Good afternoon, ladies and gentlemen, and welcome to the Luminar Full Year 2020 Year in Review and 2021 Business Update Conference Call. With me today are Austin Russell, Chief Executive Officer, and Tom Fennimore, Chief Financial Officer. As a quick reminder, this call is being recorded, and you can find the earnings release and slides that accompany this call at luminartech.com/quarterlyreview. During the call, we may refer to our unaudited GAAP financials and non-GAAP measures in our release. I would like to remind everyone that comments on this conference call may include forward-looking statements regarding the company's expected operational and financial performance for future periods. These statements are based on the company's current expectations and are subject to the Safe Harbor Statement for forward-looking statements that you'll find in today's news release. Actual results for future periods may differ materially from those expressed or implied by these forward-looking statements due to a number of risks or other factors that are described in our Form S-4 recently filed with the U.S. Securities and Exchange Commission. We are not undertaking any commitment to update these statements if conditions change. Now, I would like to turn the call over to Luminar's Founder and Chief Executive Officer, Austin Russell. Thank you, Michael, and good afternoon, everyone. Appreciate you all joining Luminar's first quarterly and full-year review as a public company. Since founding Luminar in 2012, we've worked relentlessly to build the most innovative technology from the ground up to be able to solve some of the world's most challenging problems in autonomous driving and vehicle safety. Our Go Public transaction was an incredibly important milestone in 2020 that's positioned us well to be able to further accelerate growth toward a dominant market position and from a long-term perspective for our company and the industry to ultimately help shape the future of transportation. We're hot off the heels of a watershed moment, not just for Luminar, but for the industry at large, with real autonomy coming to China in series production via our partnership with SAIC, the largest Chinese automaker. Going forward, it's really all about execution. We've never been more focused on executing against our vision or excited about what's to come, for that matter. We've had a really experienced rock star team of captains of industry that are really enabling us to execute and pull off what many thought was impossible. With that, of course, I'd like to extend my thanks to our incredible employees, investors, partners, OEMs, suppliers, and everyone's on board for the next phase of the critical journey. For our full year in review, I'd like to share a summary and refresher of some of the key milestones that we accomplished in 2020 for reference. From a product standpoint, for hardware, we launched and built our first unit of Iris, the series production version of our technology. Software, we kicked off productization of our software developments leading up to the Sentinel announcement for what we had in 2021, just last week here. From a customer standpoint, we accelerated customer adoption across key verticals, including passenger vehicle OEMs, trucking partners, and robotaxi programs, totaling to 50 partners. We won the industry's first commercial series production win for autonomy with Volvo, and then as well had two subsequent additional landmark wins with Daimler Truck and Mobileye. From a financial standpoint, as you all know, Going Public was one of the biggest events. We brought our total raised, you know, to roughly about $850 million by year-end 2020. We originally set the target for an ambitious $1 billion forward-looking order book by year-end, but, you know, along the way, we actually increased guidance and subsequently met that as we crushed it, landing at about $1.3 billion. As everyone knows, 2020 was a tough year, but we certainly made the most of it and then some. Things have only accelerated in the few months we've had as a public company in 2021. I can share more on that. First and foremost, our Iris deliverables are on schedule for the 2022 start of production. We've successfully executed day in and out to be able to meet our product milestones as we continue to industrialize our core technology in a series production product. Importantly, this is not our first rodeo building a LiDAR. You know, you can't go from zero to 100 right off the bat. You have to build multiple generations of LiDAR prototypes, LiDAR for vehicle testing, then LiDAR for development, and then finally LiDAR for series production in order for this to be truly successful in the industry. With these multiple previous generations of systems that we built, it has the same core LiDAR architecture and principle, but now we're approaching the end of that tunnel leading up to series production, and that's how we've been able to pull this off. From a milestone standpoint, we've successfully completed engineering validation testing from our Iris B- samples and are now progressing on to the final stages of B- sample production before ultimately ramping into C- sample stage later this year. The results of the rigorous testing have been very positive, and we can now say that Iris has passed key auto-grade environmental specifications. This includes shock and vibration, thermal, you know, the ability to operate in extreme heat and cold conditions, as well as the ability to survive harsh weather conditions such as, you know, rainstorm with increased protection. As a result of our team's hard work, we now have Iris LiDARs live on customer vehicles going through the data collection and development process and transitioning from our previous generation Hydra LiDAR. From a performance standpoint, our initial goal for Iris was to maintain some of the same performance of Hydra LiDAR, but this time in an auto-grade series production product. You know, Hydra set the gold standard for performance in the industry as the first to meet these very stringent automotive performance specifications, like seeing out 250-meter range for hard-to-see dark objects at 10% reflectivity, as well as very high resolution, you know, camera-like in that sense, with customers now having already been testing on hundreds of these units today in preparation for their production programs. Interestingly, we found through real-world testing that Iris actually outperforms Hydra in a few dimensions, leading to even better ranging performance with a max range out to 500 meters and even better ability to see dark objects clearly at 250 meters. Of course, Iris is also designed for high-volume manufacturability and series production is lower cost and is smaller and easier to be able to integrate into vehicles. From a manufacturing point of view, we've successfully developed our Iris pilot line in our advanced manufacturing facility in Orlando, Florida. We've now defined the initial blueprint for how to be able to successfully and efficiently build Iris, working hand in hand with our Orlando engineering team to be able to optimize the process in a highly automated capacity. We selected a contract manufacturer and series production facility in Mexico, and the next major milestone that will take place is as we transfer our blueprints