a16z Podcast - a16z Podcast: Capitalizing on an Autonomous Vehicle Future

Episode Date: February 24, 2019

with Peter Ludwig, Qasar Younis (@qasar), and Sonal Chokshi (@smc90) When people talk about autonomous vehicles, we hear everything from "we're much closer than you think" to "we're much further than you think". So where are we, really, in the widespread reality of autonomous vehicles today? It depends, of course, on how you define autonomy -- which is where a handy recap and update of the SAE (Society of Automotive Engineers) levels of autonomy comes in. But still, given everything out there from self-driving shuttles to Teslas, it's really hard to tell just where we are and where the nuances of, say, Level 2-plus vs. Level 3 might come in. This episode of the a16z Podcast takes a quick pulse on where we are in the state of autonomy in 2019 when it comes to autonomous cars, shuttles, robots -- basically any "autonomous" and/or "self-driving" vehicle out there -- as well as the analogy of mobile for understanding the space: where it works, where it breaks down. But did even the mobile industry itself really have a clear iPhone "moment"? When did mobile devices that seemed so limited -- or seemed like just "toys" -- suddenly (or not so suddenly) go to an apps layer that we use every single day? How do we build "the rails" and "the trains" at the same time in this case? And perhaps most importantly, where will the spoils of this new wave of innovation go -- to Silicon Valley or Detroit? Or outside the U.S.? Who are the players? How do regulatory -- and quite frankly, nationalistic -- concerns come into play here? And finally, how does one balance the desire to embrace innovation in an open and fast, yet still very thoughtful and safe way? The answers, according to Applied Intuition co-founder and CEO Qasar Younis and CTO Peter Ludwig (in conversation with Sonal Chokshi), have to do with commodities and capitalism, with science and science fiction, with simulation and software as infrastructure, and more... And really, how we define autonomy now, and in the future.

Hi everyone, welcome to the A6 and Z podcast. I'm Sonal. Today we're continuing our series on consumer tech trends with an episode that pulse checks the state of autonomy in 2019. Where are we with autonomous vehicles right now? We also share some clarity on what levels of autonomy means there, including touching on regulatory aspects, and also discuss, quite frankly, capitalism, what cars mean nationalistically and what it'll take to bridge the worlds of Silicon Valley and Detroit. which is why our special guests are Kazer Eunice, former C.O. at Y Combinator and co-founder and CEO of Applied Intuition, and Peter Ludwig, CTO at Applied Intuition, which builds software for the autonomous vehicle industry. Throughout the discussion, we thread the analogy of mobile to autonomous vehicles, where it applies and where it breaks down. Speaking of, be sure to also check out A6&Z.com slash autonomy for posts, decks, and videos from Benedict Evans, Frank Chen, and others. But this conversation begins by cutting through the hype on whether autonomous vehicles are coming soon or not. It's interesting. You can kind of read publications. And within a three-month period, you'll hear we're in the early days, the hype site, we're in the trough of despair. Or disillusionment, I think it's called, right, the Gardner hype cycle.

Yeah, you have pessimism. It's kind of all over the board. And then you have people saying it's here tomorrow. Yeah, exactly. And I think the probably a good analogy to think about where we are specifically is that I like, to use is where mobile was in kind of roughly 2005. What we consider to be the modern smartphone isn't really there because you're like, oh, look at this Motorola razor. It's not that powerful. And I can kind of extrapolate that maybe this BlackBerry will be cheaper, but it's very hard to really extrapolate. And so being even more specific, if you look at kind of 2010, 2011, 2012, mobile engineers highly coveted in Silicon Valley. I had a mobile company. My last startup was a messaging company. And that was kind of the bleeding heart of Silicon

Valley and that was the next wave. You kind of have a lot of that right now in autonomy where autonomous vehicle engineers, roboticists are highly valued, highly coveted. I mean, didn't like Uber like suck or Waymo suck up the entire CMU robotics department at one point? Yeah, yeah, exactly. So that's, and that's happened multiple times. These companies like May Mobility who basically are the U of M lab. You have a voyage who came out of audacity. And so, yeah, that's happening left and right. If you take that mobile analogy though, and then you think, well, in 2010, And there's 11th, there was excitement that just a few years later, 2015, 2016, nobody's, you know, writing objective C.E. These waves go really, really fast. And I think a good kind of adage. I think it was Bill Gates who said this, you know, in two years, nothing looks different.

But every 10 years, things are dramatically different. So if we look back at 2017, autonomy doesn't look that much different. The players are generally the same. But I think 10 years from now, autonomy would be very, very different insofar as it might even be a commodity. Interesting. That's kind of controversial. I think there will be a lot of parallels as well on the hardware front as well as the software front, looking back at mobile. A modern mobile phone has GPS and inertial measurement unit has all these advanced sensors that prior to mobile becoming big were very expensive electronics that were only present in potentially military systems. Right. Chris Anderson calls these components, like the peace dividends of the smartphone wars, this idea that essentially all the supply chains and all that competition and the commodification actually create. this rich and thriving ecosystem of all these commoditized parts

that can now be recombined and deployed in new ways. And today we're just at the beginning of that for automotive sensors and autonomy. Yeah, the real miracle of, I don't want to get too philosophical, but capitalism. We love philosophy. Go for it.

