AI transcript
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0:00:57 Pushkin.
0:01:05 In 2003, Chris Ermsson was a grad student at Carnegie Mellon University.
0:01:10 And he was working on a research project in Chile, in the Atacama Desert.
0:01:12 Beautiful place.
0:01:13 Very desolate.
0:01:16 The closest thing we have to Mars in many ways on Earth.
0:01:17 Which is why you were there.
0:01:18 We were.
0:01:21 We were building a robot to go look for signs of life.
0:01:23 And I was developing the navigation system for it.
0:01:28 And my PhD advisor came down and said, hey, the Defense Department has this competition.
0:01:29 They want to build a robot to drive.
0:01:33 50 miles an hour across the desert between Los Angeles and Las Vegas.
0:01:34 And I thought that just sounded awesome.
0:01:37 So we bought a Humvee.
0:01:39 And we cut the top of it.
0:01:40 Put a big electronics box in it.
0:01:41 A lot of computers.
0:01:44 All of the stuff that’s in a self-driving car today.
0:01:46 The high-performance computing.
0:01:47 The lasers.
0:01:47 The radars.
0:01:48 The cameras.
0:01:51 The HD maps were part of this.
0:01:56 It’s kind of the first time when all this stuff came together into a vehicle.
0:02:00 And then we developed it for six or nine months.
0:02:02 And then we tried to compete with it at the first DARPA challenge.
0:02:06 The team I was the technical director for.
0:02:09 We actually had the highest performing thing there.
0:02:12 It was supposed to go 126 miles across the desert.
0:02:14 It ended up going about seven.
0:02:17 When it got hung up on a berm.
0:02:19 And almost literally burst into flames.
0:02:20 And you.
0:02:22 I mean, nobody won.
0:02:23 But if anybody won, you won.
0:02:23 Right?
0:02:24 That was more.
0:02:25 Yeah, but nobody won.
0:02:25 That was farther than.
0:02:26 Yeah.
0:02:27 The key thing is nobody won.
0:02:30 If you imagine a marathon where you’re supposed to go 26 miles.
0:02:32 And the best runner went two.
0:02:32 Right?
0:02:36 And then burst into flames.
0:02:37 And then burst into flames.
0:02:38 Yeah.
0:02:45 I’m Jacob Goldstein.
0:02:46 And this is What’s Your Problem?
0:02:49 The show where I talk to people who are trying to make technological progress.
0:02:52 My guest today is Chris Urmson.
0:02:55 He’s the co-founder and CEO of Aurora.
0:02:59 A company that’s trying to bring autonomous driving to commercial trucks.
0:03:02 As you just heard, Chris started working on autonomous vehicles.
0:03:04 more than 20 years ago.
0:03:10 And in fact, his career traces the, really, the entire modern arc of self-driving cars.
0:03:15 From that first DARPA challenge to a top job at Google’s self-driving car project,
0:03:20 the project that later became Waymo, to founding Aurora, the company where he works now.
0:03:25 We talked a lot about the problems Chris is trying to solve in autonomous trucking.
0:03:29 And we also talked about the future of autonomous driving more generally.
0:03:33 But before we got to that, we talked about the earlier work he did.
0:03:37 Work that really helped get the field, the broader field, to where it is today.
0:03:47 So we’ll pick up the interview back in 2004, at that moment when his team’s autonomous car had failed and almost burst into flames.
0:03:48 It was crushing.
0:03:49 Yeah.
0:03:49 Right?
0:03:53 Like, you know, on the one hand, it was called a grand challenge, right?
0:03:56 Because, you know, a lot of people didn’t think it could be solved.
0:03:57 It was impossible.
0:04:01 Because on the one hand, it’s kind of like, okay, it was really hard.
0:04:06 On the other hand, you’ve, you know, we’re sleeping on the floor in the lab in the, you know,
0:04:11 in this garage in the middle of the desert for weeks and months trying to get this thing to go.
0:04:18 And then you launch it out there and you have this epic moment where you’re watching this thing that you’ve built tear out across the desert.
0:04:19 And you can just see the top of it.
0:04:25 And these helicopters that the military is using to track them as they’re out in the desert doing this.
0:04:29 And then you hear, you know, it’s supposed to go 120 miles.
0:04:30 And they’re like, oh, it’s stuck.
0:04:34 And then you hear, like, billowing smoke and broken.
0:04:36 And the poor thing comes back looking very sad.
0:04:39 And, you know, it was crushing.
0:04:43 But at the same time, we did set records, right?
0:04:49 If you look at kind of the product of the speed and the distance it went, this was an order of magnitude better than anyone had done before.
0:04:51 And so it was a big step.
0:04:56 And I think that was partly what encouraged the Defense Department to say, hey, come back again and try it in a year.
0:04:59 And then you did.
0:05:01 And then you did it again and again.
0:05:02 And what year do we go to?
0:05:03 Is it 2007?
0:05:05 Is that the next big moment?
0:05:06 Yeah.
0:05:08 2005 was another one of these in the desert.
0:05:12 2007, they did what they called the Urban Challenge.
0:05:17 So 2005, we were able to drive around the desert, not hit things too much.
0:05:19 2007, they say, okay, that’s great.
0:05:21 But now let’s stay on the right side of the road.
0:05:26 Let’s move in kind of pseudo-urban environments and show that that can work.
0:05:31 And that was the last of the Grand Challenges because that year we actually accomplished it.
0:05:34 We drove 60 miles around this air base and interacted with traffic.
0:05:39 They hired a bunch of stunt drivers out of Hollywood to come and drive cars around these robots to make traffic for them.
0:05:42 And it was a heck of a day.
0:05:48 And then the Defense Department, or at least DARPA, said, you know, effectively problem solved.
0:05:52 We’ve got this close enough now handed off to industry or whoever to take it from here.
0:05:56 And how did your car do in 2007?
0:05:58 We won, which was nice.
0:05:59 It was a good change.
0:06:01 So, you know, we…
0:06:03 And did it catch on fire?
0:06:04 No fire this time.
0:06:06 It just kind of worked.
0:06:13 We had a little bit of nerves at the very beginning because, you know, our system was pretty reliable, robust.
0:06:14 It worked all the time.
0:06:24 We go and bring it out to the start line and we can’t get it to boot properly because it can’t see this GPS satellites that it needed.
0:06:30 And we never had this problem before where, like, you know, frantically trying to figure out what’s going on.
0:06:35 And then we look over and realize that for race day, they’ve brought a Jumbotron.
0:06:40 And they’ve set that up right where the robots are at the starting place.
0:06:46 And it turns out they don’t really check these mobile Jumbotrons for, like, how much interference they’re generating, I guess.
0:06:48 So, we had this panic moment.
0:06:50 We said, you know, can you turn off the Jumbotron?
0:06:53 And sure enough, they turn off that and suddenly everything works again.
0:06:57 So, you know, it wasn’t without its challenges.
0:07:00 So, but it works, right?
0:07:04 So, it works and it works in a, like, quasi-real environment, a pseudo-real environment.
0:07:13 So, I mean, when you, at that moment, when you were thinking about the future, the future of self-driving cars, how did it look to you?
0:07:14 What did you think?
0:07:20 Yeah, I think at that point was starting to believe there was a thing that could happen here, right?
0:07:26 And probably, you know, certainly naively thought, oh, yeah, we’ve got this, right?
0:07:30 I mean, everybody kind of thought that, right?
0:07:31 Like…
0:07:38 I think, and that’s been part of what’s made the journey really fun for me is just, there’s just so many things to learn.
0:07:55 So many new problems to overcome along the way of taking something from a, it worked on this day in a race to, hey, we can go do something transformational that will save lives and improve the economy and, you know, do all these other great things.
0:08:08 It seems like that, the distance between it worked in a race and we can do something transformational has been longer, certainly than a lot of people thought, than a lot of, like, smart, well-informed people thought.
0:08:11 Yeah, me among them, right?
0:08:24 And, you know, it’s one of these things where I think anyone who sets out and does something interesting and exciting, often I think if they understood how hard it was going to be before they started, may not have actually taken the first step.
0:08:33 And so I feel a little lucky to have not understood that because it’s caused me to kind of stick with it and really enjoy the journey along the way.
0:08:40 I mean, entrepreneurs basically always say that thing that you just said, but in the case of autonomous driving, I really believe it, right?
0:08:42 It seems like extra true.
0:08:47 Like, 2007 was basically, like, the year the iPhone came out, right?
0:08:56 Like, which is to say in technology a long time ago, not to mention that there was, like, no computer vision as we know it today, right?
0:08:57 Which has become important.
0:08:59 I mean, so much.
0:09:06 No, it is, you know, the waves of technological evolution that we’ve seen since then are profound.
0:09:09 And we’ve been able to kind of surf those as we’ve been building it.
0:09:17 And it’s been, yeah, it is, it’s been a long time.
0:09:22 So then you go to Google, right?
0:09:24 You go to Google a couple years after that, 2009.
0:09:29 So you’re at Google from 2009 to 2016, right?
0:09:31 What do you and the team figure out?
0:09:33 And then when do you leave?
0:09:45 So we get there and we originally want to show that we could go from what we’d shown at the DARPA Challenge to something that actually worked on public roads.
0:09:53 And so we had this challenge of driving 100,000 miles on public roads and 1,000 miles of really interesting, challenging roads in the Bay Area.
0:09:59 Things like driving down Highway 1 from San Francisco to L.A. and across all the Bay Bridges and things like that.
0:10:05 With the idea that if we could prove we could do these things, then, yeah, this technology probably has legs.
0:10:09 And it was kind of a dread pirate Robert setup, right?
0:10:17 In that, you know, we were told that you’ve got, you know, two years to do this and, you know, then we’ll probably fire you the day after.
0:10:19 Right.
0:10:22 And you kind of, this was kind of with us for the time.
0:10:26 And so we worked with urgency and it turns out we did in 18 months.
0:10:30 And through that, we had some really interesting technological evolution.
0:10:39 You know, we started to see some of the, you know, early legs of deep learning starting to show up in that point during that time.
0:10:42 So this is like 2010, 2011.
0:10:43 Yeah, exactly.
0:10:44 Those times.
0:10:44 Yeah.
0:10:45 Yeah.
0:10:54 And then, but I think almost more importantly, really started, we really started to understand what this would mean to people.
0:10:54 Right.
0:11:04 That we, you know, as somebody who had worked on this because the technology was cool initially and enjoyed the challenge of it and seen the benefit to the military,
0:11:13 as we thought about, you know, as we started to get into the space and started to talk to people in the public sector about the number of lives lost on America’s roads.
0:11:15 You know, 40 plus thousand people every year.
0:11:27 The challenge that people, whether because they have physical limitations that prevent them from driving or because they’ve aged out and no longer feel comfortable driving,
0:11:33 the implications that has for their quality of life and how we can make that better for folks.
0:11:41 You know, the accessibility that we could bring to transportation that’s kind of lost with the public transit system we have in the U.S.
0:11:46 All of this, it’s like, oh, wow, there is not just, it’s not just a cool, interesting technology.
0:11:48 It’s not that I get to work with good people.
0:11:51 It’s not just that, you know, this could be valuable.
0:11:53 It’s that like this is socially really important to do as well.
0:12:04 And then, you know, over the course of the program, we got to the point where we launched for the first time a vehicle operating on public roads with nobody in it.
0:12:13 Well, actually, with somebody in it, with Steve Mann, who is a blind gentleman who’d worked with us on some of the early kind of concepts and understanding of this.
0:12:27 And he took a road in Austin, Texas, by himself and seeing the emotional impact that had on him of, you know, once again, having the freedom to get from A to B without having to ask somebody else.
0:12:30 It was just like, wow, this this actually matters.
0:12:32 So that was very cool.
0:12:38 So you mentioned the machine learning piece starting to come in.
0:12:43 It’s, I think, I was looking back at, I think it’s 2012 that AlexNet comes along, right?
0:12:46 The first kind of big computer vision breakthrough.
0:12:48 And so it is interesting.
0:12:56 I mean, when I think as a sort of lay person about autonomous cars now, I think of computer vision as like central.
0:12:59 Like, how could you even do it without that, right?
