SPEAKER_02: Wondery Plus subscribers can listen to how I built this early and ad-free right now. Join Wondery Plus in the Wondery app or on Apple Podcasts. Here's a little tip for your growing business. Get the new VentureX business card from Capital One and start earning unlimited double miles on every purchase. That's one of the reasons Jennifer Garner has one for her business. That's right. Jennifer Garner is a business owner and the co-founder of Once Upon a Farm, providers of organic snacks and meals loved by little ones and their parents. With unlimited double miles, the more Once Upon a Farm spends, the more miles they earn. Plus, the VentureX business card has no pre-set spending limit, so their purchasing power can adapt to meet their business needs. The card also gets their team access to over 1,300 airport lounges. Just imagine where the VentureX business card from Capital One can take your business. Capital One. What's in your wallet? Terms and conditions apply. Find out more at CapitalOne.com slash VentureX Business. This episode is brought to you by State Farm. If you're a small business owner, it isn't just your business. It's your life. Whatever your business might be, you want someone who understands. And that's where State Farm's small business insurance comes in. State Farm agents are small business owners too, and know what it takes to help you personalize your policies for your small business needs. Like a good neighbor? State Farm is there. Talk to your local agent today. This episode is brought to you by Vital Farms. No matter how you like your eggs, scrambled, over-easy, or sunny-side up, the people at Vital Farms believe in one thing. Keeping it bullsh** free. That's why their pasture-raised eggs come from hens who each have over 108 square feet of space to roam and forage all year round. So you can spend less time questioning your food and more time enjoying it. I love Vital Farms eggs. I buy them every time I'm at Whole Foods or at another store. And it also gives me peace of mind knowing that the hens are treated ethically. Look for the black Vital Farms carton in your grocery store and learn more at VitalFarms.com. Vital Farms. Keeping it bullsh** free. Hello and welcome to How I Built This Lab. I'm Guy Raz. There's no driver. How crazy is this? That's crazy. This is your first time ever. You're going to look at this as an adult when all cars are driverless. You're going to be like, yep, I did this driverless drive with Daddy.
SPEAKER_02: So it's probably hard to tell from the sound alone, but what you're hearing is audio from a ride I recently took in a Waymo autonomous taxi. My son and I were in San Francisco heading across the city. These taxis are now all over San Francisco and Phoenix. And yes, there is no human driver. There's no human in the car at all, unless you count me and my son, who were passengers. It's a ghost driver. And if I'm being totally honest, they're amazing. The Waymo taxi is now available 24-7 in San Francisco and Phoenix, and it operates similar to Uber or Lyft. Pull out your phone, you fire up the app, order the car, and it magically appears within minutes. Except it's fully autonomous. Waymo was spun out of Google a few years ago, but the project to build autonomous vehicles at Google actually goes back to 2009. One of the engineers on that project was Dmitry Dolgov. He's been with Waymo from the very beginning, and today he's the company's co-CEO. Dmitry was born in Russia, a child of two physics professors. He went to high school in the US and eventually returned to Russia to attend the Moscow Institute of Physics and Technology. Dmitry then came back to the US to get his PhD. In 2006, he took part in a competition called the Urban Challenge, which was sponsored by DARPA, the US defense agency. The idea was to build an autonomous vehicle that could make it through a series of obstacle courses.
SPEAKER_04: The grand challenge was to drive 150 miles through a desert. A completely static environment, but until then, robots were not capable of doing that. So it took two tries in 2004 and 2005 to accomplish that. So the next step was, let's make it a little bit more interesting. Let's make the environment dynamic. Let's add some rules of the road, stop signs, other vehicles, but do it in a controlled environment in that mock city. So that was the challenge. We built a car to do exactly that. We equipped it with a bunch of sensors, lidars, lasers, radars, cameras, computer, and then wrote software that would allow it to follow the rule, understand and follow the rules of the road and interact with other dynamic actors, whether human or other robots.