and ramp ultimately towards a C- sample production by the end of the year. Now, moving on to our transition to a full-stack autonomous vehicle company. Historically, people have thought of Luminar as a LiDAR company and the leader in LiDAR for production vehicles, but the introduction of our full-stack offering last week is hugely transformational to Luminar, moving from a LiDAR company to an autonomous vehicle company, moving from a component company to a solutions company. We call it Sentinel, which is the industry's first full-stack autonomous system for series production. It is a holistic system offering, you know, includes perception software, controls and planning software, Iris, LiDAR, and other ecosystem components. We partnered closely with Zenseact, you know, a 550-person automotive software team to be able to deliver some of the different components of Sentinel with their responsibility primarily focused around the controls, planning, and decision-making software. Sentinel will enable automakers to offer highway autonomy and proactive safety capabilities on their production vehicles for the first time. For Luminar, all of this is key in our transformation, enabling autonomy and improved vehicle safety to become ubiquitous. Lastly, I want to cover some new details about customer adoption and accelerating traction, and looking ahead, our robust pipeline. At Luminar, our mission and focus has always been to deliver product for series production vehicles in direct partnership with OEMs. That's what led us to architect and build the product the way it is, and today we remain the first and only LiDAR to really meet these specifications for autonomy in production. We're proud to share that we welcomed six new partners since the start of the year, announced today, one of them now at the production stage, SAIC, the largest automaker in China and a Fortune Global 100 company, which is the lead series production automaker partner that we have in China to deliver this industry-leading LiDAR and associated software for SAIC's R brand vehicles. This win really kicks off Luminar's foray into China and also our APAC expansion. Importantly, we remain focused on a handful of key partners that we believe have the ability to see things through to series production as we work with the majority of these top OEMs. This is as opposed to trying to create a long list of customers testing products, but may or may not really lead to production opportunities. We believe that winning just the handful of top automakers has the potential to deliver substantially more value than everyone else in the industry combined. That's why it's so important. Building these relationships early on has been critical from a product and timing perspective, and in the automotive world, you know, specifically for production programs, you generally have to be working with OEMs years in advance and design their development platforms. It's a very high barrier to entry, but equivalently a very high barrier to exit. We now have greater conviction than ever about the evolution of the industry and additional major program opportunities over the coming next couple of years as these programs are working with transition from the advanced development stage into production. When it comes to these customer production programs, we've certainly been taking the market by storm, but they can be very intense and demanding, so keeping things on track is not a trivial exercise. With that said, a quick key program overview. We're meeting our various milestones with Iris, you know, B- sample deliverables to Volvo. We've met our deliverables to Daimler Truck, Mobileye, Zenseact, and SAIC as well, which are all on track. Our deliverables in general to our development partner OEMs also remain generally on track. We're already off to an amazing start to 2021 and look forward to our best year ahead as we execute and win the industry. With that, I'd like to hand it off to our CFO, Tom Fenimore. Thank you, Austin. I will address three topics today. First, as a management team, we are focused on maximizing financial performance and shareholder value over the long term. To this end, we have set five long-term oriented milestones for us to achieve in 2021, and we'll use these milestones to measure our success for the year. Next, we will provide an update on our commercial pipeline and forward-looking order book. Finally, we will discuss our 2021 guidance and preliminary 2020 unaudited financial results. We are finalizing our 2020 audit and will file our 10-K with audited financial statements by the end of this month. I will now define our five 2021 milestones that we expect to achieve by the end of the year. The first is execution against our Iris industrialization plan. Before the end of the year, we plan to complete key steps in testing, validation, and the manufacturing blueprint for Iris while in parallel executing tool up and bringing our series production CM partner online. This is expected to culminate in the production of C- sample Iris units at our CM partner before the end of the year. The second is to win at least three major commercial programs this year, one of which we already publicly announced earlier today. The third is software. We expect strong continued development of Sentinel leading up to an alpha release at year's end. The fourth is to grow our forward-looking order book by at least 40% this year, and then our final milestone is to be disciplined in our cash spend and end 2021 with the same or slightly more cash than we had at the beginning of this year. More on that later. Onto our commercial update. We have seen a significant increase in our commercial pipeline since our last update in November. We are currently working to convert an additional 14 programs to series production awards or equivalent by the end of 2022, up from 12 in November. We ended 2020 with a forward-looking order book slightly over $1.3 billion, a little better than the increased guidance we gave in November. As a reminder, our forward-looking order book represents the estimated future revenue over the life of programs associated with our commercial wins. See the appendix in our earnings deck for a more detailed definition. Going forward, we expect to update our forward-looking order book annually, but likely not on a quarterly basis given the timing variability of program awards. Now, onto our final topic. In 2020, revenue was approximately $14 million. It is worth noting that there was nearly $1.5 million of customer billings in 2020 that during our year-end review process, we decided to defer and expect to recognize as revenue this year. For 2021, we expect revenue to be in the $25-$30 million range, consistent with the $26 million in our August forecast. A quick comment on our unit cost structure. As a management team, we are focused on delivering solid unit economics, especially our bill of material or BOM at series production scale. Correspondingly, we do not believe our gross margin during the pre-production phase is a relevant metric for the longer-term profitability potential of our programs. We remain on track to achieve our $500 BOM target per unit for series production scale. I will now transition to discuss our operating expenses and CapEx. We expect both these line items to increase significantly in 