You know, this is the, not the engineer in me, this is the MBA in me speaking. The real miracle of capitalism is there are all of these things that are made much, much better, much cheaper that are almost are the rail.

in which these industries lie on. And I think, you know, even if you're sitting in 2012, I don't think anybody had the, aha, I can't believe it. The mobile era has arrived, exclamation mark. And people, when we talk about autonomy, they almost want a declarative event, a eureka moment where autonomy is suddenly unloaded into the masses.

And when you look at mobile, that didn't ever happen. You just remember, one day you decided, I'm going to find and get that iPhone. In 2007, I was at Harvard at the time, And I remember one of my buddies getting a phone, and I said, oh, what do you think of this iPhone thing? And he goes, ah, it's kind of like a toy. You know, Chris Dixon says this at A16G a lot.

The next big thing will start out as a toy. He's modeling that off Clay Christensen's disruption theory. Yeah, who's an HBS professor, bringing you a full circle. Exactly, which is essentially that the innovations happen at the lower end or the underserved end of the market before they hit the mainstream, and it kind of tips enabled by some kind of enabling technology underneath it. Yeah, and so this type of incremental, kind of revolution or incremental changes that one day bring to you a product.

You know, even if you take the iPhone, the iPhone rests on hundreds of companies and thousands and thousands of innovations. And they're not just in, you know, the screen. No, it's in the entire ecosystem. The payment processing all the way down to, you know, the analytics for apps. The broadband and the connectivity. I mean, that's actually the missing piece for a lot of continuing installation in the mobile phase. There's so much.

Exactly. I think there are these statements made that, you know, the path to autonomy is far, far away. It is better to start autonomy company today in 2019 than ever before. So I want to ask a few questions on this. So the first thing is the kind of theme of what you're saying, and I buy this, is that, you know, innovations, they seem incremental at the time. And then they kind of tip to where they accelerate very fast. And there's some kind of combo of the two where the iPhone was like 20, 30 years in the making. But then I would also argue that there is, well, there may not be a discreet, specific single event.

It is an accumulation. There is still a quote iPhone moment in every industry where that industry sort of mainstreams and you really then begin to see and experience the potential, even if it does start off as a toy. So my first question is, for autonomy, how far away do you think we are? Not just in terms of time, but steps

towards that, quote, iPhone moment. So let's define the iPhone moment first. You know, I think it was Steve Jobs who said, you know, the 60s really happened in the 70s, and the iPhone moment really happened in the like 2012, 2013, right? The iPhone moment in my mind is when you have, you know, frankly, the 12 or 24-month period where Instagram, Snapchat, Uber, and WhatsApp are all some created, and they all are created in a roughly pretty tight time bound. That's the iPhone moment in mind.

And what that is the lower level is. So you're really saying the app layer where people are really using things. I think that's what generally the public thinks about it. Now, I think probably the more specific moment is the announcement of the iPhone. But if you look back, the announcement of the iPhone is met with skepticism. We forget that now in hindsight. There's that famous video I think of Steve Ballmer talking about how great Windows Mobile is in comparison to iPhone because it has so many more features.

Oh, I forgot that. BlackBerry was like, well, no way this is going to, this is. is going to be actually a real thing. Again, the gimmick, the toy. So if you take the iPhone moment as a 2007, we've already had that. That's the Waymo shuttles. People are like, well, these things can only go during the day. That's not very useful. I don't live in Arizona. So what the general public, though, will consider the autonomy moment is when you meet somebody who doesn't live in Silicon Valley, doesn't work in technology, and they've done, they've had an autonomous ride. Maybe it's on college campuses. Maybe it's an airport shuttle. Maybe some goods appeared at their house with an

autonomous robot. That's when you're seeing the penetration of the market into areas which are far beyond the early adopters or the, or something about it. I mean, one could argue that that to your point in terms of defining what the iPhone moment is is not the moment. It's actually the experience of the iPhone. It's the applications, the iPhone phenomenon even. So that's really what we're talking about here. So then on that front, where do you guys think we are? How far away are we from there? So we have shuttles already. This is another. I think mischaracterization or classification of autonomy, it's almost always exclusively thought as robotaxies.

And autonomy is actually much more that the adage that anything that moves will one day be autonomous. We believe that very, very deeply. And so the point being is they'll come in these like little waves. And each of those are different. The robotaxy wave is kind of a bit orthogonal to the shuttles wave, which is a real thing, which is campus shuttles, retirement.

communities. So those are different, which is orthogonal to the self-driving truck wave, which is orthogonal to the, I would say, the warehouse robots. Why do you think all of these are orthogonal to each other? One would argue that they're the same underlying kind of roboticization automation. So why are they orthogonal in your taxonomy and worldview? There are many similar technologies that are shared across the different verticals, but there's a lot of domain-specific work that's still done to make these systems actually production worthy. For example, John Deere has had a production semi-autonomous tractor trailer system for harvesting crops for more than a decade. As these systems become more and more sophisticated and more autonomous to the point where there's

no human in the loop, there is a lot of engineering effort that sort of goes in that last 10% to get to that production quality. Yeah, that's what people always talk about is that sort of last 10%, that last mile that, you know, you get the 80%, the 99%, but then you have this like percentage left, which is quote all the edge cases and all the things that people are trying to tackle. there are levels out there for how people describe these things. And so Elon Musk will make a claim about Tesla's and people will say, well, they can't handle all these edge cases, et cetera. So in this state of autonomy, 2019, where are we on the levels of autonomy?

