No PriorsRivian’s Roadmap to AI Architecture and Autonomy with Founder and CEO RJ Scaringe
EVERY SPOKEN WORD
35 min read · 6,641 words- 0:00 – 0:35
Cold Open
- RSRJ Scaringe
By twenty thirty, it'll be inconceivable to buy a car and not expect it to drive itself. Every single one of our cars, we want to have the ability for it to operate at very high levels of autonomy. Radars are extremely cheap, LiDARs are very cheap, but the really expensive part of the system is actually the onboard inference, an order of magnitude more expensive than any of the perception stack. My view is EV adoption in the United States is a reflection of the lack of choice. As consumers, we need lots of choices. We need to have variety. We self-identify with the thing we drive. The world doesn't need another Model Y; the world needs another choice.
- 0:35 – 0:58
RJ Scaringe Introduction
- SGSarah Guo
[upbeat music] Hi, listeners. Welcome back to No Priors. Today, I'm here with RJ Scaringe, the founder and CEO of Rivian. We're here to talk about their autonomy strategy, proprietary chips, their coming R2 model, whether Americans want EVs, and what our relationship to cars is going to be in the age of AI. Let's get into it. RJ, thanks so much for doing this.
- RSRJ Scaringe
Thank you for
- 0:58 – 5:19
Rivian’s Autonomy Evolution
- RSRJ Scaringe
having me.
- SGSarah Guo
So Rivian's already, uh, an incredibly cool company. How did you decide it was gonna become an autonomy company? When did that happen?
- RSRJ Scaringe
I mean, from the beginning, we thought of it as a transportation and mobility company, and in fact, even before Rivian became Rivian, when I was thinking about what's the first products, it was unclear what kind of car it would be, but or even if it was a car. But it was always clear we wanted to be at the front edge of helping to redefine what does it mean to have access to personal transportation. And so autonomy has always been part of the strategy, but it's now fully coming to life with the technology that we're building.
- SGSarah Guo
And when you think about the function of Rivian, there's transportation-
- RSRJ Scaringe
Mm-hmm.
- SGSarah Guo
-there's also the experience. Like, wh- when-- how long ago did you guys start investing in the autonomy strategy here?
- RSRJ Scaringe
Yes, we launched R1 in, um, very end of twenty twenty-one.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
And we used what I'll broadly characterize, like, a one dato approach to autonomy. So we had a perception platform. We used a, a third party, a front-facing camera that was essentially a third-party solution that then plugged into an overall framework that we built, but it was all rules-based. So the camera was fed a rules-based planner. The planner would then make a bunch of decisions around the feeds from the perception, and it was... You know, the, the moment we launched, we knew it was the wrong approach, but it was the thing we'd started working on, uh, well before the launch. And so at the end of twenty twenty-one, beginning of twenty twenty-two, we made the decision to completely reset the platform. And-
- SGSarah Guo
Was that a hard decision?
- RSRJ Scaringe
No, 'cause it was so clear. When we made, we made the-- When you're building something like this, you're, you recognize you're gonna spend many, many billions of dollars creating it. So we knew this, like, at the core of transportation is, is driving, and at the core of that is a shift to having the vehicle be capable of driving itself. And so we made the decision to redo it, like, clean sheet, you know, no legacy of what we had built in the Gen One. And that first launched from a hardware point of view in the middle of twenty twenty-four, uh, so that was with our Gen Two vehicles. You know, not a single line of sha- shared code, not a single piece of common hardware on the perception or on the compute side. And, uh, and then we had to build, like, the actual data flywheel, so we had to grow the car park to build enough of a data flywheel to then start to train the model. And what we showed in our autonomy day late last year, late in twenty twenty-five, was the beginnings of a series of really, like, super exciting steps of how this is gonna grow and expand. I say this all the time, I, I think of not just for Rivian, but I'd say for the auto industry in general, the last three years, compared to the next three years, are gonna look very different. So the rate of progress that we saw in autonomy between, let's say, twenty twenty and twenty twenty-five or twenty twenty-one and twenty twenty-five, and what we're gonna see between today and, let's say, twenty twenty-nine, twenty thirty are-- they're completely different slopes. And that really comes back to, you know, entirely new architectures now being used to develop self-driving, actually, truly AI architectures, whereas before, these were not AI architectures in the, in the true sense. They were, they were, um, u- using machine vision, but really rules-based environments that we defined as, as humans. You know, we codified them, which is very different to how they're now built today.
