Rivian at TD Cowen Conference: EV Strategies and AI Innovations

On Tuesday, 03 June 2025, Rivian Automotive (NASDAQ:RIVN) presented at the TD Cowen 9th Annual Future of the Consumer Conference, outlining its strategic initiatives in the electric vehicle (EV) market. The company highlighted its focus on brand positioning, customer satisfaction, and technological advancements, while also addressing challenges such as demand volatility and tariff concerns.

Key Takeaways

• Rivian plans to launch its R2 and R3 models, aiming to capture a broader market with prices starting at $45,000.
• The company is transitioning to an AI-driven autonomy platform, AV2.0, which promises enhanced safety features.
• Rivian holds a 35% market share in the electric SUV segment above $70,000, with an average selling price of $90,000.
• A $5.8 billion software licensing deal with Volkswagen highlights Rivian’s potential for technology licensing to other manufacturers.
• Tariff discussions and rare earth metal supply concerns impact new order rates and market volatility.

Financial Results

• Market Share: Rivian dominates the electric SUV market above $70,000 with a 35% share.
• Average Selling Price (ASP): The company’s flagship products have an ASP of approximately $90,000.
• R2 Pricing: The new R2 model will be introduced at a starting price of $45,000.
• Licensing Deal: Rivian’s $5.8 billion software licensing agreement with Volkswagen underscores its technological prowess.

Operational Updates

• R2 Production: Rivian is set to begin production of the R2 model next year, simplifying logistics by reducing trim combinations.
• Demo Drives: The company recorded a surge in demo drives in Q1, reflecting growing consumer interest.
• Autonomy Platform: Rivian’s Gen 2 autonomy platform, launched last year, is AI-centric and rapidly expanding in capabilities.

Future Outlook

• R2 Launch: Initially, Rivian will release higher-priced, fully loaded R2 configurations, followed by the $45,000 version.
• Autonomy and AI Day: Scheduled for the fall, this event will showcase Rivian’s advancements in autonomy features.
• Safety Improvements: The company aims to significantly enhance vehicle safety through its AI platform, targeting a drastic reduction in accident rates.

Q&A Highlights

• EV Market Volatility: Rivian acknowledges the influence of macroeconomic factors and trade news on consumer behavior.
• Rare Earth Metals: The company addresses supply chain concerns and the impact of trade tensions on production.
• Tariff Discussions: Ongoing tariff negotiations are affecting order rates and market dynamics.
• Autonomy Licensing: Rivian sees opportunities in licensing its autonomy technology to other manufacturers.

In conclusion, Rivian’s participation at the TD Cowen Conference provides a detailed look into its strategic direction and market positioning. For further insights, readers are encouraged to refer to the full transcript below.

Full transcript - TD Cowen 9th Annual Future of the Consumer Conference:

Unidentified speaker, Interviewer: Great. So, a lot to cover. We’ll get right to it. Maybe just to kick off, RJ, since we are at a consumer conference, talk to us about what’s led to Rivian’s success in such a difficult industry where so many other kind of EV startups struggle to build a brand, to build demand. Kind of what set you apart?

RJ, Executive, Rivian: Yeah, I mean, uniquely in the transportation automotive space, you’ve got a product that’s really complex in terms of the number of decisions and the number of components that must come together ultimately make the product, but just doing that isn’t sufficient. The the combination of attributes, positioning, design, of course price point needs to really connect with the market and so not only the product market fit but the the the result, the aggregate result of all those features needs to come together on a brand position that’s really compelling and so we spent a lot of time as a company early on debating what the positioning of business was going to be. We had a couple of pretty big pivots and ultimately landed on this really extreme point of clarity around creating a brand that helps both inspire but also enable people to go do the kinds of things you want to take photographs of and that brand position has proven to be really elastic in in not only supporting our flagship launch product line but supports what we call R2 and R3, are follow-up much lower priced products, which we’re about to launch launching next year.

Unidentified speaker, Interviewer: Awesome. Tell us about Rivian’s customers. You know, are they first time EV buyers? Do they tend to come from same segments or in the pickup and SUVs? And as you launch R2 and then R3, how are you thinking about that customer profile and how it might Yeah,

RJ, Executive, Rivian: we know, when we started to think about the product and the position of the product, we did a bunch of studies that would look at what was our ideal in terms of customer demographic and what we’d hoped would happen was we’d have a broad spread of customers that come from different segments, different political backgrounds, different cultural backgrounds and of course, we had folks, we’d hoped to have folks who would come out of non EVs which would be to say that Rivian creates new EV customers and that has proven to be true. So we have the vast majority of our customers have not owned a EV before, which is great. The other thing is we wanted that first time EV experience and the first time experience with Rivian to be really remarkable. You know, coming back to your first question on brand, there’s a lot of ways to look at the strength of the brand, but one of the helpful ways is to look at how external externally validated folks look at this. And so Consumer Reports does an annual brand survey where they actually survey customers of every brand and every company.