0:13:02 Without computers being able to, quote unquote, understand what they see.
0:13:06 But this is actually emerging just as you’re building this car, right?
0:13:06 This system.
0:13:09 So how, like, tell me about that.
0:13:14 Tell me sort of building in parallel with this technological enabling wave.
0:13:17 Yeah, there was a bunch of these things.
0:13:19 So Moore’s law was continuing to march along.
0:13:22 And the amount of computation we had on the vehicle was improving.
0:13:31 The cell phone was, believe it or not, was a big boon to us because it drove the performance of cameras.
0:13:34 So if you think about, like, you know, going from.
0:13:40 All those selfies, everybody just wanting to make better, cheaper cameras and the processing for images, yeah.
0:13:40 100.
0:13:47 But even just the physical imager itself, right, went from, you know, a one megapixel 320 by 240 camera,
0:13:56 which is what, if you’d bought a top-of-the-line, you know, Kodak digital camera back in the day, it was, you know, now my iPhone’s got 48 megapixel.
0:13:57 Right.
0:13:57 Right.
0:14:04 And so, and the quality and color performance and everything, that’s improved dramatically.
0:14:05 Yeah.
0:14:11 And then LIDAR is another thing that has really evolved over the course of the last 20 years.
0:14:20 Going from things where we could get a single point along the line to now full 3D fields of view.
0:14:26 And allowing us to combine the camera data with the LIDAR data, with the computation.
0:14:31 And then the final big thing that’s moved forward is, in the sensing side, is radar.
0:14:38 And the automotive radar, the quality that you can get out of that, the price point that that comes in at now.
0:14:46 You know, when you combine that set of advances, there’s orders of magnitude improvement in both the quality of data we can consume
0:14:49 and the amount of data that we can perform computation over.
0:14:53 And that really has unlocked our ability to understand the world around these vehicles.
0:15:00 So, you leave in 2016.
0:15:05 Like, are people getting rides in wherever it was, Chandler, Arizona, yet at that time?
0:15:07 Like, is that, is it out in the world yet when you leave?
0:15:08 Okay.
0:15:11 No, we’ve been doing demos and we were doing development.
0:15:14 I think we had vehicles in Chandler at that time and were starting to operate.
0:15:24 But they were still with a person behind the steering wheel and we were still kind of, we were building towards what ultimately became the initial channel launch.
0:15:26 Why’d you leave?
0:15:28 It was time.
0:15:29 You know, I had been there.
0:15:32 I really valued and loved the experience.
0:15:40 But at some point, I kind of lost confidence that we were going to make the decisions that we needed to make to be successful.
0:15:48 And as the person leading the organization that, you know, Google had been incredibly generous to me, given me this incredible opportunity.
0:15:51 And if I just didn’t believe it, it wasn’t my place to lead the team.
0:15:52 Sure.
0:15:58 And so, you know, I’m a big believer that in business, you, you know, kind of, you have three options.
0:16:00 You, if you see something you don’t like, you try and fix it.
0:16:02 If you can’t fix it, you get in line.
0:16:05 And if you can’t get in line, you get out of the way.
0:16:14 And, you know, I did what I could to try and, you know, kind of move things the way that I thought they needed to go and ultimately said, you know, this company’s been incredibly generous to me.
0:16:18 Let me get out of the way and let it get on its own path.
0:16:31 When you say you lost confidence that they were going to make the decisions they needed to make, I mean, obviously we should evaluate decisions based on the information available at the time.
0:16:38 But, you know, it is the case that, you know, you can get in a Waymo in San Francisco in one minute and have a beautiful ride right now.
0:16:41 Like, were you wrong?
0:16:44 I, apparently, yes.
0:16:45 Right?
0:16:49 Like, you know, like, I think there’s no way to judge it other than they’ve ultimately been successful.
0:16:54 You know, maybe would have taken a different, shorter path.
0:17:01 But, you know, I think, I think it’s, it’s, you know, I don’t know if you’re a parent, but one of the things you hope as a parent is that you,
0:17:08 you, you, you embody your kids with things and then they go off into the world and succeed.
0:17:17 And the same is true when you lead teams or build something is that, you know, you do your part and you hope it outlives you and out, you know, outperforms what you might have hoped for it.
0:17:20 And I think it’s been awesome to see Waymo succeed.
0:17:25 You know, you start Aurora in 2017, right?
0:17:30 And as, as I understand it, you didn’t start focused on trucks.
0:17:32 Like, tell me about what you’re thinking when you start the company.
0:17:33 Yeah.
0:17:34 How you get to trucks.
0:17:38 So, you know, I didn’t leave Google to start the company.
0:17:39 I left Google because it was time.
0:17:46 And I then spent some time trying to figure out what to do and kind of came to the conclusion that, you know, it was worth taking another shot at this and trying to build something.
0:17:57 And so I found two great co-founders in Sterling and Drew and we wanted to build a driver and we wanted to apply that driver and passenger cars and trucks and wherever it could go.
0:18:08 And we thought at the time we didn’t see how it was going to be possible to do trucking because based on the experience I had and others had, we looked at how far you had to see down the road to do that safely.
0:18:13 And we came to the conclusion, you just couldn’t do that with the technology that existed at the time.
0:18:16 And you have to see farther just because it takes longer for a big truck to stop.
0:18:17 It’s just physics.
0:18:17 Yeah.
0:18:20 There’s just way more kinetic energy, right?
0:18:25 They’re heavier and they’re moving at 70 miles an hour instead of in a city, you’re moving at 15 miles an hour.
0:18:32 So the combination of the speed and the way it means that it just, it just takes longer to stop farther distance down the road.
0:18:38 And so we, and then you add to that, it’s much easier to drive around a light vehicle than a big truck.
0:18:39 So, right.
0:18:41 You don’t need a special license.
0:18:42 They’re much smaller.
0:18:45 You don’t, you know, need special maintenance programs and whatnot.
0:18:48 And so we’re like, okay, let’s focus on light vehicles.
0:18:50 We see there’s a real opportunity there.
0:18:58 If we can crack the, can you see far enough problem, then trucking would be a great application to go to.
0:18:59 Yeah.
0:18:59 Yeah.
0:19:15 And so part of what I spent my time doing during the first couple of years of the company was looking, you know, basically turning over every rock we could with, with Bart, one of our early team members to find a technology that would allow us to see far enough, far enough that we could actually do trucking.
0:19:29 And ultimately we found that in this little company in Montana called Blackmore that had built this really special kind of laser range finder that because of the way it did measurements in what’s called frequency modulated continuous wave.
0:19:37 It, it, it could see basically twice as far as the rest of the LiDAR stuff could see.
0:19:44 And so we’re like, huh, we now, we, we have some really interesting driving capability.
0:19:48 We’ve now got this kind of pseudo magical LiDAR sensor that can see far enough.
0:19:52 Trucking feels like a really great application to go take on.
0:19:55 Let’s talk about a few of the things you had to figure out.
0:19:56 So you decide you’re going to do trucking.
0:19:56 Yeah.
0:20:01 And presumably by trucking, like, I mean, I know where you are now.
0:20:08 Like, so presumably by trucking, you don’t mean like the bread truck that goes to the little market by my house.
0:20:11 You mean the great big truck that goes on the freeway.
0:20:11 Yeah.
0:20:19 That’s where we thought there was the biggest opportunity was working on what we call class eight tractor trailers, big, you know, semi trucks.
0:20:20 Yeah.
0:20:22 They drive a lot of miles.
0:20:25 We don’t have enough people who want to do that job.
0:20:30 And yet it’s absolutely essential to American and worldwide way of life.
0:20:34 And there’s a real need, right?
0:20:41 As we’ve dug into it, we realized that there’s about 5,000 people killed every year in heavy truck accidents, 500,000 people injured.
0:20:56 And then we can move goods more efficiently, which, you know, is important, particularly in the, you know, this age of e-commerce where people expect things next day or, you know, be able to move those goods efficiently with customers is really valuable.
0:20:59 Okay.
0:21:09 This April, if I’ve got my dates right, you actually have a truck drive for real stuff on the freeway without someone behind the wheel, right?
0:21:11 That’s exactly right.
0:21:12 It was awesome, right?
0:21:17 We, as a company, have been building towards that for almost eight and a half years, eight and a quarter years.
0:21:22 And, you know, we take doing these things safely very seriously.
0:21:32 And really, a lot of the last couple of years has been making sure we could have confidence that when we let the thing go, that it was actually going to be safe.
0:21:34 And then we got to a point where we’re like, yeah, this is safe.
0:21:40 We can go send this out in the daylight in dry weather and have it drive back and forth between Dallas and Houston.
0:21:44 And I had the privilege of ride along in the back seat.
0:21:48 And it was awesome, right?
0:21:49 In that it worked.
0:21:51 It was incredibly boring, right?
0:21:52 It turns out it’s like a three and a half hour trip.
0:21:54 You want it to be so boring.
0:21:54 Yeah.
0:21:55 You want it to be very boring.
0:21:58 But it just kind of worked.
0:22:01 And I went down and back that day in the truck.
0:22:04 Were you hauling stuff at that point?
0:22:04 Was it business?
0:22:05 We were.
0:22:06 We were hauling pastries.
0:22:07 Yeah.
0:22:08 Oh, pastries.
0:22:08 Okay.
0:22:08 Yeah.
0:22:12 Pastries both ways?
0:22:13 That would be amazing.
0:22:15 There’s some pastries in Houston that they wanted.
0:22:18 No, I think there is a pastry imbalance.
0:22:22 I think we, for the first trip, I think we may have actually been empty.
0:22:28 But on the way back, I’m pretty sure from, for whatever reasons, the pastries diffused from Houston to Dallas.
0:22:31 So then, what happens in May?
0:22:34 In May, you put a person back behind the wheel, right?
0:22:35 Tell me about that.
0:22:35 Yeah.
0:22:39 So, as a company, we’ve really focused on do what we do best.
0:22:43 And what we do best is building a safe, capable driving system, the Aurora driver.
0:22:49 And we work with other companies like Peterbilt at Paccar and Volvo Trucks.
0:23:00 And our partners at Peterbilt called up and said, hey, we’d like you to have an observer in the seat because there’s some prototype parts in our truck.
0:23:03 And it matters to us that you put an observer in.
0:23:05 And so, we said, okay.
0:23:07 You know, we had a conversation.
0:23:09 We respect them.
0:23:10 And we ultimately put the observer in the seat.
0:23:16 And we have a person sat on board who is sat in the driver’s seat, but they’re an observer.
0:23:19 And they’re really just there because our partner asked them to put them there.
0:23:23 I mean, presumably, they’re a license to drive an 18-wheel drive.
0:23:25 It’s not just some random person watching what’s going on.
0:23:26 That’s right.
0:23:26 It’s a truck driver.
0:23:34 You know, we don’t want to put anyone in place where, you know, the Highway Patrol has to debate whether, you know, it’s just like, okay, let’s just put a truck driver there.
0:23:34 They sit there.
0:23:45 If you go to youtube.com slash Aurora driver, you can see a live video between 8 and 5 o’clock every day of our trucks driving down the road.
0:23:48 And you can see that, you know, this person sat there.
0:23:50 And sometimes they’re twiddling their sums.
0:23:51 Sometimes they’re eating Fritos.
0:23:55 You know, just observing.
0:24:03 I mean, at least from a narrative standpoint, it’s a bummer to have to put the person back behind the wheel, surely.
0:24:04 Absolutely.
0:24:06 From a narrative standpoint, it’s a bummer, right?
0:24:10 And it creates a nuance that is, you know, certainly in today’s…
0:24:12 You don’t want a person behind the wheel.
0:24:12 It’s the whole point.
0:24:13 It’s the whole point.
0:24:15 It’s you don’t want a person behind the wheel, right?
0:24:16 Totally agree.
0:24:21 But in terms of the development and delivery of what we’re building, it just doesn’t matter, right?
0:24:23 It’s a complete nothing.
0:24:25 Well, I mean, at some margin, it matters.
0:24:26 At some point, it matters, right?
0:24:28 The whole premise is you can do it without a person there.