Can you quickly break down that taxonomy for our listeners? Sure. So going through the levels, just one by one. So level zero is where most production vehicles are today. And so this would be a car that perhaps has antelac brakes and traction control, some version of electronic stability control. but the systems are all fairly, they're fairly dumb in the sense of they're not necessarily seeing the world in any way. Level 1 system will mean that there's some level of automation, so adaptive cruise control is an example of a level one system where typically there's a radar that's seeing the vehicles in front of you on the road, and then the vehicle's able to accelerate and apply the brakes automatically.

Level 2 is where things get pretty interesting. That's where you typically have a combination of a lane keep system with an adaptive cruise system. So, for example, the Tesla autopilot system is a level two system. It's able to maintain its own lane safely on the highway. And right now, the trend in production systems is automakers are trying to go to what they're calling level 2 plus, which is taking these level 2 sort of lane keep plus adaptive cruise systems, and they're adding on functionality for automatically taking freeway interchanges. And so if you can automatically take an exit and then perhaps automatically emerge into a freeway,

while the human is still behind the wheel and paying attention, that's called a level 2 plus system. That's a level 2 plus. Exactly. And so major vendors, for example, MobileI, they are now marketing their level 2 plus systems to OEMs. Level 3 is sort of a bit of a dubious classification where it's essentially saying that the user should be able to not pay attention

and the system should be able to alert them when they need to take over. So it's kind of like a passive driver, a passive human in the loop, not an active human in the loop. Exactly. The problem with that classification, though, is it sort of breaks down at the technical detail level. There are lots of situations where dangerous things can occur, where the system wouldn't necessarily be able to have worn the driver ahead of time. Within the industry, there's been hesitation to use that actual classification of level three. And that's where really the level two plus classification comes from. Right. It's a funny little distinction,

but I get it. It's almost like it's like one, two, three, four, five, and then you have like three in the middle, this weird, blurry pivot to quote true autonomy. Exactly. And I think I've seen some demos of systems that were purported to be level three, but actually then in the demos, there were events that require the driver to take over immediately. So that's not really a level three. That's really a level two system. And then when you get to level four, that's that's really where we're talking about these fully autonomous robo taxis that have some geographic fence. So for example, the Waymo pilot in Arizona, that's a level four system where there's fully autonomous vehicles, but only within a certain geographic

region. So the geo-fencing is just like the physical location of how far it can operate in. So generally there's what's called an ODD, an operational design domain, and that's the set of capabilities that the car has. And so as long as the car is within the region of the world where it knows, based on the engineers who worked in the system, where they have good confidence that it's able to handle all the situations that can occur, that's considered within the ODD. And oftentimes, it also has to do with the mapping system that's on the vehicle. And the weather and time of day. Exactly. Is this by the way also where like a lot of these cart robots and delivery robots sit because they're only delivering on campuses and constrained

spaces? Does that count as level four? That's absolutely a level four system. Because for for those, there's no human operator typically. And so it is a level four system within the ODD of the robot. Got it. And so level four is fully autonomous in that there is no human in the loop. Or at least is a human off-site, like not in the car, but maybe monitoring feeds? So technically, you can have a human in a loop, but the system needs to be able to safely handle any situation that it can be in for it to be considered level four. And so that might entail the vehicle pulling off to the side of the road,

waiting for a human to do something, but typically most of the systems that are considered level four operate the vast majority of the time fully autonomously. And then the very last level is level five, which is more of an idea than a reality. It's the notion that there could be a vehicle that is able to drive autonomously in all conditions where a human would be able to operate that vehicle. And the truth is in the industry, no one is even close to that particular goal. So that's further off.

That's quite a bit further off. Yeah. Okay. So what we're talking about here when we're talking about autonomy in this context of this podcast, you guys are actually focusing more on level four. We fundamentally believe that the tools that you're using to develop your level two systems should be actually the same tools that you use for three and four. And if you look at kind of the tooling used to develop the system, historically the tooling for level two system, what Peter mentioned earlier, LCC and ACCC, Lane Keep and adaptive cruise control,

those were more hardware-focused tools. And so they would, the quote-unquote, simulators were trying to spoof the hardware that is actually controlling the system, so the radar or the camera system. They're literally tools where you actually point the camera that would be sitting in a car in front of a, like, a monitor. That's the quote-unquote simulation. Now, the fundamental difference is you go up the levels is

there's a proliferation of scenarios. There's a finite number of scenarios when you're just going down the highway, trying to keep a lane and a certain distance when you're in an intersection with, you know, four-lane intersection, with multiple agents, all those agents can behave in many, many different ways, and the vehicle needs to be able to understand

and then navigate in that environment. And so we build tools that not only start with a level two, would then take, you know, take development all the way to level four. Interesting. So you drew the analogy earlier about the mobile analogy. But where does that apply and where does that fall apart? Because a couple of differences, I would argue here, are one that with mobile, we knew there would be some application, but there's been a lot of second and third order, you know,

applications that no one could have predicted or maybe would not have known that selfies would be such a big deal or social would be so, you know, powerful. They might have thought it might. Transactions, commerce, I think people predicted. So that's one thing. So with autonomy, it feels like it's the other way around where actually I think people do know what a lot of these things could be.

Of course, it'll be second and third order effects. One of our partners, Frank Chen, did a whole series on the second order effects of autonomy. In the real estate issue, yeah, exactly. Exactly. Insurance, how does it change? You know, infrastructure.