- SGSarah Guo
You might actually have perfect timing here, in that, uh, I got to be part of investing in sort of the first wave of independent autonomy bets that were working with the OEMs at my last investing firm.
- RSRJ Scaringe
Okay.
- SGSarah Guo
But this is, let's say, eight, ten years ago.
- RSRJ Scaringe
Yeah.
- SGSarah Guo
And-
- RSRJ Scaringe
Very different
- SGSarah Guo
... uh, as you mentioned, there's several architectural revolutions since then.
- RSRJ Scaringe
Yeah.
- SGSarah Guo
And so for companies to make that shift from, you know, we're gonna have these separate-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-perception and planning systems to more end-to-end neural networks-
- RSRJ Scaringe
Yeah.
- SGSarah Guo
I, I ask because I felt it was actually quite a hard decision for people in choosing their partners-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-and internally from a, from a technical perspective.
- RSRJ Scaringe
Well, I think it-- I mean, you can see it. So there's-- If you go back to the very beginning of the idea of self-driving, a lot of effort, a lot of spend happened for companies to build these rules-based environments and to build these more classic systems. And when transformer-based encoding came along, you know, just a couple of years ago, and it shifted very rapidly to-- it was clear that the future state was gonna be neural net based. It was hard because if you're a company that's built all these systems, it's like, do I keep investing what I had? What do I, what do I do with all this work that was, was built before? And the reality is, is a lot of it is-- the vast majority of it's gonna be pure throwaway, um, because it wasn't like a gradual shift. It was a complete rethink of how things
- 5:19 – 10:06
Why Rivian’s Tech is Vertically Integrated
- RSRJ Scaringe
are architected.
- SGSarah Guo
How did you decide that this was going to be a, an in-house effort-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-versus a partner effort? That, given-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-most people who made cars-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-said, "We're gonna go partner-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-or buy something here."
- RSRJ Scaringe
I, I guess the emotional/philosophical is on things that are really important, we've taken the approach of vertically integrating them.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
So electronics, our software, all the high-voltage systems in the vehicle, so things like motors, inverters, uh, all the power electronics, these are all things we, we develop and build in-house. And in a few cases, you know, we had to start with something that was either off-the-shelf or partially off-the-shelf, but today, all of that's completely in-house. And in the case of self-driving, we knew that long term it needed to be something that was developed internally. Uh-... We started, as I said, with a mobile-eye-centric solution, which a lot of folks did-
- SGSarah Guo
Right.
- RSRJ Scaringe
-particularly in like, you know, that twenty fifteen to twenty twenty-one timeframe. But when you really look at what's necessary to, to be successful in a neural net-based approach, there's a core set of ingredients that very few people have, and I think we uniquely have them. So first and foremost, you need to have complete control of the perception platforms. You need to have all the-- everything that the, the, the system is capable of observing, whether that's cameras, radars, or lidars, or some combination of all three. You need to have control of that, meaning there's no intermediary company that's, like, processing some of the information. And so that's powerful because you can then feed raw signals into your system. The system needs to be capable of triggering unique or interesting or noteworthy events that you can then use to train. That triggered s-- you know, those triggered moments need to then be captured, saved on the vehicle, and then when the, when the time arises where you have Wi-Fi, ideally, send it up. And the reason I say Wi-Fi, these are-- this is a large, a lot of data. So you could, of course, do it over LTE, but it's expensive, as you have to have a really robust data architecture in the vehicle. Then you need to be able to send it off, off-board, and use that with a lot of, uh, training, so with a lot of GPUs, to train a model. Companies that are either developing independent solutions that are not a car company, they typically don't have access to the type of mileage that we do, so the, the huge amount of data that our vehicles generate. Uh, if you're developing this from a sensor set point of view, you typically don't have the vehicle architecture and the vehicle car park. So we just came to the view that we have all these ingredients to do it really well.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
And it's, like, not an optional thing. It's the companies that do this well will exist. The companies that don't do this well, like, I feel really strongly this, they will not exist. They will shrink to, uh, shrink to nothing, asymptotically approach, you know, zero.
