camera and radar, but next-generation lidar. Luminar's next-gen lidar provides accurate 3D information unlike camera and radar. By fusing these three functionalities to maximize the benefits of each technology, we are much closer to what human beings can detect and even more. Here, we highlight the differences between other lidar sensors on the market today with Luminar's lidar. Luminar's lidar is capable of detecting objects more than 300 meters away and has more than 25 degrees vertical field of view and 120 degrees horizontal field of view. With these specifications, Luminar is capable of detection at even 130 kilometers per hour, enabling safety at higher speeds. While other lidars on the market have low resolution and narrow detection areas, that just doesn't meet requirements. Luminar's lidar satisfies our requirements to enable us to reach our vision of zero accidents. Yeah. As you can see, braking is really just scratching the surface, right? There are so many strange scenarios that lead to these millions and tens of millions of collisions every year on the road. With partners like Nissan, we're gonna address these, and in a way that can be deployed across fleets of cars that have been sold years ago. It's a really exciting opportunity. The next step of how we differentiate, and how we're gonna achieve all these things we talk about is through cutting down the barriers to adoption. You'll hear a ton of information in coming talks about what we're doing at the hardware component level, driving the cost, and. the cost down and the performance up of the actual piece of hardware that goes in the car. Critically important, something we've been focused on from day one. We are a company that is anchored in hardware technology. The other half of hardware technology was integrating it. We already heard some comments on this, but it gives some context to why we've spent so much time investing in partnerships in the ecosystem. We've partnered with a lot of leading roof suppliers like Webasto and Inalfa. We're starting to work with others in the ecosystem to provide a more holistic hardware solution, so it's easier to adopt this technology, right? We want it to perform as much as possible and set it up for success, not just hide it away somewhere in the vehicle and say, "Done." The last area here is critically important in an increasingly important way. We deliver software, not necessarily so that we can go sell software, although that is a nice upside, but that we can accelerate the adoption of lidar-based processing in vehicles. This is new. Lidar isn't a ubiquitous technology yet in this field, and most of our customers haven't already spent $ billions developing it. While some have, not all have. At the end of the day, our biggest opportunities in the marketplace have little to do with our lidar competitors and more to do with how do we accelerate their adoption of the technology itself. This means delivering software across a huge gamut of types, all the way down to how we control and make the most out of the data at the lidar itself through things like perception, where we're extracting understanding from this 3D point cloud all the way through to controlling the vehicle. We provide all of these pieces so that we can partner on platforms like those shown here, partner with customer automaker systems and allow them to solve their problem with all these pieces and really accelerate the adoption. To dive a little bit deeper into the real heart of a lot of the perception activities is one of our colleagues to talk a little bit about Luminar's AI engine, Annie Guan. Welcome her to the stage, and thank you very much. Thank you. Hi, my name is Annie Guan. I'm leading AI and machine learning and AI team at Luminar. Today, I'm going to share with you how Luminar is using our AI engine to deliver the next generation proactive safety and autonomy. Why do we need to use AI and machine learning? With only the raw point cloud from the sensor, you only see the points in space and reluctance, but reflectance, but you don't know where the points are and how they behave in the future. In order to develop a proactive safety and highway autonomy features, it is essential to identify what those points are and how they will behave over time. In order to classify those points into specific objects, such as people, cars, and cyclists, and predict the possible future movement based on the classification, we need to leverage the power of our AI engine. In this image, you can see that now we have applied Luminar AI engine, we have gone from just pure raw point cloud into a rich environment model, showing all different types of objects in space with their exact location, height, width, and heading. By leveraging the inherent information contained with the 3D point cloud data, we achieve a much higher level of accuracy than if we were to infer this information from only the camera images. The rich environment model that is produced using the machine learning techniques allow us to understand the surroundings and also the potential hazards on the road. With this in mind, let's take a closer look of the system and technology that power the transformation from the raw point cloud to rich environment model. Here we can see the different elements of Luminar AI engine pipeline that is capable of consuming a raw point cloud and generate 3D bounding boxes for objects, 3D lane points, barrier points, road points, and also the drivable space. At the core of the Luminar AI engine, we have 2 neural networks. One is the 3D object detection for dynamic objects, and second one is semantic segmentation for road, lane, and barrier classification. To train the neural networks, we rely on large amount of labeled training data. We also building a training infrastructure which utilize a data engine and distributed training, where data and the model are paralyzed across different GPUs. To deploy the new networks on the vehicle edge device, we must optimize network for fast, efficient inferencing using AI acceleration techniques. Let's dive into the details of the neural networks. Let's first take a look of the 3D object detection neural network. The model consumes multiple frames of raw point cloud and outputs a 3D bounding boxes with object classification. First, we perform a dynamic 3D voxelization, which divides the point cloud into a grid of voxels and map points. The 3D voxelization step preserve all the raw points, as there is no information loss in this process. Features are then generated from each point and which are fed into the neural network backbone, where we do sparse convolution. The sparse convolution step only process non-empty voxels rather than processing all voxels in the grid, which reduce the inference time. Different objects have different sizes in the point cloud. In order to address the challenges of varying size, we apply a multi-scale feature aggregation, where we create a feature maps of different scales. For large objects, such as vehicles, feature maps with a coarser resolution are used. While for small objects, such as pedestrian, feature maps with a finer resolution are used to capture the more detailed information. Finally, we do a regression and classification step to determine the 3D bounding boxes dimension, orientation, object classification, and confidence score. With this network, we can detect vehicle at 200 meter with 200 meter with centimeter level of accuracy. The second network we have is semantic segmentation. The model takes the raw point cloud and outputs classifications for the 3D points for road, lane, and barriers. We first extract point wise features, which are then projected into a bird's-eye view. The feature map from bird's-eye view then goes through an encoder-decoder network backbone to get point wise confidence score. Finally, we reproject this into the 3D space to determine the 3D point wise classification. Life-saving proactive safety function require both high confidence detection and extremely fast inference time. In order to achieve this rapid response, the neural network needs to run on edge device in the vehicle fast and efficiently. This is where AI acceleration and inference comes into play. The goal of AI acceleration is to reduce the inference latency while minimizing any potential impact on the model accuracy. At Luminar, we have been working on various techniques to achieve this goal. Some of the approaches we have been working on including quantization, pruning, mixed-precision training, and knowledge distillation. By using those techniques, the model can be run much faster for safe critical applications while still maintaining high accuracy. With these techniques, we have reduced the runtime by a factor of 2 to 4 times and can run on automotive-grade SoC in under 20 milliseconds. Machine learning and AI bot-based models require large amounts of high-quality label data in order to train the models. In our case, we have partnered with Scale AI to provide ground truth labeling across different ontologies, covering both dynamic and static objects. With that being said, I will now turn back over to Austin for a conversation with Alexandr Wang, CEO and founder of Scale AI on AI and machine learning. Thank you. All right. Well, thank you, Aaron, Matt, and Annie. That was awesome. Obviously, great to be able to see the latest as it relates to our AI, and we've been sort of developing behind the scenes, but I think great to be able to put it into the spotlight at a pivotal time for the industry. We have Alex here, the founder and CEO of Scale AI, which is our key and exclusive partner to be able to help enable this whole ecosystem around all things AI. Maybe, for those who aren't familiar, Alex, you wanna say a word on your company? Yeah. I founded this company, Scale AI. We're a deep partner of Luminar, so really excited to be here, and pretty amazing to see all the stuff that you and your team have been working on. We're an AI company based in San Francisco, California. Our core product is all around enabling datasets for AI and machine learning across a wide variety of applications. As an example, we helped build ChatGPT with OpenAI. We've worked with them since 2019, so, you know, I like to say it's been a 4-year overnight success on that one. Exactly. We've worked across the entire autonomous vehicle and automotive spectrum, working with folks from General Motors to Toyota, to many of the tech players, and have an exclusive partnership on the lidar side with Luminar. I'm sure we'll talk about this in a bit, one of the reasons for that we see is just the, A, the commercial traction that the Luminar folks have is just incredible across all of the auto OEMs. We do business with them as well, we know it's not easy to do business with them. The data, the quality of the data at a core fundamental level is dramatically better than the competition. You know, we just see this incredible opportunity to do so much more with the data, which we're gonna talk about. We also work across a wide variety of industries as well, across, you know, large e-commerce players like Instacart and Grab, to large, to the government, working with the U.S. Army and the U.S. Air Force. You know, we're based in San Francisco, and it's a really exciting partnership that we've built here. Yeah, awesome. That's to say the least, I think we're together. It's been a few years now there too since originally, you know, starting to collaborate on all of these things and getting it together. Maybe just a question on the data side. Like, how do you see the importance of, you know, this data, the fidelity of the data, and volume of data as it relates to Luminar? Maybe even more generally, you know, why Luminar? Yeah. I think if you take a big step back on the sort of arc of artificial intelligence, and Annie certainly got to this in her recent presentation. If you take a big step back, the two major drivers of the entire revolution of artificial intelligence have been massive increases in data and massive increases in computational capability. Computational ability has been powered by Moore's Law, and then data and data availability has been this sort of, like, secret driver behind a lot of this improvement. If you look at ChatGPT, for example, or the sort of language models that everyone's kids here are using to cheat on their homework. Those models are trained on literally 1 trillion tokens of data from the internet as well as whatever data that they can get a hold of. You know, there's stories of these AI companies. You know, they go hire people to go, like, scan old books and literally scan these old books for data to be able to train their algorithms on. Data in many ways is the lifeblood, and the sort of data hunger of modern AI algorithms is really very difficult to appreciate. It is. They are massively hungry, and you don't get diminishing marginal returns. Like, what you see with ChatGPT, for example, or the progression on the language side, which is sort of all the hotness, is that as you keep getting putting more and more data, the models just become smarter in very unexpected and quite profound ways. When you look at how that translates into the autonomous vehicle and automotive ecosystem, the same thing holds. You know, if you look at across much of the autonomous vehicle development today, the data volumes, despite, you know, it is a lot of data that's being produced, but that pales into comparison to what the amount of data that will be produced from production rollouts of the technology and production fleets. You know, when many consumers are buying vehicles with, you know, high-quality commercial lidars, the amount of data that will be produced from those sensors is astronomical. I think we're gonna see in many ways the same trend that we saw on the language and on the language side of AI, in the sort of autonomous vehicle side of AI, which is once you're able to amass these huge amounts of data, you get just dramatically new and different performance from the, from the algorithms. Which is. At a core level, that's exciting, then I think, okay, so what? If you have much stronger AI, what do you do? I think you build, you know, obviously, there's autonomy, which is one holy grail. I think you have a lot of interesting and exciting opportunities in other parts of your business as well. The insurance business. Insurance is obviously a place where if you had very fine-grained data and very fine-grained algorithms, you could, you know, you could underwrite significantly better, you could drive a lot, pitch. At this point, I'm pitching your business plan, but. Exactly. I think across, like, every part of the automotive stack, huge amounts of data become incredibly valuable. Yeah. You know, this is one of the reasons why this partnership is exciting for us, because, you know, there's just not that many companies that are gonna have this much data. It's going to be rare to have this much data, and we're excited to see what incredible things we can build together. Yeah. Yeah, no, it's awesome, and that's for sure. I think this is really what you're seeing today, you know, with the Luminar AI engine being relevant for, you know, detection, recognitions, you know, being able to have collision