I did an op-ed when I was at wired on folks from Autodesk that were thinking about the future of infrastructure. I think that's because you have cars out there today. Exactly. So we have an analog. Yeah, you have an analog, which mobile, you had computers,

but they're kind of fundamentally different. People didn't even believe that they could even handle the constraints in this way because that completely changes the design. And here we are talking about cars still look like cars for the most part. I mean, yeah, Google's cars could be a little kawai-like and cutesy and Waymos and all the other ones have different looks and feels. But overall, they're looking like cars. But I think that's where we're getting to the edge. The interesting stuff happens beyond that we can draw the Instagram analogy now because we're in 2019 and not 2005. In 2029 or 2039, we'll be able to say, well, it was actually in hindsight it was so obvious that there's

be people who are living maybe in autonomy or some more unique and crazy things or implications that we just don't have right now. I think sci-fi, I'm a big fan of sci-fi, and I think our imagination only goes so far. And there will, without a doubt, be autonomy applications, which we're just not thinking of 2019. I agree. And also in the sci-fi world, I think it was William Gibson. I can't remember who said that quote about, you know, don't predict the car of the future, predict the traffic jam of the future or whatever that is. I forgot who that quote. right, where I think Will Smith jumps in and he says, I want to drive this manually. So are you crazy?

I'm going to drive this manually? Like, that will become a norm. We always get caught up of will that be 2025, 2025, 2025, 2035, 2035. I'm less concerned about the preciseness of when that date will come, but that will happen. Yeah. You're just saying it's inevitable. It's inevitable. Because of the kind of the three prongs of, you know, of new products, which is cost,

convenience and safety. And guess what? Autonomy gives you all three of those things. it's cheaper, it's safer, and it's more convenient. And safer in the sense of accidents overall. Right now, I focus on the outlier incidents, which are real, and we have to worry about them, but we're not there yet, is the big thing. I mean, again, the mobile analogy is relevant here.

In 2005, you'd see those bumper stickers, you know, get off your phone. And now, if you get in a car and somebody doesn't have your phone, it's like, what are you crazy? How are you doing it? It's like the opposite, because it's mapping and all these other things that you wouldn't have thought of when you had the Motorola razor. Well, since we're talking about right now, and I agree that we don't know what we don't know, who are the players in the ecosystem right now?

Like, I can guess some of the obvious ones, like the manufacturers of cars, the mapping companies, the mobilized that supply components and sensors. Like, how would you break down the taxonomy of the players? I think the automotive industry is a good analog to some degree of what I think the autonomy industry will be. You'll have end consumer-facing companies who will have brands that interface with a consumer, whether those are ride-sharing companies, AV providers, or continue to be the BMW or the Tesla's, I think that's up for a debate.

Then you'll have folks who are supplying services. Right now in the automotive business services, quote-unquote, are the dealer services. But in the autonomy world, we always talk about and is the emergence of the software car. And so in the software car, those services are much more, they look like kind of your phone. I think that seems fairly obvious

because you see some of those already, CarPlay and Android Auto are early indications of that. And then you have the thing that you can call the infrastructure companies, just like you have in phones and in the web. There's this huge, you know, every time you go to San Jose, you see these office parks of companies you've never heard of and you wonder, why do they have 10 glass buildings? Yeah, totally.

And there'll be those companies and they'll exist in automotive as they exist right now. I mean, people, you know, Forcia and Magna, these are becoming more known in the Valley. when I worked at Bosch before, Bosch was unknown just a few years ago. And it's finally now, because of autonomy, Bosch is like a relevant name. And so I think the ecosystem will be like that. Each of the things that you have in mobile and web or more accurately automotive will continue to exist just in different shapes and shapes and forms. Because the change is pretty significant.

What we're talking about autonomy, the human driver becoming a software product, but you also have the internal combustion engine becoming an electric drive train. Yeah, and so an electric drive train, for example, that doesn't just impact the propulsion system, but it actually impacts every other component on the vehicle. For example, the cooling system, an air conditioner that's on a typical gas car is going to be different from an air conditioner system that's on an electric car. Yeah, I mean, I have a Prius, which is nowhere near autonomous, but it is electronic, partially. And I have to say, it was like a huge mindset shift for me to even realize, like, oh, all those tips

about how to check your coolant and open your hood in case of an emergency before AAA. comes, like, they don't apply anymore. The mere fact of pushing a button to turn it on instead of using a key, like, I mean, those are really mundane examples, but it's an example of what you're talking about, which is like it changes everything. Things you don't even think about. All these great revolutions are very mundane.

Yes. I like that concept, actually, because I think about that even in terms of self-improvement in your life. Like, it's always like at the mundane level that the real shit happens. Yeah, yeah. Day to day, nothing looks different. No. But when you reflect, you know, five, ten years,

it's very very different. I think in kind of the old and new, and zooming into just autonomy. You have this rich universe of companies now that are either form, forming, or are quite mature, that are doing individual components. So you have sensor companies

that Peter mentioned earlier. You have mapping companies. You have companies like us, infrastructure companies. You guys would categorize yourself as infrastructure? Yeah. I think that's probably the most accurate term. What's different about simulation in the past

versus simulation today, the simulation in the past, was usually used to build hardware, products. And we're using simulation to build a software product. That's actually really interesting. Let's pause on that for a moment. I love talking about simulation on this podcast actually in general, because to me, to your earlier point about virtual worlds, it reminds me of one of my old edities concepts of mirror worlds, David Galanter, and this idea that you can essentially turn everything into something that can be in a virtual

system. And that is, I think, what you mean by virtual world, as opposed to, quote, you know, VR virtual worlds, like only immersive. And so this idea that you can essentially softwareify everything, that's pretty significant. So that swap that you're talking about, that before we would use simulation to build hardware, and now we're using simulation to build software, let's talk a little bit more about that. Yeah, simulation is not new to automotive or aerospace. These methodologies have existed for decades and even longer than that. You would develop a product, let's say a turbine, and then you would manufacture it.