- SGSarah Guo
You think it can only be delivered in really a vertical, vertically integrated?
- RSRJ Scaringe
No.
- SGSarah Guo
Well...
- RSRJ Scaringe
I think, I think there's more than one, less than five companies outside of China that have the necessary ingredients to do this: the capital, the GPUs, the, the car park with an, you know, enough vehicles generating enough data. I'd say more than one, less than five is probably-
- SGSarah Guo
And the control of that whole training loop you're describing.
- RSRJ Scaringe
It's probably, like, more than one, less than three, maybe four. Like, there's a very small number of companies that can do this. I think the uni-unique spot we are in time right now is the one that-
- SGSarah Guo
May I ask explicitly, then? It's you, it's Tesla, it's Waymo.
- RSRJ Scaringe
Yeah.
- SGSarah Guo
Is that the three?
- RSRJ Scaringe
It's... I would include all three of those.
- SGSarah Guo
Okay.
- RSRJ Scaringe
Yeah, and there's maybe one or two others in the, in the mix.
- SGSarah Guo
Okay.
- 10:06 – 14:00
Levels of Autonomous Driving Technologies
- RSRJ Scaringe
this on, on every car.
- SGSarah Guo
You are taking, like, a sort of, you know, step-by-step approach-
- RSRJ Scaringe
Mm-hmm
- SGSarah Guo
-to levels of autonomy-
- RSRJ Scaringe
Yeah.
- SGSarah Guo
-at Rivian. How do you think about, um, how quickly you approach, like, level four or, you know-
- RSRJ Scaringe
Yeah
- SGSarah Guo
-the safety case around each of these things, how fast your team goes against this?
- RSRJ Scaringe
Yeah, I, I mean, this is... E-even this question is unique. It's just a few years ago, twenty, twenty nineteen, twenty twenty-one even, there was, like, very, like, very clearly delineated ways to approach autonomy. There was a level two approach-
- SGSarah Guo
Yeah
- RSRJ Scaringe
-which was camera-heavy, maybe with a few radars. And then there was a level four approach, which was, of course, had cameras, but had a lot of lidars. It was sort of inconceivable to think of the level two system becoming a level four, and similarly, the level four system was way overbuilt to even, like, conceivably think about putting that on every consumer vehicle.
- SGSarah Guo
Well, you didn't want the, the big work lidar-
- RSRJ Scaringe
Yeah, you didn't want all these parts
- SGSarah Guo
... and thousands of dollars in cost.
- RSRJ Scaringe
Yeah.
- SGSarah Guo
Yeah.
- RSRJ Scaringe
The tens of thousands of dollars of perception.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
So what's happened is those two worlds system, I think, have just started to very clearly merge, where the delineation between a level two, a level three, and a level four, um, in terms of perception and, and in terms of compute, has started to fade, and it's now essentially just remo-- like how capable the system is at addressing all these corner cases.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
And, you know, this is what's hard for a consumer to recognize. If you're driving a level two system or a level three system or a level four system, for ninety-nine point nine nine nine nine, like-
- SGSarah Guo
Feels the same
- RSRJ Scaringe
... identical.
- SGSarah Guo
Right.
- RSRJ Scaringe
The difference is, like, the fifth or sixth or seventh nine on that is these, like, extreme corner cases, and so I think it's actually led to a lot of confusion, where you'll be in a level two system, be like, "The car could drive itself," and you're like, "Yes, it can under-
- SGSarah Guo
Most of the roads-
- RSRJ Scaringe
Almost-
- SGSarah Guo
Millions of miles
- RSRJ Scaringe
... all conditions-
- SGSarah Guo
Yeah, yeah.
- 14:00 – 19:28
Importance of a Software-Defined Architecture
- RSRJ Scaringe
I, I always characterize like this: I think it's inconceivable for car companies to continue to operate at scale, like mass market. I think very niche, enthusiast realms-
- SGSarah Guo
Sure
- RSRJ Scaringe
... sure. But like at scale, without a software-defined architecture, which is even before you get to autonomy, just like, can you do OTAs? Do you have control of a, of a-
- SGSarah Guo
Sorry. W- w- can you define software-defined architecture?