SPEAKER_02: So I'm looking at one of the vehicles that you helped put together. It's called the Junior. And it's a Volkswagen Passat, I think. And it came in second place. This is like 2007. Was the underlying technology basically what we're talking about today? Was it pretty similar or was it like a crude version? Yes and no. It depends on how you talk about it.
SPEAKER_04: Big car plus sensors plus computers plus software, that stays. But of course, it's almost 18 years since then, everything has changed. The sensing technology has gone a very, very long way. Computers have evolved software, all the breakthroughs, especially in AI. So that led to many, many breakthroughs in the area of software. So now the system we have has the same components, but all of the components and how they work together is qualitatively, drastically different.
SPEAKER_02: It's amazing how many, these DARPA challenges, how many self-driving car companies they spawned. We've talked to Kyle Voigt of Cruise. He competed in the 2004 and 2005 challenges. Dave Ferguson of Neuro, which is another company, was part of the Carnegie Mellon team. Chris Urmson, who also obviously worked with you at Waymo, he's now with Aurora, was also a part of the Carnegie Mellon team. It's amazing how many, you knew all of these people, and this is, as you say, it was a small community of people working on this huge challenge to basically create vehicles that could be fully autonomous. That's right, that's right.
SPEAKER_04: And of course, I worked very closely for many years with Dave and Chris, and they're great friends. So yeah, it's a lot of innovation and a lot of companies and progress came out of those early days of the DARPA-Gen grant challenges.
SPEAKER_02: You and Sebastian Thrun and Chris Urmson, you all went to go work for Google, and you were part of that founding team, which was at the time a secret project, Google's self-driving car project. And at that time, it's amazing to think 2009, because it seems like ancient history now, you were given a charge by Larry Page and Sergey Brin, the co-founders of Google. You had two years to essentially accomplish two things. Do you remember what they were? Yeah, I remember them very well.
SPEAKER_04: The first one was to drive 100,000 miles in autonomous mode. That was way more than orders of magnitude, more than what anybody has done at that time. And the second one, and actually that one turned out to be more interesting and much more challenging, was to drive 10 routes. Each one was about 100 miles long, and they were very carefully selected, I think, by Larry and Sergey personally, and they were fairly devious in how they created them to make it interesting. And the goal was to drive each one from beginning to end in full autonomy, so with no human intervention, which at that time seemed almost impossible. I remember we had a lot of people, experts in the field, laugh at us when we attempted it.
SPEAKER_02: Two years to accomplish this. I think you guys finished it with three months left. Going into this project, do you remember thinking, we're never going to do this in two years?
SPEAKER_04: I was actually, maybe naively, but fairly optimistic. And it was hard, and they're all different. Yes, there are many moments where we would finish one route, and we would think ahead of what would it take to do the next one. And we would write some software, we would collect some data and test it, and then we'd actually try it, and then we would hit a bunch of crap moments of, okay, wow, this is way more difficult than we expected in even those early days. So when you did finally accomplish it, were you guys able to have a party and celebrate,
SPEAKER_02: or was it just like, nice job, now we got to keep it quiet?
SPEAKER_03: Yes, both.
SPEAKER_04: We celebrated, and it felt like it was a big accomplishment. But yeah, we kept it quiet. But that's what made it so incredibly fun. That phase was one of my favorite phases of the whole project. It's like the early days of a startup, you're up against what might seem like an impossible goal, but it's very clearly defined. You have a very clear milestone, a very clear goal. You are singularly focused on it. You have a small team. Everybody's working around the clock 24-7 and sprinting together. And every day and every hour, you're prototyping, you're learning, so you can move incredibly fast. And every day of every hour, you're making amazing progress, and you're learning new things. That was a blast.
SPEAKER_02: And every day probably presented a new series of challenges. Do you remember, what was one of the hardest challenges that you had to figure out? Something that just took longer than you thought. It wasn't coming together quickly, working on trying to make this happen. Do you remember something you worked on that it was such a hard problem to solve?