2021 given the investments we need to make for our growth plan. For CapEx, we expect to spend approximately $10-$15 million this year. After this year, we do not expect our OpEx or CapEx to grow anywhere near the rate that it has grown this year. For 2021, we expect total cash burn defined as operating cash flow less CapEx to be approximately $140 million. We raised nearly $154 million of cash from the exercise of warrants during the public warrant redemption process, which concluded on March 16th. This should help offset our cash burn this year and then some. We expect 2021 to be a peak year for our cash burn rate, and we believe we have sufficient cash on hand to reach profitability. On December 31st, 2020, we had $323.9 million shares of common stock outstanding, including the Class A and Class B shares. We attached a slide in the appendix with greater detail on the math behind this share count. I would like to include by thanking all the employees at Luminar for an amazing year in 2020. What our team was able to achieve in such challenging times was nothing short of miraculous. I'm truly honored to be a part of this team. With that, Michael, we're ready for Q&A. Many thanks, Tom. As we start the question and answer portion, for those on the phone, please dial star one to ask a question and remember to mute your computer before asking the question on the phone. Over to you, operator. Good afternoon, everyone. This is Aileen Smith on from Bank of America. Can you hear me? We can hear you. Yep. Great. First question on Sentinel, as there seems to be a lot of traction in short order with the Zenseact and Volvo announcement last week and then SAIC this morning. As we think about the components in that suite being Luminar's LiDAR and perception software and then Zenseact One Pilot autonomous driving software, what has been the reception by automakers like SAIC or others that you're in discussion with to purchase a holistic autonomous system with software from another automaker? Or is there significant interest by automakers in purchasing the base hardware and perception software from you and integrating it with their own internally developed autonomous software? Yep, yep. That's a great question as it relates to that, and yeah, it's certainly exciting to already start to get some traction, you know, just following the announcement. What it comes down to, and I think the whole problem that it's solving is that there's really only a handful of automakers that have really had the capability to develop a full-stack system and with all of the different components that have to come into play to do this. From a software standpoint, that's really where, in addition to our own perception software and some of these other software components going into it, in addition to Zenseact software, you know, we offer it as both a holistic solution, you know, which is applicable to a number of automakers, but also in an à la carte capacity to a stage where, you know, many times you'll see automakers that are maybe developing or have capabilities to develop certain parts of the software stack, but not the whole thing holistically. As a result, wouldn't be able to really make or would be a huge challenge to make, you know, a fully autonomous system for any kind of production vehicle or frankly any level of autonomy that's driver out of the loop. That's what we've developed. That's what we're going out there with, and you know, we certainly expect continued traction across the board on that. Great. That's helpful commentary. Second question, one encouraging sign, certainly relative to some of the other specs through reporting season, is the consistency of your 2021 outlook with some of the financial targets that you established last year, which I think speaks to how they may have been grounded much more so in reality than others. However, obviously you continue to execute better on converting programs to series production, which has obviously boosted the order book. Looking specifically at what was your target for, I think, EBITDA positive and perhaps free cash flow positive by 2024, has the better performance on business wins pulled forward or pushed out that target in any significant way versus your initial expectations? Sure. I'll make two comments here. First, the direct answer to your question is, as we look at our outlook and kind of the business that we've won and the business that we expect to win, we still anticipate profitability and cash flow positive somewhere in that 2024 plus or minus timeframe. We haven't seen any material change in the outlook for there. The second thing, and I just wanted to, you know, highlight a point that you mentioned there. I think one of the things that differentiates us from some of the other LiDAR companies that have gone public is a lot more of our revenue base is less associated with selling sensors to testing and development fleets. A lot of our revenue is more associated with getting ready for our series production programs, and that's either via development revenue as we really get into the execution phase of launching series production, as well as selling sensors for either pre-production programs or late-stage development fleets. That demand tends to be more predictable. I think one of the things that you saw last year, particularly in the COVID times, is a lot of these testing fleets, you know, you'll probably see them around the street here in the Bay Area, wherever you are, that, you know, that have those, you know, big LEGO-type cars out there. A lot of those were grounded at a halt for COVID, and that really pushed sales to that sector and halted them for a good chunk of 2020. Luckily, that's not our business plan, and we weren't anticipating it as much as others. Fantastic. That's great color. Thank you for taking the questions. Our next question comes from the line of Tristan Gerra. Please go ahead. Hi, guys. Good afternoon, and thanks for the slide deck. Very useful. Just wanted to get a little bit additional color on your $1.3 billion revenue funnel. Should we assume about 1.3 million units and about the same number of cars, and is that mostly L4 applications? Sure. Let me go in a little bit and more cover of exactly what is in that $1.3 billion. That was as of December 31st, 2020, when you look at the production programs that we had won at that time. Any 2020 wins are not in that number. That is our estimate over the life of the programs for the business we won, the revenue that we expect to earn, whether that's from the hardware or the software. Now, the unit pricing can depend, you know, based upon the timing, the size of the order, whether it's hardware only or whether it's hardware plus the different software functionality that we have. In terms of going down into the breakout between volumes, pricings, units, etc., that's something that we're, you know, not really, you know, going to be going into that level of detail, you know, but I think it is a good mix of, you know, our two levels of product functionality, the highway autonomy feature as well as the proactive safety feature. It also is a good mix of hardware as well as the software functionality that we have. Okay. That's useful. Then looking at your SAIC engagement, is that the first one to ramp in volume, and should we make the, you know, should