0:24:35 And so, like, at some point, like, relatively soon, I would imagine you need to do it without a person there.
0:24:36 That’s right.
0:24:39 And look forward to doing that soon.
0:24:43 We’ll be back in just a minute.
0:25:13 Plus, only iHeart can extend your message to audiences across broadcast radio.
0:25:15 Think podcasting can help your business?
0:25:16 Think iHeart.
0:25:18 Streaming, radio, and podcasting.
0:25:21 Let us show you at iHeartAdvertising.com.
0:25:23 That’s iHeartAdvertising.com.
0:25:25 You should tell the people who we are and what our new show is.
0:25:26 I’m Robert Smith.
0:25:27 And this is Jacob Goldstein.
0:25:29 And we used to host a show called Planet Money.
0:25:36 And now we’re back making this new podcast about the best ideas and people and businesses in history.
0:25:42 and some of the worst people, horrible ideas, and destructive companies in the history of business.
0:25:46 We struggled to come up with a name, decided to call it Business History.
0:25:46 You know why?
0:25:47 Why?
0:25:49 Because it’s a show about the history of business.
0:25:50 Available everywhere.
0:25:52 You get it.
0:25:53 Your podcasts.
0:25:58 Yeah, so where are you now?
0:26:03 Like, give me, we’re basically to the present now after our 20-year journey.
0:26:08 Like, what’s, like, are you, are people paying you to haul stuff?
0:26:09 Yeah, absolutely.
0:26:12 So, like, today is an incredibly exciting moment.
0:26:15 So, we have a technology that can drive a truck.
0:26:23 It has the skills necessary to drive on the freeway and drive to sites off the freeway in these industrial park areas.
0:26:24 And it does that safely.
0:26:33 And then internally, we’ve got the capability to say, okay, what are the new features we need to make this more useful for our customers?
0:26:35 And so, we launched in April.
0:26:45 About three months later, we were able to show, you know, be able to launch the next version that now doesn’t just operate in the daytime, but operates at night as well.
0:26:58 And over the course of the rest of this year, it’s really about taking and building the, you know, enhancing the skills that it has to add the few new skills it needs to be able to drive between Fort Worth and Phoenix and El Paso.
0:27:00 And so, at that point…
0:27:03 Just to be clear, the route you have now is Houston-Dallas, is that right?
0:27:03 That’s right.
0:27:03 I’m sorry.
0:27:05 We drive between Dallas and Houston.
0:27:08 And by the end of the year, we expect to be driving between Fort Worth and Phoenix.
0:27:09 Okay.
0:27:11 And what’s exciting about…
0:27:14 And Fort Worth and El Paso and El Paso and Phoenix.
0:27:20 And what’s exciting about that is Fort Worth to Phoenix is 1,000 miles.
0:27:25 And a person is not able to legally drive that in a day.
0:27:32 And so, we’ll be able to start doing things that are superhuman in more and more dimensions.
0:27:36 Presumably, the value preposition is really long drives, right?
0:27:41 Like, it makes absolutely no sense for whatever, 100 miles or something.
0:27:44 And the longer it gets, the more the economics makes sense.
0:27:44 Is that right?
0:27:45 I mean, that seems like the kiss.
0:27:50 I think it makes sense across all different kind of scales, but I think where the biggest
0:27:52 impact will ultimately be is on these long-call trips.
0:27:59 And, like, I get the freeway part in Broadway.
0:28:02 How does the not-on-the-freeway part work?
0:28:05 How constrained are you as to where you can go when you’re not on the freeway?
0:28:06 Yeah.
0:28:10 So, the capability we’re building is to be able to drive everywhere.
0:28:11 Sure.
0:28:13 But, like, now?
0:28:19 So, today, we drive from a place that’s off the freeway onto the freeway.
0:28:24 And then when we get at the Dallas end of the route, and then at the Houston end, we drive
0:28:28 about five miles from where we get off the freeway to our terminal site.
0:28:32 And along the way, we drive past customer locations.
0:28:39 So, we’re making the choice today to go to our terminals, but it’s relatively straightforward
0:28:42 to stop and go to a different terminal instead or a different site.
0:28:51 Like, how hard is that off-the-freeway part, the sort of marginal, you know, mile when you’re
0:28:52 not on the freeway?
0:28:55 Not, right, would be the short answer, right?
0:29:02 It’s, you know, we’ve put a lot of, for a long time, the primary focus of what we were
0:29:07 building was the freeway part, because, as you pointed out, that’s where the most kinetic
0:29:08 energy is.
0:29:11 That’s where, you know, that’s where the bad things could happen.
0:29:16 I mean, it’s also simpler in certain ways, right?
0:29:20 Like, it seems like turning a big truck around or just getting a truck around.
0:29:23 Like, I live in New York City, and I see 18-wheelers in New York City.
0:29:28 And, I don’t know, maybe that’s not that hard to engineer for autonomy.
0:29:29 You tell me.
0:29:30 It seems hard.
0:29:30 It looks hard.
0:29:34 Yeah, I think New York City is hard, right?
0:29:36 And I think there’ll be a time where we get to that.
0:29:41 I’m really focused, and we’re really focused on in the near term, is how do we get to the
0:29:43 place where most freight moves, right?
0:29:49 And a lot of that will go to these industrial parks and, you know, regions of a city.
0:29:55 And the reason why is it’s hard to drive a truck in New York City, right?
0:29:56 And it’s slow.
0:30:00 And so, if you’re trying to build a distribution center for these Class 8 tractors and trailers,
0:30:05 you put them in places where it’s convenient because you’re trying to run a business, not
0:30:07 build a technology showcase.
0:30:12 So, what can you not do now, autonomously?
0:30:15 So, today we can’t drive in the rain.
0:30:18 Well, in fact, that’s not actually true.
0:30:25 So, today we drive in the rain really well, but we haven’t validated that fully for driverless
0:30:25 operations.
0:30:27 And this is really an important idea, right?
0:30:31 Because if you came down to Texas and got a ride in one of our trucks and it was raining
0:30:33 out, it would work.
0:30:37 And you would go, huh, why have you guys not launched this?
0:30:42 And we would say, yeah, it basically works, but that’s not good enough.
0:30:44 It’s not good enough that it feels like it works.
0:30:46 What we want to have done is all of the diligence.
0:30:49 It basically makes me nervous with an 18-wheel truck.
0:30:49 Exactly.
0:30:51 And it should, right?
0:30:56 And so, for us, we put a lot of effort into making sure that it doesn’t just seem like it
0:30:59 works, but that we have conviction that it will work.
0:30:59 Yeah.
0:31:08 And, you know, as an example, two of the last things that we got checked off when we launched
0:31:16 were it’s, one, really high-speed motorbikes running red lights in the city.
0:31:21 So, we had done a bunch of testing, I think up to, let me say, I’m going to say some numbers
0:31:21 here.
0:31:26 These are probably not quite right, but I’ll use some numbers, you know, at 90 miles an
0:31:31 hour, because we figure, you know, 90 miles an hour on a surface road, nobody on a motorbike.
0:31:33 Meaning the motorcycles go in 90 miles an hour.
0:31:37 Motorcycles go in 90 miles an hour, and they’re going to run a red light in front of us, and we
0:31:39 want the truck to not hit that motorbike.
0:31:43 And then we’re on the freeway, and we see a motorbike doing 150 miles an hour.
0:31:50 And we’re like, okay, that is, let’s go make sure that that works, right?
0:31:53 Because, you know, at some point, we just want to have confidence.
0:31:59 And so, we went through and we found out that when motorbikes going that extremely fast, first,
0:32:03 we had to, we found that our simulation wasn’t quite up to snuff to deal with that.
0:32:04 So, we had to go fix that.
0:32:11 And then we found that our perception system wasn’t able to quite track it as well as we’d
0:32:11 want.
0:32:12 So, we had some things to fix there.
0:32:17 And so, ultimately, we got to the point where if you’re a motorbike, please don’t go test
0:32:17 this.
0:32:21 Run in a red light at 150 miles an hour, we’re going to see you.
0:32:25 And assuming, you know, we can actually see you because there’s not a building in the way,
0:32:29 we’re going to stop and, you know, not have an event with you.
0:32:35 So, is the rain analog of that, like, more rain than I can imagine and flooding and it’s
0:32:36 dark or something?
0:32:40 I mean, and maybe frozen, frozen also?
0:32:46 And so, this is, the answer is we have some good ideas of what these challenges are.
0:32:50 And so, we’re in the process of putting place the last of the tests that we need to say,
0:32:56 yeah, across the things that might be a problem, we actually handle those in a way that’s safe.
0:32:58 Once you got rain, are you good?
0:33:02 I mean, I guess you have the whole southern U.S. without snow and ice.
0:33:05 Well, it probably freezes in Texas, right?
0:33:06 Does it freeze in Texas?
0:33:06 It does.
0:33:07 They get snow in Texas.
0:33:14 But the good news is, like, the reason why a lot of freight moves around the sunbelt is
0:33:18 because trucks don’t like driving in snow, right?
0:33:21 It’s just, you know, much like people in general don’t like driving in snow.
0:33:22 But there is snow.
0:33:25 But if you’ve ever been in Texas when there’s a snowstorm, it basically shuts down.
0:33:26 Yeah.
0:33:28 So, you don’t have to solve snow.
0:33:30 You don’t have to solve snow for now.
0:33:30 For now.
0:33:32 But we will solve snow, right?
0:33:32 Sure.
0:33:35 Because all of the stuff that works for rain mostly works for snow, too.
0:33:39 I mean, all of these problems we can stipulate will be solved by somebody, right?
0:33:39 Yeah.
0:33:42 Plausibly by you, if not you, by somebody else.
0:33:45 But, like, I feel like there’s some sense of urgency.
0:33:52 Like I’ll say, so interestingly, just purely coincidentally, I talked to Boris Sofman.
0:33:53 Is it Sofman?
0:33:53 Yeah.
0:33:54 I don’t have his name in front of me.
0:33:57 And so he said, and we were not talking about you.
0:33:59 This was not a dig on you.
0:34:01 It was more talking about why he’s doing what he’s doing.
0:34:05 He said, I don’t think open road autonomy is a startup game.
0:34:12 And he basically, you probably know he thinks, I mean, he basically thinks it’s too expensive in short.
0:34:21 Too expensive and too hard in that way for a company that is capital constrained, for a company that, you know, doesn’t have a monopoly on search, let’s say.
0:34:28 And so I do feel like in talking to you, like, you plausibly may solve them, but there must be some clock for you, right?
0:34:32 You must have to get to a point where you’re making money relatively soon.
0:34:33 Is that right?
0:34:34 Yeah.
0:34:35 Well, we’ve been at the game for a while.
0:34:38 You know, we went into it eyes open, right?
0:34:46 And looked at the, you know, having spent the time with Waymo, having the history I have, I was like, this is not a $100 million problem or a $10 million problem.
0:34:47 This is a multi-billion dollar problem.
0:34:54 And so as we’ve built Aurora, it’s been, okay, we need to set ourselves up with the staff.
0:34:56 We need to set ourselves up with the capital partners.
0:35:02 We need to set ourselves up with the technology partners that allow us to take that run.
0:35:05 And I think we’ve been very careful about how we’ve done that.
0:35:07 And we’ve put ourselves in a position to succeed.
0:35:09 And I agree with Boris.
0:35:14 This is, you know, I hear people throwing out, oh, we’re going to, you know, spend $100 million to do this.
0:35:16 I’m like, you know, you haven’t even met the ante.
0:35:17 Yeah.
0:35:18 Right?
0:35:23 And so for us, we look at, say, driving in the rain.
0:35:25 We expect to be solving that by the end of this year.
0:35:26 Yeah.
0:35:27 Right?
0:35:31 And at that point, as you point out, we’ve basically unlocked the Southern Freight Belt.
0:35:35 The amount of truck travel that’s there is gigantic.
0:35:46 And so, you know, from now where we have a small number of trucks on the road, by the end of next year, the end of 26, we expect to have a few hundred trucks on the road.
0:35:51 And then the year after that, we expect to have a thousand plus trucks on the road.
0:35:52 And then we’ll build from there.