avoidance or, you know, assisted driving capabilities. You know, that, as you said, that's just the start. Actually, yeah, it's funny that you alluded to that, even, like, on the, on the insurance side and other things that as we go through that whole vertical ecosystem there too, there's relevancy, you know, literally all the way from the semiconductor level all the way up through the stack to insurance and stuff. That's great. Well, I mean, you guys are What? You've got to be the leader holistically in this space now too from all the wins that you've established and, you know, volume that you're processing there too. That's a huge and, yeah, like I said, congrats to yourself too. What do you think about from the importance of the fidelity of data as well? Because that's an important one of we have this huge volume that, I mean, for everyone's reference here, historically, autonomous test vehicles and development vehicles, I mean, you're only talking, like, fleets of hundreds of cars that have lidar on them that are collecting data and leveraging it. The whole point is now we're able to get out there with, you know, millions of vehicles, you know, it. You don't even have to wait till then. It's like, you know, tens, hundreds of thousands of vehicles in the more, you know, immediate term that we're scaling through. Obviously, there's vehicles out there today that have, that have other kind of more basic sensors. What do you think about the importance of the 3D data and the 3D aspect of it and the fidelity of that data in creating a holistic system and solution? Totally. Well, I think A, it's critical to safety. You know, if you don't know how far something is away from you might run into it, which would be really bad. I think it's relatively intuitive. As well, I mean, I think a lot of it, you're right. There are some cars with some basic lidars that have, like, you know, a few lines and, you know, that doesn't really give you a whole lot to do any sort of meaningful machine learning or deep learning on top of. If you have, you know, on some level, if, let’s say, my eyes were lidar, and I saw this room, and I had, like, a perfect 3D scan of everyone in this room, I would be able to discern, you know, almost strictly more than if I were just, you know, if I had, like, you know, my optical sensors, which are my eyes. The sort of the full amount of information that you can get out of the data, which is what a lot of these AI algorithms are trying to, like, get at, where it’s like, how do you get the full amount of information that exists implicitly within all the data, is just far more through, I think, the incredible sensors that you all have built. There's, again, there's kind of this, like, clear theme in AI, which is once people build the mechanisms by which you can collect massive amounts of data, the internet being, like, one of these collection mechanisms for getting a huge amount of data from humans. Once you build these mechanisms, sensors being a core component, then you get, you have the ability to then to glean so much more out of the AI algorithms. I think that, you know, if you go use case by use case, you start with just autonomy functionality. You know, autonomy. Contingent upon autonomous systems are gonna be safe autonomous systems. It's very, very, very challenging to get requisite levels of safety without very high fidelity, 3D sensing. I think the other piece that is exciting is, I think there's components that I think we'll discover over time. There's additional upside, which is that, you know, we're... You kind of alluded to this, but, like, we're as a machine learning AI community, we're very early on in this sort of journey of understanding and processing and building AI systems on top of lidar data and 3D data. You know, even as if you take an example, ChatGPT, this is, like, decades into using machine learning and AI on natural language processing, and then all of a sudden we have these huge breakthroughs. I think there's a lot of upside as the machine learning and AI community continue to improve upon the algorithm techniques to be able to process all this data, which is I think very exciting. I mean, I think that, you know, in many ways the one of the exciting things about our partnership is, will we have a ChatGPT moment as it pertains to automotive data? Yeah, absolutely. I think, I think we've had pretty much exactly that moment when it comes to the lidar itself, and now, you know, it's already starting, you know, when it comes to the software. That's critical, you know, working collaboratively, of course, with, you know, our partners on these things holistically. As well as, not just the automakers, but the platform providers too, you know, that we'll be talking a little bit more and, Tanner will be talking about in his section, as part of this holistic ecosystem for what we have. That's relevant. I think, you know, the interesting part, there's also seemingly a lot of synergies in terms of overlap of opportunities and customers and everything there, that I think should hopefully accelerate that, you know, as you guys are providing sort of the back end behind, you know, what we're doing for the Luminar AI engine, but also, you know, working with some of those folks yourself. Maybe I'd say, like, what do you, what do you see in terms of, you know, additional opportunities in advancing the ball forward for the industry? Like, you know, for example, anything from, you know, cross-collaborations, mapping, you know, other kinds of functionalities. You mentioned insurance, you know. Yeah, yeah. Totally. Yeah. Well, I think the exciting thing is that in many ways, one of the ways that I view our partnership is that Luminar has built this incredible platform upon which there will be one of the greatest datasets for autonomy and driving data produced. It's contingent on both of us, what are the exciting things we can build out of this dataset? As well as, how do we work together? You know, I think we're both very much so in the automotive business to get to this outcome of much safer vehicles, right? I think that like at the core, that's certainly what drives us and myself and our teams. That's what drives you and your teams. I think we've already seen that our teams have been able to and will continue to be able to work together quite effectively in accelerating that mission, right? How do we get like every automaker in a position where they're shipping safer vehicles? You know, sometimes that requires some muscle from our sales team, sometimes it requires some muscle from your sales teams. At the end of the day, I think we're making great progress along that along that journey. Yeah. Yeah, to your point, I mean, there's so much to do with the data. Insurance, there's mapping, building a live 3D map of the entire world that's constantly up to date. This is not something that exists today. You know, Like, Google Maps gets really out of date quite quickly, actually. Not the fidelity that you need for autonomous driving. There's just so much to do with the data that I think, you know, I think we're gonna discover new opportunities in future years as well. Yeah. That's awesome, man. Well, thanks for taking some time here too, and, you know, feel free, you know, speak to Alex out here in the audience during the day. Great to be able to have you in person and, awesome to see you guys leading this whole next AI revolution and providing all the back-end infrastructure to make the Luminar AI engine successful. Yeah. Thanks for having me. All right. Cheers, man. Time for a 10-minute break, please. 10 minutes. We will start again right away after 10 minutes. Thank you. Luminar Day meeting will resume in 5 minutes. Please take your seats and remember to silence all mobile devices. We're gonna start again in 5 minutes. Thank you. Luminar Day, we'll resume the meeting in 2 minutes, please. 2 minutes. Please find your way back to your seats. Thank you. Luminar Day. Please take your seats. We're gonna begin in under 1 minute. Please take your seats. Thank you. Please welcome co-founder, Luminar, Dr. Jason Eichenholz. All right. Good afternoon. Thank you, everyone. Hopefully, everyone's getting their sugar high from those brownies going. As Aaron and Dr. Weed talked about, there's really four components to a lidar system. We knew from very early days back when we were developing the Model G that we needed to move into the eye safe region, or you hear about a 1550. We knew that 'cause we could use 10 times the laser power, 17 times the photon budget, or 1 million times the energy, and still be eye safe. People told us it couldn't be done. We were able to make it happen because we developed what we call our chip level up strategy. Many people focus on the economics to make these four components of a lidar system work together. The reality is you need technology innovations that allow you to unlock the autonomy, unlock the performance. In order to do that, you can't do that with commercially available off-the-shelf components. As a small startup, we weren't able to get the attention of the industry. Now we are. We also have vertically integrated and developed our chip level up strategy. When we got the technology to work in the performance, the economics came along for the ride for free. If you take a look at our technology, and here it is example of the technology of our Black Forest Engineering ASICs and our OptoGration APDs. I'm gonna hold them up here to give you all a sense of scale what you're looking at. You're looking at this stuff on a microscope slide. It's on a microscope slide because you need a microscope to see it. We've got our subsidiary, Black Forest Engineering, that produces the mixed signal ASIC, OptoGration that makes the high sensitivity and high dynamic range receivers, excuse me, and we broke away from the limitations of silicon. We're able to have these hybrid systems that enabled the eye safe 1550 nm window, and they became accessible to all. As these devices got smaller and smaller, as you see them in there underneath the microscope, we're also able to do some pretty cool things physics-wise to unlock the performance. If you take a look at U1 and you see the Black Forest Engineering chip, and there's a very small square where you see the APD from OptoGration, you'll notice that there's no wire bonds. Those gold wire bonds, just for scale, are about the size of a 100 microns, size of the width of your hair. There's no bump bonds because we couldn't have handled the physics of the capacitance of that wire bond. We've got both physics and economics working for us enabled to unlock the performance. Here's an example of the technology and the electronics that went into the Model G with our first receiver, where Black Forest Engineering and OptoGration came together. If you look at those, you see a time-to-digital converter chip up in the front. The reality is, we were able to take all of those electronics and then put inside, in Hydra, 100 of those TDC boards. All that technology came together. To get there, Luminar was the first to have deployed a custom ASIC for lidar back in 2016. You can see the progression over time as more and more compute horsepower combined with a mixed signal ASICs go in. In 2022, Luminar was the first to take a custom ASIC like this for automotive series production, and we've taken all this technology and made it auto-grade. We've been able to take tens of thousands of dollars and turn it into single-digit dollars as we put these systems together. Running the same playbook we did before on the receivers, you can see what we did with that big hunk from the Model G of the laser and moving it into Hydra, and now what you're seeing going into Iris and our next gen systems. As the receivers became more and more sensitive, we were able to see further, and we had lower noise in each generation. We were able to then scale our lasers smaller and smaller. Less and less components, which then allowed us to drive the efficiency and also drive the point resolution. We got, again, power consumption and the economics came along for the ride. We've also significantly reduced in the latest generation, the electronic components by moving more and more functionality from those electronic boards into Black Forest Engineering ASICs. You can see how the ASICs and the technology and optoelectronics come together. The key to proactive safety is both autonomy and range, plus resolution. You need the range and the resolution. There's been almost no progress in laser diode technology for the last 2 decades. Freedom Photonics is the technology leader in scaled high brightness laser diodes, as you can see from that hockey stick of growth that we announced just back in January at Photonics West and Photonic Integrated Circuits. The lasers and the BFE ASICs are supporting Iris today, and their innovations will drive the next generation platforms and innovations on the receiver side that are coming for next generation, combined by functionality on the laser side. I have a saying, 1 plus 1 equals 11. Freedom, OptoGration, Black Forest Engineering, when combined together into entity, creates a lot of power and a lot of synergies. We internally, and you've heard them called Luminar Semiconductor. We'll be launching a unique brand for this company and a new name later in the year as a separate company owned by Luminar. I am personally exceptionally excited to be taking on a new role as chairman of this new company. Thank you. I'm also excited that we found an exceptional leader to go run this operations day to day. Mike McAuliffe will be joining as CEO of Luminar Semiconductor. Mike brings decades of experience of taking companies like this and building semiconductor and technology companies, including several startups to exit. Mike previously led Seeing Machines, a publicly held Australian company focused on computer vision and bringing market leadership in ADAS, driver monitoring systems, and processing to some of the world's largest automotive OEM. We're now gonna leverage that experience inside Luminar Semiconductor, as you heard Austin talk about grow that company. Welcome, Mike. Thank you, Jason. Thank you, Jason. First of all, it's a privilege, really, when I joined the company last year to join such bright people on such a burning mission I knew to be exciting, and I was not wrong. Luminar Semiconductor, why do we exist? What's the difference between Luminar and the three component companies? Jason described the chip up strategy. Described why OptoGration, Freedom Photonics, and Black Forest Engineering were acquired to be the best in class. Now as Luminar Semiconductor, our mission really is to take those into an integrated company and to take them to the next level, the next level of capabilities, the next level of products, to drive the current and future Luminar roadmaps. Importantly, also to create a broader ambition to be a photonics player in the wider market. At our core, what do we do? We build chip-scale components and chip-scale optoelectronic engines to solve really impactful problems for the world, working with industry leaders. Number one, of course, is our parent. Number one is Luminar, our number one customer, solving probably the most