- RSRJ Scaringe
Yeah, that's like before we even get to autonomy-
- SGSarah Guo
Yeah
- RSRJ Scaringe
... it's like these are like basics. So the way car-
- SGSarah Guo
Like core thesis of your-- one-
- RSRJ Scaringe
Yeah, yeah. So the way car electronic systems have been designed and built and have evolved, with the exception of Tesla and Rivian, every car on the road has what, what is, uh, called a domain-based architecture.
- SGSarah Guo
Mm.
- RSRJ Scaringe
So you could also call it function-based architecture. So all the functions across the vehicle, let's say chassis control or door system control or, uh, HVAC, your air conditioning system, all have little computers associated with them.
- SGSarah Guo
Right.
- RSRJ Scaringe
What we call ECUs, Electronic Control Units. And in a modern car, you might have a hundred to a hundred and fifty of these, and each of these run their own little island of software, and that little island of software is written by a supplier, more likely a supplier to the supplier.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
So you go to a, a tier one, and they hire a tier two, who writes the code base to run your HVAC, your--
- SGSarah Guo
Is this why it's impossible to debug like a software system? And-
- RSRJ Scaringe
It's also why it's really hard to do an update.
- SGSarah Guo
Yeah.
- RSRJ Scaringe
So imagine you have a hundred different islands of software-
- SGSarah Guo
Right
- RSRJ Scaringe
... written by a hundred different teams, uh, that all have to coordinate. And so if you want a feature, you know, something that manifests as a feature often involves combining functions from different domains. So a simple one to visualize is when you walk up to your car to get into it, you want it to automatically unlock, you want the HVAC to go to your preset, you want your seats to adjust, you want it to make an audible noise on the outside, you want the lights to do something.
- SGSarah Guo
Uh-huh.
- RSRJ Scaringe
You probably want the, the audio system to do something. Those are all different little ECUs in a traditional car.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
And the coordination cost in it is really high. It's very unlikely that a car company will make a change to that sequence because it involves coordinating amongst maybe ten different players. In contrast, on a, on a approach where you build a, a zonal architecture, where you have a very small number of computers, ideally, you know, one, two, maybe three, depending on the size of the car, that are running one operating system that control everything, it's very easy. So that sequence, you could make upd- updates to, you know, in a matter of minutes, maybe an hour, you could change the whole sequence of what happens when you walk up to the car, issue an over-the-air update, and it's very straightforward.
- SGSarah Guo
How often does Rivian update-
- RSRJ Scaringe
We do about-
- SGSarah Guo
So far
- RSRJ Scaringe
... one a month, and, uh, it's typically, you know, we add a couple of new features, we add refinements to existing features. We're listening to, like, what customers are seeing and asking for. But, you know, every month, the car gets, like, notably better. And it's created this really amazing dynamic where customers are, like, excited for the, for the update. They're like: "When's the next OTA going to drop?" The irony of all this is these domain-based architectures goes back to, like, how do we arrive at this? It actually goes back to fuel injection systems. So up until early 1960s, like every car on the road was completely analog. So there was no computers at all in the car. It was a hundred percent analog. And the first computers were there to drive the fuel injection systems, and car companies said, "This isn't a core competency. Let's push that little computer to run the fuel injection system to a supplier, and the supplier will make that." You know, and this is where you saw things like the Bosch fuel injection systems and never planned. It's sort of like a field of weeds. Then over the next, like seven-- sixty, seventy years, everything that became, you know, computer-controlled to any degree suddenly started to have a little ECU, a little computer associated with it, and it just, like, grew into this absolute disastrous mess that is a co- you know, today, the, the network architecture that's in truly every car on the road, with the exception of, of two companies. That what I just described is what underpins. We did a large, uh, software licensing deal, a $5.8 billion deal with Volkswagen Group-
- SGSarah Guo
Mm-hmm
- 19:28 – 23:20
Differentiating Autonomous Vehicle Models
- SGSarah Guo
So this might be an irrelevant question, but I'm curious.
- RSRJ Scaringe
Mm-hmm.