0:36:00 And so it’s, you know, the conviction we’re starting to build internally, like, yeah, this is just turning over the kind of the way we want it.
0:36:01 And we expect it is happening now.
0:36:04 And so it’s not a hypothetical that someday we’ll solve it.
0:36:08 It’s like, no, we’re, you know, four or five months kind of time frame.
0:36:10 So, well, three, four months time frame.
0:36:12 What’s the business model?
0:36:13 Yeah.
0:36:18 So our business model is to work with the ecosystem that’s there today.
0:36:23 So today, if you’re a trucking company, you buy a truck and then you pay somebody to drive that truck for you.
0:36:26 And so that’s what our company is going to do.
0:36:34 So you’ll, if you’re a company that wants an autonomous truck, you’re going to go to Packard and Peterbilt or you’re going to go to Volvo and say, I want to buy a truck.
0:36:37 And they buy the truck stuff.
0:36:43 And then it’ll roll off the line from our partner and it’ll have the Aurora driver installed on it.
0:36:47 And you’ll pay a subscription to Aurora to drive that truck for you.
0:36:47 I see.
0:36:48 Okay.
0:36:55 So you guys get paid by the mile or by the haul or something like that.
0:36:57 Yeah, that’s exactly right.
0:37:02 You know, it’s at the risk of, as a servicism, you know, it’s driver as a service.
0:37:03 Yeah.
0:37:05 That’s the way we’re thinking about the business.
0:37:07 And the trucking company is buying the truck.
0:37:08 So that’s good for you.
0:37:12 You don’t have to, when you say you’ll have a thousand trucks out there, you don’t mean you’re going to own a thousand trucks.
0:37:16 You mean you’ll have essentially a thousand autonomous drivers in trucks that other people own.
0:37:16 That’s right.
0:37:19 And this is because that’s what our customers want.
0:37:20 Yeah.
0:37:20 Right.
0:37:21 That they’re.
0:37:23 Also, it seems easier as a business.
0:37:24 Oh, it is.
0:37:27 It’s nice to not have to get into the trucking business.
0:37:28 I agreed.
0:37:31 Again, back to the philosophy of we think we’re really good at building the driver.
0:37:32 Yeah.
0:37:38 And I look at our partners, whether it’s Werner or Hirschbach or Federal Express, they know what they’re doing.
0:37:42 Why don’t we help them make their business a bit better and work together?
0:37:51 Can we talk about autonomy a little bit more broadly just since you’ve been at it so long and I’m curious what you think?
0:38:03 So, like, what do you think are the important constraints on autonomous vehicles right now, sort of broadly, technologically, you know, in terms of policy?
0:38:06 I think it’s primarily technological right now.
0:38:07 Okay.
0:38:07 Right.
0:38:16 And I’ve said that, you know, people for the better part of a decade have been, you know, when it’s convenient, hiding behind, you know, regulation or policy.
0:38:21 And, you know, the U.S. policy of regulatory environment is permissive.
0:38:26 It’s one of the things that’s allowed innovation to flourish in this country, certainly in the automotive space.
0:38:30 So, what are the important technological constraints right now?
0:38:35 Like, I mean, obviously, Waymo is thriving where it’s thriving.
0:38:40 But, like, also, there are no autonomous cars where I live and people aren’t buying them.
0:38:43 And so, like, what are the important bottlenecks right now?
0:38:47 Execution bandwidth, right?
0:38:55 So, at least where I sit at a roar today, I don’t look out and see, oh, my gosh, I don’t know how we’re going to solve that.
0:38:57 It’s, hey, we have this many people.
0:39:00 We have this much leadership bandwidth.
0:39:02 We just need to go execute, right?
0:39:09 Like, thinking industry-wide, and not to be, like, petty or something, but, like, why aren’t autonomous cars everywhere right now?
0:39:09 Yeah.
0:39:11 Because it’s really hard, right?
0:39:15 And I think the right metaphor for this is commercial aviation.
0:39:19 Like, the physics are really in grasp, and, like, you can bolt things together.
0:39:28 And yet, you know, we basically have two commercial aviation manufacturers globally, right?
0:39:28 Yeah.
0:39:29 We have Boeing and Airbus.
0:39:33 Because it’s hard to build big jet aircraft, is what you’re saying.
0:39:34 It’s hard to build them.
0:39:36 It’s hard to have conviction they’re going to be safe.
0:39:38 It’s hard to produce them, right?
0:39:45 And when I look at automated driving, I think it’s in a very similar space in that a lot of things have to work well.
0:39:49 You have to have the discipline to be able to work across all of them, make sure they all fit together.
0:39:52 And then you have to have the processes.
0:39:56 And process in Silicon Valley is often kind of a four-letter word.
0:39:58 Like, you know, you’ve got to move fast and break things.
0:40:03 But when you’re building something safety critical, you actually have to get that stuff right.
0:40:06 And the art is getting it right while also being able to do it quickly.
0:40:19 So when you think about the spread of autonomy from here, again, not just within your company, but sort of more broadly, like, how do you think it’ll play out?
0:40:30 I think it’s going to usher in an incredible new age, all right, that we should be able to dramatically reduce traffic fatalities.
0:40:44 The fact that, you know, it had been a decade without a fatality on civil aviation, and yet we had 40,000 people killed on the road every year in the U.S., like, we can bring a technology to bear to help solve this, right?
0:40:46 And I think that’s profound.
0:40:52 I think we can have a huge sustainability impact all while actually kind of powering up the U.S. economy.
0:41:07 And so for us, you know, we’ve got this mission right now that’s focused on trucking, but what we’re really building is this capability to release safety critical software and systems and this ability to understand the world.
0:41:11 And so you combine those two things, the places we can go with that are profound, right?
0:41:21 Whether it is, you know, last mile delivery or ride hailing applications or mining or farming or aviation, like, it’s just going to be a lot of fun over the next decade.
0:41:23 So, yeah, I’m psyched for it.
0:41:28 Next decade sounds fast, given the pace so far.
0:41:30 I was surprised when you said next decade at the end there.
0:41:37 Yeah, I think that, like anything, there’s a point where you have built a foundational base.
0:41:38 Yeah.
0:41:43 And then suddenly you’re like, oh, now I have this power and I have the superpower to go do these things.
0:41:47 And it’s basically the package of hardware plus software at a reductive level.
0:41:51 And you can sort of put it on other things and it’ll more or less work.
0:41:54 More importantly, it’s the process and the data.
0:41:56 And again, it does not sound sexy.
0:41:59 The data sounds sexy.
0:42:02 Like the more you talk to machine learning people, the more sexy data sounds, right?
0:42:03 Yeah.
0:42:11 And, you know, and we joke internally, you know, if you, if we have three kind of big artifacts being our software, our data, and our process.
0:42:17 Yeah, if you held a gun to my head and said, delete one of them, I’d say delete the software.
0:42:18 Interesting.
0:42:19 Right?
0:42:19 That’s really interesting.
0:42:20 Please do not delete our software.
0:42:22 Yeah.
0:42:22 Yeah.
0:42:24 No, that’s really interesting.
0:42:24 Yeah.
0:42:29 We’ll be back in a minute with the lightning round.
0:42:40 Run a business and not thinking about podcasting?
0:42:41 Think again.
0:42:46 More Americans listen to podcasts than ad-supported streaming music from Spotify and Pandora.
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0:42:59 Think podcasting can help your business?
0:43:00 Think iHeart.
0:43:03 Streaming, radio, and podcasting.
0:43:05 Let us show you at iHeartAdvertising.com.
0:43:07 That’s iHeartAdvertising.com.
0:43:10 You should tell the people who we are and what our new show is.
0:43:11 I’m Robert Smith.
0:43:12 This is Jacob Goldstein.
0:43:14 And we used to host a show called Planet Money.
0:43:21 And now we’re back making this new podcast about the best ideas and people and businesses in history.
0:43:27 And some of the worst people, horrible ideas, and destructive companies in the history of business.
0:43:30 We struggled to come up with a name, decided to call it Business History.
0:43:31 You know why?
0:43:32 Why?
0:43:33 Because it’s a show about the history of business.
0:43:35 Available everywhere.
0:43:37 You get it in your podcasts.
0:43:43 We’re going to finish with a lightning round.
0:43:45 I appreciate your time, and we’re almost done.
0:43:45 Cool.
0:43:47 Thanks for the conversation.
0:43:51 Is it right that your father was a prison warden?
0:43:52 He was, in fact, yeah.
0:43:56 Did you learn any management and or parenting tips from him?
0:43:58 Lock them up.
0:44:01 No, absolutely not.
0:44:12 You know, one of the things that stuck with me is, you know, it’s a difficult job being a prison warden because you have the staff, then you have the inmates.
0:44:17 And, right, and they’re often at odds.
0:44:21 And one of the things he said was, you know, make sure you treat everyone with respect, right?
0:44:28 That he would, you know, these are people who had made a mistake in life, you know, and you treat them with respect.
0:44:32 And, you know, I think that’s really powerful and important.
0:44:35 What’s one thing you learned working at Google?
0:44:37 Think big.
0:44:38 That’s nice.
0:44:44 I think that was, you know, Larry and Sergey never lacked for vision.
0:44:50 And I think you can often find yourself constrained by kind of your own kind of sense of what’s a limit.
0:44:54 And, like, just thinking, like, no, what, why can’t you do that?
0:44:55 Why can’t you do that?
0:45:12 Yeah, I remember just as a consumer, just as an ordinary person in the world, when they started what became Google Street View, I was like, surely you can’t take a picture of every bit of every road in America.
0:45:15 And actually, you can, and they did.
0:45:16 Yeah, right?
0:45:19 Like, I think that sense of, like, you don’t need to be intimidated by this.
0:45:21 Like, you need to think rationally.
0:45:22 You need to figure it out.
0:45:24 But, you know, I think it’s a power.
0:45:31 One of my professors at Carnegie Mellon said, dream like an amateur, execute like a professional.
0:45:32 Right?
0:45:34 And I think that’s just a really kind of profound sentiment.
0:45:38 What’s one thing your time at Google taught you not to do?
0:45:39 Ooh.
0:45:44 What did it take me not to do?
0:45:51 Maybe kind of adjacent to that, like, so when I went to Google, I thought I was a pretty good programmer.
0:45:54 You know, I was, you know, Cardi Mellon, and I was good at what I did.
0:46:02 And I’m not a bad programmer, but, like, there are truly exceptional people out in the world, right?
0:46:10 And so I think, you know, maybe don’t overestimate yourself and kind of, again, kind of think big.
0:46:12 Don’t underestimate what’s out there.
0:46:20 Chris Ermsson is the co-founder and CEO of Aurora.
0:46:25 Please email us at problematpushkin.fm.
0:46:27 We are always looking for new guests for the show.
0:46:32 Today’s show was produced by Trina Menino and Gabriel Hunter-Chang.
0:46:37 It was edited by Alexandra Gerriton and engineered by Sarah Bruguer.
0:46:41 I’m Jacob Goldstein, and we’ll be back next week with another episode of What’s Your Problem?
0:46:54 You should tell the people who we are and what our new show is.
0:46:55 I’m Robert Smith.
0:46:56 And this is Jacob Goldstein.
0:46:59 And we used to host a show called Planet Money.
0:47:05 And now we’re back making this new podcast about the best ideas and people and businesses in history.
0:47:08 And some of the worst people.
0:47:11 Horrible ideas and destructive companies in the history of business.
0:47:13 We struggled to come up with a name.
0:47:15 Decided to call it Business History.
0:47:16 You know why?
0:47:16 Why?
0:47:18 Because it’s a show about the history of business.
0:47:20 Available everywhere.
0:47:22 You get your podcasts.
0:47:24 This is an iHeart Podcast.
0:00:32 Ideas and people and businesses in history.
0:00:35 And some of the worst people.
0:00:38 Horrible ideas and destructive companies in the history of business.
0:00:40 We struggled to come up with a name.
0:00:42 Decided to call it Business History.
0:00:43 You know why?
0:00:43 Why?
0:00:45 Because it’s a show about the history of business.
0:00:47 Available everywhere.
0:00:49 You get your podcasts.
0:00:57 Pushkin.