impactful problem of them all. There are more, and today I hope to share with you some information on what they can look like. We've heard about stacks today. We've big stacks, and I guess that means that we're a sub-stack maybe. We have our own stack too. Our stack goes from, we call it photons to decisions. In some ways it represents the signal processing flow from the generation of photons with the lasers from Freedom Photonics, the detection of photons at OptoGration, and the processing of those protons from Black Forest Engineering. We combine that with advanced packaging up to what's then the next stage of DSP processing and AI processing, as described by the team earlier on. Largely that feeds the signals for lidar, the lidar software, perception and mapping as we described earlier on. Now the key insight is that the same technologies and the same capabilities that make Luminar successful, they can be applied to other markets. Other customers have similar problems who are generating photons, detecting photons, processing photons. They recognize how difficult it is, what value we can create, so they're also interested, and we can create broader opportunities across wider markets. I think it's fundamental to our strategy to understand that this common needs can drive common platforms. We only focus on the hardest photon processing problems, generation, detection, and processing. This is what lidar is. It's one of the biggest, most difficult physics problems today, but we have other customers solving similar, very difficult photonic problems. We can now take the same platforms, the same products, closely aligned and leverage that across multiple markets. We solve 1550 nm. There is a general perception that 1550 nm is traditionally an expensive process, and it's maybe a drawback. That is not the case. We have solved that problem through, number one, architecture, as Jason described, number two, advanced packaging, and number three, we can drive the economies of scale and the economics associated with that by leveraging both Luminar volume and volume to the wider market. We're shifting gears. We're shifting gears to take what has been a subscale industry, subscale ecosystem, and industrializing that at scale. We need to do that. We need to do that both for the economics and for size, weight, and cost in order to deliver lidars at millions of units. As an example, the other key advantage of siliconization is this. People think that maybe the biggest advantage is you control your own supply chain. That's true. You can control the quality. That's true. You can control the performance. That's true. The biggest advantage of siliconization in general is you can take a lot of complexity and cost out of the product. Complexity in cabling. Complexity in optics. Complexity in electromechanical. Anything you can put in silicon, you can put in silicon. I think we can see from other industry leaders like big fruit companies that owning that stack and internalizing and siliconizing anything you can delivers elegant architectures, breakthrough performance, and breakthrough economics. What's the basis of competition? How are we gonna compete? How are we gonna win? What gives me confidence? Well, number one, we have what I regard as really the brightest team maybe in the industry. By the way, that's not, that's not me saying that. That's some of our customers saying that. We've about 100 people across the three companies today. Over 85% of them are engineers, and over a third of them are PhDs in MH, you know, engineering. They're spread across our sites, Santa Barbara's lasers, ASICS in Colorado, receivers in Massachusetts. Our platforms also are very unique. We have. I won't go into the acronyms and some of these look pretty dangerous materials, but these are pretty special materials. They're special for generating photons at different wavelengths and for detecting photons at different wavelengths. We have a unique set of platforms and capabilities right down to the atomic level that we can control, design, and optimize semiconductor platforms for achieving this full stack of technologies. It's very important part of our model that even though we own the process, we have our own facilities, we control the design of the process, we are also scaling now to ship millions and millions of chips, scaling a new model of state-of-the-art fab partners, packaging partners, test partners across the world. We don't have a legacy infrastructure to worry about. We're kind of the barbarians at the gate. We've a clean sheet of paper to design a brand-new supply chain, and we can control the control of the process, the process recipes, specialized manufacturing here, and we can choose world-class, high-volume, best-in-class fabs and foundry partners in the world. That's key to our economics model as well. As we execute this strategy, what is the broader opportunity? Again, I stress broader outside of Luminar, we believe will be clearly the market leader in lidar. I don't really have to do a lot of work to generate these numbers, and you don't either. You can go to any one of the photonics companies in the public domain and look at their TAMs, their SAMs, their market analysis. The answer is it's rather large. Across communications, aerospace, precision manufacturing, broader lidar and 3D vision, emerging sectors such as optical sensing, quantum computing, quantum sensing, which are very heavy users of photonics, and life sciences, biosensing, gene sequencing. These in total are over $50 billion. That's interesting because it informs the potential runway. What we're much more interested in, and what I'm more interested in is what's the ground market pull? What's the bottom-up opportunity? Who are we working with? What problems are we solving? How do we solve them? How do we turn this into a scalable business? Something you may not know, and most people don't know, because I guess it's been under the radar or I guess under the lidar in this case. We have over 60 current programs at leading customers across the world, and we've shipped over half a million products. These products, I can tell you, are going to some of the most demanding mission-critical applications you can imagine. We have a strong reputation. People come to us to solve very hard problems, and that's core to what our potential is going forward. What's happening in the industry landscape? Well, number one, Photonics in general and III-V materials is rather immature, but we have the potential and we have the playbook to go and drive that industrialization, drive that scale, drive that economics. That's something that's core to our strategy, and we think we have the ambition, resources, and the strategy of Luminar, we have a great chance to do that. Secondly, many, many new markets and applications are really driven by laser technology. Many of the examples I shared with you earlier on, the core of that technology is laser technology, narrow beamwidth, tunable lasers, high power amplifiers, and they create new markets. We're going to use that to create a new beachhead, to land on that beachhead, and then expand, delivering a full solution of detectors and processors as well. That's key to building our stack and building our moat. In summary, I would leave you with this, the to-do list. This is our to-do list in the company. Number one, drive productization, drive scaling, and drive the chip-level roadmap for Luminar. Number two, build foundations for the company and build beachheads. Build beachheads, what we believe is a very large opportunity to build a separate company. Build, disrupt, deliver, and scale. four small words, one very large impact, we believe, for Luminar and for the industry. Lastly, I would say in the words of that great Gen Z song, you know, we've only just begun, I think stay tuned. I think it'll be an interesting journey. Thank you. Please welcome EVP and GM, Taner Ozcelik. All right. Good afternoon, everybody. You know, I've been in automotive for 2 and a half decades. In fact, I came out of retirement. I've built several billion dollars businesses from ground up. I've learned that the success in automotive relies on getting five things right, and that's what I wanna talk to you about today. First, you have to innovate. You have to innovate very rapidly. This is true for any industry. It's also true nowadays with automotive, because automotive has become basically a tech industry. You have to design and build the products that can scale easily. You have to have an architecture of the product line that makes it so easy to leverage that massive R&D that you're pouring into every product every time. Rinse and repeat and build that into the new products. Architecture happens to be also very key to competitive moat. I've learned this over my career working for some of the great. You have to make sure that whatever you design can last for decades. That's called being automotive-grade. It's important because that know-how incorporates the massive learnings of the industry that is 100 years old. It's one of the oldest industries. Many scars. Last but not least, and arguably the most important is the talent. People talked about it. It's important to have a talent base that is infused with both automotive experience and heavy technology bent. Austin showed that earlier. Let's dig into the details. As I mentioned, everything in tech relies these days heavily on innovating and innovating rapidly. You can see examples of this in many companies that either became incredibly successful or disappeared. NVIDIA, my our partner here, my alma mater, is a great example of a company that rapidly innovated and reestablished the company to new heights in almost every major generation of products. As we all know, our beloved BlackBerry, once everyone's indispensable technology, fell by the wayside. Lack of rapid innovation. Innovating and innovating rapidly is incredibly important to cementing that leadership. That's what I'm after. It's important in tech. It's important in automotive as well. I can now confidently tell you, because I'm gonna show it to you later, that Luminar is not only innovating fast and delivering on our milestones, whether it's our customers' milestones or our internal goals, we're also accelerating our pace of innovation and development. Here's the proof. Hydra, as Austin showed was the first product introduced in 2020. It was a game-changer product. Many automotive companies, including Toyota, adopted Hydra for R&D, and it was deployed in the industry in thousands of units. Hydra took 3 years to bring it to a mature functional level. Automotive industry terms that maturity sample as B-sample. Hydra was Luminar's first attempt to build something super complex, yet very effective, in my opinion. Hydra put Luminar on the map as a credible tech company, and arguably, it paved the way for the lidar industry as we know it today. Iris, on the other hand, took a little too over 2 years to get to that same stage, and it was launched in 2021. Won several customers, as Austin showed, and established itself as the first volume product designed for automotive. Its slim design, also what Austin showed, basically, and the performance coupled with it, raised a lot of eyebrows in the industry. As you know, and we already talked about this, we launched our first vehicle with Shanghai Auto in China last year. Now we're proud to announce that with Iris+, we accelerated our development pace by more than 2 times. We not only improved our execution, our rate of improvement doubled. Went from 28%, from 36 months to 26 months from Hydra to Iris, to 58%, 26 to 11 months. We accelerated. We accelerated big time. Execution is everything in automotive. 100,000 parts in automotive come together to have one SOP. You cannot be late. Otherwise, all of that massive in R&D basically gets wasted. Execution is critical. With that, I think we're now in the top class of top tech companies in terms of velocity of innovation and execution. Let me show how we did it. We kicked off Iris+ in March of last year. In one month, we had the mechanical design locked up by working very closely with our lead customer. Next month, the development picked up speed with the electrical design and thermal analysis. In June, we already had modeled it incredibly intensely and stress tested it with something called FEA, Finite Element Analysis. Basically, bunch of differential equations and complex math to solve. In August, we had already built the receiver modules. This is incredibly important. Receiver module in lidar is one of the critical subsystems that determine the performance of the product. Mike and Jason showed you some of the building blocks of that. We were able to build this incredibly complex, super critical system fast because we had the entire semiconductor chip designed and developed in-house. We would not have built this fast if we didn't have this capability in LSI in-house. It typically takes at least 1 year to get a new product from a semiconductor provider. When you get it's not exactly what you want. It's essentially the least common denominator of what the entire industry of customers want. I know this because I was on the other side of the table. Now I get to sit on both sides, semiconductor and systems. I think Luminar has a huge advantage because of that. In September, we had the first transceiver, which includes a very complex laser subsystem. In October, we had the first engineering sample in our hands. In seven months, a record for Luminar. In November, we had the first point cloud out of Iris+. I remember that day really well. The feeling was basically, you know, similar to having your baby speak for the first time. I think Iris+ said, "Marco," our vice president of engineering. That took 8 months from inception. Another record. At the beginning of January, we had the first fully assembled B-sample of Iris+. It was built in Orlando in our automated pilot assembly line. Yes, we even automated our pilot line. Thank you, Debbie and Jeff. Here we are today, ranging in our state-of-the-art test facility and producing a beautiful point cloud that I think you guys will see later today. Iris+ right now is not only speaking words, but it's now telling us a story, a story of what it sees around it, like a baby would do. It's quite a rewarding feeling. All in 11 months, from inception to today. I am incredibly proud of our team. Ladies and gentlemen, this is Iris+, world's highest performing automotive-grade lidar with largest order book. It's built to scale, built to outperform, and built to lead the industry, all in record time. We're not stopping there. Austin mentioned this. Recently, we have acquired the lidar team of Seagate. Yep, Seagate. You might be thinking, like, "What does Seagate have to do with lidar?" Of course, Austin mentioned some of that. Seagate is the largest producer of hard drives. Hard drives are optical devices. They go into data centers that all have 24/7 incredible... They have to operate incredibly reliably without major hiccups all the time. Reliability in data centers is one of the most critical things to achieve, and Seagate, I believe, nailed it by building highly reliable optical systems in tens of millions of units every year. Does that