SPEAKER_04: There's one... We had a number, some were more fundamentally challenging, some were kind of even comical setbacks, where you would do a ride. I remember one of the routes was driving on all of the freeways and crossing all the bridges in the Bay Area. And it was about 100 miles, and you go through all of the challenges, and you were attempting this drive. And the car is doing a good job. It's handling mergers and construction.
SPEAKER_02: You or somebody else was sitting in the drivers behind the wheel just in case. That's right. That's exactly right.
SPEAKER_04: That's exactly right. What made those early days a lot of fun is that if you do everything, you would be putting some hardware in the car, you would be calibrating the hardware, then the next hour you're writing some software, whether it's tools or something for the car to actually make decisions, and then you get in the car and you give it a try. So anyways, on this route, we are driving along, it's doing a job, we get almost to the very end. At this point, you're holding your breath. You're waiting for the last mile or so of that 100 mile. And the way that particular run was supposed to finish is that we're coming down the Golden Gate Bridge into the city, and there are a set of tall booths when you go through the bridge.
SPEAKER_02: Yes, as you go into the city. That's right. At the end of the Golden Gate Bridge. And they're narrow because I use them almost every day. That's exactly right.
SPEAKER_03: And the one that our car wanted to go through was closed at the time.
SPEAKER_04: And it's just not something that we ever encountered and we thought about. Oh, right.
SPEAKER_02: Because it couldn't figure out the X, the red X or the green arrow. It couldn't recognize what those meant.
SPEAKER_04: That's right. And there was actually a gate, so it would stop, but it would not change lanes and pick a different one. And it would go, oh, my God, now back to square one.
SPEAKER_02: Because probably every, it's impossible to imagine every eventuality, but something's going to come up. That's exactly right.
SPEAKER_04: And we would have to deal with high speed traffic on freeways. We had one route that went and kind of took this windy road from the Bay Area to Highway 1 through the mountains. And we were driving along and then a bicycle fell off the truck in front of us. So that's not something that that time the car could deal with. We had another route that went through downtown San Francisco and the famous Lombard Street. That's very narrow, very windy and has some of the most adventurous pedestrians and tourists in the world. So challenges like that. So that's what made it so challenging and so interesting that it was the kind of the breadth of the experience.
SPEAKER_02: And probably every single ride posed a new series of challenges. For example, some lanes are shoulder lanes, but then during heavy traffic, they're open for driving. But the lines are painted on them in such a way that it doesn't seem like a lane. Like a human could figure that out. But an autonomous vehicle probably at that time was like, wait, this doesn't make sense. The lines don't make sense. They don't align. Maybe the car was confused. That's right.
SPEAKER_04: That's right. That would be not the kind of situation or condition that at that time we were able to solve robustly. The goal there was to learn and do like we had to do the route once. So if you fail at something, you would go improve the system and you would try it again. So there was a very well scoped milestone because 100 miles is nothing if you want to build a production system. In those early days, it was long enough that it actually forces you to very deeply think and tackle some of the most fundamental, most important challenges that exist.
SPEAKER_02: We're going to take a quick break, but when we come back, more from Dmitry Dolga on how the engineers at Waymo decided to go after the big win and create a fully autonomous vehicle. Stay with us. I'm Guy Raz and you're listening to How I Built This Lab. The AI might be the most important new computer technology ever. It's storming every industry and literally billions of dollars are being invested. So buckle up. The problem is that AI needs a lot of speed and processing power, so how do you compete without costs spiraling out of control? It's time to upgrade to the next generation of the cloud. Oracle Cloud Infrastructure, or OCI. OCI is a single platform for all your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds, offers one consistent price instead of variable regional pricing, and of course, nobody does data better than Oracle. So now you can train your AI models at twice the speed and less than half the cost of other clouds. To do more and spend less, like Uber, 8x8, and Databricks Mosaic, take a free test drive of OCI at oracle.com slash built. That's oracle.com slash built. Oracle dot com slash built.