we have the expectation that it's potentially the largest in the near term in terms of size within that funnel? Yep. This is running in parallel with the Volvo program here. You know, these guys are certainly, they're moving quick. You know, there's no shortage of that for sure. You know, they're very intent on seeing this through and launching this on a pretty aggressive timeline, to be frank. I think really the only reason why it's possible to be able to do this on this timeline is just because of the fact that we get to leverage all this work that we've already done for a lead series production partner and these other landmark partners to be able to deliver to SAIC as well. That's how you can see from a product standpoint, you know, the meaning they can have. From a win perspective, yeah, I mean, this is certainly, you know, you could probably say it's the biggest passenger vehicle news or even just maybe news holistically from a commercial standpoint that we've had past year since the Volvo win there from that perspective, and maybe even for the whole industry at this stage. When it comes to delivery, I think it would be reasonable to expect that, you know, SAIC's program would be the first to achieve some level of autonomy starting on highways as well as these advanced proactive safety features that would be on the vehicle as well. We're delivering and executing that to the T and, you know, from a hardware standpoint and then, of course, as we mentioned, some of the software components as well. Congrats on that. Then last question, obviously, there's been several companies, you know, in the LiDAR space, either now publicly traded or intending on going public. Could you remind us, you know, if you feel that anybody gets close to your range or any other performance metric that you can mention? Also timing, do you feel that, you know, the design interaction you have is really because you were really first, you know, with those LiDARs from a performance standpoint and able to demonstrate that you were able to ramp this in volume? Just a quick update on the competitive landscape that you see. Yep, yep. Absolutely. I think there's really a few different factors to consider. When it comes to a technology standpoint, as you know, as I mentioned, you know, absolutely stand by the statement it's true, was true, is true, and for any foreseeable future that we see as true is that we're the, you know, first and only system that really meets those performance requirements that are needed to be able to enable autonomy in series production vehicles. When it comes down to it, you know, there's just so many different stringent performance requirements that you have to be able to get right and do simultaneously. You know, it's actually pretty straightforward to ultimately put those specs on a slide, you know, as target specifications. It's an entirely other thing to be able to spend years toiling away, having to build all these different components from the ground up to be able to solve those problems and actually be able to do so from a physics perspective. You know, we really pioneered the only way that we're aware of to actually meet all those performance specifications while at the same time, you know, having something that can be also, of course, scalable, economical, and auto-grade. From that standpoint, I think there's no question there's also been, you know, some level of noise, and always the question is, how do you see the signal through the noise? Yeah, no, I mean, it's funny we hear terms like digital LiDAR, 4D, LiDAR on a chip, you know, all these kinds of things. At the end of the day, you know, I mean, we've had, it's funny, we've had those things for some time now, and it's really just a matter of continuing to deliver. From a commercial standpoint, though, to your point, getting the wins is critical, getting that early on, because, you know, once you have this, it really is very sticky in the sense that, you know, when you win an OEM in the initial program, it's very significant in the sense that it oftentimes will trickle down from that high-end, you know, program when you're designed into the platform into multiple other programs. You know, oftentimes the OEMs have a very long time horizon associated with this. That's what's really meaningful at the end of the day. Great. Thank you very much. Our next question comes from the line of Emmanuel Rosner. Please go ahead. Hi, good afternoon, everybody. It's Emmanuel Rosner from Deutsche Bank. First question would be if you can give a little bit more color around the win with SAIC. Just wanted to double confirm that this is incremental to your $1.3 billion order book to the extent that it was announced in 2021. Can you tell us anything about what kind of volume this R brand is expected to get, not necessarily the amount of LiDARs you'd be selling, but what are we talking about, sort of like annual production there of vehicle? When you were mentioning this morning that the potential path towards getting this on other sort of like product line, do you mean the rest of the R brand or is there any path towards getting this onto the rest of the SAIC brand portfolio? A few different questions embedded there. First off, yes, that's correct. This is incremental to that $1.3 billion. That was a confirmation that we met the target that we actually raised along the way last year, and, you know, now this is on top of that. When it comes to this and the volume curves, I mean, at the end of the day, our whole focus is around like how do we realize opportunities that can make their way into real production vehicles and see some serious volumes at the end of the day. I do not think SAIC has disclosed their specific volume curve for the R brand. You know, you can feel free to ask them, you know, is it their vehicle. At the end of the day, what they have also said, and this is really consistent at the end of the day, is that there's a desire to not just have it on, you know, the higher-end vehicle programs or brands within an OEM, but to also be able to ultimately standardize, you know, Luminar across the holistic OEM. That's really what, you know, the holy grail of all of this is to be able to drive towards. You have to seed it, you have to get designed into the platform first, you know, as part of this, and, you know, just take it step by step. You know, and usually you start to see everything from, you know, the most fundamental part of it is being designed in as an option, you know, on high-end vehicle, and then scaling that down where you have ultimately standardization across, you know, multiple programs. You have to seed that, you have to get designed, and you have to do the R&D work and the significant investment that's required upfront. Understood. What can you tell us about the six new strategic partners that you mentioned for so far this year? Yeah. It is really, it is a combination. I mean, we have talked before about the three primary verticals between passenger vehicle, trucking, and robotaxi, as well as there are adjacent markets too, but, you know, the product is primarily designed around those first three. With that, you know, I can say that we have incremental programs. Again, our focus is really around the opportunities that are going to be able to deliver all the value. It is like an