The Operating System for Self Driving Cars (and Tanks, and Trucks...) With Qasar Younis and Peter Ludwig of Applied Intuition
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Casper and Peter, thank you so much for joining me today on New Pryors. Thanks for having us. I came as casual as I could for the San Francisco. I was worried about you. You're usually a buttoned up. You're wearing something nice. That's kind of, that's concerned. Is everything okay? Yeah, it is. It is. Two things. One is, you know, 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. And then secondly, you know, I got this Carhartt.

you know, thing. And I don't know if you guys know Carhartt is suddenly cool. Uh, I got the memo from the cool club newsletter. It's a Detroit brand. If anybody doesn't know, we're representing Detroit and Silicon Valley. So I just thought, um, I 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 it at $15 billion. And so I thought it was more like kind of you're done. I'm just checked out now. No, no, no, no. So last night we were having dinner with, uh, with one of the

top three global OEM CTOs. And he says, you know, I can't reveal who it is only because it's active, active negotiations on a deal. And he says, well, you know, congratulations on the fundraise. How do you feel? And I said, well, you know, honestly, I feel a little nervous. You know, we have, we have, you know, big goals ahead of us. He said, don't be a coward. Attack. I will send that message to my team. Don't be cowards. Attack. Yeah.

I mean, I guess in general, when I think about you also, I've known you for over a decade. Yeah. I think I've led two of your rounds and I feel like you're the most successful, most quiet company in AI. You're now at over a thousand 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 capital efficiency perspective. We're trying to change that quiet part, by the way. Yeah, we're here. We came up to San Francisco and wore a jean jacket. Yeah, welcome. See, mom? Yeah, exactly. Could you tell people a little bit about more generally what you do? I know you have three lines of business around engineering, tooling, autonomy, and then sort of in-car technology.

Could you kind of break down the origins of the company, how you got started, what you focus on and just kind of give a primer? Because 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. By the way, this is directly for founders more than anything else. There's a huge value in

especially when the company is young, not to be constantly out there. I'm sure there's 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 is you can operate, you know, the moment you say we do X,

There's an expectation you do X, even if X ends up being wrong. And so I think that like it's like, you know, keep your identity small kind of view. And so, yeah, the company Applied Intuition is a 15 billion dollar. We just raised 15 billion dollar profitable AI company. And with that, what we really do is we're we're in we build vehicle intelligence. So it's a broad category of how do you take.

all the positive things about AI that we're seeing in LLMs and in chat, and you take them into the real world. So how do you put intelligence in the cars and trucks and tanks and fighter jets? And it's roughly as those three business lines. So we originally started with engineering tools in order to build and deploy that type of intelligence into vehicles and test it and validate it. Because 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. Exactly. And then we expanded it to all software in the vehicle. That's broadly what the company does. In terms of what's unique about the company, I think is we've always thought pretty deeply about

building products that are going to be used quickly. If you're in the AI universe, especially in eight, nine years ago in the autonomy universe, a lot of research happening and research can be super exciting and actually quite challenging.

What's what's the word like losing huge, like metric tons of money without actually, you know, you can convince yourself you're doing some really, really impressive things. I don't know how you describe, how do you describe the company? Just underlining engineering tools, our vehicle operating system, and then autonomy and applications. And so we started in engineering tools, but you sort of reach a point where in order to make your engineering tools better, you actually need to be developing applications yourselves because that's what informs you. And if we're really getting to next generation technologies,

And then it comes to, okay, well, I want to run these applications on vehicles and well, we need a great operating system. And we think that we can do something better than anything else in the world. And so that's sort of how we ended up with those three business areas. I mean, there is a company that executed the strategies, Microsoft. Yeah. 75 to 82 was doing tools that people don't remember. That was Microsoft's reason. Then they went into operating systems and they went to applications like, you know, Office and Windows and stuff like that, Office and Word and stuff like that. We're doing the same except,

the hardware is not PC manufacturers, it's cars and trucks. And I think what's, you know, one of the old Peter Thiel things, like, what do you believe to be true that other people don't believe when we were starting the company? If you remember, there were a lot of startups in 2016, 2017 doing self-driving. And our view was there's no path

to autonomy, there's no path to like this next generation because without the manufacturers in the loop. Today, we're almost like a Tesla minus the hardware. We do all this stuff that a Tesla has or some other companies, but we put it, we didn't partner with manufacturers to bring that technology to them. - Yeah, it's really interesting 'cause if you look at the self-driving wave, to your point, there's like two dozen different companies or three dozen, there's tons of companies.

