The Operating System for Self Driving Cars (and Tanks, and Trucks...) With Qasar Younis and Peter Ludwig of Applied Intuition

Kastor and Peter, thank you so much for joining me today on No Priors.

Thanks for having us.

Thanks for having us.

I came as casual as I could for San Francisco—

I was worried about you. You usually have a button-up. You’re wearing something nice. I was concerned. Is everything okay?

Yeah, it is. 2 things. One is, I wanted to fit in with the San Francisco vibe—you know, Sunnyvale. I usually dress more like Peter, to be honest. I think that’s my outfit.

Yeah.

You guys are just clowning on Chad.

Wow.

And then, secondly, I got this Carhartt thing, and I don’t know if you guys know, Carhartt is suddenly cool. I got the memo from the cool club newsletter.

Wow.

It’s a Detroit brand, if anybody doesn’t know.

Yeah, yeah.

We’re representing Detroit in Silicon Valley.

Wow, nice. Very nice.

But—

Yeah, I just thought—

You’re not impressed. It’s okay.

I’m extremely impressed. I thought it was one of those things where I think you guys just raised at a $15 billion valuation—

Yeah.

—and so I thought it was more like—

Oh, yeah.

You’re done. You’re just checked out now. You’re done with global events.

No, no. No, no.

Last night, we were having dinner with one of the top 3 global OEM CTOs. I can’t reveal who it is only because they’re active in negotiations on a deal. He says, “Well, congratulations on the fundraise. How do you feel?” And I said, “Well, honestly, I feel a little nervous. We have big goals ahead of us.” He said, “Don’t be a coward.”

Attack.

Yeah, yeah, yeah.

I was like, “Okay, I will send that message to my team: ‘Don’t be cowards. Attack.’”

In general, when I think about you, I’ve known you for over a decade. I think I’ve led 2 of your rounds, and I feel like you’re the most successful, most quiet company in AI. You’re now at over 1,000 people. You’re in the hundreds of millions of revenue. You’ve been profitable the whole time, so you haven’t spent a dime, I think, of any of the money that you’ve ever raised, which is pretty insane from a—

Unbelievable to me as well.

—capital-efficiency perspective.

Well, we’re trying to change that quiet part, by the way.

Yeah.

Yeah, well, we’re here.

But you’ve been super quiet and stealthy.

We came up to San Francisco—

Wow.

—and wore a jean jacket.

Yeah, welcome.

See, Mom?

Yeah, exactly.

1. Applied Intuition Builds Vehicle Intelligence

Could you tell people a little bit more generally about what you do? I know you have 3 lines of business around engineering tooling, autonomy, and then an in-car-related product. Could you break down the origins of the company, how you got started, what you focus on, and give a primer? I think, again, you’ve accomplished an enormous amount. There’s still a lot ahead of you, but my gosh, you’ve done so much stuff.

Yeah. One thing, by the way, directly for founders more than anything else, is that there’s huge value, especially when the company is young, in not being constantly out there. I’m sure there are downsides as well, like people don’t know you and it’s harder to recruit or whatever. That’s never really been a huge issue for us.

But the advantages you get are that you can operate. The moment you say, “We do X,” there’s an expectation you do X, even if X ends up being wrong. I think it’s like the “keep your identity small” kind of view.

Okay.

The company, Applied Intuition, is a $15 billion. We just raised $15 billion profitable AI company. What we really do is build vehicle intelligence. It’s a broad category: How do you take all the positive things about AI that we’re seeing in LLMs and chat, and take them into the real world? How do you put intelligence into cars and trucks and tanks and fighter jets?

It’s roughly 3 business lines. We originally started with engineering tools in order to build and deploy that type of intelligence into vehicles, and test it and validate it. Unlike your laptop, these are safety-critical systems.

This was initially stuff that was built, I think, for the self-driving world, right? You were doing simulation environments and—

Exactly. And then we expanded to all software in the vehicle. That’s broadly what the company does.

In terms of what’s unique about the company, I think we’ve always thought pretty deeply about building products that are going to be used—

Mm-hmm.

—quickly.

If you’re in the AI universe, especially 8 or 9 years ago in the autonomy universe, there was a lot of research happening. Research can be super exciting, and you can convince yourself you’re doing some really impressive things while losing huge amounts of money.

By the way, how do you describe the company?

Just underlining engineering tools, our vehicle operating system, and then autonomy and applications. We started in engineering tools, but you reach a point where, in order to make your engineering tools better, you actually need to be developing applications yourselves, because that informs you and is important for getting to next-generation technologies.

Then it comes to, “Okay, well, I want to run these applications on vehicles, and we need a great operating system.” We think that we can do something better than anything else in the world. That’s how we end up with those 3 business areas.

There is a company that executed those strategies: Microsoft.

Yeah.

From 1975 to 1982, Microsoft was doing tools. If people don’t remember, that was Microsoft’s original business. Then they went to operating systems, and they went to applications like Office and Word and stuff like that.

We’re doing the same, except the hardware is not PC manufacturers; it’s cars—

Yeah.

—and trucks.

