Rivian’s Roadmap to AI Architecture and Autonomy with Founder and CEO RJ Scaringe

By 2030, 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. 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. Thank you for having me. So Rivian’s already an incredibly cool company. How did you decide it was going to become an autonomy company when that happened? 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 would be. But even if it was a car, but it was always really 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 not fully coming to life with the technology that we're building. And you think about the function of Rivian, there's transportation, there's also the experience like when, how long ago did you guys start investing in the autonomy strategy here? Yes, we launched our one in very end of 2021. And we used what I'll broadly characterize like a 1.0 approach to autonomy. We had a perception platform we used 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 cameras 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 moment we launched it we knew it was the wrong approach, but it was the thing we'd started working on well before the launch. RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... You know, no legacy of what we had built in the Gen 1. And that first launched from a hardware point of view in the middle of 2024. So it was with our Gen 2 vehicles. You know, not a single line of shared code, not a single piece of common hardware on the perception or on the compute side. And then we had to build, like, the actual data flywheel. So we had to grow the car park to build enough of the data flywheel to then start to train the model. And what we showed in our autonomy data late last year, late in 2025, was the beginnings of a series of really, like, super exciting steps of how this is going to grow and expand. I say this all the time. 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 going to look very different. So the rate of progress that we saw in autonomy between, let's say 2020 and 2025 or 2021 and 2025, and what we're going to see between today. RJ, let's say 2029, 2030 are.. RJden are completely different slopes and that really comes back to, you know, entirely new architectures and not being used to develop self driving. RJactually, truly. RJAI architectures whereas before these were not AI architectures in the, in the true sense. They were they were using machine vision, but really rules based environments that we defined this as humans. RJnaan we codified them is very different than how they're now called today.

Avis serviceman see 240%. 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. Okay. But this is, let's say, eight, ten years ago. Yeah. And as you mentioned, there's several architectural revolutions since then. Yeah. And so for companies to make that shift from, you know, we're going to have these separate perception and planning systems to more end-to-end neural networks. I asked because I felt it was actually quite a hard decision for people choosing their partners and from a technical perspective. 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. JJ Scaringe First thinking of a new concept in real estate making cutting from the PRE and fourth from the EST It was a couple of years ago and it shifted very rapidly to it was clear that the future state was going to be neural net based It was hard because if you a company that built all these systems it like do I keep investing what I had What do I do with all this work that was built before? And the reality is, is a lot of it is, the vast majority of it's going to be pure throwaway. Because it wasn't like a gradual shift, it was a complete rethink of how things are architected. How did you decide that this was going to be an in-house effort? So, we're talking about a partner effort. Yeah. That given most people who made cars said, we're going to go partner or buy something here. Yeah. I guess the emotional slash philosophical is on things that are really important, we've taken the approach of vertically integrating them. So electronics, our software, all the high voltage systems in the vehicle, so things like motors, inverters, all the power electronics, these are all things 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 jojo

But... to continue making use of this week'sossați consumer effects... have you ever been portrayed as the product that you love Perhaps literary terms Front Ports Jeff Merry Petra Tighask 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, 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 lot of data. So you could, of course, do it over LTE, but it's expensive. If you need to have a really robust architecture in the vehicle, then you need to be able to send it off, off board, and use that with a lot of 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 huge amount of data that our vehicles generate. RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... 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 car park with enough vehicles generating enough data. I say more than one, less than five.

And the control of that whole training loop you're describing. 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 unique spot we are in time right now is the one that... Can I ask explicitly then? It's you, it's Tesla, it's Waymo. Is that the three? PJ Slauson-I'll include all three of those, and there's one or two others you mixed. but I think the challenge is you have to look at not just the moment in time for performance where we are today, do you have the ingredients to continue making progress at a very high rate over the next four or five years. And so a lot of the solutions that are more 1.0� Robinson Beeестно based and are sort of stuck in that framework, I think, have a truly a RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... It's a decision to make our chip in-house. Is that more a capability decision or a cost decision? It's a cost. We want to have it on everything. So every single one of our cars, we want to have the ability for it to operate at very high levels of autonomy. And so we design spec and build the cameras. Radars are extremely cheap. LiDARs are now very, very cheap. But the really expensive part of the system is actually the onboard inference. And so that's like an order of magnitude more expensive than any of the perception stack. I think people focused on the perception because it the things we can visualize what the brain is actually the most expensive part And so we brought that in as a way to remove cost from the system RJ talks upcoming launch Rivian R2 model aims distinct affordable mass alternative Tesla Model Y Plus

The question is unique. It was just a few years ago, 20, 2019, 2021 even, there was like very, like very clearly delineated ways to approach autonomy. There was a level two approach, 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 in place. RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... I like This gets millions of.. Yeah. All conditions. Yeah. Except these very unique corner cases and so to your point on safety cases, the question

then becomes is like how confident are we in the system capability in covering these really obscure unlikely rare events which of course if they're not covered well it can lead to really, you know, terrible outcome, you know, the vehicle in a bad collision. And so that's where the neural net based approach has just changed things a lot. The capabilities are so much stronger and the ability now I think for us to deploy on a lot more vehicles have a car park that's very large. So we went from you know a few years ago state-of-the-art was you'd have a test development fleet of maybe a few hundred vehicles, maybe like high hundreds of vehicles. To now like thousands and thousands every single car on the road is part of your data fleet that's identifying these unique car cases and then running the model against them to RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... I think that that's going to play out in the market where like autonomy will be so important as a driving feature, core feature of the car that there's just going to be a big market share shift to those who can figure it out. I know you're biased here, but I'm like, no, no, no, no, I think it's, it's, it's a hard question to answer. So I think it's, I always characterize like this. I think it's inconceivable for a car company to continue to operate at scale, like mass market. I think very niche,