extreme version of the Pareto principle where, you know, you could see, for example, like, you know, 5% of the programs delivering 95% of the value. That is why it is just so important to be able to stay focused. These kinds of programs are incredibly intensive to be able to work with. That's why we're establishing this office out in Shanghai, you know, co-located with SAIC, as well as, you know, just to be able to have a general foray into China and be able to facilitate future wins as well. Yeah, that's the story. Just to be clear, the six new strategic partnerships, these are essentially new companies that you're working with that you weren't with last year? That is correct. Those are at, you know, generally either anywhere from a validation stage to advanced development and pre-production stage. Those are new companies that we're working with. That's correct. In terms of the, you know, production stage announcement and what we have for this, you know, this, you know, large-scale, you know, opportunity here and basically what we put together with SAIC, that was one of those six. They are at varying stages, of course. Okay. That makes sense. Can you talk a little bit about, in your conversation with automakers, interest level for sort of like rapid deployment of LiDAR and any differences by region? Do you see it now happening somewhat faster in China, potentially prompted by some of the new EV players that are already coming out with some LiDAR? Is there similar desire in the U.S. or in Europe, or is it maybe on a slightly longer timeline? Yeah, yeah, absolutely. You know, I think it's ultimately a little bit all over the place and automaker-dependent, you know, depending on the vision that's there. I'd say for pretty much a lot of the forward-looking ones, there's some innate desire to want to have a play. In fact, I mean, in China, there's even some, you know, pressure from a, you know, government and regulatory perspective to be as a holistic mandate to be able to enable these features and capabilities for what autonomy can do, you know, in the really just next few years as part of all of this. You know, I mean, that's, of course, where we come into play, you uniquely being the only one that can truly enable these kinds of capabilities. Yeah, I mean, off to a great start there, but we, you know, continue to expect to be able to, with our existing programs and new programs, be able to win on a global basis. You know, certain ones are front leaders from an automaker perspective, certain ones are fast followers, you know, that adopted after the same kind of technology that the lead ones do. You know, Volvo is historically known for being like a lead adopter, you know, for example, as they did with other new types of safety technologies and, you know, the Mobileye and other stuff in this world. Expect this to be no different. Great. Thank you so much. Our next questions come from the line of Ethan [Terry] Please go ahead. Hi everybody and congrats on the first earnings call. Just maybe a first one for Tom on just kind of, you know, we think ahead to the original 2025 revenue targets. I think originally you had four additional programs reflected in the model. You're targeting three additional commercial wins this year. First question, maybe just talk about the level of confidence given that you have greater visibility now around what those potential wins might be on that 2025 outlook and whether Sentinel should be thought of as a potential upside to that as you begin to market that. Sure. What I would say is the pace of the commercial activity, both in terms of the discussions that we're having with our existing customers and relationships, as well as the conversion cycle in terms of converting those existing relationships into the series production wins, that is happening faster than we were expecting. When we kind of look at the guidance that we gave for 2025 last summer as part of our going public process, we look at that, and I would say the pace of activity that we need to be on in order to meet or exceed that, that's actually coming to fruition a lot faster than we were expecting. I think that that gives us increased confidence in obtaining some of those targets that we've talked about there before. Having Sentinel ready to go is, you know, clearly helpful to us getting there. I think the fact that when you look at what we announced over the last few weeks with a Sentinel win at both Volvo as well as SAIC, that's clearly helpful in getting us to where we want to be in 2025. Great. Let me just follow up to that on the funnel. So you have 14 advanced development and production opportunities, 50-plus customer partners. Do you care to maybe, you know, estimate by year-end of the 50-plus partners, you know, what you might be able to convert into advanced development or the RFQ phase by year-end? Yeah, you know, I have not really thought about a thoughtful answer to that 50 to 14. What I would say is when what we are spending most of our time on is converting those 14 into series production or equivalent wins, what we are seeing is it is more happening naturally that those 50 want to get to the market because as they see the other automakers and their competitors wanting to get to the market, they are kind of naturally, you know, moving down the funnel as we laid out that page in terms of working with us trying to get to the series production stage. One important clarification is that, you know, ultimately what we're spending most of our time on is, you know, we have to execute, you know, these programs, right? Like this is a lot of work that's involved to be able to see this through, you know, to that series production phase. That's why, you know, with the four programs that we were originally talking about, I mean, that was kind of the initial appetite, you know, that was had and interest. You know, we actually didn't even plan at all for SAIC or frankly, really even the full foray into China. That is incremental. You know, part of what we're doing is continuing to invest, continuing to accelerate that and be able to take on more programs. There's clearly interest and we're going big on it. We want to make sure to not take on too many such that, you know, the last thing you ever want to do is see one of the programs or multiple programs not successfully launched. That is what we want to keep our focus on, keep our eye on the ball. Absolutely, Austin. Maybe last one for you. Going back to slide nine, you know, around the data collection that you're now collecting on the LiDARs on customer vehicles. Are you able to use that data for software development? Maybe talk about the potential advantage you could gain through the data collection, through the validation phase. And then on the, it's interesting to see the outperformance of the range and reflectivity versus prior generation. What led to that? I mean, that just sort of happened during, you know, better tuning and testing. I'm just curious kind of what led to that upside in the performance metrics. Yep, yep. You know, I mean, ultimately when we set a spec for something, you know, we always try to, you know, underpromise and overdeliver at the end of the day. When it comes down to it, I think from an Iris standpoint, I mean, the amount of work and just raw engineering that went into