0:01:05 In 2003, Chris Ermsson was a grad student at Carnegie Mellon University.
0:01:10 And he was working on a research project in Chile, in the Atacama Desert.
0:01:12 Beautiful place.
0:01:13 Very desolate.
0:01:16 The closest thing we have to Mars in many ways on Earth.
0:01:17 Which is why you were there.
0:01:18 We were.
0:01:21 We were building a robot to go look for signs of life.
0:01:23 And I was developing the navigation system for it.
0:01:28 And my PhD advisor came down and said, hey, the Defense Department has this competition.
0:01:29 They want to build a robot to drive.
0:01:33 50 miles an hour across the desert between Los Angeles and Las Vegas.
0:01:34 And I thought that just sounded awesome.
0:01:37 So we bought a Humvee.
0:01:39 And we cut the top of it.
0:01:40 Put a big electronics box in it.
0:01:41 A lot of computers.
0:01:44 All of the stuff that’s in a self-driving car today.
0:01:46 The high-performance computing.
0:01:47 The lasers.
0:01:47 The radars.
0:01:48 The cameras.
0:01:51 The HD maps were part of this.
0:01:56 It’s kind of the first time when all this stuff came together into a vehicle.
0:02:00 And then we developed it for six or nine months.
0:02:02 And then we tried to compete with it at the first DARPA challenge.
0:02:06 The team I was the technical director for.
0:02:09 We actually had the highest performing thing there.
0:02:12 It was supposed to go 126 miles across the desert.
0:02:14 It ended up going about seven.
0:02:17 When it got hung up on a berm.
0:02:19 And almost literally burst into flames.
0:02:20 And you.
0:02:22 I mean, nobody won.
0:02:23 But if anybody won, you won.
0:02:23 Right?
0:02:24 That was more.
0:02:25 Yeah, but nobody won.
0:02:25 That was farther than.
0:02:26 Yeah.
0:02:27 The key thing is nobody won.
0:02:30 If you imagine a marathon where you’re supposed to go 26 miles.
0:02:32 And the best runner went two.
0:02:32 Right?
0:02:36 And then burst into flames.
0:02:37 And then burst into flames.
0:02:38 Yeah.
0:02:45 I’m Jacob Goldstein.
0:02:46 And this is What’s Your Problem?
0:02:49 The show where I talk to people who are trying to make technological progress.
0:02:52 My guest today is Chris Urmson.
0:02:55 He’s the co-founder and CEO of Aurora.
0:02:59 A company that’s trying to bring autonomous driving to commercial trucks.
0:03:02 As you just heard, Chris started working on autonomous vehicles.
0:03:04 more than 20 years ago.
0:03:10 And in fact, his career traces the, really, the entire modern arc of self-driving cars.
0:03:15 From that first DARPA challenge to a top job at Google’s self-driving car project,
0:03:20 the project that later became Waymo, to founding Aurora, the company where he works now.
0:03:25 We talked a lot about the problems Chris is trying to solve in autonomous trucking.
0:03:29 And we also talked about the future of autonomous driving more generally.
0:03:33 But before we got to that, we talked about the earlier work he did.
0:03:37 Work that really helped get the field, the broader field, to where it is today.
0:03:47 So we’ll pick up the interview back in 2004, at that moment when his team’s autonomous car had failed and almost burst into flames.
0:03:48 It was crushing.
0:03:49 Yeah.
0:03:49 Right?
0:03:53 Like, you know, on the one hand, it was called a grand challenge, right?
0:03:56 Because, you know, a lot of people didn’t think it could be solved.
0:03:57 It was impossible.
0:04:01 Because on the one hand, it’s kind of like, okay, it was really hard.
0:04:06 On the other hand, you’ve, you know, we’re sleeping on the floor in the lab in the, you know,
0:04:11 in this garage in the middle of the desert for weeks and months trying to get this thing to go.
0:04:18 And then you launch it out there and you have this epic moment where you’re watching this thing that you’ve built tear out across the desert.
0:04:19 And you can just see the top of it.
0:04:25 And these helicopters that the military is using to track them as they’re out in the desert doing this.
0:04:29 And then you hear, you know, it’s supposed to go 120 miles.
0:04:30 And they’re like, oh, it’s stuck.
0:04:34 And then you hear, like, billowing smoke and broken.
0:04:36 And the poor thing comes back looking very sad.
0:04:39 And, you know, it was crushing.
0:04:43 But at the same time, we did set records, right?
0:04:49 If you look at kind of the product of the speed and the distance it went, this was an order of magnitude better than anyone had done before.
0:04:51 And so it was a big step.
0:04:56 And I think that was partly what encouraged the Defense Department to say, hey, come back again and try it in a year.
0:04:59 And then you did.
0:05:01 And then you did it again and again.
0:05:02 And what year do we go to?
0:05:03 Is it 2007?
0:05:05 Is that the next big moment?
0:05:06 Yeah.
0:05:08 2005 was another one of these in the desert.
0:05:12 2007, they did what they called the Urban Challenge.
0:05:17 So 2005, we were able to drive around the desert, not hit things too much.
0:05:19 2007, they say, okay, that’s great.
0:05:21 But now let’s stay on the right side of the road.
0:05:26 Let’s move in kind of pseudo-urban environments and show that that can work.
0:05:31 And that was the last of the Grand Challenges because that year we actually accomplished it.
0:05:34 We drove 60 miles around this air base and interacted with traffic.
0:05:39 They hired a bunch of stunt drivers out of Hollywood to come and drive cars around these robots to make traffic for them.
0:05:42 And it was a heck of a day.
0:05:48 And then the Defense Department, or at least DARPA, said, you know, effectively problem solved.
0:05:52 We’ve got this close enough now handed off to industry or whoever to take it from here.
0:05:56 And how did your car do in 2007?
0:05:58 We won, which was nice.
0:05:59 It was a good change.
0:06:01 So, you know, we…
0:06:03 And did it catch on fire?
0:06:04 No fire this time.
0:06:06 It just kind of worked.
0:06:13 We had a little bit of nerves at the very beginning because, you know, our system was pretty reliable, robust.
0:06:14 It worked all the time.
0:06:24 We go and bring it out to the start line and we can’t get it to boot properly because it can’t see this GPS satellites that it needed.
0:06:30 And we never had this problem before where, like, you know, frantically trying to figure out what’s going on.
0:06:35 And then we look over and realize that for race day, they’ve brought a Jumbotron.
0:06:40 And they’ve set that up right where the robots are at the starting place.
0:06:46 And it turns out they don’t really check these mobile Jumbotrons for, like, how much interference they’re generating, I guess.
0:06:48 So, we had this panic moment.
0:06:50 We said, you know, can you turn off the Jumbotron?
0:06:53 And sure enough, they turn off that and suddenly everything works again.
0:06:57 So, you know, it wasn’t without its challenges.
0:07:00 So, but it works, right?
0:07:04 So, it works and it works in a, like, quasi-real environment, a pseudo-real environment.
0:07:13 So, I mean, when you, at that moment, when you were thinking about the future, the future of self-driving cars, how did it look to you?
0:07:14 What did you think?
0:07:20 Yeah, I think at that point was starting to believe there was a thing that could happen here, right?
0:07:26 And probably, you know, certainly naively thought, oh, yeah, we’ve got this, right?
0:07:30 I mean, everybody kind of thought that, right?
0:07:31 Like…
0:07:38 I think, and that’s been part of what’s made the journey really fun for me is just, there’s just so many things to learn.
0:07:55 So many new problems to overcome along the way of taking something from a, it worked on this day in a race to, hey, we can go do something transformational that will save lives and improve the economy and, you know, do all these other great things.
0:08:08 It seems like that, the distance between it worked in a race and we can do something transformational has been longer, certainly than a lot of people thought, than a lot of, like, smart, well-informed people thought.
0:08:11 Yeah, me among them, right?
0:08:24 And, you know, it’s one of these things where I think anyone who sets out and does something interesting and exciting, often I think if they understood how hard it was going to be before they started, may not have actually taken the first step.
0:08:33 And so I feel a little lucky to have not understood that because it’s caused me to kind of stick with it and really enjoy the journey along the way.
0:08:40 I mean, entrepreneurs basically always say that thing that you just said, but in the case of autonomous driving, I really believe it, right?
0:08:42 It seems like extra true.
0:08:47 Like, 2007 was basically, like, the year the iPhone came out, right?
0:08:56 Like, which is to say in technology a long time ago, not to mention that there was, like, no computer vision as we know it today, right?
0:08:57 Which has become important.
0:08:59 I mean, so much.
0:09:06 No, it is, you know, the waves of technological evolution that we’ve seen since then are profound.
0:09:09 And we’ve been able to kind of surf those as we’ve been building it.
0:09:17 And it’s been, yeah, it is, it’s been a long time.
0:09:22 So then you go to Google, right?
0:09:24 You go to Google a couple years after that, 2009.
0:09:29 So you’re at Google from 2009 to 2016, right?
0:09:31 What do you and the team figure out?
0:09:33 And then when do you leave?
0:09:45 So we get there and we originally want to show that we could go from what we’d shown at the DARPA Challenge to something that actually worked on public roads.
0:09:53 And so we had this challenge of driving 100,000 miles on public roads and 1,000 miles of really interesting, challenging roads in the Bay Area.
0:09:59 Things like driving down Highway 1 from San Francisco to L.A. and across all the Bay Bridges and things like that.
0:10:05 With the idea that if we could prove we could do these things, then, yeah, this technology probably has legs.
0:10:09 And it was kind of a dread pirate Robert setup, right?
0:10:17 In that, you know, we were told that you’ve got, you know, two years to do this and, you know, then we’ll probably fire you the day after.
0:10:19 Right.
0:10:22 And you kind of, this was kind of with us for the time.
0:10:26 And so we worked with urgency and it turns out we did in 18 months.
0:10:30 And through that, we had some really interesting technological evolution.
0:10:39 You know, we started to see some of the, you know, early legs of deep learning starting to show up in that point during that time.
0:10:42 So this is like 2010, 2011.
0:10:43 Yeah, exactly.
0:10:44 Those times.
0:10:44 Yeah.
0:10:45 Yeah.
0:10:54 And then, but I think almost more importantly, really started, we really started to understand what this would mean to people.
0:10:54 Right.
0:11:04 That we, you know, as somebody who had worked on this because the technology was cool initially and enjoyed the challenge of it and seen the benefit to the military,
0:11:13 as we thought about, you know, as we started to get into the space and started to talk to people in the public sector about the number of lives lost on America’s roads.
0:11:15 You know, 40 plus thousand people every year.
0:11:27 The challenge that people, whether because they have physical limitations that prevent them from driving or because they’ve aged out and no longer feel comfortable driving,
0:11:33 the implications that has for their quality of life and how we can make that better for folks.
0:11:41 You know, the accessibility that we could bring to transportation that’s kind of lost with the public transit system we have in the U.S.
0:11:46 All of this, it’s like, oh, wow, there is not just, it’s not just a cool, interesting technology.
0:11:48 It’s not that I get to work with good people.
0:11:51 It’s not just that, you know, this could be valuable.
0:11:53 It’s that like this is socially really important to do as well.
0:12:04 And then, you know, over the course of the program, we got to the point where we launched for the first time a vehicle operating on public roads with nobody in it.
0:12:13 Well, actually, with somebody in it, with Steve Mann, who is a blind gentleman who’d worked with us on some of the early kind of concepts and understanding of this.
0:12:27 And he took a road in Austin, Texas, by himself and seeing the emotional impact that had on him of, you know, once again, having the freedom to get from A to B without having to ask somebody else.
0:12:30 It was just like, wow, this this actually matters.
0:12:32 So that was very cool.
0:12:38 So you mentioned the machine learning piece starting to come in.
0:12:43 It’s, I think, I was looking back at, I think it’s 2012 that AlexNet comes along, right?
0:12:46 The first kind of big computer vision breakthrough.
0:12:48 And so it is interesting.
0:12:56 I mean, when I think as a sort of lay person about autonomous cars now, I think of computer vision as like central.
0:12:59 Like, how could you even do it without that, right?
0:13:02 Without computers being able to, quote unquote, understand what they see.