And then if you look at the ones that have arguably been most successful in the U.S., it's two incumbents, right? It's Waymo, which is a subsidiary of Google, and then Tesla. And then you guys are sort of providing that same sort of stack more generally for any automotive provider to sort of adopt and use. And I think it's not only the self-driving or the economy side that you folks really focus on, but I think the OS is really powerful. You sell, to your point, defense, construction, but a lot of your business is the giant automotive construction.

companies around the world. Could you talk a little bit about what you're providing through that OS and why it's beneficial and what does it actually do? When we refer to the vehicle operating system, we're talking about the full software stack that runs on these embedded systems that run on these vehicles. So at the lowest level, right, we even do bootloaders because if you want to do very reliable updates to embedded systems, you have to control the bootloader. And then you go above that and we can talk about the actual, um,

the technical gory details of the operating system itself. So think about like a true operating system. But on top of that, you have to have the middleware, which is responsible for some abstraction, but also some really important safety critical data transport aspects of it. On top of that, you actually have the applications that are running and the

Also many, many layers to those, of course, but they end up really controlling the vehicle, but then also displaying information. And then information could be displayed to somebody who's in the vehicle or it could actually be displayed to someone who's outside of a vehicle. Let's say in the mining example. What I mean, Peter worked on Android at Google. That's where we met. We worked together at Google. What is the big lessons from Android?

Especially on hardware diversity, right? That's kind of, I think, the big innovation up there. Android, it's 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 just

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. And there are a lot of lessons, both at the technical and non-technical level, on how to actually enforce that. So there's this thing called the compatibility test suite, which is super important. And it's this enormous set of tests and test infrastructure that allow these hardware makers. I think it's like north of that. It's like millions I've heard, yeah.

It wasn't as big when we were working on it back then. But what do you get? You get this OS that can be used by billions of people on many thousands of different types of devices. So 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 and 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's lots of different manufacturers for a lot of different modules. There's sort of embedded intelligence, or at least embedded systems on each one of these devices. And it's really hard for traditional car OEM to actually make use of some of the capabilities of these things because they don't really have a good either API or interface to interact with them. And I think you all have kind of built out that full layer to hook into all these different... Yeah, and I would adjust that the...

you know, that's not really embedded intelligence. A lot of the stuff that's the software that's on these. It's embedded non-intelligence. Yeah. A lot of just IO, you know, it's, it's the seat warmer turns on and off and you can actually pull all of that into a, into a central, you know, CPU. And that gives you a lot of efficiency, not only in just the ability that now all the signals are centrally processed and you can do more interesting things like Tesla does. But it's also just

cheaper you're you're taking all these like redundant systems which are all kind of you know poorly managed and built with different software stacks within each of the sub components and uh and you're removing wiring harnesses i mean thousands of dollars of physical hardware can literally be removed to get more functionality so so you're basically streamline lining the guts of a car and you're replacing hardware components with software yeah and then removing a lot of the yeah and i would say that

People who grew up, let's say, purely in the Silicon Valley mindset or purely in the mindset of, I can go to the store and buy this computer and I can write software and this computer runs whatever operating system and it generally works. You're 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 actually deployed in a field, and then just the cost constraints that you have. Like fundamentally, cost matters a lot, especially in embedded systems. And you have all these constraints and we still want to do really advanced things. And I think something that we've done really well is figuring out how to do some really advanced things, but actually in a cost-effective way. In the kind of current zeitgeist of Silicon Valley where you have humanoids emerging, a lot of these questions are not answered on that side. Now, it's better in the sense of