One of the old Peter Thiel things is, “What do you believe to be true that other people don’t believe?” When we were starting the company, there were a lot of startups in 2016 and 2017 doing self-driving. Our view was that there’s no path to autonomy—there’s no path to these next-generation vehicles—without the manufacturers in the loop.

Today, we’re almost like a Tesla minus the hardware. We do all the stuff that a Tesla has, or that some other companies have, but we partner with manufacturers to bring that technology to them.

Yeah. If you look at the self-driving wave, to your point, there were 2 dozen or 3 dozen different companies.

More, yeah.

Tons of companies. And then if you look at the ones that have arguably been most successful in the U.S., it’s 2 incumbents, right? It’s Waymo, which is a subsidiary of Google, and then Tesla. You guys are providing that same sort of stack more generally for any automotive provider to adopt and use.

I think it’s not only the self-driving or autonomy side that you focus on, but the OS is really powerful. You sell to defense and construction, but a lot of your business is with the giant automotive companies around the world.

Could you talk a little about what you’re providing through that OS and why it’s beneficial? What does it actually do?

2. The Vehicle Software Stack

When we refer to the vehicle operating system, we’re talking about the full software stack that runs on these embedded systems in these vehicles.

At the lowest level, we even do bootloaders, because if you want to do very reliable updates to embedded systems, you have to control the bootloader. Then you go above that, and we can talk about the technical, gory details of the operating system itself. Think of it like a true operating system.

Mm-hmm.

On top of that, you have the middleware, which is responsible for some abstraction, but also for some really important safety-critical data-transport aspects of it.

On top of that, you have the applications that are running, and many, many layers to those, of course. They end up controlling the vehicle, but also displaying information. That information could be displayed to somebody who’s in the vehicle, or it could actually be displayed to someone who’s outside a vehicle, let’s say in the mining example.

What is the big lesson from Android? Peter worked on Android at Google—that’s where we met. We worked together at Google. What are the big lessons from Android, especially on hardware diversity? That’s the big innovation, I think.

Android is an incredible story, from where it started to where it is today. I think it’s true that Android is the number-one OS in the world. It runs on more devices than anything else, by a healthy margin. The big thing that Android figured out was how to run applications uniformly on a huge variety of hardware and how to do that in a way that the user experience is actually consistent. There are a lot of lessons, both at the technical and nontechnical level, on how to enforce that.

Mm-hmm.

There’s this thing called the Compatibility Test Suite, which is super important. It’s an enormous set of tests and test infrastructure that allows these hardware makers—

I think it’s north of—

It’s like millions, I’ve heard.

Yeah.

It wasn’t nearly as big when we were working on it back then.

Yeah.

What do you get? You get this OS that can be used by billions of people on many thousands of different types of devices. Certainly, in our work, we’ve taken inspiration from some of those techniques and practices to make sure that our technology is applicable to such a wide variety of vehicle types, chipsets, and all of the details there.

It seems like one key insight there as well is that if you look at the supply chain for automotive, there are lots of different manufacturers for a lot of different modules. There’s embedded software—really, some embedded systems—on each one of these devices, and it’s really hard for traditional car OEMs to make use of some of the capabilities of these things because they don’t really have a good API or interface to interact with them. I think you’ve built out that full layer to hook into all these different—

Exactly.

—that—

I would adjust that. That’s not really embedded intelligence. A lot of the stuff that’s—

Yeah. It’s embedded, not intelligence. That’s how I like to put it.

A lot of it is just I/O. The seat warmer turns on and off, and you can pull all of that into a central CPU.

Mm-hmm.

That gives you a lot of efficiency, not only in the ability to have all the signals centrally processed and do more interesting things, like Tesla does, but it’s also just cheaper. You’re taking all these redundant systems, which are all poorly managed and built with different software stacks within each of the subcomponents, and you’re removing wiring harnesses. Thousands of dollars of physical hardware can literally be removed to get more functionality.

So you’re basically streamlining the guts of a car, replacing hardware components with software, and removing a lot of the—

Yeah, and I would say that people who grew up purely in the Silicon Valley mindset—or purely in the mindset of, “I can go to the store and buy this computer, I can write software, and this computer runs whatever operating system and generally works”—are so abstracted away from some of the very complicated details of how that hardware works. It’s overly simple.

When you actually get into safety-critical systems, there’s so much complexity in how reliable this hardware needs to be, how long it needs to last when it’s deployed in the field, and the cost constraints that you have. Fundamentally, cost matters a lot, especially in embedded systems. You have all these constraints, and we still want to do really advanced things. I think something that we’ve done really well is figuring out how to do some really advanced things in a cost-effective way.

Sure.

In the current Silicon Valley zeitgeist, where you have humanoids emerging, a lot of these questions are not answered on that side. It’s better in the sense that a lot of these companies are vertically integrated—they’re doing the hardware and the software—and the system is way more complex and more simple than a car.

But in the truck business, car business, tanks, and jets, you’re talking about hundreds of companies, sometimes thousands of companies, working on an individual product. They all come with very different views.

Yeah.

And nobody’s really stitching all that together except for you all.

Yeah. Since we don’t have a wiring-harness business, we don’t make chips, and we’re not a cloud provider, we can really come to the manufacturer and say, “Hey, you actually need a new way of operating this vehicle.”