You'd develop a bridge, and then you'd build it. Using software simulation is different because you have this. these products that are out there in the real world, and they're going to continue to inform the thing that you're developing in the simulator world. And so this connection of, it's almost like reality in the loop. It's a little feedback loop, but you're right. Reality in the loop is a more significant wave. It's less linear. X creates Y, Y creates Z. Z goes and influences X, and it's a nonlinear circle. And because of that, more infrastructure than purely simulation, because like, for instance, if you're managing large amounts of data, is that really simulation?

Technically, it's not. But you need to do that. in order to make your simulations useful connecting to the car. Is that part of simulation? No, but that's, so that's why I think where the larger umbrella is infrastructure. I mean, you could say, you know, HD mapping is really an infrastructure play, right? Those are the rails on which the train rides. It's also infrastructure in the sense that it's used continuously on an ongoing basis, whereas the traditional forms of simulation were typically used sort of for this big, bag moment,

which is the creation of this final hardware specification, which is then going to be made. It's shipped. It is delivered. It is done. This is never done. You guys, I mean, it's a terrible analogy, but it's a little bit like a Kanye album. It's continuing to evolve in the wild.

And after it's dropped, it's going to keep getting modified and what that. It's a real life goal I had of comparing my simulation company to. Well, we're all fans of music. So, you know, using your analogy of trains, because you mentioned like the train tracks. So this is interesting because what we're really describing here is laying down the tracks while also inventing the train itself. And the two things are kind of like moving targets against each other, et cetera.

So what does that mean for the evolution of the ecosystem? I think overall there is a co-evolution of sorts that happens between each of the different components involved. And so, for example, sensor companies and mapping companies and ensuring that the latest advancements that they have in their own products are then accurately represented inside of simulation. It's like the phone supply chain we're talking about earlier, right? So all these little revolutions and miracles happening

and the untold story that hasn't been discussed is if you're building autonomy yourself, what's the right path? Is the path to go vertical and build everything yourself or is the path to buy things off the shelf? Where in this ecosystem, where do you draw that line

of what is critical for autonomy, quote, and what is not? And so, you know, my rough view, and I would say largely, what is not differentiated between the companies the mapping companies included

you should basically buy off the shelf that's commoditized and you should be differentiating elsewhere because mapping companies are censor companies which are all kind of

have the same role in different ways we're spreading our R&D costs across 10, 20, 30, 50 players and therefore each individual player gets a more advanced product for a cheaper cost and that's capitalism right

you're driving market efficiency when people talk about a new industry will drive market efficiencies like tactically how does it happen it happens where you have individual players who are now unbundling the cost onto a bunch of people yeah a bunch of different companies and then those people who are participating almost in that consortium are getting the benefit of it now that doesn't mean you can go ahead and you can definitely go and do that vertical company there will always be an apple in every ecosystem yeah exactly but you know there's only you know you better be Steve Jobs right exactly and what I love about what you're just

describing and this is capitalism. It's funny because we might as well say cloud is capitalism at this point to make that syllogism. But it is the AWS moment in this ecosystem and it's talking about the fact that you can actually then free a whole new wave of companies to do things. I do find that very fascinating because until now I would have thought that autonomy is only for like the big big big five car companies. So the AWS example is exactly right. You can roll your own server. Some people have pride in running their website off their local. But guess what? What? Your consumers actually don't care if you're running on-prem, AWS, GCP, Azure, or whatever. They just want the service. They just want the service. And so, by the way, this happened in automotive. Automotive started, you know, Alfred P. Sloan. Wait, who's Alfred P. Sloan. I don't know who that is. Oh, okay. So they are early automotive pioneers. Oh, I would have thought it was Henry Ford. Sloan was, so he's not technically the founder of General Motors, but Sloan and Kettering were essentially the leaders of General Motors. GM was founded by a person named William Durant who had started another car company.

The amazing thing about the AV industry today is it's almost copy and paste of the automotive industry 100 years ago because you have these individual personalities who are shaping companies in their own way. Some get fired. They start competing companies. There's all this drama between existing players

who are coming in. There's a lot of M&A activity happening. Oh, this is all my favorite things when we talk about how software and tech evolution is taking you back to an earlier era. That's one of my favorite themes ever. The Sloans of the world and the Henry Ford's of the world, they wrote and they tried to build vertical companies.

I mean, Ford used to do everything. They used to get rubber from plants. They would forge steel. I think they even owned the farms where things were grown. So guess what? We don't do that. Why? Because it's actually more efficient to have a supplier ecosystem. Well, that's like capitalism to the T. I mean, that's like the classic, you don't want to, it's very, who was it? Someone did an experiment where they tried making their own sandwich from scratch. If they grew the vegetables, I think they had to outsource the cheat. They have to, they take the cows and the cheese. And I think they estimated it to be like over almost $2,000. And capitalism makes that sandwich $7.

So try doing that for like, or a computer, something that's more manageable. You know, there are, you can go on YouTube and watch videos about people trying to build their own phones. They end up just going to China and buying it for a bunch of suppliers. that's actually the faster way to do it. And the ecosystem conversation that's happening every single day in these autonomy teams is, oh, wow, we don't have that many engineers. Oh, wow, there's another huge pilot that somebody has announced

and how can we move faster? One of the easy rules of thumbs of you can see how sophisticated in AV leadership is just asking them, where's that line? And that line, that circle of competence should be as small as possible. that small circle in autonomy is algorithms.