I don't even know if you're a car enthusiast. 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. Sorry, can you define software-defined architecture? Yeah, that's like before we even get to autonomy. Yeah. It's like, these are like basics. So the way car like. The core thesis of Rivian. 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 is called a digital 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 HVAC, your air conditioning system, all have little computers associated with them. Right. What we call ECUs electronic control units And in a modern car you might have 100 to 150 of these And each of these run their own little island of software And that little island of software is written J twenties And that's why it's impossible to debug, like, a software system. It's also why it's really hard to do an update. So imagine you have 100 different islands of software written by 100 different teams 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. You probably want the audio system to do something. Those are all different little ECUs in a traditional car. 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 10 different players. In contrast, on an approach where you build a zonal architecture where you have a very small number of computers,

You know, I leveraged on race cars tied to dusty environment since the early edit sensory you know one, two, maybe three that control everything, really. Or in a matter of minutes maybe an hour you can change the whole sequence and we are able to come to the car and it's very straightforward. And you know, how often does Rivian update? It's typically one a month. RJ talks about the new features Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... There's no computers at all in the car. It's 100% 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. And this is where you saw things like the Bosch fuel injection systems. Never planned. It's sort of like a field of weeds. Then over the next 60, 70 years, everything that became computer-controlled to any degree is suddenly starting to have a little bit of a problem. RJ

RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... Things projects in missions ranged from So this might be an irrelevant question, but I am curious. Do you think that the autonomy, like the models that maybe the three, maybe the one, maybe the five companies that come up with this, develop are fundamentally different over time? Because I spent a lot of time in the AI ecosystem and the, let's say the language-oriented foundation models, like feel like they're converging at this moment in time. I look at a Rivian and I'm like, I don't know, people venture in that thing. Do you actually want it to do different things, have different styles or capabilities?

Or is it really just like, as much autonomy as possible safety case? Well, first, this is a great question. I want my car to drive really awesome. Like in the LLM world, a lot of it has converged because the training data sets are nearly the same. Yeah. So we're taking 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 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 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 those cover corner cases better, so the cameras have incredible low light and bright light performance. The dynamic range of the cameras is stronger. We have more cameras, a lot more megapixels. We have radar, which is great for object detection. And the lidar, which is a very powerful tool for training the models. And so imagine 800 feet in front of us, there's a little speck into 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 like a ground truth fleet to help train your cameras. Putting that in every single one of That was a core part of how we thought about our strategy. We're going to go not as heavy as, let's say, a Waymo, on perception, but heavier than, let's say, Tesla, to build a really robust data platform on a vehicle-by-vehicle basis. And then we have a car park that's going to grow significantly with the expansion with R2. Yeah, so I think first and foremost is there is no common internet data. So the data sets that we're going to be picking up, though, are going to be very similar. But you have to go acquire it.

But there's still different decisions about what data you care about acquiring. Yeah. Well, I think this is what to like, how does a car feel? Ultimately, it needs to be safe. And the differences in the way it drives or feels are going to be more about like, what's the UI, the user interface of it? RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian R2 model aims distinct affordable mass alternative Tesla Model Y Plus Can we talk about what the R2 means for the company and some of the key design decisions here? I was just talking to Jonathan, one of your lead designers, about the constraints and aiming for more mass market and more volume here. I mean, yeah, you said it. So R1, it's a flagship product. Its average selling price is around $90,000. It's the best-selling, the R1S is the best-selling premium electric HV in the country. RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus...

RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... The overall adoption rate in the United States of EV is around 8%. The vast majority of vehicle buyers are buying vehicles that are under $70,000 with the average sale price of about 50. And so if you look at the number of vehicle choices you have at a price point that's under $70,000, depending on the year, this of course changes year to year, there's well in excess of 300 different vehicle model line choices, putting aside trims and performance packages, Thank you for watching RJ talks upcoming launch Rivian R2 model aims distinct affordable mass alternative Tesla Model Y Plus

мыслी It's almost identical. of 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 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. 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, RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus...

RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus... We not talking about a new EV Let make it good We think of it as let make the best possible vehicle we can imagine So incredible performance and great range great 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 are first time ever owning an EV is a Rivian which is RJ talks upcoming launch Rivian R2 model aims distinct affordable mass alternative Tesla Model Y Plus Still think they're pretty cool. And, you know, as they become more like utilitarian services with the rise of robo-taxis as a concept of like, you know, serving some of the function, which a car did before. How do you think our relationship with cars changes or vehicles over time? I do think we're going to see a shift. It's an interesting philosophical question. RJ talks upcoming launch Rivian’s R2 model, aims distinct, affordable, mass-market alternative Tesla Model Y. Plus...

It's gonna continue to some degree, but it is going to evolve. And the way we look at it with our products, and even how we've laid out and contemplated the purpose of the brand. We really 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 that they would hope to have memories of years to come. So 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. R1 views this on UberPro magnetic carpets, 100% auto automatic or Yokohama data critical computing relationships that drink on it. Summarize work done when we build셨 내� Get in your源 Associate development team on face time. R2 thinly filtering allosing high-end products with passes Stockholm test parachutingicht quarantine messthaai central etheranca. debugger rumors are showingよろしく for 4%. usa specific launched pre-trial cars Katie T license and architecture is proyecto is that dual electric vehicles withunta Meslos meridian There a lot of Sarah Guo, Rivian Founder CEO RJ Scaringe. Autonomous vehicle technology moved past human-coded rules era neural networks custom computer chips. Rivian Founder CEO RJ Scaringe. Autonomous vehicle technology moved past human-coded vehicles. Find us on Twitter at NoPriorsPod. Subscribe to our YouTube channel if you want to see our faces. Follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week. And sign up for emails or find transcripts for every episode at no-priors.com.