So that’s one area that you have. Are you able to announce any customers that are working with you on this, or do you—

Yeah, publicly, we have a bunch of customers. The hero customer we came out with publicly was Porsche, so I think everybody knows them.

Yeah.

They’re generally considered to be the most competent OEM on the planet. If you look at a Ferrari, a Ferrari will make more dollars per vehicle because it’s truly a luxury good, but Porsches are the most profitable cars on the planet. There are $30,000 to $40,000 in profit per vehicle. They found that sweet spot of high volume and the ability to charge a lot because of the brand.

I think a company like that is getting pressure from Tesla. People are looking at Teslas, and even though they’re very different products, people are looking at them. I think we’re helping Porsche offer a consumer experience that is at par, if not better.

I would say it’s pressure from Tesla and also the upstart Chinese companies. There’s a lot of interesting stuff happening in China.

3. China Changes The Car Race

How do you think about that? One of the big shifts that’s happened globally is the rise of Chinese manufacturers like BYD and Xiaomi, which actually launched a car within 5 years, I think. That’s pretty amazing, because I think they were doing cell phones and other sorts of hardware, but they never really did anything in automotive.

The claim is that these systems are actually pretty good on the self-driving side and in a variety of other ways. What do you view as the global impact of these Chinese car manufacturers rising up?

There’s lots of nuance here. Number 1, they are good. The car business is extremely international. What I’m going to say next applies also to trucks, construction, and mining.

In the ’80s and ’90s, the big boogeyman was Japan. If you grew up in Michigan and Detroit like us, that’s all it was: Japan was coming. They were buying Rockefeller Center, and we were all going to be speaking Japanese soon. Obviously, that didn’t happen.

Yeah, yeah.

Then it was the Koreans. From 2000 to 2010, it was, “Hyundai’s coming,” along with all the conglomerates there.

Kia and things like that.

Yeah, exactly. Genesis, et cetera. That obviously didn’t happen. Right now, the newest version of that is China. There will be another one, whether it’s Vietnam, India, or something else that comes after China.

What the upstart wants to do is look at the industry without any legacy platforms, so they can enter the business with a blank slate, and you get a lot of advantages from that. You don’t have all of these vehicles out there that you’re servicing and maintaining, or brands that already have some legacy to them.

That’s allowed them—the Chinese Communist Party and broadly the Chinese ecosystem—to use this EV shift to introduce lots and lots of brands at lots of different price points, all with pretty impressive products. What it’s not is—

The autonomy stuff—we go to China regularly and test-drive these vehicles. They’re super impressive.

Mm-hmm.

They’re better than Tesla, to be very, very clear.

On autonomy or other features?

On autonomy and other features.

Yeah.

All around. Super impressive. I think if you look back at some of Elon’s statements, he’s seen the same thing over the years.

Yeah.

And then you can just honestly look at the sales of—

Teslas in China. They’re not that impressive.

Sure.

It’s because if you go there and do the comparison, the local stuff is really good.

Yeah.

Now, the stuff that’s not talked about often is that there are subsidies happening. The Chinese consider this to be a national asset. They look at the car business as we look at defense. They’re willing to subsidize it because, fundamentally, the car business is, in some ways—and as a matter of fact—their jobs program.

Yeah.

So you have hundreds of thousands of people who work in these industries and then service these industries, and they create entire economies around cities. We think about one manufacturing plant. Let’s say it’s a $1 billion or $5 billion investment. The large OEMs have dozens, sometimes hundreds of manufacturing plants.

Yeah.

When you talk about global industry, you don’t get any bigger than industrials and automotive.

Mm-hmm.

China is like, “Okay, if we’re going to be a superpower, we need to have a real industry.” I think if you fast-forward 5 to 10 years, you’re going to see heavy consolidation. You’re seeing the early versions of that. We’re seeing that the Huaweis of the world are starting to become this new generation of supplier. I mean, if we could be a company, we would be Huawei.

Yeah.

It’s a super impressive company. Everyone thinks about Huawei on the mobile phone side. We’re talking about their automotive business. They provide everything: a platform, a reference vehicle, and they allow the OEM to really focus on what they’re good at, which is manufacturing, marketing, branding, distribution, and consumer experiences.

Yeah.

So it is a really interesting ecosystem to keep an eye on. It’s the most dynamic ecosystem on the planet right now.

How do you think that impacts the economies of some of these countries? If I look at the US, I think we’re very lucky. I have a Tesla. I think it’s a fantastic car, and I think it’s almost like a local champion in terms of EVs and autonomy in the US.

It is, yeah.

It’s an American car company, by the way. People forget that. People only think the American car companies are in Detroit.

Tesla is an amazing American car company.

Yeah.

In Europe, it feels like they’re much more threatened by the Chinese OEMs, in part because they’re letting them enter the markets. In the US, there are heavier tariffs around them or other means to prevent access. In Europe, it feels like certain markets are pretty wide open, and you see BYD and others gaining share really aggressively. How do you think about that from a policy perspective in Europe? Is that not going to really hurt the economies there?

A resident European. I mean, there’s always a question of trade and trade deficit. European companies, as well as American companies, benefited a lot from the Chinese market. General Motors and Volkswagen, just as examples, have made a lot of profit in China over the years. From a fairness perspective, you can see, just by trade, that it makes sense that there’s some balance that can be achieved there.