A lot of these companies are kind of verticalized. They're doing the hardware and the software, and the system is way... It's more complex and more simple than a car. But in trucks business, car business, tanks, jets, you're talking about hundreds of companies, sometimes thousands of companies working on an individual product. And they all come with very different views. And nobody's really stitching all that together except you. Yeah. And we don't, since we're not... We don't have a wiring harness business, and we don't make chips.

we can, or we're not a cloud provider. We can really come to the manufacturer and say, hey, you actually need a new way of, you know, 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? Yeah, I mean, publicly, we have a bunch of customers. Publicly are the hero customer that we'd come out with was Porsche. So I think everybody knows. It's generally considered to be

the most competent OEM on the planet in terms of, um, you look at a Ferrari, a Ferrari will make more dollars per vehicle cause it's truly a luxury good. But, um, Porsches are the most profitable cars on the planet. It is 30 to $40,000 in profit per vehicle. So they found that sweet spot of high volume and, you know, ability to charge a lot because of the brand. Uh, and I think, you know, a company like that is getting pressure from a Tesla that says, you know,

people are looking at those. And even though they're very different products, people are looking at those. And so I think we're helping them offer a consumer experience which is at par, if not better. And I would say it's a pressure from Tesla and also the upstart Chinese companies. There's a lot of interesting stuff happening in China. How do you think about that? So I think one of the big shifts that's happened globally is...

is this rise of chinese manufacturers like byd xiaomi actually launched a car i think within five years which is pretty amazing because i think there are like cell phones and other sorts of hardware but they never really did anything in automotive um the claim is that these systems are actually pretty good on the self-driving side and in a variety of other ways um you know what what do you view as the global impact of these chinese car manufacturers rising up lots of nuance here um

So number one, they are good. So the car business is extremely international. And what I'm gonna say next applies also to trucking, construction, and mining. But in the '80s and '90s, the big boogeyman was Japan. And if you grew up in Michigan and Detroit like us,

That's all it was Japan's coming. They're buying Rockefeller Center and you know, they were gonna be working speaking Japanese soon. Obviously, yeah Then it was the Koreans. So 2000 to 2010 was Hyundai's coming and all the conglomerates there Yeah, exactly Genesis etc that obviously didn't happen right now at the newest version of that is China There will be another one but there'll be Vietnam or India or something will come after China. So

what the upstart wants to do is they look at the industry, they don't have any legacy platforms, and so they can enter the business with a blank slate. And you get a lot of advantage of that. You don't have all of these, you know, you have hundreds of millions of vehicles out there you're servicing and maintaining, and brands that already have some legacy to them. And that's allowed them to, with this EV shift, introduce they being the Chinese Communist Party and broadly the Chinese ecosystem, to introduce lots and lots of brands,

at lots of different price points that all have pretty impressive products. Though what it's not, so the autonomy stuff, you know, we go to China regularly and we test drive these vehicles. Super impressive. And better than Tesla, to be like very, very clear. On autonomy or other features? On autonomy and other features. Yeah. All around, all around. Like super impressive. I think if you look back at, you know, Elon, some of his statements about...

He's seen the same thing over the years. And then you can just honestly look at the sales of Teslas in China. It's not that impressive. It's because if you go there and you do the comparison, the local stuff is really good. Now, the stuff that's not talked about often is there is subsidies that are happening. The Chinese consider this to be a national asset. They look at the car business as a—we look at defense. And they're willing to subsidize it because—

fundamentally the car business in some ways and any of these manufacturers are there like jobs programs. Yeah. So you have hundreds of thousands of, you know, people who work in these industries and then service these industries and they create entire economies around cities. We think about like a, you know, one manufacturing plant, let's say it's a billion, $5 billion investments. The large OEMs have,

dozens, sometimes hundreds of manufacturing plants. And these are, when you talk about global industry, you don't get any bigger than in the industrials and then automotive. And so China's like, okay, if we're going to be a superpower, we need to have a real industry. I think you fast forward five to 10 years, you're going to see a heavy consolidation. You're seeing the early versions of that we saw, you know, already, which is the, like the Huawei's of the world are starting to become this like new generation supplier of

I mean, if we could be a company, we would be Huawei. Like it's a super impressive company. Not on the, everyone thinks about Huawei on the mobile phone side. We're talking about their automotive business. They provide everything and they provide a platform, a reference vehicle and allows the OEM then to really focus on what they're good at, which is manufacturing, marketing, branding, distribution and consumer experiences.