0:13:06 But this is actually emerging just as you’re building this car, right?
0:13:06 This system.
0:13:09 So how, like, tell me about that.
0:13:14 Tell me sort of building in parallel with this technological enabling wave.
0:13:17 Yeah, there was a bunch of these things.
0:13:19 So Moore’s law was continuing to march along.
0:13:22 And the amount of computation we had on the vehicle was improving.
0:13:31 The cell phone was, believe it or not, was a big boon to us because it drove the performance of cameras.
0:13:34 So if you think about, like, you know, going from.
0:13:40 All those selfies, everybody just wanting to make better, cheaper cameras and the processing for images, yeah.
0:13:40 100.
0:13:47 But even just the physical imager itself, right, went from, you know, a one megapixel 320 by 240 camera,
0:13:56 which is what, if you’d bought a top-of-the-line, you know, Kodak digital camera back in the day, it was, you know, now my iPhone’s got 48 megapixel.
0:13:57 Right.
0:13:57 Right.
0:14:04 And so, and the quality and color performance and everything, that’s improved dramatically.
0:14:05 Yeah.
0:14:11 And then LIDAR is another thing that has really evolved over the course of the last 20 years.
0:14:20 Going from things where we could get a single point along the line to now full 3D fields of view.
0:14:26 And allowing us to combine the camera data with the LIDAR data, with the computation.
0:14:31 And then the final big thing that’s moved forward is, in the sensing side, is radar.
0:14:38 And the automotive radar, the quality that you can get out of that, the price point that that comes in at now.
0:14:46 You know, when you combine that set of advances, there’s orders of magnitude improvement in both the quality of data we can consume
0:14:49 and the amount of data that we can perform computation over.
0:14:53 And that really has unlocked our ability to understand the world around these vehicles.
0:15:00 So, you leave in 2016.
0:15:05 Like, are people getting rides in wherever it was, Chandler, Arizona, yet at that time?
0:15:07 Like, is that, is it out in the world yet when you leave?
0:15:08 Okay.
0:15:11 No, we’ve been doing demos and we were doing development.
0:15:14 I think we had vehicles in Chandler at that time and were starting to operate.
0:15:24 But they were still with a person behind the steering wheel and we were still kind of, we were building towards what ultimately became the initial channel launch.
0:15:26 Why’d you leave?
0:15:28 It was time.
0:15:29 You know, I had been there.
0:15:32 I really valued and loved the experience.
0:15:40 But at some point, I kind of lost confidence that we were going to make the decisions that we needed to make to be successful.
0:15:48 And as the person leading the organization that, you know, Google had been incredibly generous to me, given me this incredible opportunity.
0:15:51 And if I just didn’t believe it, it wasn’t my place to lead the team.
0:15:52 Sure.
0:15:58 And so, you know, I’m a big believer that in business, you, you know, kind of, you have three options.
0:16:00 You, if you see something you don’t like, you try and fix it.
0:16:02 If you can’t fix it, you get in line.
0:16:05 And if you can’t get in line, you get out of the way.
0:16:14 And, you know, I did what I could to try and, you know, kind of move things the way that I thought they needed to go and ultimately said, you know, this company’s been incredibly generous to me.
0:16:18 Let me get out of the way and let it get on its own path.
0:16:31 When you say you lost confidence that they were going to make the decisions they needed to make, I mean, obviously we should evaluate decisions based on the information available at the time.
0:16:38 But, you know, it is the case that, you know, you can get in a Waymo in San Francisco in one minute and have a beautiful ride right now.
0:16:41 Like, were you wrong?
0:16:44 I, apparently, yes.
0:16:45 Right?
0:16:49 Like, you know, like, I think there’s no way to judge it other than they’ve ultimately been successful.
0:16:54 You know, maybe would have taken a different, shorter path.
0:17:01 But, you know, I think, I think it’s, it’s, you know, I don’t know if you’re a parent, but one of the things you hope as a parent is that you,
0:17:08 you, you, you embody your kids with things and then they go off into the world and succeed.
0:17:17 And the same is true when you lead teams or build something is that, you know, you do your part and you hope it outlives you and out, you know, outperforms what you might have hoped for it.
0:17:20 And I think it’s been awesome to see Waymo succeed.
0:17:25 You know, you start Aurora in 2017, right?
0:17:30 And as, as I understand it, you didn’t start focused on trucks.
0:17:32 Like, tell me about what you’re thinking when you start the company.
0:17:33 Yeah.
0:17:34 How you get to trucks.
0:17:38 So, you know, I didn’t leave Google to start the company.
0:17:39 I left Google because it was time.
0:17:46 And I then spent some time trying to figure out what to do and kind of came to the conclusion that, you know, it was worth taking another shot at this and trying to build something.
0:17:57 And so I found two great co-founders in Sterling and Drew and we wanted to build a driver and we wanted to apply that driver and passenger cars and trucks and wherever it could go.
0:18:08 And we thought at the time we didn’t see how it was going to be possible to do trucking because based on the experience I had and others had, we looked at how far you had to see down the road to do that safely.
0:18:13 And we came to the conclusion, you just couldn’t do that with the technology that existed at the time.
0:18:16 And you have to see farther just because it takes longer for a big truck to stop.
0:18:17 It’s just physics.
0:18:17 Yeah.
0:18:20 There’s just way more kinetic energy, right?
0:18:25 They’re heavier and they’re moving at 70 miles an hour instead of in a city, you’re moving at 15 miles an hour.
0:18:32 So the combination of the speed and the way it means that it just, it just takes longer to stop farther distance down the road.
0:18:38 And so we, and then you add to that, it’s much easier to drive around a light vehicle than a big truck.
0:18:39 So, right.
0:18:41 You don’t need a special license.
0:18:42 They’re much smaller.
0:18:45 You don’t, you know, need special maintenance programs and whatnot.
0:18:48 And so we’re like, okay, let’s focus on light vehicles.
0:18:50 We see there’s a real opportunity there.
0:18:58 If we can crack the, can you see far enough problem, then trucking would be a great application to go to.
0:18:59 Yeah.
0:18:59 Yeah.
0:19:15 And so part of what I spent my time doing during the first couple of years of the company was looking, you know, basically turning over every rock we could with, with Bart, one of our early team members to find a technology that would allow us to see far enough, far enough that we could actually do trucking.
0:19:29 And ultimately we found that in this little company in Montana called Blackmore that had built this really special kind of laser range finder that because of the way it did measurements in what’s called frequency modulated continuous wave.
0:19:37 It, it, it could see basically twice as far as the rest of the LiDAR stuff could see.
0:19:44 And so we’re like, huh, we now, we, we have some really interesting driving capability.
0:19:48 We’ve now got this kind of pseudo magical LiDAR sensor that can see far enough.
0:19:52 Trucking feels like a really great application to go take on.
0:19:55 Let’s talk about a few of the things you had to figure out.
0:19:56 So you decide you’re going to do trucking.
0:19:56 Yeah.
0:20:01 And presumably by trucking, like, I mean, I know where you are now.
0:20:08 Like, so presumably by trucking, you don’t mean like the bread truck that goes to the little market by my house.
0:20:11 You mean the great big truck that goes on the freeway.
0:20:11 Yeah.
0:20:19 That’s where we thought there was the biggest opportunity was working on what we call class eight tractor trailers, big, you know, semi trucks.
0:20:20 Yeah.
0:20:22 They drive a lot of miles.
0:20:25 We don’t have enough people who want to do that job.
0:20:30 And yet it’s absolutely essential to American and worldwide way of life.
0:20:34 And there’s a real need, right?
0:20:41 As we’ve dug into it, we realized that there’s about 5,000 people killed every year in heavy truck accidents, 500,000 people injured.
0:20:56 And then we can move goods more efficiently, which, you know, is important, particularly in the, you know, this age of e-commerce where people expect things next day or, you know, be able to move those goods efficiently with customers is really valuable.
0:20:59 Okay.
0:21:09 This April, if I’ve got my dates right, you actually have a truck drive for real stuff on the freeway without someone behind the wheel, right?
0:21:11 That’s exactly right.
0:21:12 It was awesome, right?
0:21:17 We, as a company, have been building towards that for almost eight and a half years, eight and a quarter years.
0:21:22 And, you know, we take doing these things safely very seriously.
0:21:32 And really, a lot of the last couple of years has been making sure we could have confidence that when we let the thing go, that it was actually going to be safe.
0:21:34 And then we got to a point where we’re like, yeah, this is safe.
0:21:40 We can go send this out in the daylight in dry weather and have it drive back and forth between Dallas and Houston.
0:21:44 And I had the privilege of ride along in the back seat.
0:21:48 And it was awesome, right?
0:21:49 In that it worked.
0:21:51 It was incredibly boring, right?
0:21:52 It turns out it’s like a three and a half hour trip.
0:21:54 You want it to be so boring.
0:21:54 Yeah.
0:21:55 You want it to be very boring.
0:21:58 But it just kind of worked.
0:22:01 And I went down and back that day in the truck.
0:22:04 Were you hauling stuff at that point?
0:22:04 Was it business?
0:22:05 We were.
0:22:06 We were hauling pastries.
0:22:07 Yeah.
0:22:08 Oh, pastries.
0:22:08 Okay.
0:22:08 Yeah.
0:22:12 Pastries both ways?
0:22:13 That would be amazing.
0:22:15 There’s some pastries in Houston that they wanted.
0:22:18 No, I think there is a pastry imbalance.
0:22:22 I think we, for the first trip, I think we may have actually been empty.
0:22:28 But on the way back, I’m pretty sure from, for whatever reasons, the pastries diffused from Houston to Dallas.
0:22:31 So then, what happens in May?
0:22:34 In May, you put a person back behind the wheel, right?
0:22:35 Tell me about that.
0:22:35 Yeah.
0:22:39 So, as a company, we’ve really focused on do what we do best.
0:22:43 And what we do best is building a safe, capable driving system, the Aurora driver.
0:22:49 And we work with other companies like Peterbilt at Paccar and Volvo Trucks.
0:23:00 And our partners at Peterbilt called up and said, hey, we’d like you to have an observer in the seat because there’s some prototype parts in our truck.
0:23:03 And it matters to us that you put an observer in.
0:23:05 And so, we said, okay.
0:23:07 You know, we had a conversation.
0:23:09 We respect them.
0:23:10 And we ultimately put the observer in the seat.
0:23:16 And we have a person sat on board who is sat in the driver’s seat, but they’re an observer.
0:23:19 And they’re really just there because our partner asked them to put them there.
0:23:23 I mean, presumably, they’re a license to drive an 18-wheel drive.
0:23:25 It’s not just some random person watching what’s going on.
0:23:26 That’s right.
0:23:26 It’s a truck driver.
0:23:34 You know, we don’t want to put anyone in place where, you know, the Highway Patrol has to debate whether, you know, it’s just like, okay, let’s just put a truck driver there.
0:23:34 They sit there.
0:23:45 If you go to youtube.com slash Aurora driver, you can see a live video between 8 and 5 o’clock every day of our trucks driving down the road.
0:23:48 And you can see that, you know, this person sat there.
0:23:50 And sometimes they’re twiddling their sums.
0:23:51 Sometimes they’re eating Fritos.
0:23:55 You know, just observing.
0:24:03 I mean, at least from a narrative standpoint, it’s a bummer to have to put the person back behind the wheel, surely.
0:24:04 Absolutely.
0:24:06 From a narrative standpoint, it’s a bummer, right?
0:24:10 And it creates a nuance that is, you know, certainly in today’s…
0:24:12 You don’t want a person behind the wheel.
0:24:12 It’s the whole point.
0:24:13 It’s the whole point.
0:24:15 It’s you don’t want a person behind the wheel, right?
0:24:16 Totally agree.
0:24:21 But in terms of the development and delivery of what we’re building, it just doesn’t matter, right?
0:24:23 It’s a complete nothing.
0:24:25 Well, I mean, at some margin, it matters.
0:24:26 At some point, it matters, right?
0:24:28 The whole premise is you can do it without a person there.
0:24:35 And so, like, at some point, like, relatively soon, I would imagine you need to do it without a person there.