sound familiar? Yep, you got it. lidar is also incredibly complex optical system. Has to be built reliably so it can perform the ultra stringent automotive reliability requirements. You wouldn't have guessed. There's a lot of parallel. When we first saw the opportunity at Seagate, I mean, literally as a company, we pounced at it. I've never seen a company this excited on any acquisition. One unified company. What I show here, and as you can see here, there's tremendous amount of commonalities between highly reliable and highly scalable optical hard drives and lidar. We believe we can leverage about 80% of the know-how in building hard drives to lidar. Our partnership with Seagate is not only that, it expands to supply chain and manufacturing and leveraging all of their expertise in that regard as well. This, in my opinion, is immense. We're incredibly delighted to welcome the Seagate team to our home and leverage their R&D and manufacturing expertise to accelerate our ambitions in lidar for the automotive industry. Welcome home, Seagate team. How do you build products that can scale fast and delight the customers at the same time? The answer, I work with a lot of companies, many people here work in a lot of companies, the answer lies in platformization. If you look at any company that has scaled its products to tens or even hundreds of millions of units, whether it's Apple, NVIDIA, or even Mercedes or Volvo, you'll see that their development is always based on platforms. Platforms allow for rapid development. Platforms allow for tailoring to all customers' needs without the full-scale customization. Platforms create immense leverage on R&D, which can be rinsed and repeated over generations of products. It's often how well a company has platformized its development is what determines its ultimate success. At the core of platformization is modularity. We create modules of technology, each of which can be innovated on its own, at its own pace, its own constraints, and often leveraging different parts of the industries. Take, for instance, the receiver module. The receivers we use are all built in-house in LSI at a rapid pace, fitting exactly to our needs. In our history of innovation in APDs, the avalanche photodiodes, which are the detectors, is a testament to the power of modular detectors. Our APDs have never failed in the field, and we have supplied to lots of mission-critical applications like military and aerospace. Emitter, on the other hand, I believe is another subsystem that I think we haven't even, you know, scratched the surface in terms of innovation. We're on a rapid path to increase both the performance and the cost, and lower the cost at the same time in lasers. I would say you haven't seen anything yet. Stay tuned till you see the next generation of lasers that we're building at the moment. You will be blown away. Processor complex we have is also highly specialized, and we build our own ASICs in-house again in LSI. We have, again, a massive runway in innovation in ASICs ahead of us. Modularity and platformization is absolutely key to scaling and winning multiple designs, and that's exactly what we're doing. Again, here is the proof of that. We have racked up eight top-tier OEM design wins to date with the same Iris family spanning across more than 20 production vehicle models. That's because of its platform design. Because it was designed as a platform, same family of products were able to garner millions of units in design wins, which in dollar terms equates to $ billions of revenues over lifetime. You heard about our announcement with Mercedes last week. That announcement basically was about increasing the breadth of our products adoption across Mercedes to a wide range of vehicles, amounting to, again, just in itself, $ billions in revenues from a single company, from a single product line. That's the power of platformization. The other key point I wanna make is this: just as platformizing our own products is important, so is partnering with highly successful platform companies. That's NVIDIA, that's Qualcomm, that's Mobileye. Each of these companies have platforms on their own, and we're delighted to be part of their platform. Say, for instance, NVIDIA, we're thrilled to be part of their Hyperion platform as an exclusive partner to them in lidar. Mobileye is a clear leader in ADAS based on cameras, and we're delighted to be partnering with them in their MaaS or Mobility as a Service initiative. Mobileye happens to benefit from lidar in urban and other ODD environments like operational design domains. Qualcomm is our newest partner, as they have announced at CES as part of their Snapdragon Ride platform. We're super excited to be working with the world's best of the best in computing platforms. Next, I'll turn it over to Gary, an old friend of mine from NVIDIA, to say a few words about our partnership. Hello, I'm Gary Hicok, Senior Vice President of Automotive at NVIDIA. Luminar is a highly valued automotive ecosystem partner for NVIDIA. We've been working closely together since 2018. As safety is our highest priority in developing autonomous vehicles, NVIDIA has long recognized that lidar is an important component of a diverse and redundant sensor suite, and helps us create a robust autonomous vehicle perception system. Our collaboration with Luminar enables us to integrate best-in-class technologies for autonomous driving functions. NVIDIA DRIVE is a high-performance open platform designed for the entire transportation industry to build automated and autonomous vehicles, from passenger cars to commercial trucks, to robotaxis, and to shuttles. At the core, our fully programmable AI supercomputer gives OEMs and tier ones the flexibility to select the best and most cost-effective sensor solutions for their unique needs. NVIDIA DRIVE Sim software tools uniquely enable the physically accurate simulation of sensors, their positions on the vehicle, and then allow runtime real-time perception algorithms to ensure the system will perform safely in the real world. In 2021, NVIDIA announced that we had selected Luminar's Iris long-range lidar solution as part of the sensor suite for our NVIDIA DRIVE Hyperion 8 autonomous vehicle development platform and reference architecture. This forward-facing long-range lidar will be used in DRIVE Hyperion's Level 3 highway driving configuration. We believe Luminar offers a unique scalable solution that complements DRIVE Hyperion, which is accelerating the development of autonomous vehicles around the world. Offering automakers a qualified, complete sensor suite coupled with NVIDIA's centralized high-performance compute and AI software, DRIVE Hyperion provides everything needed to develop production autonomous vehicles. We applaud Luminar's effort in bringing to market cutting-edge lidar solutions that meet the stringent performance, safety, security, and automotive-grade requirements for the autonomous vehicle industry. Thank you. Well, thank you, Gary. We're obviously absolutely thrilled to be partnering with you, and I cannot wait to innovate with you together at Luminar at the speed of light, and he knows exactly what I mean. I've talked a lot about how we think do things at Luminar, but not so much about the architecture of what we're building. As I mentioned, architecture is incredibly key to the success of the products that are built on that architecture. Good architectures allow for scale. Bad architectures waste a lot of valuable R&D dollars because they cause major misses in the mass market sometimes. Good architectures delight customers because they perform the best. They are built for reliability and are easy to build. Good architectures are simple. Bad architectures are complex and cannot easily scale. Elegant architectures are the ones that are both simple and high-performing. Simple and high-performing. That's exactly, I believe, what we have. That is, my hats off, Austin's brainchild. Someone that devoted all of his life to photonics. Much so that he didn't even wanna waste time at Stanford. When you're building an elegant architecture, you first have to start with the ingredients or the building blocks. Ingredient selection is absolutely key because building a highly scalable, highly reliable architecture is absolutely important. Those are the... These five are the core elements of building a world-class architecture. Everything you see here in blue is built internally at Luminar. Why is that important? Because with this, we can not only build a product the way we want, but we can build the building blocks of the architecture the way we want, at the pace we want. That's the power of vertical innovation. That power in ingredient selection results in this elegant architecture. On the right is our elegant, wonderfully elegant architecture. It's simple, yet hugely powerful. That's the reason we're winning. On the left is all of our competitors' architectures. Some of them already in the graveyard. Wrong architectures can be, unfortunately, very unforgiving. Ask that to all the lidar companies that folded in the last 12 months. Let me mention one more thing about this 1550 versus 905 debate. I bought a company in my old company that built 905 technology, and we marketed and sold our products to practically everyone but Luminar in the lidar industry, including Innoviz and SI. I know what 905 can do and what 905 cannot do. In that case, I was focused on short range and manned robotics. The nuance is the architecture. 905 needs arrays. In fact, the detectors themselves are a bunch of detectors clustered together like SiPMs, silicon photomultipliers. Arrays mean cost. It's now getting basically in the order of hundreds of these to build a good 905 detector. In our architecture, we use a few, usually 1 or 2 detectors. Even if the III-V semiconductor material is a bit more costly in wafer terms, we use orders of magnitude less wafers. The cost of 1550, regardless of what they tell you, doesn't matter. As Jason mentioned before, I think it's practically in the order of single-digit dollars. Single-digit dollars for us. That's the fallacy of 905 argument. What's more, 905 cannot give you the range that 1550 can. Here's the proof. That's why people are buying our product. Both performance and cost scale better with 1550. The icing on the cake, 1550 happens to be more eye safe. I wanna wrap up my talk with arguably the most important thing about building products for automotive, and that has to do with building these products for an industry that has seen it all in terms of companies that came and went. Companies that struggle to build shareholder return because they struggle to build highly reliable products. We know them all. We take being automotive-grade to the heart. We pour our hearts and souls into designing something that can last for the lifespan of vehicles. Products that can tolerate harsh environments from extreme temperatures to harsh vibration requirements, and to all sorts of other severe operating modes. Some of you may not be familiar with what it means to be automotive-grade. The acronyms I show here are only some of the things that you have to do to be called automotive-grade. Just take a look at the soup of alphabets. That's why many startups cannot survive and cross the chasm, as the great old author Geoffrey Moore put it once. We did it. As you can see, being automotive touches every single stage of development, from concept to serious production and beyond. Many companies fall into the chasm somewhere in the middle, and successful companies not only cross the chasm, but understand the power of iteration to get it just perfect, especially from development to spec. Happens to be the area that people just fall. We did exactly that with Iris and Iris+, and crossed the chasm, iterated rapidly, and brought the company to where it is right now. Building products and great products is just not easy. There are many facets of perfecting that art, but one last thing in that regard that I want to leave you with is testing. Testing is pivotal to any product success. The more you test, the better you test, the more success you have in the marketplace. It's that simple. We built what we believe to be the world's largest, most advanced facility for testing. It's over 300 meters long with up to 500 meters of total ranging capability. lidar is a sensor you measure and reconstruct the world in terms of photon by photon, which are elements of light that each travel at 300 million meters per second. Our testing facility had to be so advanced that we could measure these deviations from this insane level of precision needed to build a great product. It's truly mind-blowing to see what we do and how we do it. Finally, I would like to thank our entire employees for building these great products, delighting our customers, and building a great company along the way. Our talent, in my opinion, this is why I'm so excited about this company, is unmatched in terms of skills, breadth of experience, level of passion, and just sheer intellect. We have the best of both worlds, as Austin mentioned. We have about half of our company pure, from pure tech background and the other half from automotive. A perfect blend for a great journey. I can't wait to build many great new products that will change the automotive industry, help save lives, and bring more comfort to our travels. With that, I'd like to say thank you and hand it over to my colleague, Debbie Pappas, Vice President of Manufacturing Operations. All right. Thank you, Tanner. Good afternoon. Hopefully, all of you are feeling the energy now. As has been talked about all afternoon, Luminar's lidar is recognized as industry-leading. What does it take to constantly design and build premium quality lidars at scale? It's an approach to quality that touches everything we do. In this session, we'll take you through our efforts to successfully industrialize and scale our manufacturing capabilities to serve global automakers whose rising demands are placing pressure for near perfection in every aspect of our business. In the automotive industry, exceptional quality performance is one of those rising demands. There are three keys to our automotive quality approach at Luminar: advancing industry standards, commitment to quality, and implementing key quality initiatives. We are leading the industry to raise the bar for safety and autonomy and engaging with industry standards organizations. Luminar's business system aligns to proven automotive best practices captured by Automotive Quality Management Standard, better known as IATF 16949. Was released by the International Automotive Task Force Group. I was a board member of the AIAG organization, which is one of those members. It's a U.S. trade association that's tied to that task force. Luminar has also been assessed by a high-end German OEM against the VDA 6.3 Standard, and received favorable feedback on addressing the observations that were noted during that assessment. Not only do these standards they're required by our customers, compliance delivers improved business performance. Luminar is driven to secure an automotive certified business and supply chain. Our quality management system consists of five main components. Design quality, as Tanner