And 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 sort of the economies of some of these countries? So if I look at the U.S., 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 EV and autonomy in the U.S. It's an American car company, by the way. People only think the American car companies are in Detroit. Tesla is an American car company.

In Europe, it feels like they're much more threatened by the Chinese OEMs in part because they're letting them enter the markets, right? In the US, there's heavier tariffs around it or other means to sort of prevent access. In Europe, it feels like certain markets are pretty wide open and you see BYD and others gaining share really aggressively.

Is that a, how do you think about that from a policy perspective in Europe? And is that, you know, not going to really hurt the economies there? I think there's a resident European. I mean, there's always a question of trade and trade deficit. And so, I mean, European companies, as well as American companies, they benefited a lot from the Chinese market, right? General Motors, Volkswagen, just as an example. So they've

Over the years, they've made a lot of profit in China. And so just from, let's say, a furnace perspective, you can see it just by trade, right? It makes sense that there's some balance that can be achieved there. 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 there. And then once you start manufacturing within the country, oftentimes those cost deltas actually go away. Right.

Like whether, no matter what the brand is, if it's a local brand or an international brand, if it's manufactured in the same place, you use the end up with a product that's going to be of similar cost. Yeah, when you talk about like, if you look at, so if you open your car, you can look at the content of the car in your door frame. It says this is, where is it made and how much of it is made? This is not a new thing. In Michigan and Detroit, this is a 50-year-old, 70-year-old debate. And because...

there are real implications where if you just buy all the subcomponents from foreign countries and then you assemble them in Detroit, that doesn't mean it's made in Detroit. My slightly more caustic view or aggressive view on Europe is Europeans are a little bit of asleep at the wheel in the sense of, I think, if I could inject something into the brains of the leadership of whether it's the EU commissioners or the industrial families and leads is,

It's like what I was told, you got to fight. And there's almost just like, oh, it's going to be, you know, the Chinese are so cheap. The reality is-

It's not. There's a finite amount of dollars it requires to make something. And when these factories are so automated, that labor arbitrage, which historically was the reason why China was really, you know, cheaper, goes away. So a fully automated factory in Romania versus, you know, China, they're not as different as you think. I, you know, I fall into the category of you for at least for America being an American citizen is we can't just be a consuming state. We have to build.

Because with that building, you also provide jobs and expertise. And there are countless case studies of American companies that offshore are manufacturing. You hear the Detroit annoyance here, right? Offshore are manufacturing to other countries, including Mexico. Then the knowledge of building things is there. And then if you're...

you're Mexican, you're Vietnamese, you're Indian, whatever you are, then you're like, all I just need a little thin layer. And this vacuum company is now, 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, because I was entering the workforce at the time in the late nineties. And the view was at the point was like, oh, this is globalization and it's okay. And it's like, we have to have a bit more strategy because it's,

The reality is everybody on the planet has some strategy. Thailand has some strategy. Brazil has some strategy. The U.S. basically made a conscious choice to allow its industrial base to leave, even though it was phrased in a different lens. But that was a conscious choice. It's our naive view that the system will just take care of itself.

It doesn't because everyone doesn't play by the same rules globally. And I think in industries like us, if you're an AI company in, you know, in San Francisco and you supply, you know, let's say developers that are mostly based, 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 we have the best technical talent still.

You hear about deep seek, you hear about these other things. They're absolutely real. They're not, again, you can't discount it. And by the way,

It's not that for America to win, China has to lose. The UK won, Germany won, Japan won, and the US still won. 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. And I think that's where my view always is. If we're on the same term, we're playing field. In that context, Silicon Valley has some huge advantages. The best of the world come here.