And for the last two years now, we’ve come out by far as the number one rated brand in in across all auto companies. So this past year, I think we won by something wild like thirteen, fourteen points. So it’s a significant margin between us and the next closest and maybe at a similar level of, you know, success in the year prior. And that of course translates to market share. So our flagship products which we have today are the dominant market share players.

So if you’re looking at an electric SUV over $70,000 we have a commanding level of market share around 35%, and our ASP is much higher than that. Our ASP is around $90,000. And so the hope is we can translate the brand success, the customer satisfaction, and the market share penetration we’ve had at this relatively narrow TAM, you know, very high price point, into the much more affordable price point with RR2, which is a, you know, starts at $45,000.

Unidentified speaker, Interviewer: Terrific. And I think last year at the Investor Day, you shared that brand awareness in The US is only about 40%. Mhmm. Any updates on that metric? Kind of where you’ve seen that trend?

RJ, Executive, Rivian: It’s continuing to grow and I mean, for for all the obvious things. We we have efforts to drive that through marketing and you know, we have some endorsements we have or partnerships we have with with specific brand advocates. But one of the most powerful things is just having more of them on the road. And so if you’re in Southern California, Northern California, Seattle, Portland, increasingly here along the East Coast, you’re seeing more, but like on the West Coast, you just they’re everywhere. You know, a good metric is my drive to school with my kids is a drive to my kids’ school is about 10 miles.

And two years ago, counted about four or five rivians on the way in. Today, it’s every trip’s over 25 rivians. It’s Of course, we’re in Palo Alto area, is very dense rivine population, but we’re seeing them more on the roads and it just helps drive overall awareness.

Unidentified speaker, Interviewer: Terrific. And maybe, Arjun, on that point, because I think you raised an important point, right, when we look at the EV market today, it’s kind of been very uneven from a geographic basis. When you’re thinking about the R2 and R3 launch, could those potentially catalyze demand in the kind of central part of the country? Are there things you can do help promote that, either in product or in brand?

RJ, Executive, Rivian: Yeah, mean, just to call it out, I mean, like Santa Clara County, EV purchase rate’s like over 40%. Across the whole United States, it’s around 8%. And so you do see this real clustering of EV sales, particularly on the coast as you called out the center of the country, little less so. Part of this is just due to lack of choice. So in the combustion world, there’s three on the order of 300 different nameplates you can pick from, so that’s brand and product line.

In the EV and a lot of those are very compelling, in the EV space under $50,000, which is where the majority of the market is, there’s very very few and I would argue, like honestly, like well under what, you know, fingers on your hand, it’s like a couple and of course, you see that manifest in significant market share accumulation with one company with Tesla and Tesla’s Model three and Model Model Y are exceptional products, but it’s one specific point of view as to what a vehicle is in terms of form factor, design aesthetic, brand positioning. And to go from 8% to to 20% or 30% or ultimate %, we’re gonna need more choice than just one compelling option. And so we need to see market share much more distributed and much more players in the space.

Unidentified speaker, Interviewer: Yeah, actually, I couldn’t agree with you more on that level of choice. Maybe one related question to that is, as you’re planning for R2 and then R3, how are you thinking about the number of trim combinations you would offer? Because on one hand, if you go with few trims, it’s maybe more efficient for your manufacturing, maybe it’s better for margins in theory, then maybe you do limit the choice of having some design changes. How are you thinking about that level of choice within your next kind of platform to try to widen out the buyer base and

RJ, Executive, Rivian: Yeah. On r one, we had a lot when we launched, we had a lot of trim combinations, too many in terms of color combinations with powertrain and battery pack. On r two, we’ve really narrowed that, but we’ve done it very thoughtfully by combining and putting essentially into baskets different sets of features and different combinations of color and interior trim. And what that’s allowed us is to dramatically reduce the SKU count and simplify logistics beyond just the production side, but actually simplify the movement and placement of vehicles for sale. And one of the unique things about being a direct to consumer brand, Tesla of course has this as well, is we have to be very thoughtful around where we place inventory.