shared with you, ensures that we design for reliability, manufacturability, and assembly. Product validation confirms that our lidars meet the demand of our customers' applications. Built-in quality is the commitment our advanced manufacturing engineers and contract manufacturers make to build consistently flawless lidars every day by leveraging technology and error prevention. Supplier quality maintains alignment with Luminar's design requirements and our quality expectations. Continuous improvement is a cornerstone of our commitment to quality as we drive robust problem-solving to improve performance, also efficiency and productivity. Luminar is investing to scale our quality management systems and our processes while embracing zero defect strategies and advancing an automotive quality mindset throughout the organization. These strategies are translated to our entire supply base. You will see shortly a video demonstration of built-in quality in Luminar's high volume assembly and manufacturing lines at our contract manufacturers. A tour later today of Luminar's long-range test facility illustrates our product validation approach to ensure lidar performance excellence. Luminar works closely with our supplier partners to ensure that our products are the highest quality and most efficient to manufacture. A successful Luminar supplier meets the criteria shown on this chart. Beginning at the top left, the willingness to invest their business for growth, quality, and technology leadership. Demonstrated quality leadership across industries, but in particular, automotive. Product and process innovation is key. A Luminar supplier is expected to deliver required quality product at the lowest cost. 75% of our purchases are covered by long-term partnerships that provide suppliers incentives to continually invest in their business. Our suppliers meet our global product requirements and serve our production and distribution needs locally. As of today, we have 89 suppliers in 16 countries that have demonstrated ability to scale and are automotive grade capable, which ensures our customers are receiving the best quality product at the right time and at the most competitive cost. Global supplier management operation is deployed everywhere our supply base is located, which ensures quality and delivery expectations are maintained. Our contract manufacturing partners are an extension of Luminar, assisting us actively by managing much of the extended supply base. As you heard from Jason and Mike, the strategic acquisition of the LSI businesses assures we have the most critical lidar components secured. We are aggressively looking to expand our ability to directly control all aspects of our supply chain. Our automotive customers require ISO and IATF certifications that span business processes, including purchasing, product design, validation, and manufacturing. That translates to our suppliers. As we have progressed from an R&D tech-focused company to an automotive tier one supplier, we have seen that transition reflected in the quality of our supplier partners. Over the last five years, we have progressed from a mix of 80% ISO only and 20% IATF ISO certified suppliers to 2% ISO and 98% IATF ISO. The objective is to continue to drive that number to 100%. In addition to our suppliers, Luminar expects to be fully certified later this year. Our industrials journey has been underway since 2016. Focused first on expanding our Orlando pilot line to keep up with customer demand for samples and at the same time producing sensors for our design validation. Low volume equipment is installed at our contract manufacturers, Celestica in Mexico and Fabrinet in Thailand. Since late last year, volumes have been ramping up. We completed all customer low volume run at rate checks at our shared Celestica facility. As been mentioned, we started production for SAIC's Rising Auto R7. We are focused on the next phase of industrialization with our dedicated partners as we prepare for scale and additional customer launches. Luminar is on track to have our dedicated high volume facilities online in 2023. Jeff Gisel, our VP of manufacturing, will now take you on that scaling journey. Thank you. Thank you, Deb. Good afternoon to everybody. Ever since I was a little kid schlepping around my bucket of LEGO, I have absolutely loved to build stuff. Some say that was just last week, but that's a lie. Here at Luminar, with a management team and founders that conceived of a vision and assembled a management team for a noble vision, with a great best-in-class product and customers that keep wanting to add zeros to their volume expectations, it's a great place to build stuff. I'm super excited about what we have in front of us. To start off with, I'd like to show our a little bit more detail on our automated line that we're pleased to report is coming in ahead of what the previous guidance was and is now expected to be online in the second quarter of this year. Here you can see a small segment of the lines. The line is built on a modular flexible architecture, so it's easy to be able to change and adapt to the changing product requirements, changing volume requirements. It actually comes for the Iris version in 5 sections. There's 5 separate sub-assemblies that all culminate in the final build of that product. 4 out of those 5 lines are not only installed, but have passed in conjunction with our customer, all the requirements necessary to get qualified for the site acceptance. By the end of March, the fifth segment will be also qualified in conjunction with our customer. By the second quarter, we will be able to complete all the remaining qualifications necessary and be able to produce our first sensor at this high volume facility. It's highly automated. Each step in that has multiple types of quality checks, whether it be two-dimensional camera vision systems, three-dimensional camera vision systems, which you can see there, and a variety of sensors in that. Almost every step is error-proof to make sure that we have a reliable product at the end. That line, as you see it, is capable of 250,000 units per year. At the end of 2023, there'll be after we make the first sensor, there'll be some ramp-up curve as we get everyone trained and ramp up the line. By year-end, 250,000 a year will be the run rate. With a modest investment, it can be scaled to a half a million sensors per year. Obviously, we have to scale up the transceiver as well in Thailand to keep pace. We have our partner in Celestica doing the final assembly and the final test and calibration being supplied by the transceiver and optical components out of Thailand. Here's some video of a brand-new dedicated facility which we're in the process of launching now. This facility is designed to be able to keep pace with the facility that we have down in Mexico. All the transceiver, the polygon balancing, is all coming out of the Thailand operation. Everything for the build-up. This is really just the beginning. The next generation Iris+, as Tanner alluded to, is gonna set the stage for an even easier route to our scalability goals. In conjunction with engineering, we've worked hard to make the Iris+ even more efficient to manufacture. We put in a pilot line in Orlando just to test proof of concept for what we thought we could do from an assembly. We've already been able to prove out with that line that the next generation will take almost one-third, or will be one-third of, not one-third less, one-third of the floor space required for the Iris and roughly one-third the labor as well. Beyond the Iris, the work that we're setting the stage for with the, in conjunction with the Seagate acquisition will take us to another whole level of momentum as we start to our journey in scalability. Obviously, our customers are global, so we have to be global as well. The sites where we actually are related to the operation and the manufacturing, we've got our Minnesota and our Florida sites. This is where we'll do a lot of the development and basic process work that we have to do to prove out before we go to high volume. We'll also do some prototype builds out of Minnesota and Florida. Mexico is concentrating on Iris, final assembly and the test. Thailand is, again, where we get most of our transceiver and optical components from. We're happy to say that the next footprint, the site that we're looking for now will be planned in Asia. In Asia, we're looking to install another 500,000 units per year. In summary, we've got the process resources to be able to develop the core technologies that we need to scale in Minnesota and Florida. We're already in series production, learning every day with the products that we have. We're already ahead of guidance in that on our first high volume ramp-up, and we're well-positioned with an increasingly efficient design architecture to further facilitate that scale and expansion into Asia. With that, I think we'll pass it on to Tom. Please welcome CFO of Luminar, Tom Fennimore. All right, everyone. We're in the home stretch here on the final presentation for the day. I plan to cover three topics. First, I'm gonna talk about our China business and strategy. Second, I'm gonna go into a bit more detail about our new insurance product and business. Finally, I'll close with the discussion of the numbers, both our results in 2022, our 2023 guidance and milestones, and our updated medium and longer-term financial targets. All right, let's start by discussing China. China is near and dear to my heart. I spent three years living in Beijing last decade covering the automotive industry. My wife and I started our family there. We raised our first son in his formative years there. After I left China, I would go there multiple times a year until COVID. I know that industry relatively well for a foreigner, have a lot of the relationships there today. China is a very important market for Luminar. We wanna continue to be a winner in China. We wanna grow and be successful in China. We wanna be a winner in China, we need to have a thoughtful strategy to execute. Let me walk you through what we did in 2022, despite a lot of challenges, including travel restrictions preventing us from getting there. Last year, we made significant progress in building the foundation of our China business. We hired Jackie Chen to run our business. He used to run Harman's China business and Schaeffler's China business. He's a very dynamic leader, who not only understands the local China industry very well, but he knows how to operate within a multinational company to deliver at China speed, which is very important. We have formed our own legal entity in China. We're building out our headquarters in Shanghai. We're building out a local team, primary engineers, to support our local customers and vehicle deployment. Finally, as we discussed last year, we reached our first SOP with the Rising Auto R7 brand at the tail end of last year. Not bad for not being able to go over there. Before I go into more details of what our strategy is, I wanna spend a second taking a deeper dive into the China market. Last year, in 2022, there were over 20 million vehicles sold in China. Approximately half of them were foreign brand names. What do I mean by that? That's Volvo, Mercedes, Nissan, selling vehicles in China, primarily through their JV partners, but with their brands. The other half is local China brands, if you actually take a deeper dive into that, about 3.5 million vehicles, the fastest-growing segment, are new electric vehicles. That number has increased five times in two years. It's rapidly growing. It is important in that EV segment to be viewed as a technology leader, we see those type of companies as the ones that wanna adopt lidar technology the fastest. If you take a deeper dive into that 3.5 million, we also look at the price point where our technology, which is the best, we believe, in the China market, but maybe not necessarily the most, the cheapest, where it makes sense for us to focus on that. If you actually look at vehicles priced 250,000 RMB or above, which is about low to mid $40,000, depending upon where the exchange rate is, that's about a third of that $3.5 million, that is our focus area. When you take the foreign-branded vehicles, which we're gonna have natural exposure to from our global relationships and our global progress, plus that, call it, top tier of that new EV brand, that's nearly 60% of the market that we believe is gonna be very addressable for us. Let me go in a little bit more detail on our China strategy. We talked about the focus customer strategy, the first two I discussed on the previous side. We're also focused on the commercial trucking space, are making some progress there as well with that customer base. Second, we wanna continue to expand our China footprint. We're gonna accelerate our growth of the local engineering team there. You need to build out the right software and data structure in China to comply with local regulations, and we're starting to do that. As Jeff Gisel and Debbie Pappas talked about, we're looking to establish our Asia manufacturing capabilities there to help serve the China market. Finally, we can't be successful in China on our own or as successful. We wanna work with the right strategic partners. I'm gonna go into more detail in a bit on two of them, Pony.ai, who's an autonomous leader in the China and the global landscape, and then ECARX, which really helps the Geely family of vehicles develop new technology. We have strategic partnerships in place with them. We're gonna explore other potential partnerships as well to help us grow in China and do so in a smart way. I'm gonna go in a little bit more detail on our relationship with Pony. Last year, we expanded our partnership with Pony. As I mentioned, they're a leader in the China autonomous vehicle market, as well as globally. We will be their long-range lidar supplier for their next generation of vehicles with an expected SOP somewhere around 2025. In addition, we extended our partnership to include the commercial vehicle market, as well as additional software and development support. I'm gonna have here's a video from Pony CEO, James Peng, to talk more about Pony and the relationship with Luminar. Hello everyone. I'm James Peng, Founder and the CEO of Pony.ai. The vision of Pony.ai is to build a safe and reliable autonomous driving solutions and delivering it at a global scale. Since very early on, we view lidar as an essential sensor for our autonomous driving vehicles, because lidar has the capability to view the surrounding world in 3D with great precision. From very early on, we have worked with Luminar to use Luminar lidars as an essential part of our autonomous driving solutions. Over the years, we have really enjoyed a tremendous growth in all aspects of our business. We have launched a full driverless autonomous driving vehicles in both Beijing and Guangzhou. This is the first time we have seen fully autonomous driving vehicles navigating the complex traffic scenarios in major cities in China. Besides the robotaxi, we are also working on robo-truck and licensing our technology to the OEMs to really make the mobility to be much safer. We were fortunate to have Luminar as our partner