That's the coveted golden nugget. It takes confidence to focus, narrow, laser focus like that. So you can go to like a completely different industry. Go to consumer CPG or you can go to consulting. If McKinsey or a, you know, Unilever or whoever it is will very clearly say, hey, you know what, this is the hill, this is the hill we die on. This hill, we have to be better than everybody else. The only way we win this hill is we abandon every other hill.

Right. Well, this begs a question. and Benedict often asked a similar question in his post on autonomy a lot, which is, you know, will Tesla become more like Detroit? Is Detroit more likely to acquire the Silicon Valley mindset faster, or is Silicon Valley going to move faster in sort of learning the skills of Detroit? I think there's no path to autonomy that doesn't go through Silicon Valley and Detroit. So it's an and not enough. And when you say Detroit, we mean roughly the automotive centers, Chittgart included. I mean, Japan and Korea and China included in that.

Right. You don't mean Detroit geographically. I mean, the entire category of car manufacturing, right? Yeah, as a secondhand for the automotive industry. Because Detroit has the delivery mechanisms, which are the brands and the factories which build these vehicles and the channel, for lack of better words. This is not an internet product. The channel is not a website. The channel is the traditional OEM business.

But the thing that you're distributing through this channel is almost ideally built in Silicon Valley. Again, we're talking about that circle of competence and how small you can make it. So where Silicon Valley, I think, strays is when we start doing things, which frankly speaking are outside this very small circle of software. And I get a little nervous when, you know, companies are doing a lot of hardware because there are other hardware centers in the world, which are arguably better, or when even broadly, like, you know, on podcast, people start talking about, like, these other things. And it's like, you know, If we went to some group of factory owners who, I don't know,

you know, our specialists and shoes, you know, they don't get on podcasts and then start like quantificating about, you know, you know, things outside of their little circle of competence. Yeah, totally. They talk about, hey, leather price and, hey, how are you getting cheaper electricity? I mean, I hear you. It's both. It's both arrogant and charming at the same time.

Yeah, exactly. But it's good because it pushes. It pushes you to go into try new things. Try new things. Yeah. And now, and so the magic happens where you're pushing trying new things in your area of competence, right? I can go and try to be an NBA basketball player. But guess what? It's probably not going to work, no matter how much effort and, you know, I put into. But so I think there's a

similar, you know, relationship between Detroit and Silicon Valley. There is a real merger. And my background, you know, both Peter and I, we grew up in Detroit area. Oh, I had no idea. You guys grew up in Detroit? Yeah, yeah. Of all the random coincidence is, not only we grew up in the same town. We grew up in the same subdivision. We're literally at the same crossroads for people who are in Detroit. It's 22 and Shainer in Shelby Township. I went to GMI or now Kettering University, which is the General Motors Institute. Peter went to U of M. So I actually started my career at a small engineering tool company in Michigan, but really my entire family works on the motive. So you guys are like Detroit born and bred. Yeah, I worked five years of General Motors,

two years at Bosch. And then we're in the same team on Google Maps. This is five, eight years, seven years ago, long time ago. And we saw chauffeur, which was, which became Waymo. And I remember saying to Peter, man, this is going to hit Detroit like a ton of bricks. Yeah. Kettering is located in Flint, Flint, so I spent five years of Flint. And, you know, when you look at places like Flint, you know, you really start thinking long and hard about like, well, where do people get these new jobs? That was the theme in the 90s in the early 2000s when I was growing up was, oh, there's going to be this revolution and all these people in Michigan are so suddenly going to have these great new jobs and guess what you know my family included those jobs didn't come my dad

never became a software engineer in his late 50s that doesn't happen and then also i think any business and the human experience is emotional to some degree i mean we very much like practice that belief yeah is this connection between you guys are really um we're really long on the Detroit Silicon Valley and not the oar so what do you think then that the winning company maybe it's not a winning company there's plenty of room for many but where is it going to sit and how How is it going to look? Well, it's like, you know, where does the winning automotive player today sit? I think it's very hard to answer that question.

There's at least, there's at least a few in every major geography. And the supply chain, which is really what the auto businesses, is everywhere. These are such massive industries. They have epicenters. So I think the autonomy software stack will probably for a long time be in Silicon Valley. But even you can look at like TRIAD, the Toyota Research Institute's autonomous division. based in Tokyo, you have other companies, BMW, Daimler. Even TRIAD actually has presence here in the Valley as well as in the Detroit area.

So I think this concept of like there's a company that wins it for A town. I think that's different. I think we sometimes get that analog because of the internet where you have Google, which is basically home team, which is Mountain View. Yeah, I mean, a lot of the companies are like Silicon Valley and Seattle and there's like a few centers that are very focused. I think these large industries that are very intertwined with these. each other. It's a lot less concentrated like that. I think the real fundamental issue we have, and this is getting more philosophical again, is what the internet is done and what software has

done is it's concentrated wealth. We talk about wealth concentration as like somehow blaming sometimes, you know, a certain political viewpoint. But really, they're so efficient software companies that does bring a disproportionate amount of money to where the upper center is. And so how can we make sure that that that concentration you know that the next wave which is autonomy doesn't keep

just kind of underlying that one of the other things that is not talked a lot about autonomy but should be talked about autonomy is these are national questions the German government won't just let Waymo come take over Germany and let Daimler and BMW go under business and the same thing

is true for Hyundai in Korea Honda and Toyota in Japan and the Chinese companies, because there's a recognition that if all of these cash flows end up going to these little neighborhoods in the suburbs of San Francisco, maybe that's not good for our national interest. In the Internet, because it was a new market, wasn't very visceral. Daimler is a visceral. Bosch is a German thing. Peugeot is a French thing. It's like the classic discussions around manufacturing, like, you know, this idea that, like, it's a physical product that is made in India, made in China, made in Japan. Made in Italy, you know, it's very specific, and you're right, there is a very national sentiment.