So it's like just as much as we complain about China, Mexico, Germany, we want to attract that talent and to live here and to build here. And we're still, I think, the best in the world. So if we think ahead and we say, okay, we went through a period where

parts of our manufacturing and industrial base were effectively exported to other countries under labor arbitrage, effectively, or cheaper labor. A lot of know-how went out of the country and kind of stayed there. And in some cases, it almost feels like we've lost some of that know-how over time. Does robotics and autonomy and the automation of factories allow a moment in time where we can bring that back? A factory arbitrarily anywhere

is cost competitive based on automation versus labor. Is this a moment in time? And how should people act on that from a policy perspective? Or how should, how should we be thinking about that more broadly from the perspective of starting companies or innovation? We don't know policy. We're not, we didn't go to, you know, Kennedy school went to engineering schools. So, uh, but I think broadly speaking, I think it is a huge opportunity and you see companies like rebuild and Andrew roll and taking advantage of this reality. So I think if I'm a founder, um,

It's an extremely inspiring time because everybody is seeing this opportunity and willing to fund it. You know, these companies like Rebuild Andral 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 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 also you spend a lot on models, right?

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, where that's heading? - Yeah, so we do a lot of work in autonomy, right? So 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.

And so fighter jets and drones and boats and all of these things, there's a huge data problem. Data is not nearly as easy to collect in some of those domains as it is, let's say, on the on-road domain. So we've had to do a lot of work over the years on how do we actually collect this data and make this 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's a few things I think that we've done that have been super advantageous over the years. So we've been investing in synthetic data for quite a while. And the details of how that works has 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. And you can extend synthetic data into a bunch of other domains, including into classified domains for defense.

where you can actually get some really interesting advantages. And then I'd say 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, the new research papers come out, as long as you have that corpus of data, you can do really interesting things. And 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 have been previously impossible just using newer techniques applied to the data that we have. I think one technical strategy that's been quite advantageous for us is

I think we always wanted a weight in the way. I mean, explicitly, we talked about this weight in the wings until like the autonomy ecosystem converged on a handful of techniques and this kind of post transformer boom. And then just seeing like 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 like can't be. There was a I mean, you're not talking about.

three years ago, there's a huge debate on if, you know, end to end in the many ways, and then this market, it's a marketing phrase as much as a technical phrase, end to end camera heavy systems where they are, they're gonna, are they gonna be able to perform? I think the big, big thing. So now,

We're on the same page that autonomy is definitely going to happen. And when you're, you know, playing in the ecosystem, you also know kind of which way it's going to happen. And so now the question is, who's going to monetize this and who's going to take advantage of it? And, you know, 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. And so people kind of interchange these and this, 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 like much more likely to continue to exist. And the big story of the many dozens of autonomy companies actually isn't, I mean, they,

They know as much as us and we know as much as them. And simply because we recruit many dozens of people from, you know, I think we're probably Waymo's biggest employer outside of Waymo and Cruz and Tesla, all of these organizations. So it's not like there's this false belief

view that there's some secret in how to build self-driving tech. Actually, within the business, everybody knows how to build it. And it's just like, you know, in these podcasts where you're always going to stay fairly high level, you're not going to get into that, you know, into that depth. But generally, the ecosystem's conversion on what those techniques will be. That was not the case just four years ago. A lot of debate. And then as we saw,

okay, there's a convergence. This is when you really, you know, move it. You folks basically waited for that moment in time where the techniques and the purchase crystallized. You're like, okay, now's our moment in time to really enter the market. And stay alive until then. 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, you know, in automotive terms, there's research, advanced engineering and production. We've always kind of hovered around advanced engineering where 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 like some system integrator. One of the things that I find really interesting about the adoption of generative AI is the bar is often higher for these AI systems than it is for people in terms of how good the output has to be.