every aspect of this, you know, we're on our, you know, in some of these cases, like seventh generation of subcomponent that's gone into Iris over all these different iterations of LiDARs, perfecting it along the way to be able to get to this stage. It's just so much work that's involved. To be able to do that has now allowed us to be able to uplevel even further the capabilities of the device. When it comes to the data collection side, this is something that's a critical step, you know, from a customer standpoint and their overall deployments. The key milestone as part of the programs that we are now going through at this stage. From a long-term data perspective, I do think that one often underestimated aspect of this is just the sheer amount and value of this kind of true 3D data that you can get when in series production. It's really, you know, as we're deploying this with Volvo, with SAIC, with all of these guys, you know, the level of data that you get to utilize has been completely unforeseen to be able to have LiDAR data. I mean, the largest fleet of test vehicles out there is like, you know, maybe you have like Waymo at like 500 vehicles or, you know, some of the different programs in the hundreds of whatever it may be. The point is that when you have this kind of capability now on tens, hundreds of thousands, millions of vehicles, you can really see a global scale deployment of capabilities and further feature expansion as it scales out. That is the long-term value. That's very helpful. Thank you. Our next question comes from the line of Mr. Michael Filatov. Please go ahead. Hi, can you hear me? We can hear you. Yep. You there, Michael? Yeah, hi. Can you hear me? Yes, we can hear you. We can. Okay. Great. Sorry about that. Yeah, this is Michael Filatov from Berenberg. I just want to go back to the volume question. You know, I guess, you know, you said fundamentally you start off as sort of a high-end luxury option for consumers. What I'm wondering is, you know, let's say you assume, you know, our brand is maybe 30,000 units a year next year. I mean, what are you assuming for an attach rate, you know, or a take rate from consumers on that sort of high-end luxury option for, you know, including your LiDAR? Yeah, you know, I think it's impossible to ultimately say what a take rate is. You know, we have in our own models, you know, we modeled like, you know, for example, those four program wins, you know, and assume take rates. I think we try to be reasonably conservative when doing that. You know, obviously having the huge upside with greater take rates and then extreme upside with, you know, standardization as you progress to that. You know, maybe Tom, you can provide more details like what, you know, what do we have in the models? What do you think is, you know, the take rate opportunity? Sure. So, you know, we have some pretty good data points in the U.S. as well as Europe. When you look at some of the systems out there, whether it's the Tesla Full Self-Driving system or if you look at some of the other Autopilot type versions out there, you can look at that. If they're priced somewhere in the $7,000-$10,000 range, you see take rates somewhere in the 30% plus or minus range. If they're priced somewhere in the $3,000-$5,000 range, you see some significantly higher take rates. We have some data. Clearly we'll look at what IHS and LMC and other third parties are saying as we kind of assess it. You know, for China, there's less data points that are available to us. As we have kind of built out our initial assessment of what the SAIC forecast would be, both on a year-by-year basis as well as what we are eventually going to include in our backlog when we update it again, you know, we are being conservative with the take rates in the early part of the year. The other interesting thing that SAIC mentioned in their press release is ultimately their plan is to introduce this and hopefully make it standard not only on the R brand, but potentially other SAIC local brands as well. The, you know, important distinction here, by the way, too, in terms of what's being compared to that maybe has like that 30% take rate at, you know, very high prices, like the Tesla Full Self-Driving system, the other kinds of systems out there, you know, that are powered by Mobileye or whatever, maybe those are level two ADAS systems where you have to keep your hands on the wheel, eyes on the road constantly ahead. This is a true autonomous, you know, capability of level three to four on highways starting out, as well as these advanced safety features. They can also be produced at, frankly, you know, lower ASPs than what people are even asking for today. That's why, you know, even if we're, you know, low double digits in, you know, from an expectation or modeling perspective in terms of what we have to be conservative, hopefully it's as it emerges and as it scales and over time that take rate grows dramatically and ultimately reaches 100%. Understood. Yeah. I guess what I'm trying to get here, you know, ultimately is, you know, at what price point for the Luminar product or LiDAR do you think, you know, you start to scale into sort of more high volume platforms, right? You know, some have said a couple hundred dollars. I guess what are you guys baking in from a cost curve decline, right? And sort of an attach rate trade-off there sort of in the out years to hit your targets? You know, it's a good question as part of this. I'd almost say that when it comes to this, it's really less about even the unit economics of, you know, how low can you get the BOM or whatever it may be, you know, incrementally to be able to have, you know, more units out there, more programs. I think there's a general sweet spot that when you're in that, it just makes a lot of sense from just a pure value perspective. But you have to start somewhere with programs. Like you can't integrate into, if you tried to integrate into every program all at the same time simultaneously, you know, you'd probably not be super successful. You know, even with the resources and what we have and the product that we have. You know, it just takes time to be able to work through this. But when it comes down to it, really, as it was mentioned, you know, people are charging well into the single digit thousands oftentimes for these basic assisted driving systems like level two, you know, with it's basically a lane keep assist attached to, you know, automated cruise control. That's really all it is at the end of the day. This is a completely different level of capability where you can take your hands off, eyes off, you know, on the highways, read a book, use your phone, watch a movie, work on your laptop, take a nap, that kind of thing in terms of what it's ultimately capable of here. In addition, of course, these proactive safety features of dramatically improving vehicle safety, you know, helping, you know, eliminate some of the 1.3 million lives lost on the road every year. We've even talked about some of the second order insurance implications, you know, that we may be able to actually in part or full capture as part of all of this. All of those factors coming into play, I think the business case is actually there today for standardization across the rest of the industry, at least in our case for what we have. That