- SGSarah Guo
Um, do you think that the autonomy, like the models that maybe the three-
- RSRJ Scaringe
Yeah.
- SGSarah Guo
-maybe the one, maybe the five companies-
- RSRJ Scaringe
Yeah
- SGSarah Guo
... that come up with this, uh, develop, are fundamentally different over time? Because I spent a lot of time in the AI ecosystem, and-
- RSRJ Scaringe
Yeah
- SGSarah Guo
... the let's say, the language-oriented foundation models-
- RSRJ Scaringe
Yeah
- SGSarah Guo
... like, feel like they're converging at this moment in time.
- RSRJ Scaringe
Oh, yeah.
- SGSarah Guo
I, I look at a Rivian, and I'm like, I don't know, people adventure in that thing.
- RSRJ Scaringe
Yeah.
- SGSarah Guo
Do, do you actually want it to do different things, have different styles or capabilities?
- RSRJ Scaringe
Yeah.
- SGSarah Guo
Or is it really just like, uh, you know, as much autonomy as possible, safety case?
- RSRJ Scaringe
Well, first, I-- there's a, I-- yes, this is a great, this is a great question. Um-
- SGSarah Guo
I want my car to drive me also. [chuckles]
- RSRJ Scaringe
So like in the LLM world-
- SGSarah Guo
Yeah
- RSRJ Scaringe
... it, a lot of it has converged because it's the training data set's nearly the same.
- SGSarah Guo
Yeah.
- RSRJ Scaringe
Yeah, so we're taking the, the breadth of knowledge that's contained on the internet, and we're training models off of that. In the case of driving a vehicle, there is no internet of driving data, and so you need both a robust sensor set to be able to capture the data, and you need a car park, you know, that has enough vehicles in it. And so, of course, Tesla has the largest car park of vehicles by far. Our approach to this is we have a, a higher level of capability on our perception stacks. We have better cameras, we have radar, and of course, with R2, we'll have a lidar as well. A huge part of that strategy is not only do those cover corner cases better, so the cameras have incredible low light and high, you know, bright light performance, so the dynamic range of the cameras is stronger. We have more cameras, a lot more megapixels. Uh, we have radar, which is great for object detection, and a lidar, which is-- it's a very powerful tool for training the, the models. And so imagine eight hundred feet in front of us, there's a little speck, and to a camera, it's hard to figure out what that is, and historically, what we would do to train that is you would have a lidar sitting on the vehicle on a, on a, like a ground truth fleet to help train your cameras. Putting that on every single one of our cars is-- turns our entire fleet into this amazing training platform, this data acquisition machine. That was a core part of how we thought about our strategy, is we're gonna go, you know, not as heavy as, let's say, a Waymo on perception-
- SGSarah Guo
Mm-hmm
- RSRJ Scaringe
... but heavier than, let's say, Tesla, to build a really robust data platform on a vehicle-by-vehicle basis, and then with a car park that's gonna gr-grow significantly with the expansion with R2. Yeah, so I, I think first and foremost is there is no common internet data, so the data sets that we're gonna be picking up, though, are gonna be very similar.
- SGSarah Guo
Mm-hmm.
- RSRJ Scaringe
But, but you have to go acquire yourself.
- SGSarah Guo
But there's still different decisions about what data you care about acquiring, yeah.
- RSRJ Scaringe
Well, I think this is what [clears throat] to, like, how does a car feel? Ultimately, it needs to be safe, and the differences in the way it drives or feels are gonna be more about like, what's the UI, the user interface of it? You know, like even we just updated some of our features. We have three settings for how the vehicle drives: mild, medium, and spicy.
- 23:20 – 25:02
R2: The First Mass Market Autonomous Vehicle
- RSRJ Scaringe
makes it. You know, it's hard to say today.
- SGSarah Guo
Can we talk about what the R2 means for, like, the company-
- RSRJ Scaringe
Mm
- SGSarah Guo
... and some, some of the key design decisions here? I was just talking to Jonathan, one of your lead designers-
- RSRJ Scaringe
Yeah
- SGSarah Guo
... about the constraints and, you know, aiming for more mass market and more volume here.