SPEAKER_00: Hey, Guy Raz and HIVT listeners. My name is Richard Crowdy and my favorite episode as a business professor is the founding of BET because it summarizes business schools perfectly and keeping revenues up and keeping costs down. It also shows that a complex company like a media company can be founded by an individual that bootstraps it with the proper type of innovation. Bob Johnson is also a legend and he's hilarious. I've actually been listening to my top 15 to try to come up with a list for my business students. So thank you Guy Raz and cheers.
SPEAKER_02: If you want to share your favorite episode of How I Built This, record a short voice memo on your phone telling us your name, where you're from, what your favorite episode is, and why. A lot like the voice memo you just heard. And email it to us at HIVT at ID dot wondery dot com and we'll share your favorites right here in the ad breaks and future episodes. And thanks so much. We love you guys. You're the best. And now back to the show. Welcome back to How I Built This Lab. I'm Guy Raz. My guest today is Dmitry Dolgov, the co-CEO of the autonomous vehicle company Waymo. I guess in those early days, the Google strategy was really on creating driver assist technologies. Not necessarily fully autonomous cars, but cars that could make it easier for drivers to navigate. Basically, what you've got in like a Tesla now or some other cars that have driver assist technologies. But I guess around 2013, there was a conscious decision to pivot the focus because most of your testing was done on freeways. That's right. But what I think you guys and most people involved in the space realize is that to really create complexity, you've got to test these in cities. They've got to navigate city centers and stoplights and left turns and intersections. And so what happened in 2013 to kind of get you guys to focus, to shift your focus on
SPEAKER_02: building a fully autonomous vehicle instead of just driver assist technology? Right.
SPEAKER_04: I would say there are a number of things. As you mentioned, the first phase was just learning and understanding the complexity of the problem. Then we said, let's try to build a product. And that was the driver assist system. We tried it. That was actually reasonably successful. We had run a pilot where we gave these cars to about 100 Google employees and they could use them to commute and take them around on their daily trips. So that was around 2011, 2012. So then in 2013, we looked at the whole thing and we made this decision to go after full autonomy. So the reasons were several. One was what we learned from people using the driver assist system. They would over trust it. They would put on makeup and text and one guy actually fell asleep. Car handled everything fine, but that is not what we wanted to see. So that was one of the reasons. Another one was that we actually made progress on the core, most difficult aspects of this driving task on surface trees. So that gave us a bit more optimism of going after the big prize. And this also at the same time, the field was moving forward. So if we wanted to really make an impact and make improved transportation globally, I thought, hey, the field driver assist systems will develop their other companies and you'll be pushing in that direction. But let's play to our strength and let's go after the uncompromising big win and big unlock in the space, which is full autonomy and actually building what we now call the Waymo driver that's responsible for the whole task of driving beginning and to end with no human behind the wheel.
SPEAKER_02: What do you remember about the conversations and the ambitions? Was it like, hey, let's build the technology for fully autonomous vehicles that we can then maybe one day license? Or was it, no, let's basically become a car company. Let's make fully autonomous technology and purpose-built vehicles and eventually sell these to consumers that they can have for themselves. Was it either of those ambitions discussed?
SPEAKER_04: I don't think we ever seriously entertained building a car. It just never made sense to me or others to do that. We're not a car company. Building cars is hard. There's many companies that spend a hundred years getting very, very good at it. We did in the early days of design a low speed vehicle that we called the Firefly because we needed to take that first, that was our zero to one moment of full autonomy. It was a prototype. It was like that you publicly should display it in 2014.
SPEAKER_02: But that wasn't the goal. It wasn't, we're not going to build cars. But we're going to build the technology that can power any car to become autonomous. That's exactly right.