But what I love about what you're describing, too, though, is it is true capitalism, because I think capitalism gets a bad rap for the inequality, which is a fair complaint and a fair criticism. But to me, true capitalism is something that raises all boats in the ocean. Yeah, so I'm Pakistani. My birth in Pakistan, my family were from a small farming village. For the first, you know, rough seven years of my life, I was in this, you know, in this remote farm. village in the roughly in this valley and uh you know what's a real luxury hot showers yeah and so you know when i when i had that hot shower in the morning and i drink that cold water you don't take it for granted i think capitalism i know i feel the same way about electricity i mean my dad i was born and raised here but

my dad's from india small village and he grew up without electricity and then he later got electricity and i was just marveling just very recently in our families at the valley that we had electric beers. Yeah. That's insane. Like before electricity was not even available to people and now you have mass produced little tiny LED lights and like little bases as candles. That's freaking amazing. Exactly. No, I agree. So on that front. I think where autonomy is different is I think it has the potential and I think whether we like it or not, there is a regulatory aspect to this entire conversation. So I have a question about this because you brought up the point about there being a national interest. There's also a local city and state level of interest. Mark wrote an op-ed a few years

ago in Politico arguing that you can use a form of regulatory arbitrage where, like, say, Detroit could actually loosen some of the barriers, just like, you know, I think Governor Ducey's doing in Arizona, where you have different cities offering different incentives and doing more experiments so that they can ensure the ecosystem kind of grows up locally. How, A, is that really happening, given your thesis, it sounds like you're saying that everything can happen everywhere, and there's room for all kinds of players. And B, what do you see is there of the regulatory and policy issues

in the autonomy ecosystem? Yeah, I think everything can happen everywhere is more of this concept of there are so many components and these components will come from everywhere. One of my friends who's Indian who wish that states themselves in India would have more of a control over their own laws because he believes that within the U.S., the states creating their own mini regulatory environments

is almost like a mini form of capitalism. It's a competitive between the states. of capitalism, actually. And states or laboratories of innovation or cities are, too. That sort of federalist style, I think it wasn't an enabling condition for success. It's a feature, not a bug. Yes, I agree. And it's a great feature because the state like Indiana says,

hey, listen, maybe this is in our best interest because we're a state that trucks go through and we're going to make sure we make that toll income. But if you're a state like Arizona, and maybe you don't have that and you have this great testing ground, historically Arizona belonged before autonomy is a bit of, approving grounds for the auto business, that, hey, we see that, you know, the Arizona approving grounds for General Motors brought all of this, you know, business over the last 20 years, 30 years. It takes a lot of courage, by the way, because they did have, I think, the first instance of a

fatality through autonomy. So when we do talk about these states sort of taking the leap, there is sort of a cost you pay because in the case of Arizona, I think they were the first to have the first fatality related to autonomy. And of course, that's going to happen. I'm not trying to minimize it. that's a really big deal, but that is, I think, one of the tradeoffs is at cost. I think the states that are making those decisions are opening some of them and their citizens

to that risk. And so the citizens then elect those representatives who then say, hey, this is or is not the tradeoff that I want to have. Right. That matches their needs. And I think, though, probably what, again, doesn't get covered is I think that night there We're also 10 other pedestrian accidents in America where people died. You're right. There is a statistical thing, which is hard to think about when you're talking at a personal level.

It is tough because that's a real family. And if you're that person, you don't care. There's 10 other or 11 other people that die that night also. These are the guardrails we roughly think are ones that can be employed. You don't want to have complete laissez-faire open. everybody does whatever and pure permissionless innovation we're talking about moving killing robots this is like a human being like they're like one of the things we don't think about in silicon valley a lot of it a lot of times engineers in the auto business over the last years have gone to

prison i had no idea just a Volkswagen diesel scandal put employees a Volkswagen in prison and so there is real consequences when you're dealing with a product which an automotive product which can harm the public. The other end, though, is if you put in regulations and they're onerous and they're significant, guess what? Squelge's innovation? 100%.

And we're talking this. This conversation has been very U.S. centric. Maybe 1980 capitalism was a very, you know, regional thing. The real revolution that's happened in the last, you know, 30, 40 years is a capitalist revolution. It's just the shade of capitalism. And so when you think about China, which is a different shade of capitalism, if you think about Europe, which is a different shade of capitalism,

generally different approaches, but, you know, some regulatory environments are very open, and we have to be aware of that for not only the Silicon Valley and Detroit companies, but just in general as Americans, of being in an economy which is healthy and productive and at the cutting edge, but at the same time, U.S. citizens, you don't want to be a laboratory for private entities to make a profit. And so there is a very nuanced approach there. At the end of the day, we're really advocates of best practices for safe development. And so that means really taking the steps necessary to ensure that the systems and the software are safe before they actually go to the public.