- RSRJ Scaringe
Uh, I mean, yeah, you said it. It's, uh, so R1, it's a flagship product. Its average selling price is around ninety thousand dollars. It's the best-selling-- the R1S is the best-selling premium electric SUV in the country. So its electric SUV is over seventy thousand dollars, and we're the best-selling premium SUV, electric or non-electric, in the state of California. So it sells really well. You know, it outsells everything in its class, like a model-- Tesla Model Y, it outsells like two to one. But, um, because of the price, it's just limiting in terms of how much volume we can achieve with that platform.... And so R2 is the, our first truly mass market product with pricing that's, as we've said, gonna start at forty-five and allows people that are in that, you know, the average price of a new car in the United States is fifty thousand dollars, in that like forty-five to fifty-five thousand dollar price range, uh, I think to have a really great choice. And to date, there haven't been a lot of great choices there. You know, there's- I'd say there's like sort of singular set of great choices with the Model, Model 3, Model Y. Uh, and of course, that's, that's shown through the extreme market share capture of fifty percent, roughly market share. Goes up or down, but around that, call, uh, call it half the EV market is Model 3 or Model Y. So there's just such an untapped opportunity to pull customers out of ICE vehicles, out of internal combustion vehicles, with a choice that's, you know, has characteristics that are different and unique
- 25:02 – 29:05
Do Americans Want EVs?
- RSRJ Scaringe
relative to a Tesla.
- SGSarah Guo
These are like two substantive, should be rapid-fire questions, but they're, they're important for me to ask you. Do Americans want EVs? Like, why haven't they adopted them faster?
- RSRJ Scaringe
Well, yeah, I think to the last question, I think causality is always a hard thing to, you know, really understand, but let's zoom out here. The, the overall adoption rate in the United States of EVs is around eight percent. The vast majority of vehicle buyers are buying vehicles that are under seventy thousand dollars, with the average sale price of about fifty. And so if you look at the number of vehicle choices you have at a price point that's under seventy thousand dollars, depending on the year, this of course changes year to year, there's well in excess of three hundred different vehicle model line choices, putting aside trims and performance packages, but just in terms of like overall vehicle types. And so you can buy hatchbacks, minivans, SUVs, you know, two-seaters, convertibles. I mean, there's a whole array of different things you can buy. And in the EV space, I think, and this is-- I think there's more than one, less than three great choices, and I'd say Tesla with the Model 3, Model Y is absolutely one of those. But there's so few choices that if you are looking for a form factor that's not a Tesla-
- SGSarah Guo
So you think it's just missing product set that people are gonna want?
- RSRJ Scaringe
I think it's like-
- SGSarah Guo
Yeah
- RSRJ Scaringe
... an extreme lack of choice, is how you put it.
- SGSarah Guo
Mm.
- RSRJ Scaringe
Um, like a shocking lack of choice, and this is what gets into interesting, like corporate psychology. But because of the success of the Model Y, in particular, the EV choices that do exist that are outside of Tesla are often very similar to a Model Y.
- SGSarah Guo
Sure.
- RSRJ Scaringe
So if you were to like draw like an outline, if you looked at the side view profile of a lot of its alternatives and draw a profile and then put it next to a Model Y, it's almost identical.
- SGSarah Guo
There's a design sketch over here of all- basically the Model Y and all its competitors that are copycat.
- RSRJ Scaringe
They're all basically the same.
- SGSarah Guo
Yeah.
- RSRJ Scaringe
It's like if you want a Model Y, buy a Model Y, versus getting-
- SGSarah Guo
You want something different.