Sure.

I think in the long term, though, absolutely these questions always arise, and you hit a point where the volumes become high enough that countries will demand that you manufacture it there.

Mm-hmm.

Once you start manufacturing within the country, oftentimes those cost deltas actually go away. No matter what the brand is—whether it’s a local brand or an international brand—if it’s manufactured in the same place, you usually end up with a product that’s going to be of similar cost.

Yeah. If you open your car, you can look at the content of the car in your door frame. It says where it is made and how much of it is made where. This is not a new thing. In Michigan and Detroit, this is a 50- or 70-year-old debate because there are real implications: if you just buy all the subcomponents from foreign countries and then assemble them in Detroit, that doesn’t mean it’s made in Detroit. My slightly more caustic, or aggressive, view on Europe is that Europeans are a little bit asleep at the wheel.

Mm.

I think, if I could inject something into the brains of the leadership—whether it’s the EU commissioners or the industrial families and leaders—it’s what I was told: “You gotta fight.”

Yeah.

There’s almost this attitude that the Chinese are so cheap. The reality is, they’re not. There’s a finite amount of dollars required to make something, and when these factories are so automated, that labor arbitrage—which historically was why China was really cheaper—goes away. A fully automated factory in Romania versus China isn’t as different as you think.

I fall into the view that, at least for America, as an American citizen, we can’t just be a consuming state. We have to build. Because with that building, you also provide jobs and expertise.

Yeah.

There are countless case studies of American companies that offshore our manufacturing. You hear the Detroit analogy here, right?

Yeah, yeah.

They offshore our manufacturing to other countries, including Mexico. Then the knowledge of building things is there. If you’re Chinese, Mexican, Vietnamese, Indian, whatever you are, then you’re like, “Oh, I just need a little thin layer. I get all the profits. I don’t need the 25 employees sitting in San Diego marketing this thing.”

Growing up in Michigan, I remember this very clearly because I was entering the workforce at the time, in the late ’90s. The view at that point was, “Oh, this is globalization, and it’s okay.” We have to have a bit more strategy. The reality is everybody on the planet has some strategy.

Yeah.

Thailand has some strategy. Brazil has some strategy.

Yeah. The US basically made a conscious choice to allow its industrial base to leave, even though it was phrased through a different lens. But that was a conscious choice.

It’s our naive view that the system will just take care of itself.

Yeah.

It doesn’t, because not everyone plays by the same rules globally.

Yeah.

I think in industries like ours, if you’re an AI company in San Francisco and your developers are mostly based there, that doesn’t matter. For us, we’re a truly global company, so we think about a lot of these things all the time.

The advantage that we have, which is extremely significant, is that we still have the best technical talent. You hear about DeepSeek, you hear about these other things. They’re absolutely real. Again, you can’t discount it. And, by the way, it’s not that for America to win, China has to lose.

Sure.

We can—the UK won, Germany won, Japan won, and the US still won.

Yeah.

We can live in a world where everybody is winning. We don’t have to have this conflict, but we do have to agree on the terms of engagement.

Mm-hmm.

My view is always: look, if we’re on the same terms or playing field, Silicon Valley has some huge advantages.

Uh-huh.

The best in the world come here. So, just as much as we complain about China, Mexico, Germany, whatever, we want to attract that talent to live here and build here, and we’re still, I think, the best in the world.

4. Robotics Revives American Industry

So if we think ahead, we went through a period where parts of our manufacturing and industrial base were effectively exported to other countries under labor arbitrage—effectively, cheaper labor. A lot of know-how went out of the country and stayed there, and in some cases, it almost feels like we’ve lost some of that know-how over time.

Do robotics, autonomy, and the automation of factories allow a moment in time where we can bring that back? A factory anywhere is cost-competitive based on automation versus labor. Is this a moment in time? How should people act on that from a policy perspective, or how should we be thinking about that more broadly from the perspective of starting companies or innovation?

We don’t know policy.

We didn't go to—

Yeah, sure.

Kennedy School. We went to engineering schools. But I think, broadly speaking, it is a huge opportunity, and you see companies like Rebuild and Anduril taking advantage of this reality. If I'm a founder, it's an extremely inspiring time because everybody is seeing this opportunity and willing to fund it.

Yeah.

These companies like Rebuild and Anduril are funded by classic venture capitalists. They're not funded by some PE shop that's doing a roll-up in New York.

Yeah. Makes sense. And then I guess the other piece of it is that you all spend—I mean, you're a very profitable company, which has always been very impressive, given how much you've scaled the team and scaled your efforts, but you also spend a lot on models and on the development of different AI-based tooling. Could you talk a little bit more about what sorts of models you've been training, how you think about the world there, and where that's heading?

Yeah. We do a lot of work in autonomy, right? We talk a lot about our work in L4 trucking, and we have some really interesting things there right now, largely in Japan. That itself is a huge part of this, and there's an awful lot of data and model training that goes into that. We also do interesting work in autonomy in aerial and maritime as well.

Mm-hmm.

Fighter jets, drones, boats, and all of these things have a huge data problem. Data is not nearly as easy to collect in some of those domains as it is, let's say, in the on-road domain.