SPEAKER_04: That's exactly right. And it was the evolution of the thing that then crystallized in the Waymo mission, which is to build the Waymo driver and then over time deployed in different products and different commercial applications, whether right-healing, trucking deliveries, and eventually personally owned vehicles. And that's the path that we set for ourselves and the path that we've been on since that pivot in 2013.
SPEAKER_02: Now in some ways the real work begins because between 2013 and let's say 2023, right, which we're going to get to because it's incredibly exciting what is going on now in San Francisco and Phoenix and a couple other places. But that 10-year period, probably all of a sudden you're back to kind of startup mode because you've got to get these cars, this technology to be absolutely foolproof perfect, but in complex environments like San Francisco, which I think is next to New York is one of the most complex driving environments in the United States. Tell me a little bit about the process that then began. Was that what happened? Was it a shift to like, okay, let's see what these can do in cities?
SPEAKER_04: That's exactly right. We didn't start with the full complexity of San Francisco in those early days. So we can kind of think of that 10 years as maybe three phases that correspond to three generations of our technology, three generations of our driver. That first one was on that low-speed vehicle, the Firefly. That's what we called the third generation of our driver. And by the way, just to clarify, the Firefly probably was designed to be like a campus
SPEAKER_02: type of vehicle, right, like in a university or an office park, not necessarily in the city. That's exactly right.
SPEAKER_04: I mean, it was a low-speed vehicle. It can only move up to 25 miles an hour. So we're thinking maybe large retirement communities or campuses. Like a shuttle that would just get off and on. That's exactly right. And in that first phase on that third generation of our driver, the goal was to actually build something that can take a fully autonomous trip. And we actually did that in 2015. And we put a friend of our project, his name is Steve Mann, he happens to be blind. And then 2015, he took the first autonomous ride in Austin, Texas. It was the first person, the first public person outside of Google to take a ride.
SPEAKER_02: I remember this, this is a YouTube video of it. And yeah, it was in Austin. And yeah, I mean, that was kind of a big deal.
SPEAKER_04: Yeah, it was a huge moment when we're able to do this first ride in 2015. It was a big celebration after that. Yeah, I can imagine.
SPEAKER_02: So at that point, you and your team had built this third generation version of the Waymo driver that could actually take a fully autonomous trip, which is a big deal. And you were essentially betting that this vehicle would keep passengers safe on real city streets, right? What went into the safety design?
SPEAKER_04: That's right. That's right. And that early phase is what kind of forced us to start thinking about this very fundamental question. What does it mean for a self-driving fully autonomous vehicle to be ready? I convinced it out on this path in 2013. I said, okay, we're going to need a car. It needs to have a bunch of safety systems. Does that exist? No. Okay, well, let's design one and work with partners to manufacture it. So we put a lot of thought and work into making it safe. It had like a foam front. It had a Plexiglas window. The sensor poles were attached with magnets so they could detach if something were to happen. And then the sensors at that time didn't have the level of reliability or capability that we would need, that we would trust to go to full autonomy. So we built, that generation had our own lighters and custom sensor suite. And then of course the software that we had to build, none of that existed.
SPEAKER_02: So let's talk about the technology for a moment because you mentioned LIDAR and radar and some of these things, we know what they are. LIDAR, for example, uses basically light lasers to measure distance. And you've got radar technology, cameras all over the car. Can you just kind of break down how they work? I mean, a lot of people who drive Teslas, for example, I have one, if you use what Tesla calls full self-driving, which is not really full self-driving, but they rely primarily on cameras. They don't use LIDAR or radar technology. Tesla argues that that is, the other ones are just redundancies that are unnecessary. Tell me how your technology works and why you think it's better.
SPEAKER_04: These sensors are, they kind of have fundamentally different and complimentary physical properties. So cameras give you the high resolution and the richness of color. And how many cameras, by the way, on a Waymo vehicle now?