We don’t have a traditional dealer system that absorbs inventory and therefore absorbs working capital. It’s on us to own that and so we try to minimize that as much as possible, but customers want to, you know, you walk in, you see a vehicle, you like it, you like to take delivery of it that day or within the next few days, and so simplification of that portfolio actually helps with the delivery timeline. But we’re talking about like low hundreds in terms of number of possible build combinations, but that’s an order of magnitude less than what we have on R1.

Unidentified speaker, Interviewer: Terrific, and as we start production kind of next year of R2, you know, how soon thereafter should we expect a $45,000 version? It’s always tempting to kind of go high initially, low volume, high The pushback to that is that maybe then consumers, you know, start to think of the vehicle as priced higher than it actually is once

RJ, Executive, Rivian: the volume mean, we talk about this all time. We launch configuration which, you know, it’s like balancing, everybody wants something slightly different but we want to have a very narrow set of build combinations that we start with to simplify logistics, simplify production and that initial narrow combination of vehicles we’re building will be higher priced because it’s a fully loaded vehicle. And then shortly after launch, we’ll introduce different specs, but importantly, our our our $45,000 spec. But it’ll be pretty quick. Now the the big challenge we have on r two, which is similar to r one, is there’s a really large demand backlog and r one, really didn’t get this right.

You have a bunch of customers. If we say we’re starting production on x date, everyone regardless of when you put your order in believes that you’re getting your vehicle on that day and so it’s not as if we can like instantly like deliver hundreds of thousands of vehicles on day one of production so there’s going to be a long period of time for some of the some folks to get their vehicles. And it’s just expectation management. So we’re gonna be doing a lot over the next year to manage folks’ expectations to say, look, even if you have enough reservation, you may not get your vehicle until 2026, which is it’s a great problem to have, but it is truly a challenge when you have this much of a built up demand backlog.

Unidentified speaker, Interviewer: Terrific. Maybe shifting back to the near term, any updates on just the current demand environment? And it’s been a bit of a choppy start for the EV market. How are things trending?

RJ, Executive, Rivian: Yeah, for us with today with our R1 products, the R1 team, R1 asset truck and an SUV, those being premium flagship products, there is the inherent challenge of that segment being more compressed where you see consumers maybe deciding instead of buying a $90,000 car to buy something that’s more affordable. And so while the overall volume is still strong for the industry, the volume at the segments segments that we’re operating in is becoming more, you know, just more compressed. Now our share within that segment, as I said before, is is very strong. We have the highest share in that in in the segments that we’re in. But but we really look at this and say, we wish we could have r two ready because the the price positioning of r two between, you know, 45 and $55,000 really hits the bullseye of where the market sits today.

The average new car price is around $49,000 so it’s a really nice positioning and the product packaging and overall layout is just perfect for the market.

Unidentified speaker, Interviewer: Great, and I think one of the interesting things related to that that came out of your Q1 earnings is I think you had record demo drives in Q1 despite the just overall more challenging kind of sales environment for the industry. Do you think that record demo drives are potential indicator pent up demand? Like, when the macro picture improves, you know, maybe you do kind of see a bit of a snapback just because people are still engaged very much.

RJ, Executive, Rivian: There’s so many variables right now that influence consumer behavior and we’ve seen a level of volatility just in daily order rate that has been very unique to the last, call it six months. Just because of the overall macro concerns around what’s gonna happen to to the economy. And so you see folks as, you know, if if trade relationship if tariff discussions go a certain direction, we see demand move in different directions. If we see the perception of how some of the tax credits will be interpreted or enforced or changed, we see big swings in behavior. But it’s in in many ways, think the the highly volatile nature of, like, we may have we’ve had situations where we’ve had the best day ever in terms of orders followed by one of the worst days ever, which makes no sense, but it’s it’s just the swing of the news is driving behaviors of consumers, and I think that’s probably gonna continue until we see things stabilize with with just the overall trade environment.

Unidentified speaker, Interviewer: Terrific. And maybe one more near term question, and we’ll get into the economy platform, which is very exciting, but any updated thoughts on tariffs? There’s been some concern in the industry around rare earth. Any updated thoughts around those topics?

RJ, Executive, Rivian: The rare, just as context, the rare earth metals issue is big issue, not just for automotive, but many industries, specifically in automotive, to make the electric motors that are used in every vehicle on the road today, whether it’s us or Tesla or someone else, they’re using magnets and those magnets have heavier earth metals that go into them. And if you were to do a Google search and say, where does the world’s dysprosium, which is a heavy earth metal, where does that sit? You’d say, oh, there’s lots of dysprosium. It’s in many countries and many places. But the challenge is that by far and away, the vast majority of the processing of most of these materials resides in China.