Yeah, you're talking about simulation here. We've talked about simulation earlier in terms of the industry evolution. But simulation itself got a bad rap for a while. You know, there's a lot of companies that sort of felt like, oh, my God, simulation. It had a bad rap for a while. It's like, you know, I think trying to do VR. and AR to some degree in the 1980s. And so I think simulation, which has been different than ARVR,

is there are no complex systems that are being developed without simulation. Aircraft, military systems, automotive internal combustion engines, microprocessors, simulation is everywhere. And so I think that's because the underlying kind of software industry has become so much more advanced. It's computationally more efficient. you can apply, you have things like the cloud revolution, the ability to point lots and lots of resources at the problems.

I was like to say it's shifted from constrained to abundant. And that essentially creates abundant sensors, abundant data, you can waste bits. You can essentially simulate complex things unbounded in a way that humans can't even remotely conceive of. Yeah. That does answer the why now question. What are the limits of simulation?

I mean, we are talking about complex systems on a shit ton of edge cases here. Yeah, I mean, at the more technical level, simulations are never perfect. There's always going to be some difference between a simulation and a real physical system. We like to get our simulations to the point where they are plenty good enough for useful development. Good enough for development. Good enough for development. Good enough for pushing these forward and to give a very high confidence that the behaviors in simulation are representative of the real behaviors. But with that said, there will always be situations and scenarios where there are differences in behavior

between the similar environment and the real environment. Of course, right. Okay, so what's also interesting about this is that it essentially lets you get the three Cs that you described earlier, cost, convenience, and safety in one system. And to the regulatory point that you brought up, Kasser, it is, it lets you kind of strike that just right balance in there. But the big thing now, because you've been talking in this podcast about this importance of differentiation,

if this is a tool that everyone has, it sounds like they would differentiate on data. So how do you, in this ecosystem, are you making this argument that there's this horizontal versus vertical layer, Are all these players willing to share in the ecosystem, the mapping companies, the sensor companies, the big vehicle companies? How do you navigate the data side? Data means a lot of different things. It's not like scenarios and data that you have for autonomy, but it is the autonomy engineer who themselves are understanding how are the methodologies to best develop an autonomy system.

There is some what we call light network effects there between companies. Well, I mean, if you go to Stanford, they teach classes. that help you learn ANSIS's simulation tools. So there's literally this public company called ANSIS that does simulation tools and you can learn how to use it by taking classes at Stanford. And that's the same thing with AutoCAD.

If you look back, if you look, there are many tools that kind of fall into this group. I mean, when you learn how to program, you're actually just learning tools. Now, what's happened with software development is those tools have become really just a commodity. And there's many different ways.

And so we're still in quite a nascent, niche field with autonomy, so the tools are not a commodity. These tools are so hard to build. These two, the simulation is, it's not a trivial thing to build. At the end of the day, the lowest cost solution will win, but of course it has to be a real solution. Yeah, it has to actually solve something. And that's the industry is still working out. Right. It's actually kind of funny because the conundrum here is that software is bits and it's abundant and therefore it's accessible to everybody. But the specialties and the algorithms I'm clearly hearing and like the nuance of the the art. We used to call it know-how. When I used to be at Park, it was kind of the idea of

the know-how and the differentiation. But the point is, it's basically going the way of mobile. And you've been drawing the analogy, and we've talked a bit about where the analogy breaks down and where it applies. How do you think this plays out, given that you are a horizontal player? There aren't really big horizontal huge, like apples and Googles. There are vertical companies. Well, they are, but actually, you know, each of the sub-components, the phone manufacturers themselves, companies that do analytics for mobile, companies that do ads for mobile, a lot of horizontal players. Anything that exists both on Android and iOS is in some way a cross-platform horizontal play, right? And so I think where the commoditization

has happened, quote unquote, is in the apps themselves. I'm reading this book, The Five Ages of the Universe, which is the physics of eternity, right? Fascinating. So what happens? You'd write that book down. You know, trillions. Like, what happens at the end of the universe, right? All the stars have now died. Oh my God. I really need to be this book. This is totally my jam. I'm like really obsessed with space and evolution right now. It's a, it can be dry. I find it very interesting. But the point is once you get into these outer edges, the strange things start happening. And so we're now in that mobile age where there are applications that are gaining users very, very, very quickly and still not being valuable. Or some applications

that might not have as many users but can become super, super valuable because they're catered towards a very specific audience that needs that thing. And so I think with autonomy, I think the arc here, you'll see all these individual modules will be run by individual players

because there is this natural arc in capitalism which says the independent providers can do cheaper, better, and faster than anybody doing it vertically. But the question is, will the algorithms themselves ultimately be commoditized? And I think that's when you get into this far edge of the universe was like, could we be in a situation in 10 or 15 years that like today

starting a mobile app is very, very easy. That starting an autonomy company is very trivial. I think it would be very hard in 2005 to think that Kim Kardashian or whoever would have their own app and it would make millions and tens of millions of dollars. But that's the reality today because that's so niche. It's not just, it's not just, hey, it's a phone app. It's a phone app on a specific platform for a specific celebrity and just their fans. Because everybody else can just consume Instagram or something else. And so that real edge, I think that far off the world of autonomy 10 or 15 years from now, imagine if you could build an autonomous vehicle very quickly and very easily. If that could happen, what does that make the industry? Yeah, no, it's like a theme

we talk about actually is that the edge is where it's at. I mean, in computing and innovation. I mean, it's basically the democratization of autonomy. Well, you guys, thank you for joining the A6 and Z podcast. Thanks for having us. Thanks for having us.