over the years, and we have worked together on many aspects of our solution. We really view the scalable and reliable lidar solution that Luminar provided to us can help us to make the system even safer. Our hope is that with an even deepened collaboration between Pony and Luminar, we'll be able to build our next generation solution that really empowers a very large scaled autonomous driving trucks. I hope that our partnership can result in even greater things down the road. Thank you. Great. Thank you, James. Last year, we also entered into a strategic partnership with ECARX, a key technology provider to the Geely ecosystem in China. We are working together to jointly develop an ADAS and autonomous turnkey solution, specifically designed for the local China market that utilizes our lidar and other technologies. Here is Ziyu Shen, ECARX CEO, to talk more about ECARX and its partnership with Luminar. Hi, I'm Ziyu Shen, Chairman and CEO of ECARX. We are a global mobility tech provider that partners with OEMs and technology leaders to reshaped automotive landscape as the industry transitions to an all-electrical future. We are developing a full-stack solution, central computer, System-on-Chip, and software to help continuously improve the in-car user experience and advance the development of new connected automated cars. The ecosystem of partners we work with is extremely important to the delivery of our end goal, transforming cars into fully integrated information, communication, and transportation devices. ECARX and the Luminar partnership began in May last year, when Luminar made a strategic investment into ECARX as part of our Nasdaq listing. At the time, we committed to work together on automotive grade technologies, with aim of enabling advanced safety and automated driving capabilities. Luminar is a true innovator, bringing new technology vital for the deployment of safe, automated highway driving to the global industry. By partnering with Luminar and other tech leaders, ECARX wants to develop a cooperative ecosystem that accelerates the transition to smart mobility. By integrating Luminar's long-range lidar and software with ECARX suite of automotive intelligence products, automakers in China and internationally will have a clear path to deploy advanced safety technologies and driving capabilities on serious production vehicles. Great. Thank you, Ziyu. We're excited to work with you and develop this product together for the local China market. I will now transition to talk a little bit more about our Luminar Insurance product and strategy. Austin talked at the beginning of his presentation about how our technology is gonna significantly improve vehicle safety, and how that is gonna result in what we believe are gonna be very meaningful insurance savings. As you can see from here, 80% of forward collisions fall into three categories that we think our technology is going to directly reduce, mitigate, or even eliminate these type of insurance or these type of collision scenarios. We also anticipate that the traditional insurance companies are gonna be very slow to adjust their pricing to reflect the improvements that our technology brings. As a result, we want to be in a position after studying this problem, looking at what others have done in the industry, how we think the traditional insurance companies are gonna behave, of putting our money where our mouth is in building our own insurance business to capture and underwrite these savings to help subsidize the cost of our technology, including driving standardization across vehicle lines as opposed to having it as an option. If we're not willing to bet on our technology, why should anybody else? Our technology is gonna create these insurance savings. If we don't do anything in our OEM partners, the traditional insurance companies are gonna capture those savings instead of the people providing the value. Let me try to frame what the opportunity here. As Austin mentioned, the average vehicle insurance premium in the U.S. is about $1,750 a year. If we're able to get 20% insurance savings, which we believe could be a conservative number, that's about $350 a year, almost $2,000 over 6 years. That's almost twice the price of our current Iris lidar. How are we gonna do this? Our plan is to build a scalable and asset-light insurance product that we can partner with our OEMs with and make it scalable to work with multiple OEM partners. We also wanna build the flexibility to go directly to the consumer and the purchaser of our vehicle. This insurance product we want to offer significant discounts to consumers who purchase vehicles with our technology to encourage the purchase if it's standard or the option selection if it's an option. We plan to do this by building our own digital insurance MGA to operate the business and our own insurance captive to manage the risk. We intend to obtain reinsurance protection to mitigate the risk. We will use reputable third-party operating partners who. There's about several industry leaders and a technology platform, this has been done before, to minimize the investment, enhance scalability, and allow us to build this quickly without applying a lot of capital to it. Our initial target markets are the passenger vehicle markets and commercial truck markets in the U.S., but we will hope to scale this over time globally. We expect to have our initial insurance product ready to go in 2024 in select U.S. states. Why are we confident we can do this? We hired Alex T, who did this at Tesla. He's the person who built Tesla's insurance platform. He's gonna oversee the construction and industrialization and launch of our insurance product. He knows how to do this well. He knows how to do this quickly. He knows how to do this digitally. He knows how to leverage technology and third-party partners to do this in a very asset-light and scalable way. As Matt Austin mentioned earlier, we are also partnering with Swiss Re, a leader in the global reinsurance industry. Swiss Re is working with us to both test our technology on real-life vehicles to help quantify the safety improvements and insurance savings and helping to bring our insurance business to life. We also intend to work with Swiss Re to build our insurance pricing algorithms and to participate in the insurance risk. Here is Russell Higginbotham, the CEO of Swiss Re Solutions, to share more about our partnership. Hi, everyone. I'm Russell Higginbotham. I'm the CEO of Swiss Re's Solutions division. Swiss Re, you may or may not have heard of us, we're a 160-year-old company. We're active in all of the lines of business of insurance around the world and in all the major markets in the world. Our Solutions division is actually where we try to bring all the knowledge we've gained over the many years to our market. Let me tell you, we're excited about our partnership with Luminar. We're excited to partner with them and to work with their life-saving technology to bring safer driving to the world. Mobility is clearly becoming more and more autonomous, and that means that some risks associated with mobility go away, but others, new ones, they appear. These new risks need to be understood and assessed. This is what we do. We capture real data around the advancements and around driving behavior and around the conditions of driving. Actually, then we translate those into risk assets and risk insights. Ultimately, what we do is help insurers around the world understand the risks and help them price the risks, which is ultimately what insurance is all about. What we're specifically gonna be doing is assessing the safety capabilities of Luminar's lidar sensor technology and actually working out how it works in reality, how it prevents and how it mitigates risk. As I said before, we translate that into risk scores. This offers a, as well as helping the insurers, this offers a feedback loop to the engineers at Luminar as it's a continuous learning process around driver behavior and the conditions around driving. At Swiss Re, we're excited about this partnership with Luminar. I think it makes their excellent technology more viable. It makes it more commercial in the real world. It clearly enhances road safety, and it makes insurance more affordable. I think ultimately, that makes the world more resilient, and I think if you bring all those things together, we would all say that that can't be bad. Great. All right. Now on to the final topic, the financial section. Let's start off, we talked about this at CES. We met or beat our 4 key public milestones last year. We reached series production with Iris at SAIC. We made great progress on our Sentinel software suite. We ended the year, as Austin mentioned, with over 20 awarded program lines. We talked about Polestar earlier this month. We talked about Mercedes last week. You know, we introduced Scale this week. We ended the year with an order book size of $3.4 billion. Talk more about that in a second. Here's a summary of our results for Q4 and full year in 2022. We recorded $11.1 million in revenue during the quarter and $40.7 million for the year. Both of these were in the range, but out the lower end of our guidance. The reason for that was primarily due to the timing of our NRE revenue recognition. Of the $40.7 million in fiscal year 2022, a lot of that was program development revenue, which, you know, is NRE related, which was, you know, a portion, you know, that kind of drove that timing risk. We had a GAAP EPS loss of $0.40 and a non-GAAP loss of $0.26 in Q4. This was slightly higher than expectations as we accelerated investments in industrialization and future product development. As you can see, we got a lot going on at Luminar. We're not only launching Volvo with Iris, now Mercedes with Iris+. We have more business. We're investing in our future product line. The growth is there. We are focused on the long-term value creation, even if it's at the expense of spending a little bit more in the near term. We ended the year with $489 million of cash. Cash spend was higher sequentially, primarily for the same reasons our EPS was higher. We expect our quarterly cash spend to decline as our new dedicated Mexico facility starts to ramp up in the second half of this year. Now let's talk about our 2023 milestones and financial guidance. We are laser-focused on execution in 2023. While we have a lot of milestones here at Luminar for the year, there are three that are the most critical. First, we need to scale up our series production. That means bringing our high volume automated facility in Mexico online and meeting Volvo's SOP requirements. Our second milestone is to keep advancing our technology and product roadmap. Specifically, we expect by the end of this year to enter the seed phase for Iris+. We wanna develop a prototype of our next generation lidar that the team spoke about earlier, and we wanna complete the necessary base software for the Volvo and Mercedes SOP. Our third milestone is to continue to grow our business, and we wanna grow our order book by at least $1 billion this year. Now let's turn to 2023 financial guidance. We expect to at least double our revenue this year. We expect the revenue to ramp as we go through the year and really step up once we get our new Mexico line up and running, so it will be a little back-end weighted. We expect Q1 revenue to be in the range of, call it, $11 million-$13 million, and EPS for the quarter to be roughly in line with what we saw the last quarter or two. We expect to be non-GAAP gross margin positive by Q4 as we launch our new facility, increase production there and lower sensor contribution cost. We expect to have at least $300 million in cash and liquidity at the end of the year. We expect that 2022 was our peak cash spend year, and our quarterly cash spend rate should begin to improve in the second half of this year as our new facility ramp up and our launch costs associated with it ramp down. Finally, I would expect our share count at the end of the year to be in the 395 million-400 million range. Now let's talk a little bit in more detail about our forward-looking order book. As a reminder, we tend to be conservative on how we calculate this. Not only do we only include customers that we won in here, as defined by them giving us a series production program or equivalent and having that memorialized in a signed agreement, but for those won customers, we only include the vehicle lines that they have officially awarded to us. While we're talking to them about their future product roadmaps and are confident we're gonna be on more and more business, look at what we've done with Volvo, Polestar, and Mercedes over the last year or so as a track record of our ability to grow with our customers. We don't include any vehicle lines in this order book until it is officially awarded to us. For those awarded vehicle lines, we use IHS assumptions for volume when available, contracted pricing, and conservative management judgments if they're not available. Based upon that conservative calculations, we ended the 2022, as I talked about, with a $3.4 billion order book. We expect it to grow at least $1 billion this year. I'm gonna transition now to talk about our updated midterm and longer-term guidance. You know, I apologize for the financial modeling experts in this room. This may be a little too basic, but, you know, I think it's a good overview of how we updated our longer-term model and how it help everyone think about how our business is gonna grow. The foundation of our longer-term model and our growth is the number of Luminar-equipped vehicles sold. That translates roughly into sensors sold, maybe a little bit off if there's multiple sensors on a vehicle, but I think you get the point. There's three components of that. One are the awarded programs. That's our order book. The order book goes from potential revenue to actual revenue when each of those vehicle lines reaches SOP. The second bucket is the additional programs at existing customers. As I said, we have a track record of growing with our existing customers. If the vehicle line is officially awarded, it's in the previous box. If we're in there talking to them and have good visibility on when they're gonna put our technology on their next vehicle programs, we put them in there probability weighted, adjusted in terms of, you know, we take a haircut to it because it's not won yet. Finally, there's new customers. These are the customers that we haven't officially won yet. We're not done winning. We're talking to a lot of other people out there. When we have something ready to announce, we'll announce it. We have a portion of non-won customers yet in our volume projection. We'll try to quantify that there in a second. Needless to say, we're talking to a lot of people, a lot of great conversations there. Okay, that's volume. Pricing. What's my revenue per Luminar-equipped vehicle? Well, I got, call it the hardware and base software ASP. We're, you know, we're moving to an integrated approach. I talked before about how the base software for Volvo and Mercedes needs to be ready to go. What we're seeing now is our customers are asking us to put more software capabilities into our base lidar. We're kind of including that for the