And so as the trade tensions between The United States and China rose, China put in place export controls that effectively limited the export of these rare earth metals to The United States, and that was a huge concern. Surprisingly not talked about very much because it wasn’t just electric vehicles, but all medical imaging equipment, lasers, you know, lot of very important industries to us, the defense industry, frankly, would just be shut down without rare earth metals. And so we spent a lot of time figuring out how we would solve that in, call it, less than elegant supply chains to to be able to continue production. But fortunately, as the trade tensions with with China have eased, those export controls have also been eased, and so those rare earth metals are are starting to move again, is which is really important. But it’s a reminder, I think, from a from an industry point of view, from a supply chain point of view of of some of these really critical dependencies that we have on on other countries, and here specifically China.

And so we see a heightened focus right now on mid to longer term solutions to remove either remove heavier earth metals from the design, which with which are new technical solutions or to find new ways to create those processing or downstream supply of those materials which is not something you do in a matter of months, it’s something that will take many many years to do but there is, I’d say, renewed investment interest in that space.

Unidentified speaker, Interviewer: Terrific. Shifting to the autonomy platform, obviously, have a big part of the Rivian story as well. Maybe provide kind of your vision of what the autonomy platform can be in the next few years, how you’re approaching this megatrend maybe differently than some of the other companies out there.

RJ, Executive, Rivian: Yeah, mean, maybe a little bit of history on autonomy because it does all link together. So if we think, wind the clock back to like, call it 2014, ’20 ’15, is when we start to think about vehicle autonomy, the idea of a vehicle driving itself in a more substantial way and the way those systems were developed is you would have a perception stack, so some combination of cameras, maybe radars, maybe lidars, a set of sensors that is perceiving the world that would take in imagery or take in information and process it. So they’d identify objects, we would then classify those objects and those classified objects would have vectors associated with them, so velocity and acceleration in x, y and z. And all that object based information would then be handed to a rules based planner. When I say rules based planner, a planner that’s has a set of rules that makes determinations around what to do based upon a pre programmed set of intended behaviors for all those objects.

And so that approach is what you saw Waymo launch with, that’s of course Tesla autopilot was built with that and what you’ll now hear that called is you’ll hear people say that’s 81 dot o. And so it’s a rules based program solution. Just a couple years ago, in the late twenty twenty one, early ’20 ’20 ’2 time frame, as we start to see the use of transformers and full neural net approach to language emerge with the idea of these large foundation models and large language models. That same approach started to be adopted for autonomous vehicles. And so what has dramatically shifted how we develop these systems, including ourselves, our Gen one vehicle that we launched in 2021 was a rules based solution.

It is not it’s not the right technology topology for the long term. And we launched our Gen two about this time last year, which is completely designed around AI. And to be completely designed around AI to define or to describe what that system looks like, different than having a bunch of perception that then classifies objects and associates vectors with those and hands them to a rules based program planner, you now take all the data from your perception stack before making any decisions or any determinations on what those things are, you fuse that information together to create a very accurate and robust view of the world and you then take actions on that and the actions are informed by a large scale, large parameter foundation model that’s built through a data flywheel that you’re training by observing the operations of the vehicles in these different conditions. And so you create a true neural net, a true model of how to behave in the world. And much like the way we as humans would learn to drive a vehicle, we’ve now taught our AI systems to do the same.

And the reason I call that out is there’s truly zero carryover between an AV one point zero and an AV two point zero solution, and the ingredients necessary to be successful in the long term are very different than what was important to be successful in AV one point zero. And so what you need to be successful now is you need complete control complete control of the perception stack, meaning your cameras have to provide raw information, they can’t go through a, you know, any sort of filter or any sort of layer of abstraction, let’s say through a tier one supplier. We need raw information from your cameras, if you have them your radars and if you have them your lidars, you need to build a robust view of of the state of the world real time in the vehicle with your inference platform. That data as well needs to be piped offline through a really robust data platform that forms this really large data flywheel that you’re using to train offline this model. And this offline model is a large parameter, it’s a multi billion parameter model that is understanding and building an understanding of how the physical world works and what’s running in the vehicle on inference is a distilled version of that.