And it's kind of striking, right? If you ask somebody like, how should I do a Series A pitch? You'll take whatever they say because there's a confidence. And then like, you know, you do it in chat, you'd be like, no, actually this isn't right. You look at self-driving 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 for, you know, like, should it be at human level? Should it be dramatically better? Like how much better? Yeah, there's a colloquial and then there's like a regulatory answer. And the colloquial answer, my view is, and that many people in the industry is, um,

Most of the systems are pretty good right now. Like they're already, certainly Waymo, if you just like, you use a proxy metrics, like mean time to disengagement on a Waymo, that's tens of thousands of miles. Yeah. Well, it's also like, I guess people measure the number of accidents, injuries, fatalities per mile, right? Yeah, exactly. So like all of those,

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

When the Waymo has taken that view and a Waymo engineer would always say, well, FSD is nothing like us. You can't have a Tesla with nobody in the driver's seat. Elon is trying to change that. But there's a liability piece of it, but separate from that. I mean, the media headline is always Waymo causes an accident versus Waymo saved N lives. Yeah, exactly. 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. Progress requires some of that risk. And I think-

But the key thing is the risk is lower. In other words, 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. 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, they're just not the same mistakes that a human would make.

And so then when it makes the news, a human will see that and be like, well, that's completely crazy. Like, how could that happen? But it's more of a result of the technology itself. Yeah, but I think, you know, just going back to the journalist kind of media view, we are what our incentives are, right? And the incentives there, a journalist writing nine people died of pedestrian fatalities last night in America. Well, that happens every single night. Sure. It's not interesting. And so it's just trying to get clicks. And the clicks are,

you know, the Uber ATG car in Arizona killed somebody is just, people talk about that all the time. Happened years ago. And it's like, you know how many hundreds of people have died in America from human driven vehicles? But that's on the, let's say on the cultural colloquial side, on the regulatory side, the issue that you have in America

broadly speaking, mature developed economies is the bureaucracy is the bureaucracy's goal is to, you know, create more bureaucracy. Yeah. And so a place like the National, you know, Transportation Authority is going to Department of Transportation is going to

say, hey, for airbags, we did this. So this new technology comes and we definitely need to regulate it in this way. Take a more extreme example. Take a country like Spain or Italy where the government is really, you know, very bureaucratic. Imagine you take Italy and just remove the government. I'm not saying, you know, a revolution, but remove the government and say, we're going to build these government institutions for the things they need today. Like that defragging and that the garbage of maintenance, that garbage collection never happens. And these systems are,

So it's like a lot of it is just illogical. That makes sense. And you're talking about the programming term garbage collection. Yeah, exactly. And yeah, I would just add that... Not garbage collection. These autonomous systems, they will be significantly safer than human drivers and provably so. And 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 this like

proofability aspect of that something is safe. But it's never going to be perfect. Like you can fundamentally, you can easily design traffic scenarios where the autonomous vehicle gets into an accident by 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's two ways of transporting people. One is this one that the computer does and it virtually is perfect. And the other one is this like half-asleep alien

18-year-old teenager going to Starbucks shift after partying all night. Like no objective, you know, would pick the teenagers. The same thing, I think, even you look at like AI in the, like why is ChatGPT so loved?

search exists. There's all this legacy. It's just a better product. What do you think is the timeline to large scale adoption of autonomy? So obviously Waymo is growing really quickly right now. Tesla is continuing to push forward on different autonomous systems. Like how many years away do you think we are from general availability? Yeah, 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 kind of bound it to America for now and then we can talk to the rest of the world.

Every vehicle manufacturer in America that ships a real amount of cars is building some version of a Tesla competitor. So I think general availability on a FSD-like system over the next five years is going to be common, just like navigation systems. Now, how good those systems are and what the price points are, those will all define the breadth of those features.

Waymo will continue to expand cities. I think we're seeing Waymo in 2025 with what was promised in like 2018, 2019, which is we're going to do 40 city rollouts and that's going to be the next, you know, two or three years. The example really to think about this is let's say we're sitting in 20, 2007, the iPhone just launched and you asked me how fast are we going to see the iPhone in lots of people's hands?

It's like slow, slow, slow. And then suddenly everybody has it. I think there's going to be some version of that. One, you know, again, anecdotal example is I go to L.A. and, you know, it's not Silicon Valley. Yeah. Everybody knows about self-driving. That was not the case like 12 months ago. Yeah. And why is that? Because the Waymos are everywhere. Yeah.