0:24:36 That’s right.
0:24:39 And look forward to doing that soon.
0:24:43 We’ll be back in just a minute.
0:25:13 Plus, only iHeart can extend your message to audiences across broadcast radio.
0:25:15 Think podcasting can help your business?
0:25:16 Think iHeart.
0:25:18 Streaming, radio, and podcasting.
0:25:21 Let us show you at iHeartAdvertising.com.
0:25:23 That’s iHeartAdvertising.com.
0:25:25 You should tell the people who we are and what our new show is.
0:25:26 I’m Robert Smith.
0:25:27 And this is Jacob Goldstein.
0:25:29 And we used to host a show called Planet Money.
0:25:36 And now we’re back making this new podcast about the best ideas and people and businesses in history.
0:25:42 and some of the worst people, horrible ideas, and destructive companies in the history of business.
0:25:46 We struggled to come up with a name, decided to call it Business History.
0:25:46 You know why?
0:25:47 Why?
0:25:49 Because it’s a show about the history of business.
0:25:50 Available everywhere.
0:25:52 You get it.
0:25:53 Your podcasts.
0:25:58 Yeah, so where are you now?
0:26:03 Like, give me, we’re basically to the present now after our 20-year journey.
0:26:08 Like, what’s, like, are you, are people paying you to haul stuff?
0:26:09 Yeah, absolutely.
0:26:12 So, like, today is an incredibly exciting moment.
0:26:15 So, we have a technology that can drive a truck.
0:26:23 It has the skills necessary to drive on the freeway and drive to sites off the freeway in these industrial park areas.
0:26:24 And it does that safely.
0:26:33 And then internally, we’ve got the capability to say, okay, what are the new features we need to make this more useful for our customers?
0:26:35 And so, we launched in April.
0:26:45 About three months later, we were able to show, you know, be able to launch the next version that now doesn’t just operate in the daytime, but operates at night as well.
0:26:58 And over the course of the rest of this year, it’s really about taking and building the, you know, enhancing the skills that it has to add the few new skills it needs to be able to drive between Fort Worth and Phoenix and El Paso.
0:27:00 And so, at that point…
0:27:03 Just to be clear, the route you have now is Houston-Dallas, is that right?
0:27:03 That’s right.
0:27:03 I’m sorry.
0:27:05 We drive between Dallas and Houston.
0:27:08 And by the end of the year, we expect to be driving between Fort Worth and Phoenix.
0:27:09 Okay.
0:27:11 And what’s exciting about…
0:27:14 And Fort Worth and El Paso and El Paso and Phoenix.
0:27:20 And what’s exciting about that is Fort Worth to Phoenix is 1,000 miles.
0:27:25 And a person is not able to legally drive that in a day.
0:27:32 And so, we’ll be able to start doing things that are superhuman in more and more dimensions.
0:27:36 Presumably, the value preposition is really long drives, right?
0:27:41 Like, it makes absolutely no sense for whatever, 100 miles or something.
0:27:44 And the longer it gets, the more the economics makes sense.
0:27:44 Is that right?
0:27:45 I mean, that seems like the kiss.
0:27:50 I think it makes sense across all different kind of scales, but I think where the biggest
0:27:52 impact will ultimately be is on these long-call trips.
0:27:59 And, like, I get the freeway part in Broadway.
0:28:02 How does the not-on-the-freeway part work?
0:28:05 How constrained are you as to where you can go when you’re not on the freeway?
0:28:06 Yeah.
0:28:10 So, the capability we’re building is to be able to drive everywhere.
0:28:11 Sure.
0:28:13 But, like, now?
0:28:19 So, today, we drive from a place that’s off the freeway onto the freeway.
0:28:24 And then when we get at the Dallas end of the route, and then at the Houston end, we drive
0:28:28 about five miles from where we get off the freeway to our terminal site.
0:28:32 And along the way, we drive past customer locations.
0:28:39 So, we’re making the choice today to go to our terminals, but it’s relatively straightforward
0:28:42 to stop and go to a different terminal instead or a different site.
0:28:51 Like, how hard is that off-the-freeway part, the sort of marginal, you know, mile when you’re
0:28:52 not on the freeway?
0:28:55 Not, right, would be the short answer, right?
0:29:02 It’s, you know, we’ve put a lot of, for a long time, the primary focus of what we were
0:29:07 building was the freeway part, because, as you pointed out, that’s where the most kinetic
0:29:08 energy is.
0:29:11 That’s where, you know, that’s where the bad things could happen.
0:29:16 I mean, it’s also simpler in certain ways, right?
0:29:20 Like, it seems like turning a big truck around or just getting a truck around.
0:29:23 Like, I live in New York City, and I see 18-wheelers in New York City.
0:29:28 And, I don’t know, maybe that’s not that hard to engineer for autonomy.
0:29:29 You tell me.
0:29:30 It seems hard.
0:29:30 It looks hard.
0:29:34 Yeah, I think New York City is hard, right?
0:29:36 And I think there’ll be a time where we get to that.
0:29:41 I’m really focused, and we’re really focused on in the near term, is how do we get to the
0:29:43 place where most freight moves, right?
0:29:49 And a lot of that will go to these industrial parks and, you know, regions of a city.
0:29:55 And the reason why is it’s hard to drive a truck in New York City, right?
0:29:56 And it’s slow.
0:30:00 And so, if you’re trying to build a distribution center for these Class 8 tractors and trailers,
0:30:05 you put them in places where it’s convenient because you’re trying to run a business, not
0:30:07 build a technology showcase.
0:30:12 So, what can you not do now, autonomously?
0:30:15 So, today we can’t drive in the rain.
0:30:18 Well, in fact, that’s not actually true.
0:30:25 So, today we drive in the rain really well, but we haven’t validated that fully for driverless
0:30:25 operations.
0:30:27 And this is really an important idea, right?
0:30:31 Because if you came down to Texas and got a ride in one of our trucks and it was raining
0:30:33 out, it would work.
0:30:37 And you would go, huh, why have you guys not launched this?
0:30:42 And we would say, yeah, it basically works, but that’s not good enough.
0:30:44 It’s not good enough that it feels like it works.
0:30:46 What we want to have done is all of the diligence.
0:30:49 It basically makes me nervous with an 18-wheel truck.
0:30:49 Exactly.
0:30:51 And it should, right?
0:30:56 And so, for us, we put a lot of effort into making sure that it doesn’t just seem like it
0:30:59 works, but that we have conviction that it will work.
0:30:59 Yeah.
0:31:08 And, you know, as an example, two of the last things that we got checked off when we launched
0:31:16 were it’s, one, really high-speed motorbikes running red lights in the city.
0:31:21 So, we had done a bunch of testing, I think up to, let me say, I’m going to say some numbers
0:31:21 here.
0:31:26 These are probably not quite right, but I’ll use some numbers, you know, at 90 miles an
0:31:31 hour, because we figure, you know, 90 miles an hour on a surface road, nobody on a motorbike.
0:31:33 Meaning the motorcycles go in 90 miles an hour.
0:31:37 Motorcycles go in 90 miles an hour, and they’re going to run a red light in front of us, and we
0:31:39 want the truck to not hit that motorbike.
0:31:43 And then we’re on the freeway, and we see a motorbike doing 150 miles an hour.
0:31:50 And we’re like, okay, that is, let’s go make sure that that works, right?
0:31:53 Because, you know, at some point, we just want to have confidence.
0:31:59 And so, we went through and we found out that when motorbikes going that extremely fast, first,
0:32:03 we had to, we found that our simulation wasn’t quite up to snuff to deal with that.
0:32:04 So, we had to go fix that.
0:32:11 And then we found that our perception system wasn’t able to quite track it as well as we’d
0:32:11 want.
0:32:12 So, we had some things to fix there.
0:32:17 And so, ultimately, we got to the point where if you’re a motorbike, please don’t go test
0:32:17 this.
0:32:21 Run in a red light at 150 miles an hour, we’re going to see you.
0:32:25 And assuming, you know, we can actually see you because there’s not a building in the way,
0:32:29 we’re going to stop and, you know, not have an event with you.
0:32:35 So, is the rain analog of that, like, more rain than I can imagine and flooding and it’s
0:32:36 dark or something?
0:32:40 I mean, and maybe frozen, frozen also?
0:32:46 And so, this is, the answer is we have some good ideas of what these challenges are.
0:32:50 And so, we’re in the process of putting place the last of the tests that we need to say,
0:32:56 yeah, across the things that might be a problem, we actually handle those in a way that’s safe.
0:32:58 Once you got rain, are you good?
0:33:02 I mean, I guess you have the whole southern U.S. without snow and ice.
0:33:05 Well, it probably freezes in Texas, right?
0:33:06 Does it freeze in Texas?
0:33:06 It does.
0:33:07 They get snow in Texas.
0:33:14 But the good news is, like, the reason why a lot of freight moves around the sunbelt is
0:33:18 because trucks don’t like driving in snow, right?
0:33:21 It’s just, you know, much like people in general don’t like driving in snow.
0:33:22 But there is snow.
0:33:25 But if you’ve ever been in Texas when there’s a snowstorm, it basically shuts down.
0:33:26 Yeah.
0:33:28 So, you don’t have to solve snow.
0:33:30 You don’t have to solve snow for now.
0:33:30 For now.
0:33:32 But we will solve snow, right?
0:33:32 Sure.
0:33:35 Because all of the stuff that works for rain mostly works for snow, too.
0:33:39 I mean, all of these problems we can stipulate will be solved by somebody, right?
0:33:39 Yeah.
0:33:42 Plausibly by you, if not you, by somebody else.
0:33:45 But, like, I feel like there’s some sense of urgency.
0:33:52 Like I’ll say, so interestingly, just purely coincidentally, I talked to Boris Sofman.
0:33:53 Is it Sofman?
0:33:53 Yeah.
0:33:54 I don’t have his name in front of me.
0:33:57 And so he said, and we were not talking about you.
0:33:59 This was not a dig on you.
0:34:01 It was more talking about why he’s doing what he’s doing.
0:34:05 He said, I don’t think open road autonomy is a startup game.
0:34:12 And he basically, you probably know he thinks, I mean, he basically thinks it’s too expensive in short.
0:34:21 Too expensive and too hard in that way for a company that is capital constrained, for a company that, you know, doesn’t have a monopoly on search, let’s say.
0:34:28 And so I do feel like in talking to you, like, you plausibly may solve them, but there must be some clock for you, right?
0:34:32 You must have to get to a point where you’re making money relatively soon.
0:34:33 Is that right?
0:34:34 Yeah.
0:34:35 Well, we’ve been at the game for a while.
0:34:38 You know, we went into it eyes open, right?
0:34:46 And looked at the, you know, having spent the time with Waymo, having the history I have, I was like, this is not a $100 million problem or a $10 million problem.
0:34:47 This is a multi-billion dollar problem.
0:34:54 And so as we’ve built Aurora, it’s been, okay, we need to set ourselves up with the staff.
0:34:56 We need to set ourselves up with the capital partners.
0:35:02 We need to set ourselves up with the technology partners that allow us to take that run.
0:35:05 And I think we’ve been very careful about how we’ve done that.
0:35:07 And we’ve put ourselves in a position to succeed.
0:35:09 And I agree with Boris.
0:35:14 This is, you know, I hear people throwing out, oh, we’re going to, you know, spend $100 million to do this.
0:35:16 I’m like, you know, you haven’t even met the ante.
0:35:17 Yeah.
0:35:18 Right?
0:35:23 And so for us, we look at, say, driving in the rain.
0:35:25 We expect to be solving that by the end of this year.
0:35:26 Yeah.
0:35:27 Right?
0:35:31 And at that point, as you point out, we’ve basically unlocked the Southern Freight Belt.
0:35:35 The amount of truck travel that’s there is gigantic.
0:35:46 And so, you know, from now where we have a small number of trucks on the road, by the end of next year, the end of 26, we expect to have a few hundred trucks on the road.
0:35:51 And then the year after that, we expect to have a thousand plus trucks on the road.
0:35:52 And then we’ll build from there.
0:36:00 And so it’s, you know, the conviction we’re starting to build internally, like, yeah, this is just turning over the kind of the way we want it.