So it’s a smaller parameter model, but it can run real time in the vehicle. And so to do that, you need control your sensor stack, you need control your data platform in the vehicle, you need control the inference platform in the vehicle, you need a ton of GPUs, and you need a really efficient way to move data between the vehicle and the cloud offline. And you don’t want to do that through LTE because you’ll spend a fortune, so you need to have a set of vehicles that have really robust WiFi policies and users that have selected to enable WiFi and a whole bunch of incentives to drive that to ensure you have a low cost way to move all this data. And so there are very, very few companies that have architectures like that. Of course, Tesla’s in that camp.

We are also in that camp. And for this system to work, you’d benefit from the scale of the flywheel, meaning you need a large enough car park for it to start to create some of the momentum. And so on our gen two vehicle, we architected everything, contemplated this contemplating this. We launched it on our one middle of last year and that fleet size has grown and the data flywheel has become very capable and we’re now starting to see the beginnings of this really nonlinear growth curve in terms of features and capability. And we’ve announced we’re having an autonomy and AI day in the fall, and we wanna really pull the sheets off of everything that’s coming in terms of pipeline.

This is I think this is the most important area of the business. It’s our biggest by far spend category in r and d, and I think there’s a lot of misconceptions around how to design these systems, what a daily what what a true data flywheel looks like. When I say that, you know, how you architect the the the dedicated cluster of GPUs, what your inference platform needs to do and how it needs to be architected. There’s a lot of very different, strategies than what we we saw for ten years prior. And so I couldn’t be more excited about this part of our business.

We’re just now starting to see it’s like classic. You spend amount of time, effort, and money on all the stuff below the surface and finally it sort of comes up above the surface and you start to see it in the form of customer benefit. So we’re just starting to see that now, but by the fall, customers will start to get pretty fairly trained on this rapid rate of progress on the features in the vehicle. And that’ll coincide with when we have our AI day.

Unidentified speaker, Interviewer: Terrific. Artu, when we think about Eyes Off, where everyone’s trying to get to, what do you think is the killer app for consumers? Is it highway? Is it sharing robo taxi? Is it other things that the vehicle could do?

There’s so much.

RJ, Executive, Rivian: Yeah. Well, this is really an important point on on on, like, this new generation, this AV2.0 as it’s often referred to, which is in the in the previous world, you you had a you had a a two pronged approach for how you in AV1.o, you had hardware light systems that sort of capped out because of the perception stack at a level two feature. So hands on wheel, eyes on the road. And the other approach or topology was to have like really hardware heavy, you know, a la Waymo, but you know, tens of thousands of dollars of perception and compute the vehicle, but that would raise the ceiling, if you will, up to a level four, you know, hands off, eyes off, you know, occupant or driverless vehicle. And what’s happened as you move to an AI centric approach is it’s the same stack.

It’s the same architecture. It’s just a continuum of the the robustness of the model, the robustness of the perception stack to identify and see challenging corner cases, and the robustness of that sensor stack in informing and growing and strengthening the model. And so for us, we look at what we’re now developing as being on this continuum where there’s not a there’s not a an artificial or glass ceiling that exists. It it it truly can scale to level four, but it will take further increases in compute onboard, so inference, further improvements in perception, and a lot more training of the model. But the model is accretive.

The training that you do with a lesser sensor set informs the brain, if you will, the neural net, in the same way that we as humans, as we develop better senses and grow as humans, our brain doesn’t throw away the information we gained from ages one to five to replace it with better information we get from ages five to 10. It’s just, it’s it’s aggregate, it’s aggregating together. So I say all that because I think the there’s a few big break points revenue point of view or go to market point of view that are really important. So in a personally owned vehicle, we think one of the most valuable is getting to highway hands off, which we’ve done today, but then hands off plus eyes off, which means without needing to, you don’t have any need to look at the road, you can be doing emails, you can be reading a book, you can be having a conversation with your kids in the back seat, but you are not an active participant in any way to whatsoever in the operation of the vehicle. And so that hands off, eyes off, might hear called level three.

So you’re in the vehicle, you might be asked to retake control but you’re given twenty seconds to retake control. It’s not a dynamic, it’s not a, you know, active dynamic retaking of control. I think that naturally makes a lot of sense on a highway because you have large chunks of time, but over time that becomes valuable everywhere. So our view is we go, we’re hands off today, go hands off, we add eyes off fairly soon, we then go hands off, eyes off beyond highways, so inclusive of your feeder roads, your surface roads, suburban environments, which is sort of full scope level three. And then the natural step beyond that is to remove the need for a driver in the vehicle so the vehicle can reposition itself or move itself when it’s empty.