Mm-hmm.

So we've had to do a lot of work over the years on how we actually collect this data and make it useful, and put it into formats such that you can actually get good performance out of the autonomy models that you train.

Is there anything you can share in terms of some of the approaches you've taken there?

Yes. There are a few things that I think we've done that have been super advantageous over the years. We've been investing in synthetic data for quite a while, and the details of how that works have evolved and actually gone through several generations in our own tech stack. Traditionally, you had a very computer-graphics-heavy approach. Now you have approaches that use things like Gaussian splash and diffusion models to do really interesting things with synthetic data. You can extend synthetic data into a bunch of other domains, including classified domains for defense, where you can get some really interesting advantages.

Mm-hmm.

Broadly in autonomy, you always have this thing where, if you have interesting data, as the machine-learning techniques change and as, let's say, new research papers come out, as long as you have that corpus of data, you can do really interesting things. We've seen our own technology evolve in that direction as well, where we were actually able to use data that we collected even years ago to do things and get levels of performance that would've been previously impossible, just using newer techniques applied to this data that we have.

I think one technical strategy that's been quite advantageous for us is that we always wanted to wait in the wings until—explicitly, we talked about this—the autonomy ecosystem converged on a handful of techniques, and then this kind of post-transformer boom happened. You can ride in v13, the Tesla FSD product, right? Or you can go to China and ride in these, and you're like, “This is it.”

Yeah.

This can't be. I mean, you're not talking about 3 years ago; there was a huge debate on whether end-to-end, in the many ways that end-to-end is marketed—

Yeah.

It's a marketing—

Yeah.

Phrase as much as a technical phrase. End-to-end, camera-heavy systems—are they going to be able to perform? I think the big thing is, now we're on the same page that autonomy is definitely going to happen.

Yeah.

And when you're playing in the ecosystem, you also know which way it's going to happen.

Yeah.

And so now the question is, who's going to monetize this?

Mm-hmm.

And who's going to take advantage of it? The Waymo stuff is super impressive, but it is worth putting an asterisk. The business model hasn't been figured out yet. The Tesla business model has been figured out.

Mm-hmm.

And so people kind of conflate these, and they often talk poorly about the Tesla system by saying, “Oh, it's dangerous, and it's not as good as a Waymo.” Yeah, but the—

Much more likely to continue to exist. The big story of the many dozens of autonomy companies actually isn't—I mean, they know as much as us, and we know as much as them, simply because we recruit many dozens of people from—I think we're probably Waymo's biggest employer outside of Waymo—and Cruise and Tesla, all of these organizations. So it's not like there's this false view that there's some secret in how to build self-driving tech. Actually, within the business, everybody knows how to build it.

Yeah.

In these podcasts, we're always going to stay fairly high-level. You're not going to get into that depth, but—

Mm-hmm.

Generally, the ecosystem's convergence on what those techniques will be—that was not the case just 4 years ago. There was a lot of debate. And then, as we saw, okay, there's a convergence. This is when you really move it.

Yeah, makes sense. You folks basically waited for that moment in time where the techniques and approaches crystallized, and you're like, “Okay, now's our moment in time to really enter the market—

And stay alive until now.

—because we don't have to do the research. Or we do different types of research, but we can kind of wait for state-of-the-art and just jump straight in.”

I mean, we're really, in automotive terms, there's research, advanced engineering, and production. We've always kind of hovered around advanced engineering. It's like, you don't want to just try things and have a group of 50 to 80 researchers publishing papers. But at the same time, you can't just be some systems integrator.

Uh-huh. One of the things that I find really interesting about the adoption of generative AI is that the bar is often higher for these AI systems than it is for people in terms of how good the output has to be. It's kind of striking, right? So—

If you ask somebody, “How should I do a Series A pitch?”

Yeah.

You'll take whatever they say because they say it with confidence, and then you do it in ChatGPT, and you're like, “No, actually, this isn't right.”

If you look at self-driving—

Yeah.

—and you look at the safety record, the claim for many of these companies is that you decrease death and injury dramatically by just adopting self-driving. And yet, from a regulatory perspective, there's all sorts of hurdles to adoption. What is the right bar for safety for autonomous systems? Should it be at the human level? Should it be dramatically better? How much better?

Yeah, there's a colloquial answer, and then there's a regulatory answer. On the colloquial answer, my view, and that of many people in the industry, is that most of the systems are pretty good right now. They're already—certainly Waymo, if you use a proxy or metric—

It's like, yeah, it's—

Like mean time to disengagement.

Mm-hmm.

On a Waymo, that's tens of thousands of miles.

Yeah.

That's 30,000 miles.

Well, it's also—I guess people measure the number of accidents and injuries—

Yeah.

—fatalities per mile, right?

Yeah, exactly.

And—

So, all of those—Waymo's way better. Not even kind of close. Frankly speaking, a lot of these L2+ systems are a lot better. We're in a capitalist environment, and there's liability involved, and so the question really fundamentally emerges: who's liable for what? In the historic debate, roughly what you have is: am I the driver who's responsible, or is the vehicle responsible? And that can actually be boiled down to: is there somebody in the driver's seat?