does not change the fact that, you know, we can have all the dominoes set up, you still have to execute along the way. This is what we are just so focused on, being able to see this through. You know, kicking off, I mean, just as this year has been so, 2020 was so pivotal, this year is incredibly pivotal. Next year at, you know, SOP is definitely going to be a continued watershed moment. Awesome. I appreciate it. One more quick one. What is the power consumption on the Iris? I know you have released it for the Hydra. Can you disclose that? Yeah, I think we had it at like, it was like 20, it depends on the conditions, but it was like plus or minus, you know, 20 watts or so. You know, when it comes down to it, I think the important part is that you really have a product that can meet all these different auto-grade qualifications. You know, for example, from a power standpoint, the important part is that you need to make sure that you can actually meet these temperature ranges going from - 40 degrees Celsius all the way up to really hot conditions, like, you know, whether you're in Siberia or whether you're in Death Valley, you know, this is the kind of conditions that automakers require for you to be able to operate in. That's where we've been able to pass those tests, you know, as part of a critical phase. I mean, this is a very intensive process of industrializing Iris to get through that. You know, we're really the first to be able to do that with this kind of product that's built for the autonomous space and industry and able to enable some of these capabilities that we're talking about. That's what we've been able to do. I appreciate it. Thank you very much. Operator, why don't we go ahead and hand it off? Final question to Joseph Back, and then we'll go ahead and conclude here. I know we started a few minutes late. We'll run over here a couple of minutes. All right. Joseph Back, please go ahead. Thanks very much for squeezing me in. Good afternoon. Just to go back to the SAIC announcement, I just want to be clear. I know it has components of the Sentinel software system, but it does not have what you're doing with Zenseact, right? And that's not going to be a requirement that automakers necessarily take it with Zenseact software. I just want to confirm that. Yeah. Yeah, we're not requiring automakers to be able to take every component of Sentinel. In this case, it includes, you know, other software components as part of it. Initially, you know, this specific deal does not include the Zenseact component as part of this, given we also just, you know, finalized that last week. You know, we're working through it, but there's obviously great opportunities ahead. What the Zenseact component allows us to be able to do is expand to even more automakers, such that like particularly ones that really don't have anything when it comes to the autonomous space. That's when you have the controls, planning, actuation, decision-making part of this stack, which takes a huge amount of work to develop. I mean, in our case, it's, you know, 500 plus experts, you know, that have been working through this. That's what's just so significant is having that license and having the ability to now, as part of the plan, you know, work with other automakers on this is something that actually allows everybody to ultimately be competitive and not a, you know, commoditized automaker. As part of that, also, you know, move towards the mission. This is a big part of Volvo's vision as well is, you know, like having a long-term vision of seeing minimizing road deaths altogether, but also just minimizing collisions of vehicles from a safety standpoint. It's a great partnership all around. We've also, of course, though, productized all of this software work that we've been doing to date and have been successful with that as well. Just leveraging that Zenseact software for part of the stack that's available for certain automakers, does that at all meaningfully change your internal R&D? Like, is that something you otherwise would have had to develop or it's sort of on the margin? It's not overly meaningful. Yeah, I'd say there's no question that it saves. I mean, it's all just a question of what's the TAM that you're also addressing as part of this. Like if it's just the LiDAR, you know, we know what the constraints are with this. But, you know, having this full stack system can, like, you know, triple your TAM as part of what's actually addressable. That's really important because, you know, and without any software at all, it's maybe even, you know, just a small fraction of the total market in terms of what's feasible to address. Having this portion is definitely there. It's an investment that we would have realistically given just all the success we've had, have otherwise made as part of this and was kind of some of the thinking. At the same time, yeah, I mean, you could say this saves, you know, hundreds of millions, heck, maybe even over the long term, you know, billions of dollars as part of this aggregate investment. At the same time, going all in with this, it still does require some kind of non-trivial investment, you know, if you want to go big and go through with this, you know, there's still a significant development cycle that has to take place. You know, we still have, we're responsible for also doing the work to be able to work with the different OEMs and integrate the solution. You know, we catalyzed this by actually, you know, earlier on and all the puzzle pieces have fallen into place. You may recall we did an acqui-hire in Munich of a previous Samsung ADAS team that had deep experience, you know, with a number of the German OEMs and integrating systems there. Those are the same people that are actually now working on Sentinel with the Zenseact team. That gives you a little bit of perspective. Otherwise, yeah, we're all in and look forward to seeing the continued success with it. Okay. And then maybe just a very big picture. Like I know you mentioned earlier about how your system is much different from level two systems out there today. I agree. There has also been a bunch of press recently about a bunch of level two crashes and maybe some of the nomenclature around that. Are you at all worried that that could impact autonomous adoption? It's a great question. I think the only reason why there's any association with autonomous and those kinds of crashes is just because sometimes people call those features autonomous. The reality is that they're not autonomous at all. You know, these are purely assisted driving systems that sometimes can be used in some capacities as if they're autonomous and then that's when those things happen. In some, and not to make it morbid in any capacity, but in some weird way, it actually, you know, enhances the visibility and the use case behind why this stuff is just so important to be able to do and to be able to get right and to actually enable true autonomous capabilities. You know, it doesn't change it. In fact, it realistically only enhances the case as part of all of this. Again, you know, what we're doing here is just a totally different capability. It's the difference between having some basic level of sensing to be able to understand what's going on around you and be able to help, you know, guide you between a couple of