But all that exists along a common technology backbone where everything that’s being built is building towards that end state.

Unidentified speaker, Interviewer: Interesting. RJ, as you build the autonomy platform and launch more features, clearly the technology can also accrue to vehicle safety. Can you talk about, in a couple of years, how safe are Rivian’s vehicles? Are there opportunities for you with an insurance? Yeah.

Reduced cost of ownership? How big could that be for the I

RJ, Executive, Rivian: mean, to be clear, we’re like if you use Rivian’s what we call highway feature today where you can get on the road and it drives itself on the highway, it’s remarkably safer than a human, than the best human. And so we have an insurance offering, and one of the reasons we built the insurance side of our business was contemplating exactly this. And your rate actually goes down the more you use our driver plus feature. So if, let’s say, you use it all the time when you’re on the highway, you will have a notably lower rate because the risk profile is dramatically reduced. And so I think this will just be a common trend, and it’s all the obvious things.

You know, we as humans are, we’re good at dealing with complexity, we’re actually quite bad at dealing with, like, boring driving, so we end up texting, we end up looking away, we end up getting distracted. And so if you look at the number of deaths in vehicles today, it hasn’t really improved that much despite the amazing progress we’ve made in passive safety, you know, ability for a vehicle to absorb a crash because the number of distracted accidents has gone up so much. And so I do think we’re at sort of, call it peak automotive death rate. I mean, that’s not a very glamorous way to describe, but it’s I think we’re gonna start to see that start to come down dramatically as we see humans play less and less of a critical role in the operation of the vehicle. And with that, you’ll see insurance rates come down.

But the challenge with autonomy is it’s not like you being 10 times better is enough. So just to put some scale to this, in The United States alone, which is a relatively safe driving environment as far as, countries go, we have over forty thousand deaths per year in vehicles. So if every car instantly was driven by the car itself and not the driver, and we said there was an order of magnitude of 10 x improvement in safety, we would still have four thousand deaths, which is nowhere near good enough. You can imagine how hard it would be for us as businesses to operate if we had that many people dying because of mistakes of the vehicle. So it needs to be orders of magnitude better.

We think of it as four orders of magnitude better, and so that will come and I think we’ll see that very rapidly in highways where the idea of a vehicle crashing on a highway when it’s in an autonomous mode will be near zero, and then we’ll translate that into these more complex urban and suburban environments.

Unidentified speaker, Interviewer: Terrific. On the hands free eyes on feature you have today, safer than a human, was that performance better or in line with what you were expecting internally when you launched it? I’m just curious if the inference and the training is actually doing better than what you

RJ, Executive, Rivian: Well, the metric for us, like the acceptability criteria for us to say this is a feature that we’re gonna offer, it had to be meaningfully better. So it was, I would call it a requirement, like we wouldn’t have launched it if wasn’t better.

Unidentified speaker, Interviewer: And how’s customer reception been?

RJ, Executive, Rivian: Great, great. I mean, this just blows my mind. Today on our vehicles with a narrow set of applications, meaning highways, it’s not every road, a very significant portion of our miles, double digit percentage of our miles overall are driven by Rivian, not by the driver. And so you can imagine as we grow to every highway, every surface road, every suburban street, we think that once you use a platform like this, it’s really nice. And when you get your time back, I think most often people choose to say, I may enjoy driving, but most of the time I’d rather just have the car drive me.

Interesting. And so we think that it’s a very sticky take rate.

Unidentified speaker, Interviewer: Wow. I know we’re out of time, I’ll sneak one more in, RJ. Maybe early days in the autonomy platform, but any thoughts on licensing opportunities in the future at least?

RJ, Executive, Rivian: Yeah, I mean, we have quite a bit of experience in working with other companies, so we have a very large partnership with Amazon. Amazon’s also our largest shareholder. So we build, if you see their electric vans, I don’t know if they’re operating here in the city, but they’ve got the largest deployed fleet of electric delivery vans in the world and we actually design and build those in partnership with them. And then more recently, we have a large $5,800,000,000 software licensing deal with Volkswagen where we provide them with our base operating system and some of our core compute platforms. And I think that certainly as the auto industry moves to become much more dependent of our own software and technology, in particular AI, traditional car companies don’t have these competencies and it’s not something that they’ve built.

And, you know, we see a lot of potential business in providing some of this technology to other manufacturers.

Unidentified speaker, Interviewer: Terrific. I think we’ll leave it there. Was a great conversation, Arti. Thanks so much for joining me in thanking Thank you.

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