Yeah.

Waymo has taken that view, and a Waymo engineer would always say, “Well, FSD's nothing like us; you can't have a Tesla with nobody in the driver's seat.” Elon is trying to change that.

Sure. There's a liability piece of it, but separate from that, the media headline is always, “Waymo causes an accident,” versus, “Waymo saved N lives.”

Yeah, exactly.

Right? Or, “Tesla caused an accident,” versus, “Tesla...” And so—

I think it's human nature as well. We can't be afraid of our own shadow.

Mm-hmm.

Progress requires some of that risk.

Sure.

And I think part of it is having the economics—

But the key thing is the risk is lower. In other words—

Way lower.

It seems like a lot of the media headlines are actually the opposite, where there's a purposeful amplification of danger, even if the danger is decreased, right?

Yeah.

And we've seen that in a number of other instances, too. So it does feel like a purposeful approach by the people writing the news.

I think part of the issue is that sometimes the mistakes that the autonomy systems make are just not the same mistakes that a human would make. So when it makes the news, a human will see that and be like, “Well, that's completely crazy. How could that happen?” But it's more a result of the technology itself.

Yeah. But I think, just going back to the journalist and media view, we are what our incentives are, right? A journalist writing, “9 people died of pedestrian fatalities last night in America”—well, that happens every single night.

Sure.

It's not interesting.

Yeah. Yeah.

And so it's just trying to get clicks, and the clicks are, you know, “The Uber ATG car in Arizona killed somebody.” People talk about that all the time. It happened years ago, and it's like—

Yeah.

You know how many hundreds of people have died in America from human-driven vehicles? But that's on the cultural, colloquial side.

Sure.

On the regulatory side, the issue that we have in, broadly speaking, mature, developed economies is that bureaucracy's goal is to create more bureaucracy.

Mm-hmm.

And so a place like the Department of Transportation is going to say, “Hey, with airbags, we did this.”

Yeah.

“So this new technology comes in, and we definitely need to regulate it in this way.”

Mm-hmm.

Take a more extreme example. Take a country like Spain or Italy—

Mm-hmm.

Where the government is really very bureaucratic.

Yeah.

Imagine you take Italy and just remove the government. I'm not saying a revolution, but remove the government and say, “We're going to build these government institutions for the things they need today.” Like defragging, garbage collection, and maintenance—garbage collection never happens in these systems. So a lot of it's just illogical.

Yeah, makes sense. And you're talking about the programming term garbage collection and—

Yeah.

Yeah.

Exactly.

Something like that.

And, yeah, I would just add that these—

Not garbage collection.

Yeah, sorry. These autonomous systems will be significantly safer than human drivers—

Mm-hmm.

And provably so.

Mm-hmm.

Actually, a lot of the technology that we develop as a company contributes to this across the industry, and we do a lot of work in verification and validation, which is around the provability aspect of something being safe. But it's never going to be perfect. You can easily design traffic scenarios where the autonomous vehicle gets into an accident through no fault of its own, and so you can't have that bar, right? It has to be—

Imagine this alien shows up to the planet, and it's like, “There are 2 ways of transporting people. One is this one, where the computer does it, and it's virtually perfect. And the other one is this half-asleep 18-year-old teenager—

Yeah.

Going to a Starbucks shift after partying all night.”

Yeah.

No objective comparison would pick the teenagers.

Yeah, yeah.

The same thing, I think, even if you look at AI. Why is ChatGPT so loved? Search exists. There's all this legacy search; it's just a better product.

What do you think is the timeline to large-scale adoption of autonomy? Obviously, Waymo's growing really quickly right now. Tesla is continuing to push forward on different autonomous systems. How many years away do you think we are from—

General availability?

Yeah, general availability, and frameworks changing from a regulatory or other perspective. So it's just kind of—

Very, very nuanced question, because it's different in different countries. So let's bound it to America for now, and then we can talk about the rest of the world. Every vehicle manufacturer in America that ships a significant number of cars is building some version of a Tesla competitor. So I think general availability of an FSD-like system over the next 5 years is going to be common, just like navigation systems.

Yeah.

Now, how good those systems are and what the price points are will all define the breadth of those features. Waymo will continue to expand to cities. I think we're seeing Waymo in 2025 do what they promised in 2018 or 2019, which is, “We're going to do 40-city rollouts,” and that's going to be the next 2 or 3 years.

The example, really, to think about this is: let's say we're sitting in 2007, the iPhone just launched, and you ask me, “How fast are we going to see the iPhone in lots of people's hands?”

Yeah.

It's like, slow, slow, slow, and then suddenly everybody has it.

Yeah.

I think there's going to be some version of that. One anecdotal example is that I go to LA, and it's not Silicon Valley.

Yeah.

Everybody knows about self-driving. That was not the case 12 months ago.

Yeah.

And why is that? Because Waymos are everywhere.

Yeah.

For the first time, when I explain Applied Intuition, people are like, “Oh, I get it.” Before, they were just like—you know, they had all these almost Luddite-like responses.

Yeah.

And every person who sits in a Waymo just converts over to, “Okay, self-driving is a thing.” The natural next step is, “Okay, why doesn't my car have some version of this? I'm in a passenger car.”