SPEAKER_04: On the current generation, we have kind of all of them, including internal ones, we have 29 cameras. 29 cameras, okay. Yeah. But they're passive sensors, right? Somebody else has to bring the light, whether it's your headlights or the sun. Radars and LIDARs, in contrast, are active sensors. So they blast their own energy out on the wall, and then they get returns, and from that, they can make sense of the environment. And they use different wavelengths. So they can kind of punch through fog or rain much better than LIDAR or camera. So as a human driver, I'm sure you can relate to how difficult they drive. Due to drive at night, for example, at night, if you have somebody in an oncoming car with their headlights on, high beams, it kind of blinds you. It's very hard to see. It doesn't affect radar or LIDAR or similarly driving in dense rain or fog. So this is why we think kind of using all of the sensors and fusing them in our AI and ML models so that you can extract the best signal and see the world in the best possible way, gives us an advantage. And really, you can build a prototype or build a driver assist system without needing all of that extra capability, extra redundancy. But if you really want to take the driver out and go for full autonomy, it gives you a boost.
SPEAKER_02: All right. So just to clarify, basically, you have the first successful ride with a third generation vehicle in 2015. And then in 2016, Waymo actually spins out of Google as an independent company. And then the next year, you become the first company to start regularly operating these AVs in Chandler, Arizona. These are even more advanced than the previous version. What's the idea of like, hey, let's get these in really good shape and then we'll turn them into like Ubers? That's right.
SPEAKER_04: That's right. At that point, we were pretty clear that that was going to be our first deployment, our first product. And essentially, that's what we launched in Chandler. That's when we created the Waymo One product and the Waymo One application. And then 2018 in Chandler, we started offering the service to external riders. And then in 2020 in Chandler, Arizona, we launched the first fully autonomous ride healing service that was open to the public. Anybody could just download the app and call a car. That was our fourth generation Pacifica minivan. An empty car would go show up and take anywhere. So then we made this decision that it was not the best path forward to kind of incrementally grow and scale that system. We made the decision to make a hop to what we call the fifth generation of our driver. That's in the JLR I-Paces Pacificas and a whole new... This is the Jaguar. That's right. That's right. And we said, hey, let's take a big step. It's going to be a different car. It's going to be a new generation of hardware. It's going to be very different software with big bets on in your state of the art AI. And okay, let's go after the full complexity of the problem, including the full density of downtown Phoenix and downtown San Francisco. So that's what we were working on that timeframe to then on that new generation or the Waymo driver to launch the Waymo One service.
SPEAKER_02: We're going to take a quick break, but when we come back, how Waymo One works today and Dimitri's take on the future of autonomous vehicles. Stay with us. I'm Guy Raz and you're listening to How I Built This Lab. This episode is sponsored by Nissan. Nissan has a car for everyone. Every driver who wants more. More fun. More freedom. More action. More electric. More head-turning style. From sports cars to sedans to EVs, pickups and crossovers, with Nissan, there is no compromising on your next adventure. Whether you're taking a detour or going way off the grid, Nissans like the Frontier, Pathfinder or Rogue have various forms of four-wheel drive that are built to take on off-road challenge with a suite of capabilities that make them truly fun to drive on and off-road. Learn more at nissanusa.com.
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SPEAKER_02: Welcome back to how I built this lab. I'm Guy Raz. My guest is Dmitry Dolgov, the co-CEO of the autonomous vehicle company Waymo, which has started to roll out Waymo one, its autonomous ride hailing service in San Francisco. The city gave you permission to be a ride hailing service for 24 hours a day. And I get I've used them probably a dozen times now. They're Jaguar SUVs, all electric. And they drive around the city and you just order it like an Uber. You just go out and you know, go on your app and it comes and then you unlock the door with your phone and you get in and you hit start and it goes. And I can't even tell you how many times the first question I get from people is aren't you scared? Aren't you terrified when you get in one of these things? And so I have my answer. So what's your answer when people say that to you? Like this just seems terrifying for a machine to drive you around a city like it seems so scary like it could, you know, you could just go haywire and drive off a bridge or something. What do you say to people when they ask you that?