- RSRJ Scaringe
Yes. So you have all these companies who are trying to create their own version of Model Y, and it's like, it's unfortunate because they didn't say, "Well, what can we do that's unique and different?" And so for us, we think the Model Y is a great car. I've owned one. M- many folks on our team have owned one, but the world doesn't need another Model Y. The world needs another choice. And so I think, uh, this is a reframing of just how we look at transportation, is it's such a big space. It's such an area of personal expression that we need as, as consumers, we need lots of choices. We need to have variety. We self-identify with the thing we drive. We just haven't had it. So I think my view is the EV adoption in the United States is a reflection of the lack of choice. Uh, there's one set of really great choices with Model 3 and Model Y. I think there needs to be many more. And so even looking at our partnership with Volkswagen Group, a big motivator for that, which ties to our mission, was, can we take our technology platform-
- SGSarah Guo
Mm-hmm
- RSRJ Scaringe
... and allow that to be expressed through a variety of really interesting, uh, and very storied brands and different form factors, different price points, um, of course, different segments? And I think the more choices we have, the more it's gonna lead to broader-based adoption of electric vehicles, which creates, I think, a, a very positive level of momentum around the space. It's, it's worth noting on that point, when we look at how we develop a car, like take R2, we don't think of it as, this is someone who's gonna buy an EV, let's make it good. We think of it as, let's make the best possible vehicle, you know, we can imagine. So incredible performance and, and, you know, great range, great, uh, dynamics, tons of storage, and the person buying it will be drawn into electrification because the car is just the best choice they have. And we took that same view with R1, and on R1, the vast majority of our customers, their first time ever owning an EV-
- SGSarah Guo
Mm-hmm
- RSRJ Scaringe
... is a Rivian, which is, which is really good. If, if all we were doing is moving customers between one or two brands, it wouldn't be accomplishing the goal. We have to create new EV customers with products that are so compelling that it
- 29:05 – 30:45
How Our Relationship to Vehicles is Evolving
- RSRJ Scaringe
just draws people in.
- SGSarah Guo
So that leads into my, my very last question here. I grew up thinking, like, a car is a huge part of my identity.
- RSRJ Scaringe
Mm-hmm.
- SGSarah Guo
Love cars, drove them, still think they're pretty cool. Uh, and, you know, as they become more like utilitarian services-
- RSRJ Scaringe
Mm
- SGSarah Guo
... with, uh, the rise of robotaxis as a concept-
- RSRJ Scaringe
Yeah
- SGSarah Guo
... of like, you know, serving some of the function-
- RSRJ Scaringe
Yeah, yeah
- SGSarah Guo
... that your car did before, how do you think our relationship with cars changes or vehicles over time?
- RSRJ Scaringe
I do think it's-- we're gonna see a shift. Yeah, it's an interesting, like, philosophical, philosophical question, why, why are cars such a part of our society, and why do we have this affinity for them in a way that we don't have that feeling for other things in our life that are really important? Like I don't, I don't look at my refrigerator and think, "I really love that"-
- SGSarah Guo
Mm-hmm
- RSRJ Scaringe
... um, in the same way that I do with a car. And I think part of it is a car enables this personal freedom. It allows you to explore. Um, it's, it's something that you not only ride in, but it be- becomes part of an expression of self, and I think that's probably gonna continue to some degree, but it is going to evolve. And, and the way we look at it, uh, with our products and even how we've laid out and contemplated the, the purpose of the brand, we really look at, look at it through the lens of the vehicles and the products we make need to both enable people to go do the kinds of things, you know, that they would hope to have memories of years to come. So we, we often say, the kinds of things you'd want to take photographs of. But more than just enabling it, which is a functional requirement, like, can it drive there? You know, can it fit the stuff, your, your pets, your gear, your friends, your, your all of your stuff? More than just enabling it, can it inspire it?
- 30:45 – 31:45
Conclusion
- SGSarah Guo
Mm.
- RSRJ Scaringe
And so can the brand and the way we present what we're building and the way we make design decisions inspire you to go do the things you want to remember for years to come? And so there's little, like, design decisions we take that link to that. So a flashlight in the door-
- SGSarah Guo
Mm-hmm
- RSRJ Scaringe
... is an invitation to explore. It's an invitation to go look at things at night. Uh, the-
- SGSarah Guo
Or the tree house.
- RSRJ Scaringe
Yeah, there's-- Exactly. So there's all these little decisions we made throughout the whole car, funny you say, that are just designed to, like, engage that element of inspiring people to go, like, imagine that life they wanna have.
- SGSarah Guo
Awesome. Thank you so much, RJ.
- RSRJ Scaringe
Thank you.
- SGSarah Guo
Congrats on the R2-
- RSRJ Scaringe
Yeah
- SGSarah Guo
... and, uh, on the autonomy program.
- RSRJ Scaringe
Thank you.
- SGSarah Guo
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Episode duration: 31:46
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