Yeah.

So I think the whole window of expectations for self-driving was, let's say, 2015 to 2020. And that's really 2025 to 2030.

Mm-hmm.

But I think general availability is coming quickly. I don't want you—

I would just add, as an engineer, I think the next 5 years are probably the most exciting period—

For sure.

Imaginable, because whether it's automotive, defense—so think planes, ground vehicles, boats—all of general robotics, right now we don't see a real rate limit to how fast we can advance technology. We're just making progress every single day on all these things, and we don't see a point where that progress is going to slow.

Yeah, it's definitely funny from an engineering perspective. It's saddening somehow that all the people got excited when it wasn't ready. But this is the best time to work on self-driving. It's ready to go mainstream and, frankly speaking, to monetize. All the billions spent on Cruise, Argo, and those companies—all of that didn't go for nothing.

Mm-hmm.

That's in people's heads, and those people continue to work on the technology, so I think it's a super, super exciting time, yeah.

It's kind of a magic moment in time in the industry, and that's—

Yeah.

That's true of autonomous systems, and obviously it's true with all the language models and—

Yeah.

ChatGPT and all the things people are seeing.

Maybe extrapolating from that question is: when will this stuff be completely commoditized?

Mm-hmm.

Where your expectation for self-driving is $0.

Yeah.

I expect it for free. Right now, when you get in a car, you're not like, “CarPlay, I need to pay $3 a month to...” No, my phone is just being projected in the heads-up display, as expected, for free. I think by 2030 or 2035, you're going to have deep downward pricing pressure.

Mm-hmm.

To where the expectation is going to be close to free.

Yeah.

And I think the—not to pick on Waymo a lot, but it's just the easy one because we're in San Francisco, we see all these cars around, and it continues to still exist. That's a big question, right? You spend $12–15 billion developing this technology, and it commoditizes before you monetize it. That's a super, super scary situation.

Mm-hmm. Mm-hmm.

And I think Waymo's public offering and Waymo's business model are going to be big, big questions. If they pull it off, it's phenomenal.

Phenomenal for everybody in the industry.

It's very transformative in all sorts of ways, in terms of the magical experience of getting in the car and everything else. I think they've done a really good job.

I would go out on a limb and say the self-driving revolution will have as much of an impact as the LLM revolution happening. Because not everyone grew up in Detroit, you don't appreciate these little things: the entire way everything's designed, where hospitals are, how parking works—it's all based on cars. Cars are this invisible thing that's around you. It's like electricity.

Yeah.

This invisible thing that's around you. It's impacting every single thing.

Yeah.

Can you imagine going for a month and not interacting with a car?

Yeah.

Or a week?

Mm-hmm.

Yeah, no, it's interesting because I remember when all the 1st wave of self-driving stuff was happening, there'd be these dinners and conversations around self-driving adoption. At the time, people were really worried about truck drivers being displaced, and I remember meeting with different congresspeople to talk about that specific issue they were worried about. To your point, I think people have kind of underthought the degree to which urban design is, in the modern world, designed around cars. It's about where you put the parking lot—

Everything. Grocery stores. How far they are from neighborhoods. All of that—how big can they be? How small should they be? If you look at New York and why New York is the way New York is, it's because the car is actually not the main thing in your life. It's actually the subway and walking. And there's no other place like New York.

Yeah, yeah. And eventually what you should end up with is lots somewhere outside of a city with a bunch of cars, and then when you need a car, you push a button and it comes in and grabs you and takes you wherever you want. Yeah, and you probably need fewer vehicles—

Yeah, I think—

Well, that's where there's a debate. I think you see this with mobile phones: as calling became free—remember, calling used to be minutes—

Sure.

—and texts used to cost 10 cents a pop.

Yeah.

Texts and calling haven't gone down. They've gone way through the roof, orders of magnitude higher than we communicated 20 years ago. Only 20 years ago—not a long time ago. So there is a version that, in 20 years from now, we have an order of magnitude higher. Imagine if everyone had a private jet.

Mm-hmm.

Do you think people are flying less around the world?

More. They're flying a lot more. So I think there's a version that you have a lot more actual miles driven.

Yeah. And the inside cabin of the car can change dramatically, right? You can work out in the back if you want to, if you're in the right—

But that doesn't necessarily mean there's more traffic. It doesn't necessarily mean you need more parking lots. I'm in the optimistic view of the world, and this is, again, my view. The issue with Europe sometimes is that instead of the knee-jerk reaction being no, the knee-jerk reaction should be yes.

Mm-hmm.

This will usher in more productivity. We shouldn't have huge percentages of our cities as empty parking lots.

Uh-huh.

You make those parks. It's really nice, and I think self-driving can help it. Beyond just the fact that literally fewer humans die.

So you've kind of laid out your vision in terms of autonomy and the reworking of cities, and some really large-scale, very exciting things that are coming, and how you guys are going to help power that for the industry. How do you think about using AI in other parts of your business?

Yeah, specifically in tooling and in the vehicle OS—let's say, the in-cabin experience. Number 1, the way software is being developed: we see this through all the coding-assistant tools. All of that needs to happen in automotive and these other industries, and so we're at the heart of that.