time being in, you know, all the hardware category, there is, you know, a good element of software-enabled capabilities that are in the base hardware that we sell. I wanna talk about this software and solutions content per vehicle. What is that? That is additional functionality from our Sentinel software suite. We talked about HD mapping. We talked about insurance. I kind of think about that as the net insurance profit, so, you know, there's gonna be revenue risk. I just said, "Okay, let's just kinda put the profit in there." This is take rate adjusted. As much as I would like this to be on every vehicle, you know, the content per vehicle here is measured in the thousands of dollars. What we do is we take rate adjust it, and we'll kinda talk about what that take rate adjusted ASP is gonna be. This stuff, really, if you step back and think what we're doing, it's represented by the insurance business we're getting into as well as the mapping, but our lidar creates an ecosystem of value. You see it on the insurance. There, we're putting our money where our mouth is to help our customers and the consumer capture that value. Mapping, we're gonna be collecting all this rich data. You know, we talked about what we're doing with Scale. You know, that's an acquisition we made last year. We see that as an opportunity. If our technology's standard on each vehicle, when you upgrade the consumer to highway autonomy, that creates a lot of incremental profit. Some of this software and solutions content per vehicle will be up front, some of it will be subscription, and some of it, based upon the conversations, will be revenue sharing. Our lidar can create a lot of value in the ecosystem, and we wanna work collaboratively with our OEM partners to try to capture that value to help accelerate the adoption. That gets me to revenue. Let's look. Can we go back? I accidentally hit the button. Okay. Unit contribution costs. Okay, primarily looking at the cost of the sensor. There's the BOM, there's the manufacturing conversion cost, what Celestica, Fabrinet, and our future partners charge us. There's gonna be other variable costs, warranty, logistics. In the case of when we start selling the software and solution, there are gonna be some cost to services associated with that as well. Let's look at the other key items. There's gonna be my OpEx and other fixed costs. There's gonna be the CapEx and the investments I need to make to continue to grow. You know, we have this great new business that we're forming, Luminar Semiconductor. You know, B-Mike's been appointed to run that. These provide the core components to our lidar. Separately, we've asked Mike to go and grow that business. We see great opportunities there, but the lion's share of the growth in this model is coming from, you know, our core lidar and associated business. All right. Next year, I'm gonna spend a few minutes to talk about how our forward-looking order book starts to translate into annual volume and revenue. A key point I wanna leave you with is that we have the awarded business in place and the customers in place to support this massive scaling in our business. Sometime next year, once, you know, that Volvo business is up and running, as well as the other business we have, we're gonna reach that 100K+ rate, right? We're starting to, you know, ramp up. When are we gonna get to that 1 million mark, right? Cause, you know, 100,000’s one. Let's go in order of magnitude higher, that 1 million. Well, 70% of it, over 70% of that volume to get to 1 million, we already have awarded. Once again, I'm not talking about from customers, all of the customers we want, just the specific awarded programs. We're 70% of the way there. While we're gonna win new business between now and that timeframe, I don't need any new customers to get there. If I just take the programs we're actively talking to our existing customers with, we're gonna easily exceed that 1 million. The key to get there is going to be to continue to ramp up with Volvo and Polestar, win some incremental business there, launch this massive Mercedes win that we have, and then really move from the development stage with Nissan to the series production stage. I say that's gonna happen in 2026, 2027. Why am I being so imprecise on the time? Well, as Austin said, there's about 20 vehicle lines in there, and there's 20 SOPs. While Luminar can control us being ready, there's a lot of other things that could cause some uncertainty in the timing. Remember, what converts our order book from potential revenue to actual revenue is getting to SOP. This isn't easy building this stuff, let alone the lidar, let alone the other eco, you know, systems on the car to do that. You know, I don't wanna be too precise in the timing, but give you guys a general sense of when we're gonna get there, but we're absolutely confident we're gonna get there. Now let's go to 2030. 2030, we expect to be north of 5 million units. Just with our existing customers, the awarded business plus the stuff we're talking to them about, probability weighted, we're about 75% of the way there. I'm very confident we're gonna win additional customers to get us to that number, if not higher. Growth isn't gonna be done in 2030. That 5 million units is about 5% of the global vehicle build. When you step back and look at that, it's not that high of a number. I think Hesai put in their IPO document that they expect close to $50 million vehicles sold in 2030 with a lidar on it. I'd be very disappointed if we only had a 10% market share in 2030. We expect our order book by 2030 to give you a sense of how much growth is left to be close to $60 billion. Let's look at the unit economics roadmap. First, that revenue per Luminar-equipped vehicle. 2025 target. This is when the initial launch of Volvo should be fully up and running. Polestar there as well. We expect that average revenue per sensor sold to be about $1,000, it's gonna consist primarily of that hardware and base software ASP. As we get to 2030, this is when we wanna start to capture that additional value in the ecosystem, right? I still think we're gonna be at roughly that $1,000 revenue per sensor, take rate adjusted. The actual content per vehicle is much higher there. What we're gonna try to do is capture those software and solutions, monetize it, and use that to bring the cost of our lidar down to increase penetration. Let's look at the unit contribution cost. Our 2025 target, which is primarily the Iris family, we expect to be about $650. That's BOM, plus manufacturing costs, plus other COGS. By the time we get to 2030, we're gonna be in our next-gen sensor, and it's gonna primarily be the BOM and the manufacturing cost for that being sold, plus a little bit of cost of service for the software and solutions. We expect the BOM to be in that $350 range. All right, let's look at the OpEx and CapEx. All right, we ended 2022 with a non-GAAP OpEx of about $221 million. A lot of the infrastructure we need to put in place to grow our business is there today. In fact, there's a lot of what I would say launch costs and other stuff associated in that number now. We expect probably another 20% growth in that number in 2023 as we start to bring this stuff online. We expect that number to tail off a little bit in 2024 and be roughly flat, then from there, grow roughly 10%-20% per annum. CapEx, we spent about $50 million last year. You know, we're bringing up this new Mexico line, you know, investing in the automation equipment, building it out. This year we expect that number to be cut in about half, as we kind of finally bring it up and do the, you know, the remaining investments necessary to do that. Next year is when you're gonna see the lion's share of the investment necessary for this new Asia manufacturing facility. We learned a lot doing our first plant. We think that there's gonna be a lot of improvements for the second one, and so we expect the necessary CapEx investment to be in the $15 million-$20 million range. That's primarily gonna be in 2024. After that, you know, we're gonna learn even more. We're continuing to design our product not only for capability but for manufacturability. A rough rule of thumb is each 1 million unit of incremental capacity we need to add would be about an incremental $10 million of CapEx. All right, profitability roadmap. This year, by the end of this year, gross margin profitable. By the end of next year, core business break even. What do I mean by that? That's our core lidar and components business. If I wasn't making any investments in software, insurance solutions, etc., we believe that we can be profitable by then. We don't think that's the right thing to do. We're focused on longer term shareholder value creation. As a result, we're gonna get to profitability by the end of 2025. If you look at 2030, take the unit economics that I talked about on the previous page, the fact that a lot of our OpEx and CapEx is in there, we expect to have operating margins in the 35%-40% as we get to the end of this decade. All right, I wanna spend a couple moments talking about our M&A strategy. We talked about the Seagate lidar acquisition we did earlier this year. We did Freedom Photonics last year, as well as Civil Maps and OptoGration before. We wanna be positioned in this environment because we believe we're not only gonna be a survivor, but a thriver, and we wanna be able to act opportunistically. There are smaller companies that are struggling with their balance sheets and there are big corporations who no longer wanted to invest in the autonomous landscape. Our phone is ringing a lot with the opportunities. We're gonna say no to the vast majority of opportunities that present us, but there are gonna be some interesting things that come through. Anything we do is gonna be small to mid-size and a strong strategic fit. What do I mean by a strong strategic fit? It helps build out the software and solutions ecosystem I talked about. Anything that helps us vertically integrate in the core components, anything that will accelerate our R&D efforts. Acqui-hires of great engineering teams. If you actually look at the M&A deals we've done in the last two years, looks a lot like that. One of the things we're gonna do is while we have enough cash to get to breakeven plus a cushion, I wanna protect that cash. I want our stock to be the primary acquisition currency of choice. One of the things you're gonna see us do here in the next few days is file some equity registration statements that will allow us to move quickly for those compelling opportunities that we see. These are gonna be modest in size, and we'll use them if we see a compelling M&A opportunity, and if we don't, we won't use them. All right. I'm gonna leave you with four concluding remarks. First, we have the customer wins in place today to exponentially scale our sensor and revenue growth. I walked you through the credible path to get to 100K, 1 million and 5 million unit run rates. We expect At least double our revenue each year for the next several years on our journey there. We have a credible path to profitability. Gross margin by the end of this year, core business by the end of next year, company by 2025. At the same time, we're gonna be investing in this product road map to drive growth, allow us to capture this value in the ecosystem that our lidar creates and achieve superior margins. Finally, you met the great team in place here that Austin built today. This is the team that can get this done. There's an even better team, no offense to the folks in this room, below them. As I mentioned before, we have the cash on hand plus a cushion to get us to the profitability and make these investments. With that, I'm gonna wrap up this presentation. I'm gonna invite Trey up here to help MC the Q&A. Austin, if I could ask you to join me to help help me with the Q&A, that'd be great as well. Oh, I'm supposed to sit down. All right. Thanks, everybody, for joining us for what's been a wonderful day. I wanna remind everybody who's watching via livestream on the webcast, you can email us at investors.luminartech.com if you have questions. Then here in the room we've got a couple of mic runners, Kara and Tushar here. If you can just raise your hand, they'll find you, and we'll get the questions that way. Right up here. Yeah, let's go ahead, Emmanuel. Thank you so much. Emmanuel Rosner from Deutsche Bank, and thanks for hosting this event. First question maybe on some of these content per vehicle sort of opportunity and when I'm looking at end of decade targets. You have it essentially stable around sort of like $1,000 opportunity, sort of like mixed adjusted take rate adjusted. Can you maybe speak a little bit about what goes inside this to sort of be able to maintain it at such a high level as you? Software content going up. I guess can you just maybe give a little bit of a breakdown on how you would basically maintain such a high revenue per, you know, per vehicle, per sensor, despite obviously, maybe, you know, competition and other dynamics? Yeah, sure. Here's what's gonna happen with that, Emmanuel. As we start to commercialize our Software Sentinel suite, there's gonna be additional software products that we can sell, the perception and the full stack capabilities for the proactive safety and the highway autonomy product that we're offering. The content per vehicle on those can raise anywhere from like, you know, call it, you know, mid to high $10s for something like perception to a lot higher for the proactive safety and the highway autonomy. We're also having conversations with our customers to be creative in terms of how we price those. Instead of doing it just up front, which is the traditional OEM model, you can do subscription-based, which is where a lot of our customers are wanting to do. We're also willing, as you see with the insurance, to bet on ourselves. If you wanna upgrade the consumer to the highway autonomy or the next generation ADAS safety, you need the hardware on the vehicle when it's sold and the standardization. That can create a very profitable upgrade revenue stream for the OEM as the consumer either upgrades that at the time of the purchase or any time over there via the over-the-air updates. You know, could we at some point in the future move where maybe we would take a little bit less on the lidar up front but then a little bit more of that upgrade fee as well and kind of partner with our OEM customers and, you know, once again, bet on ourselves and what our technology can do. I think this is actually a really interesting one and something that's overlooked. Actually a really good question in terms of total content per vehicle. I think it actually would be interesting, you know, we can even maybe at the, you know, next earnings or something to do a more detailed breakdown. What I think is relevant, there's multiple different factors that affect these cars that basically involve very counterintuitive dynamics, like when it comes to the economics. Like for example, the whole point is the least amount of value you will get on a Luminar-equipped vehicle will be on the first day. The most amount of value is at the end state. It can already improve vehicle safety significantly off the bat, then