And so it's like for the first time when I explain applied intuition, people are like, oh, I get it. Before they were just like, you know, all these like almost like Luddite kind of responses. And it's every person who sits in a Waymo, they just, they convert over to, okay, self-driving is a thing. The natural next step is, okay, why doesn't my car have some version of this from a passenger car? So I think like,

the whole window of expectations for self-driving was like 20, let's say 15 to 2020. And that's really like 2025 to 2030. But I think general availability is coming quickly. I don't know. - I would just add like, as an engineer, I think the next five years are probably the most exciting period imaginable because whether it's automotive, defense, so think planes, ground vehicles, boats, all general robotics, like all of these things,

Right now, we don't see a...

a real rate limit to how fast we can advance technology. Like we're just making progress every single day on all of these things. And we don't see a point where that progress is going to slow. Yeah, it's definitely like, it's funny from like an engineering perspective. It's sad and somehow that like all the people got excited like when it wasn't right. Like this is the best time to work on self-driving. Like it's ready, it's ready to go mainstream. And frankly speaking, to monetize all the billions spent on Cruise and Argo and those companies,

all of that didn't go for nothing. That's in people's heads and those people continue to work on the technology. So I think it's a super, super exciting. It's kind of a magical moment in time in the industry. And that's true of autonomous systems. And obviously it's true with all the sort of

- Language models and chat GPTs and all that. - Maybe extrapolating from that question is like, when will this stuff be completely commoditized? Where it's like your expectation for self-driving is zero dollars. I expect it for free. Like right now when you get in a car, you're not like CarPlay, I need to pay like $3 a month to, no, it's my phone is just being projected in the heads up display as expected for free. I think 2030, 2040.

2035, you're going to have deep downward pricing pressure, like to where it's like the expectation is going to be close to free. And I think the, not to pick on Waymo a lot, but it's just the easy one because we're in San Francisco to see all these cars around and it's continued to still exist. That's a big question, right? You spend 12, $15 billion on developing this technology and it commoditizes before you monetize it.

That's a super, super scary situation. 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. It feels very transformative in all sorts of ways in terms of, you know, the magical experience of getting in the car and

you know, everything else. I think they've done a really good job. And I mean, I would go on a limit, say like the self-driving revolution will have as much of an impact as the LLM revolution is happening. Like we, because not everyone grew up in Detroit, you don't appreciate these little things. All the way where everything's designed, where hospitals are, how parking, it's all based on cars. Cars are this,

Like it's this invisible thing that it's like electricity. It's invisible things around you. It's impacting every single thing. Can you imagine going for a month and not interacting with a car? Yeah. Or a week? Yeah, no, it's interesting because I remember when all the first 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 Congress people to talk about that specific issue that they're worried about.

And 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 where do you put the parking lot? Everything. Grocery stores. How far they are from neighborhoods. 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 actually the car is not the main thing of your life. It's actually the subway and walking. And there's no other place like New York. Yeah, and eventually what you should end up with is lots somewhere outside of the city with a bunch of cars. And then when you need a car, you push a button and it comes in and it grabs you and it takes you wherever you want. And you probably need fewer vehicles. Yeah, I think that's where there's a debate. I think you see this with mobile phones is as calling became free. Remember, calling used to be minutes and text used to cost 10 cents a pop. Text and calling haven't gone down.

They've gone way through the roof. Orders of magnitude higher than we ever communicated in 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. 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 position. But that doesn't necessarily mean there's more traffic. It doesn't necessarily mean you need more parking lots. You could actually... I'm in the optimistic view of the world, and this is, again, my view, the issue with Europe and sometimes is, instead of the knee-jerk reaction being no, the knee-jerk reaction should be yes. This will usher more productivity. It brings up... You know, we shouldn't have...

huge percentage points of our city is just empty parking lots. You make those parks, it's really nice. And I think self-driving can help beyond that, just it's literally less humans die. - So you've kind of laid out your vision in terms of economy and sort of the reworking of cities and some really large scale things that are very exciting that are coming and how you guys are gonna help power that for the industry. How do you think about using AI in other parts of your business? - Yeah, and specifically in tooling and in the vehicle OS, let's say in-cabin experience.