There's a lot—

That's why we're changing our name to Windsurf Automotive. Yeah, exactly. Yeah.

Because on that, there are a lot of very interesting constraints to the problem when you talk about building software for vehicles.

Mm.

So I think we're in a really interesting spot where we both have the AI technology, and we also have the expertise and all of these really interesting constraints on the software that's actually being developed. So I think you'll see some interesting stuff from us.

Yeah, and then on the vehicle OS side, or the in-cabin side, the vision there is pretty straightforward, which we're working on now. You take a mining operator, and he walks up to his Komatsu dirt mover, this giant machine that moves dirt basically 24/7. That machine should know who that person is, and as they enter, that person can have a conversation with the machine, because the machine sees it. It sees the world around it. It's multimodal, and it can sense it.

What really happens on a mine in terms of safety is a little bit of intelligence goes a long way, and so what you're starting to see is the emergence of this teaming. And I think that type of AI experience—

Mm-hmm.

—is, I think, more fundamentally important than even just getting Waymo going or just getting L2, because that's the hidden part of the economy, whether it's writing software for the engineering tools that write software for safety-critical systems or the stuff that happens beyond your eyes. And that's the stuff I think we're super excited about, without even going into defense. Defense is its own universe.

The short version of what we're seeing in defense is—this has been talked about by others, but we're certainly experiencing it—as defense is moving from 1 person, 1 machine to 1 person, many machines.

Uh-huh.

The way to think about intelligence within these other domains and dominions isn't just, "Well, how can you use an LLM—

Sure.

—there?" It really is, "Well, what does intelligence look like for a warfighter in the field who has a couple hundred drones?"

Yeah.

And how does he say, "Okay, I need this there, and I need it fast, and I get information from other parts of the force and other forces and other countries to actually make that decision very, very quickly"?

Yeah. Then the problem space is all about autonomy for the individual system, it's about collaborative autonomy for the swarm, and then it's about the comms and the RF between all of these systems and how the data's actually moved between them. So, really, really interesting problems, and yeah, we've got some really interesting tech things, right?

So we think vehicle intelligence, trademark—

Yeah.

—is like this. Yeah, you know, it's funny. As a founder, for the founders who are listening, it's super rare to actually work on stuff that you really love, and it's no disrespect to people who work on, like, the dentist CRM.

Sure.

But it's a lot more fun than dentist CRMs. Because it's like taking AI in a way which is not just the chatbot—

Sure.

—which is great for all the reasons it is, but it's beyond that.

So, one of the things that I think is unique about Applied Intuition is you also have a very large and deep bench on the design side. And you think deeply about these forward-looking experiences, both in-cabin and more broadly. Could you talk a little bit more about both that team and also that future that you're imagining that's coming?

Yeah, I think in the ChatGPT world, there's some design there, obviously, and it's significant, but once you're truly multimodal in the in-cabin consumer passenger vehicle, there's lots of screens, and just the way you interact, it's not just a button and a voice.

Mm.

And so some of that work is still under wraps, but we're doing real work there.

Mm-hmm.

If people are particularly interested in that, especially from a designer's perspective, and you're tired of doing login screens for Google—

Mm-hmm.

—or spending 6 years on just changing the shade of the sign-in, we're really working on fundamental experiences, like HMI, in the way that I think a lot of people at CMU, when they're doing their—

Some very deep experiences where you walk into the car. It somehow recognizes you. The seat moves into place for you versus somebody else who drives it sometimes. Everything auto-adjusts. Your playlist comes on, whatever it is. It logs you in.

Yeah, and just how it interacts with you. Design isn't only pixels. It's an experience, right?

Yeah.

Yeah, so I think design is a huge area for us as well.

And then I guess from a team or hiring perspective, to your point on great things to work on, are there specific types of profiles you're looking for, or are you just hiring across the board? How are you thinking about that right now?

Well, fortunately, we'll be hiring across the board. Obviously, I think we hire from all the spectrum, from pure researchers all the way to folks who are working on the other end of infrastructure implementation.

Yeah.

I think we have over 100 roles available.

Yeah, I mean, of course, everyone, ourselves included, is always looking for great AI talent. That goes without saying, but we also have, I would say, an extremely deep appreciation for really strong software engineers who are also deep in operating systems and the systems engineering realm. We work on stuff that's very important and very technical, and so people who like hard problems like to work at Applied.

Yes. Something we're proud of about our company is that 82% of it is software engineering. It's extremely concentrated.

Very concentrated, yeah.

It's a very, very technical company. We build products, you know.

Mm-hmm.

We're not doing services and things like that.

Yeah.

So that allows, you know, if you like that kind of stuff, if you like building products, we're, I think, an interesting place. We might not be that cool, though. I think there's a—

You got the jean jacket.

You know, I got the Carhartt jacket.

I got the jean jacket, right, right, right.

That's about it. Last time you'll see this.

Oh, yeah.

It's like a costume.

Yeah. Just roll with it this whole time.

The best evidence it's a costume is that I'm uncomfortable in it.

Hey.

It's like I'm wearing a clown outfit.

You look good. You look good. You look good. Yeah. Great. Well, thank you so much for joining me today.

Yeah, thanks for having me. Thanks for having me. It's awesome.