only continues to improve that over time as the software develops, as the systems develop, as the systems are deployed. So the value of that system on the vehicle ultimately, continues to accelerate via over-the-air updates, which generally the... I mean, I don't know if there's a single model that we're on that isn't equipped with that capability. That's a relevant point. The other part that's interesting that I think is just when it comes to these other, you know, systems and services, it's really... It depen... Like we... I think we were very, very conservative when it comes to modeling these things because we don't need any of this ultimately to be incredibly successful. Like heck, even with just the lidar, Like, like we can be incredibly successful. you know, you're, you're probably not gonna build a multi-hundred billion dollar company doing just that. That, that's where I, at the end of the day, that's where I think like expanding with that ecosystem makes sense. Like, for example, just the insurance alone from what I said in my presentation, that's like, you know, people spend on average in the U.S. $20,000 for a vehicle over its lifespan there too. That's like, I mean, 20x the content value of the lidar. If we could actually save a material portion of that by safety improvements and other stuff on that. The point is that then that comes into the take rate. you know, what's the take rate on that? That's where you can end up with a dramatic variance into the thousands. The same thing for like, you know, if you have automakers that are charging you know, $5,000 for a highway autonomy system. You know, it's the same kind of discussion there. All of that is accretive. And I think ultimately will transform from something that is like a one-time fixed $1,000 thing into X dollars on an annualized basis in a subscription model. I would be surprised if by the end of this decade that whole software and services capability and division into products that we're building aren't on subscription as opposed to like one-time upfront sales. If you think about it, like for example, insurance already is the ultimate subscription, you know, if you think about it. That's just a different way to look at it. Thanks. Coming to Itay. Great. Thanks. Itay Michaeli from Citi. Thanks again for hosting the event. Austin, to your answer just before, around the software opportunity for lidar to get better, maybe talk about your customers' appetite to, as we've already seen, to standardize your lidar initially, maybe out of the 20 programs or production models you're on, maybe what portion do you think will be standard and how long? Maybe, Tom, on the 2030 projections, what are you assuming in terms of the success of the insurance in terms of signups? I know it's early days, but what, in your model, kind of what are you assuming in terms of where that is in 2030? Yeah. Do you want me to go first? Cause, you know. Yeah. Go ahead. When you look at the insurance, we're assuming very, very, very low initial penetration rates. I've seen enough from our conversations with multiple customers to make the decision to invest in this now. The amount of investment here isn't as big as you would think. As I said, Alex walked me through how we built it at Tesla. We're talking tens of millions of dollars, not hundreds of millions of dollars to get this out and build at least a product ready to go for that. What's in there now is very, very, very low, I would say single-digit penetration until we prove this out. We have a good sense of like what the penetration rate is for Tesla or the OEMs there, but I gotta see some real-life data before this really starts to juice the model. There's, you know, a lot of potential there. It goes back to your point, and I don't wanna steal your thunder on the standardization, but if you're able to partner with the OEMs on this and underwrite those insurance savings together, because once again, those insurance savings are gonna be there. We go to our OEMs and say, "If we don't do anything, then the traditional insurance companies are gonna capture that value. Let's go capture this value together. We built out this insurance infrastructure. It's scalable. You don't do the work. We did it, and let's go collect these checks together." Like, that's our pitch and, you know, it takes time for that to resonate, but, you know, that is advanced to the stage where we're willing to make that investment now. I think that's absolutely 100% the right approach. I think, you know, having the right, very conservative attitude on these things too is super important. Like, for example, even in the revenue build, you know, when you take a look at it like for 2030, you know, it doesn't have any or like negligible, you know, stuff for insurance and things of the like because, you know, the Listen, the reality is that if we build a, you know, a business that can get to, you know, $5 million, or $5 billion run rate there too at that period of time with a $60 billion, you know, forward-looking order book, I think we're like. That's already such dramatic growth where it puts you more into the category of like, you know, beyond what the Mobileye of today is or even what NVIDIA was a handful of years ago. We don't need to promise that to make it super successful. It doesn't mean that we're not investigating. I think that's actually going to help accelerate the rest of that standardization vision, as Tom was mentioning, because it basically. It will help speed up the pro. Like there's already a business case today to have a lidar on every vehicle there too, independent of if even if there was no safety savings at all. Once you add that into the equation and factor it in, there is no reason why every automaker shouldn't have this product on every car that's produced. It just makes. It rounds out the math to make it incredibly compelling. Even that, you know, 5 million vehicles, that's only a 5% market penetration, right, you know, by that time. There's a lot left to be able to cover and a lot of upside with the kinds of ASPs and hopefully content value should substantially accelerate then beyond that. Thanks for the question, Itay. Let me go to one that we got from the live stream, and then we'll go back to the room. I think this one's gonna be for you, Austin. Can you share more details around the recent Mercedes announcement? What's the primary differentiation that drove the expansion of the win without any on-road experience validation of the technology with another series production launch? Yeah. No, it's a good question. I mean, look, listen, these are very, very big bets. You know, I think probably as you guys saw today, it's extremely uncommon, maybe even unheard of, to have a, like, automotive supplier, like, at this stage, like, be able to get the level of focus and attention, everything from, you know, the heads of these companies that are employing hundreds of thousands of people with millions of things going on, you know, that probably have a lot of stuff to do during to ensure successful execution of the business holistically. The reason why is because I think the leadership of these companies strongly believe this is core to the overall roadmap and strategy of the automotive industry and their businesses generally going forward. I think, we are seeing adoption of this kind of technology at an unprecedented breakneck rate relative to what we see for other kinds of, you know, technologies historically in the automotive industry, where normally you would, by all means, you would wait through successful execution of this. That said, there is more behind the scenes. We absolutely have to prove ourselves at every step of the way. Like, we manage like day-to-day, week-to-week schedules for every automotive program. Like it is a very intensive execution, and that's what we're constantly heads down doing here. We successfully proved out that we could execute to that stage and met all the milestones for the program ultimately to get that confidence to be able to scale successfully. That's what enabled that major decision to be made. Then obviously, I mean, it goes without saying from the other stuff, the technology sort of speaks for itself. I mean, it's differentiated. There's nothing else that could enable that capability with them. In this case, it's not even just a matter of like, oh, is it Luminar or someone else? It's like, oh, is it, is it Luminar, or are we gonna wait X number of years to put it on the vehicles when it's de-risked? I mean, these guys are basically betting the futures of their company on us, and if we don't ship, their car's gonna have a hole in the roof. You know. Yeah. Thanks, Austin. Yeah, let's come back here to Jason. Yeah. Hello. This is a personal investor. I had a question about the business in Japan. Are you guys seeing an uptick in interest from OEMs? What year will the Nissan deal possibly bear fruits? Yeah. The answer to your first part of the question, Jason, is absolutely. I think Everybody noticed what Nissan did. To remind everyone, Nissan came out last year and said they're developing this next generation safety system, where our lidar is gonna be a key part of it. You saw some of the commercials, and videos that they've released about that, and we're working actively with them on that development stage. A lot of the other Japanese OEMs noticed, and as you can say, that has resulted in activity. You know, we'll talk about that when there's something to talk about. Nissan has said publicly that they plan to start deploying that technology on their vehicles starting the middle part of this decade, and by the end of this decade, 2030, have it on virtually every vehicle that they make. When you go back to that 1 million unit a year run rate that we talked about in 2026 and 2027, that first phase of Nissan, you know, we assume happens roughly in that timeframe. It's actually what we're assuming is a very small percentage of it. Just to highlight, we talked about the conservatism in our order book. We're in the development stage now with Nissan. We've gotta get this system to work with Nissan, and then they're gonna start deploying it on their production vehicles. We're working with them in terms of what that rollout schedule is gonna be and then getting to the formal nomination process. Right now in my order book, I have 0 in there for Nissan, right? If we're successful developing it and rolling it out, and we get to that virtually every vehicle they make in 2030, Nissan makes 4 million vehicles a year, right? You saw that 5 million unit number I put up there, when three-quarters of that is kind of from our existing customers. I have nowhere near that full 4 million in our model as of now. There's some, but nowhere near that 4 million. We're very excited about that. That is all progressing on the right thing. When we get formal vehicle line awards, then we'll start moving that into our order book. All right. All All right. One more question. Go ahead. Hey, guys. This is Joshua Buchalter from TD Cowen. Thanks for hosting a very informative day. I mean, what it was clear throughout, you guys are working on a lot. you know, how should we rank order, in particular, the opportunities within that other non-core lidar hardware, software bucket? Which ones are you most excited about? How much are those contributing to the forward-looking order book and your future. Yeah. Projections? Great question. When I talked about our public milestones for this year, I put top three up there for a reason, That's really execute, execute, grow our business, and continue to invest in this product roadmap. In order for any of this to be successful, we gotta make these lidars, we gotta make these lidars in scale, and we gotta get them on a lot of vehicles out there. That's the top focus for this company this year and what everybody is focusing on. We're gonna continue to make investments in the other stuff, the software and solution. Right now, remember, what's in my order book is only awarded business. The business we have awarded today is primarily that hardware plus the base software. It's a rounding error for that other stuff in terms of what's in our order book. We're very confident that that's ultimately gonna start to result in, you know, real scalable revenue in the second half of this decade, and that's why we're making those investment. There's a lot of upside in that order book and even what's in our longer-term, midterm and longer-term financial projections. I think that that's the important part is that no matter what, like, we have the fundamental must-dos, you know, cannot fail and what we need to execute on across the board. That in and of itself can and will build a massively valuable business, you know, when it comes down to it. Like I think the other things, it just is upside. What we fortunately are in a position of luxury where we have the ability to make those investments and to get to that upside and still have the, you know, the business, the cash, liquidity, the revenue, and everything else to support, you know, what we need to do initially. I mean, you take a look, it's like the perfect example of this. You know, Mobileye is actually one that just recently went public again here, right? You know, is that I think when they had, you know, what, $350 million revenue, they were on the order of like $10 billion, ended up getting bought out for $15 billion. Now what? You know, it's, they have over $1 billion, and it's like, what? $30 billion plus, you know, as a, as a company in terms of value. Like, that goes to show even, like, without all this autonomous, even without, like, just being able to have, like, a great fundamental business with that core growth underlying, like, the equivalent of what we're doing for the lidar side is great. Obviously, the distinction here, and I think what's relevant is that, you know, we are provide. Even from a lidar level, we're providing systems with huge content value on a vehicle. Like, it's basically, our market opportunity is, you know, probably like 10x, you know, what the fundamentals of like a basic ADAS system is, you know, for or a chip for that. I think that's why everybody's trying to go after that ultimately for that additional upside. I think that's the way to characterize it. Thanks so much. Just a couple of announcements before we kind of do a final video. I wanna thank everybody who joined on the live stream. Thanks for spending the afternoon or morning with us. We really appreciate it. We're super passionate about the business. Hope you are too. For the folks who joined us in Orlando, huge thanks. It's not over yet. Now, we're gonna do all those great things that you heard us talk about, we're gonna go let you experience at our long-range test facility, where we're gonna have demonstrations. And, we've got our Head of Software out there, CJ Moore, and his team, who've been doing tons of work to get ready for that. I look forward to you being able to meet him out there. The buses are gonna be directly behind you out these doors this way. Then we'll go out there for some demonstrations and some adult beverages. With the live stream, we're gonna have one last video, this will be the end of the show. Thanks, everyone. Thank you.