SPEAKER_04: Oh, you know, I at this point, I think I'm much more anxious about human drivers than I am about the Waymo driver. So I have full confidence. But of course, you know, I've been in those cars, you know, many, many times, you know, hundreds, thousands of times over the years. But what we see with other people like it's very natural to have that anxiety. It's a very different, very new system and new product. What we very consistently see and I guess I would love to hear if that matches your experience. But once people get in the car, just you know, after a couple of minutes, they get very comfortable and they go back to you know, doing whatever they want to be doing like, you know, back on their phone and check. Yeah, exactly.
SPEAKER_02: I know. I know. I went to my son in it and drove across San Francisco and yeah, within like 30 seconds or 45 seconds, the first time ever he's in there, he's like back looking at his phone. And it's true. It's you get in it, and then it goes. And it's really cool. You're looking out looking at the steering wheel turn for the first 45 seconds, and then you're done. And then you're just like going back to what you were doing answering emails or whatever. But it is it is amazing that it you know, how sort of bizarrely ordinary it feels after after a couple seconds.
SPEAKER_04: Yeah, but that's great. Yeah, I mean, that that's that that's incredibly exciting. And I think some people kind of draw this parallel that you can have your brain switches to passenger mode. Yeah. And yeah, you do get all of these benefits of, you know, privacy, whether you want to have a conversation with somebody in the car that you're in the car with, or you want to make a phone call. And I mean, yeah, that's exactly why we're why we're so excited about this product.
SPEAKER_02: All right. So, Dimitri, in general, right? I'm optimistic when it comes to technology, but I have to also admit that healthy skepticism is important, right? I mean, we've been promised technologies that are going to make our lives better and change the world only to be, you know, sorely disappointed by them. I think it's really amazing what's what's happening with autonomous vehicles. But I guess I wonder, you know, do you understand some of the cause for concern or some of the skepticism around it?
SPEAKER_04: Yes, I think it's very natural. That needs very new technology. It's very different. So I think if you look back in history, it's very common that when a new thing comes around, there is skepticism. There are lots of questions. There is excitement, but there's also a lot of sensitivity.
SPEAKER_02: But I wonder, I mean, you know, it's one thing to say, hey, you know, don't worry, this is going to be OK. But how can you guarantee or convince people that the technology couldn't be misused, couldn't be, you know, manipulated in a way that endangers human life?
SPEAKER_04: Well, I guess we should start, I would start with a status quo, right? We are not OK, right? If you look at just how many lives are lost to the transportation system that we have today, I'm sure you have heard these numbers before, but well-known that in the U.S. alone, more than 40,000 people die every year. I just need to take a step back. This is kind of insane. I mean, if we were to invent cars today, our transportation system, like, no way we would allow this. And I think we over time, we just kind of slowly boiled ourselves as a society to, you know, accept that. And I think as a first order impact of this technology, you know, we can do better. We can do much better. And we are, you know, we're seeing that today. We have driven north of five million fully autonomous miles today. And we've shared some data from the safety impact that our cars have. And I think at this point, we have a fairly robust body of evidence that shows that our cars actually have very clear safety benefits where they operate.
SPEAKER_02: How do we think about, and there's no easy answer right now because it's both an ethical and a legal question, but how do we think about liability? Right? If let's say, I own a car that is fully autonomous with Waymo's technology, let's say, in 10 years from now. And I'm in the back and I'm just doing my work, or I'm asleep, you know, which I should rather be doing. I just go to sleep and let it drive me from San Francisco to LA, which would be great. But it gets in an accident of just a very fluke accident, maybe another car hits it or something. How do we account for liability? I mean, who's responsible? Is the owner of the car? Is Waymo's technology like, how is that going to work?