Number one, the way software is being developed, we see this through all the, you know, the coding assistant tools. All of that needs to happen in automotive and these other industries. So we're at the heart of that. That's why we're changing our name to Windsurf Automotive.

On that, there is a lot of very interesting constraints to the problem when you talk about building software for vehicles. And so I think we as a company, 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 in-cabin side,

side, you know, the vision there is a pretty straightforward, you know, which we're working on now, which is you take a, you know, a mining operator and he walks up to his Komatsu dirt mover, this giant machine that, you know, moves dirt basically 24 seven, that machine should know who that person is. And as they enter, uh,

that person can have that 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 this emergence, this teeming. And I think that type of AI experience is...

I think is more fundamentally important than even just getting Waymo going or just getting out to, because that's the hidden part of the economy, whether it's writing software for the engineering tools that write software 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, this has been talked about by others, but we're certainly experiencing it as defense is moving from one person, one machine to one person to many machines. The way to think about intelligence within these other domains and dominions isn't just, well, how can you use an LLM there? It really is like, well, what does intelligence look like?

for a warfighter in the field who has a couple hundred drones? Yeah. And how does he say, OK, I need this there and I need it fast now to get information from other, you know, other parts of the force and other forces and other countries to actually make that decision very, very quickly. Yeah. 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 the comms and the RF between all of these systems and and how the data is actually moved between them. And so really, really interesting problems.

and uh yeah we've got some really interesting so like you know we think vehicle intelligence trademark is like this yeah i you know it's funny you know as founder for the founders who are listening it's super rare to actually work on stuff that you you know you really love and it's no disrespect to people who work on like the dentist crm sure but it's like a lot more fun than that to see because it's like taking ai in a way which is

not just the chat box, which is great for all the reasons it is, but it's, it's like beyond that. So, you know, one of the things that I think is unique about applied intuition is you also have a very large and sort of deep bench on the design side. Yeah. And you think deeply about these sort of forward-looking experiences, both in cabin and more broadly.

Could you talk a little bit more about both that team, but also that future that you're imagining that's coming? Yeah, I think if you, you know, in the chat GPT world, there's some design there, obviously, and it's significant. But once you're truly like 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. And so there's still some of that work is under wraps, but yeah.

we're doing real work there. If people are particularly interested in that, especially from a designer's perspective and you're tired of doing like login screens for Google, like this is like, or like, you know, spending six years on just changing the shade of the sign in. So 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- - So 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 like everything auto adjusts yeah your playlist comes on whatever it is it kind of logs you in yeah and just like how it interacts with you design isn't only pixels it's an experience right um

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 just hiring across the board or how are you thinking about that right now? Well, fortunately, we're hiring across the board. Obviously, I think we hire from all, let's say, the spectrum of like pure researchers all the way to folks who are working on the other end of just like infrastructure implementation. I think we have like over 100 roles available.

Of course, everyone, ourselves included, is always looking for great AI talent. So that goes without saying. But we also have, I would say, an extremely deep appreciation for just really strong software engineers that are also just deep in the operating systems and the, let's say, systems engineering realm. We work on stuff that's very important and very, very technical. And so, yeah, people who like hard problems like to work at Pod. Yes, our company is something we're proud of. It's like 80 people.

2% software engineering is extremely concentrated. It's a very, very technical company. And we build products, you know, we're not doing services and things like that. So that allows, you know, if you like that kind of stuff, you like building products,

you know, I think we're an interesting place. We might not be that cool though. I think there's, I got the, I got the, I got the car jacket. That's about it. Last time you'll see this. It's like a costume. The best evidence it's a costume is I'm uncomfortable. It's like I'm wearing like a clown outfit. Great. Well, thank you so much for joining me. Yeah. Thanks for having us. Awesome.

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