0:36:01 And we expect it is happening now.
0:36:04 And so it’s not a hypothetical that someday we’ll solve it.
0:36:08 It’s like, no, we’re, you know, four or five months kind of time frame.
0:36:10 So, well, three, four months time frame.
0:36:12 What’s the business model?
0:36:13 Yeah.
0:36:18 So our business model is to work with the ecosystem that’s there today.
0:36:23 So today, if you’re a trucking company, you buy a truck and then you pay somebody to drive that truck for you.
0:36:26 And so that’s what our company is going to do.
0:36:34 So you’ll, if you’re a company that wants an autonomous truck, you’re going to go to Packard and Peterbilt or you’re going to go to Volvo and say, I want to buy a truck.
0:36:37 And they buy the truck stuff.
0:36:43 And then it’ll roll off the line from our partner and it’ll have the Aurora driver installed on it.
0:36:47 And you’ll pay a subscription to Aurora to drive that truck for you.
0:36:47 I see.
0:36:48 Okay.
0:36:55 So you guys get paid by the mile or by the haul or something like that.
0:36:57 Yeah, that’s exactly right.
0:37:02 You know, it’s at the risk of, as a servicism, you know, it’s driver as a service.
0:37:03 Yeah.
0:37:05 That’s the way we’re thinking about the business.
0:37:07 And the trucking company is buying the truck.
0:37:08 So that’s good for you.
0:37:12 You don’t have to, when you say you’ll have a thousand trucks out there, you don’t mean you’re going to own a thousand trucks.
0:37:16 You mean you’ll have essentially a thousand autonomous drivers in trucks that other people own.
0:37:16 That’s right.
0:37:19 And this is because that’s what our customers want.
0:37:20 Yeah.
0:37:20 Right.
0:37:21 That they’re.
0:37:23 Also, it seems easier as a business.
0:37:24 Oh, it is.
0:37:27 It’s nice to not have to get into the trucking business.
0:37:28 I agreed.
0:37:31 Again, back to the philosophy of we think we’re really good at building the driver.
0:37:32 Yeah.
0:37:38 And I look at our partners, whether it’s Werner or Hirschbach or Federal Express, they know what they’re doing.
0:37:42 Why don’t we help them make their business a bit better and work together?
0:37:51 Can we talk about autonomy a little bit more broadly just since you’ve been at it so long and I’m curious what you think?
0:38:03 So, like, what do you think are the important constraints on autonomous vehicles right now, sort of broadly, technologically, you know, in terms of policy?
0:38:06 I think it’s primarily technological right now.
0:38:07 Okay.
0:38:07 Right.
0:38:16 And I’ve said that, you know, people for the better part of a decade have been, you know, when it’s convenient, hiding behind, you know, regulation or policy.
0:38:21 And, you know, the U.S. policy of regulatory environment is permissive.
0:38:26 It’s one of the things that’s allowed innovation to flourish in this country, certainly in the automotive space.
0:38:30 So, what are the important technological constraints right now?
0:38:35 Like, I mean, obviously, Waymo is thriving where it’s thriving.
0:38:40 But, like, also, there are no autonomous cars where I live and people aren’t buying them.
0:38:43 And so, like, what are the important bottlenecks right now?
0:38:47 Execution bandwidth, right?
0:38:55 So, at least where I sit at a roar today, I don’t look out and see, oh, my gosh, I don’t know how we’re going to solve that.
0:38:57 It’s, hey, we have this many people.
0:39:00 We have this much leadership bandwidth.
0:39:02 We just need to go execute, right?
0:39:09 Like, thinking industry-wide, and not to be, like, petty or something, but, like, why aren’t autonomous cars everywhere right now?
0:39:09 Yeah.
0:39:11 Because it’s really hard, right?
0:39:15 And I think the right metaphor for this is commercial aviation.
0:39:19 Like, the physics are really in grasp, and, like, you can bolt things together.
0:39:28 And yet, you know, we basically have two commercial aviation manufacturers globally, right?
0:39:28 Yeah.
0:39:29 We have Boeing and Airbus.
0:39:33 Because it’s hard to build big jet aircraft, is what you’re saying.
0:39:34 It’s hard to build them.
0:39:36 It’s hard to have conviction they’re going to be safe.
0:39:38 It’s hard to produce them, right?
0:39:45 And when I look at automated driving, I think it’s in a very similar space in that a lot of things have to work well.
0:39:49 You have to have the discipline to be able to work across all of them, make sure they all fit together.
0:39:52 And then you have to have the processes.
0:39:56 And process in Silicon Valley is often kind of a four-letter word.
0:39:58 Like, you know, you’ve got to move fast and break things.
0:40:03 But when you’re building something safety critical, you actually have to get that stuff right.
0:40:06 And the art is getting it right while also being able to do it quickly.
0:40:19 So when you think about the spread of autonomy from here, again, not just within your company, but sort of more broadly, like, how do you think it’ll play out?
0:40:30 I think it’s going to usher in an incredible new age, all right, that we should be able to dramatically reduce traffic fatalities.
0:40:44 The fact that, you know, it had been a decade without a fatality on civil aviation, and yet we had 40,000 people killed on the road every year in the U.S., like, we can bring a technology to bear to help solve this, right?
0:40:46 And I think that’s profound.
0:40:52 I think we can have a huge sustainability impact all while actually kind of powering up the U.S. economy.
0:41:07 And so for us, you know, we’ve got this mission right now that’s focused on trucking, but what we’re really building is this capability to release safety critical software and systems and this ability to understand the world.
0:41:11 And so you combine those two things, the places we can go with that are profound, right?
0:41:21 Whether it is, you know, last mile delivery or ride hailing applications or mining or farming or aviation, like, it’s just going to be a lot of fun over the next decade.
0:41:23 So, yeah, I’m psyched for it.
0:41:28 Next decade sounds fast, given the pace so far.
0:41:30 I was surprised when you said next decade at the end there.
0:41:37 Yeah, I think that, like anything, there’s a point where you have built a foundational base.
0:41:38 Yeah.
0:41:43 And then suddenly you’re like, oh, now I have this power and I have the superpower to go do these things.
0:41:47 And it’s basically the package of hardware plus software at a reductive level.
0:41:51 And you can sort of put it on other things and it’ll more or less work.
0:41:54 More importantly, it’s the process and the data.
0:41:56 And again, it does not sound sexy.
0:41:59 The data sounds sexy.
0:42:02 Like the more you talk to machine learning people, the more sexy data sounds, right?
0:42:03 Yeah.
0:42:11 And, you know, and we joke internally, you know, if you, if we have three kind of big artifacts being our software, our data, and our process.
0:42:17 Yeah, if you held a gun to my head and said, delete one of them, I’d say delete the software.
0:42:18 Interesting.
0:42:19 Right?
0:42:19 That’s really interesting.
0:42:20 Please do not delete our software.
0:42:22 Yeah.
0:42:22 Yeah.
0:42:24 No, that’s really interesting.
0:42:24 Yeah.
0:42:29 We’ll be back in a minute with the lightning round.
0:42:40 Run a business and not thinking about podcasting?
0:42:41 Think again.
0:42:46 More Americans listen to podcasts than ad-supported streaming music from Spotify and Pandora.
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0:42:57 Plus, only iHeart can extend your message to audiences across broadcast radio.
0:42:59 Think podcasting can help your business?
0:43:00 Think iHeart.
0:43:03 Streaming, radio, and podcasting.
0:43:05 Let us show you at iHeartAdvertising.com.
0:43:07 That’s iHeartAdvertising.com.
0:43:10 You should tell the people who we are and what our new show is.
0:43:11 I’m Robert Smith.
0:43:12 This is Jacob Goldstein.
0:43:14 And we used to host a show called Planet Money.
0:43:21 And now we’re back making this new podcast about the best ideas and people and businesses in history.
0:43:27 And some of the worst people, horrible ideas, and destructive companies in the history of business.
0:43:30 We struggled to come up with a name, decided to call it Business History.
0:43:31 You know why?
0:43:32 Why?
0:43:33 Because it’s a show about the history of business.
0:43:35 Available everywhere.
0:43:37 You get it in your podcasts.
0:43:43 We’re going to finish with a lightning round.
0:43:45 I appreciate your time, and we’re almost done.
0:43:45 Cool.
0:43:47 Thanks for the conversation.
0:43:51 Is it right that your father was a prison warden?
0:43:52 He was, in fact, yeah.
0:43:56 Did you learn any management and or parenting tips from him?
0:43:58 Lock them up.
0:44:01 No, absolutely not.
0:44:12 You know, one of the things that stuck with me is, you know, it’s a difficult job being a prison warden because you have the staff, then you have the inmates.
0:44:17 And, right, and they’re often at odds.
0:44:21 And one of the things he said was, you know, make sure you treat everyone with respect, right?
0:44:28 That he would, you know, these are people who had made a mistake in life, you know, and you treat them with respect.
0:44:32 And, you know, I think that’s really powerful and important.
0:44:35 What’s one thing you learned working at Google?
0:44:37 Think big.
0:44:38 That’s nice.
0:44:44 I think that was, you know, Larry and Sergey never lacked for vision.
0:44:50 And I think you can often find yourself constrained by kind of your own kind of sense of what’s a limit.
0:44:54 And, like, just thinking, like, no, what, why can’t you do that?
0:44:55 Why can’t you do that?
0:45:12 Yeah, I remember just as a consumer, just as an ordinary person in the world, when they started what became Google Street View, I was like, surely you can’t take a picture of every bit of every road in America.
0:45:15 And actually, you can, and they did.
0:45:16 Yeah, right?
0:45:19 Like, I think that sense of, like, you don’t need to be intimidated by this.
0:45:21 Like, you need to think rationally.
0:45:22 You need to figure it out.
0:45:24 But, you know, I think it’s a power.
0:45:31 One of my professors at Carnegie Mellon said, dream like an amateur, execute like a professional.
0:45:32 Right?
0:45:34 And I think that’s just a really kind of profound sentiment.
0:45:38 What’s one thing your time at Google taught you not to do?
0:45:39 Ooh.
0:45:44 What did it take me not to do?
0:45:51 Maybe kind of adjacent to that, like, so when I went to Google, I thought I was a pretty good programmer.
0:45:54 You know, I was, you know, Cardi Mellon, and I was good at what I did.
0:46:02 And I’m not a bad programmer, but, like, there are truly exceptional people out in the world, right?
0:46:10 And so I think, you know, maybe don’t overestimate yourself and kind of, again, kind of think big.
0:46:12 Don’t underestimate what’s out there.
0:46:20 Chris Ermsson is the co-founder and CEO of Aurora.
0:46:25 Please email us at problematpushkin.fm.
0:46:27 We are always looking for new guests for the show.
0:46:32 Today’s show was produced by Trina Menino and Gabriel Hunter-Chang.
0:46:37 It was edited by Alexandra Gerriton and engineered by Sarah Bruguer.
0:46:41 I’m Jacob Goldstein, and we’ll be back next week with another episode of What’s Your Problem?
0:46:54 You should tell the people who we are and what our new show is.
0:46:55 I’m Robert Smith.
0:46:56 And this is Jacob Goldstein.
0:46:59 And we used to host a show called Planet Money.
0:47:05 And now we’re back making this new podcast about the best ideas and people and businesses in history.
0:47:08 And some of the worst people.
0:47:11 Horrible ideas and destructive companies in the history of business.
0:47:13 We struggled to come up with a name.
0:47:15 Decided to call it Business History.
0:47:16 You know why?
0:47:16 Why?
0:47:18 Because it’s a show about the history of business.
0:47:20 Available everywhere.
0:47:22 You get your podcasts.
0:47:24 This is an iHeart Podcast.
Chris Urmson is the co-founder and CEO of Aurora, a company trying to bring autonomous driving to commercial trucking.
Chris led a team at the 2004 DARPA challenge that launched the autonomous vehicle industry. Then he held a senior role at Google’s self-driving car project, which later became Waymo.
On the show today, he talks about the long arc of autonomous driving, why he left Google, and the future of autonomous trucking.
See omnystudio.com/listener for privacy information.
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