lanes with an auto steer or an automatic cruise control. This is the whole point in terms of what this level and accuracy of data can actually allow you to take your hands off and eyes off ultimately, as well as just from a basic safety perspective, you know, actually start proactively preventing accidents, which really hasn't been like everything right now is just reactive and people still die on roads today all the time and, you know, tens of millions of crashes as well and injuries associated with these things. That's what we have ahead of us there and it's going to make a huge difference holistically on those fronts. Thank you very much. Anyone got questions on some of the items, Mr. Gus Richards? Please go ahead. Yes. Thanks for squeezing me in. Just can you give us a sense of what the, you know, revenue differences between per unit when you have full stack software plus the sensor and perception software versus just the sensor? Yep. Yep. So yeah, from a total vehicle content value perspective, you know, and I think Tom shared some of the details before around, you know, the thinking around this is that for highway autonomy, you know, generally about $2,500 worth of addressable content on a vehicle on average, you know, for proactive safety on the order of $1,000 of addressable content value on a vehicle on average. You know, that kind of gives you a general sense of this and still allows, you know, profit margins, you know, for, you know, non-trivial nature for the OEMs as well. When it comes down to it, you know, our goal is obviously being able to make sure that we can, one, actually make it possible to be able to have these capabilities and make that addressable in the first place. Second is to be able to get the largest slice of that pie there. In some cases, it may be the whole thing. In some cases, it may be 75% of it. In some cases, it may be 25% of it, you know, but usually more than that. That is a dynamic model that we have as part of the holistic Sentinel offering. In terms of Sentinel versus Mobileye, is it complimentary? Is it, you know, competitive? There has been a lot of questions about, you know, how sticky your work with Mobileye on the robotaxi is ultimately going to be. If you could address that as well, that would be helpful. Yep. Yep. I mentioned, I think the thing is with all of these different programs, I mean, there's a reason why this time right now is so pivotal of getting designed into these different programs. At the same time, of course, you know, there's no question companies see the value of just how critical and fundamental this is, you know, to this entire industry and as a catalyst for everything going forward and the kind of ASPs that you have. You know, this is not a, you know, a $40 camera that we're selling on a vehicle. You know, there's serious content value and serious margins to be had as part of this. When it comes down to it, the important part here is though, is that the correct answer is ultimately no, we do not really compete with, you know, frankly, I mean, you brought up the name Mobileye, but we do not really compete with any of those guys when it comes to an autonomous vehicle standpoint. It is a little bit hard to think of. It is like, okay, well, when you say you are, you know, you are making this transition or have made this transition from a LiDAR company to this, you know, autonomous vehicle company from a full stack standpoint, does that mean you are competing with Waymo, Cruise, you know, Mobileye, you know, Aurora, whatever it may be? The answer is actually no, not at all. Again, what we are very, very focused on is not the robotaxi market for this. That does not mean that we will not work with those companies and we sell into those companies and that is totally fine. It is a model that we support for any foreseeable future as part of this, which is great. When it comes to the actual production vehicle market, there is really nothing there that actually supports this. I mean, from a software standpoint, that is why we have been so intent on developing this and seeing this through, you know, and when it comes to, when it comes to passenger cars as well as trucks for that matter as well, which is often an overlooked area for this. That is where the Zenseact team comes into play. That is where all this, again, we are focused on production hardware, production software. This is not an R&D vehicle, you know, that is at a test stage with a supercomputer in the trunk. This is something that's actually capable of being put onto these vehicles. That's why it's just, you know, so far advanced when it comes to all of these things, and why it's so meaningful. Okay. And then just in terms of the stickiness, once you're designed into one of these, how, you know, how difficult is it to just switch sensors? You know, it's really just a question of to what lengths. I mean, the reality is that there are a lot of fundamental dependencies that happen, you know, when you work with different companies, when you integrate the software on top of the hardware and do the different data collection aspects of all this. It's effectively impossible to just, you know, one-to-one swap out a sensor from another sensor that's already designed in. That's not to say that you can never do those things. It just means that you have to rewrite a huge portion of your code base, recollect the data, do all of these other things all over again, you know, which could take years' worth of work and possibly not even practical or economical. I mean, at the end of the day, you know, the platform design cycle and lifetime over the different OEMs, like I mentioned, you know, is as many on the order of generally like seven years, you know, with these things with a few year lead up oftentimes, you know, when it comes to this. That's where, you know, it's just so important to be able to get designed in the platform early on, start working with these companies and these things. At the end of the day though, I don't really see this as a, this is not like a primary mode of defense, so to say, for us. Like we have the technology that actually solves the problem. Like we have that today. Like there's really no dramatic incremental benefit. Like if you wanted to display something, you would have to have something that actually also meets the specs like we do in terms of what's required, but at the same time does so with a validated product that's already proven out that has the economies of scale, which is a little bit of a chicken and the egg problem. When we already get the eggs, you know, makes a difference. On top of that, you know, we have the data, we have all this other stuff. That's why it's, you know, I mean, not that we're worried from a technology perspective either. You know, we have, you know, again, the only way from a physics standpoint we're aware of this as well as the largest patent portfolio in the industry. You know, it's pretty much more than all the other major players combined. Yeah, I think that's kind of how we think about the problem. I got it. Thank you. That was very helpful. Outstanding. On behalf of Luminar, we'd like to thank our tremendously supportive investor base as well as the analyst community for joining us today. With that, we can conclude our inaugural business update call. Thank you very much.