SPEAKER_04: For the actions of the Waymo driver, the responsibility lies with Waymo. If it was the fault of another actor, another driver, then you can follow the established processes that are well understood and well studied by, for example, insurance companies. They have decades of experience of evaluating exactly that question. And this is where I think that study that Swissaree has done was very encouraging that when they looked at almost four million miles of our fully autonomous operation, they found that massive reduction in, you know, 100% reduction in bodily injury claims and, you know, 4X reduction in property damage, right? So that then you can apply, like you can marry the two and you're starting to see the benefits.
SPEAKER_02: So if Waymo is, I mean, basically, if in a future scenario, somebody's in a Waymo car, the Waymo vehicle crashes, and there's some kind of fluke and Waymo is responsible, I mean, you guys have to accept that liability. But I guess, in order to get to that position, you have to be rock solid confident that that will never happen.
SPEAKER_04: Well, that's what we spend, that's one of the hardest questions that we spend, you know, more than a decade working on. We have, we've developed a very robust multifaceted readiness and safety framework. And actually, that's something we shared publicly. And it's that what we see in all of those methodologies as we improve and validate our system that the day of the day is what gives us confidence in the performance of the system.
SPEAKER_02: How many cars do you have on the streets of San Francisco now?
SPEAKER_04: We have a fleet in San Francisco of about 250 vehicles. You know, they're not all out at the same time, but it gives you an approximate order of magnitude.
SPEAKER_02: And Phoenix?
SPEAKER_04: About the same, I want to say about a couple hundred cars as well.
SPEAKER_02: So here's the question. Is the part of the business model right now for Waymo to become like a ride-hailing service? Like, you know, I'm sure, I know you've got a partnership that you announced with Uber, but I mean, is the idea that, you know, in 10 years time, this is going to be the primary, your primary business or a part of what you do? Give me a sense of, is Waymo going to be a ride-hailing service or is it going to be a technology company that licenses its technology to both ride-hailing services and, you know, automobile manufacturers and others?
SPEAKER_04: Well, we think of ourselves as building a generalizable Waymo driver. And the business model is to deploy it in different product lines, different commercial applications. There's three main ones. Ride-hailing, that's what we call Waymo One. Then there's trucking and deliveries, moving goods. And then the third one is personally owned vehicles. So that's the long-term vision. We want the driver, there's trillions of miles being traveled. I think there's almost three trillion in the U.S. alone, you know, much more across the world. So we want to have a positive impact on some meaningful fraction of all of those miles. So the first business and the first product is Waymo One and ride-hailing. But we're exploring different, you know, other different partnerships. I just mentioned that the Uber partnership that we just launched, I think, where it is-
SPEAKER_02: And that partnership, by the way, is, what is it going to look like? It's going to be the Uber app will also hail Waymo cars? That's right.
SPEAKER_04: That's right. You can use the Uber app and get a fully autonomous vehicle.
SPEAKER_02: This is not a money-making operation for Waymo right now. I mean, the ride-hailing service is still in its infancy, but, you know, there's been billions of dollars invested into Waymo. And I have to imagine ride-hailing is not where you're going to make your money. It's going to be from selling this technology. So what- Tell me, just from the business perspective, when do you see a path to profitability?
SPEAKER_04: Well, you know, a challenge a little bit that ride-hailing is a massive opportunity. It is a very big market today, but it's growing. There's expectations that it's going to be significantly bigger by the end of the decade. But on top of that, if you factor in the benefits and the positive economics that fully autonomous vehicles can bring to the table, there's potential for that to expand quite a bit. So we are very laser focused on that as our primary business line. Beyond that, we want to pursue trucking and deliveries and then eventually personally owned vehicles. But ride-hailing, I would not dismiss that at all.
SPEAKER_02: So probably unrealistic to say that within 10 years, ordinary people could buy a fully autonomous vehicle for themselves, but probably not unrealistic to say that in 10 years from now in most major urban centers in the U.S., there will be autonomous taxis available for anybody to use.
SPEAKER_04: I definitely agree with the latter, and I would not dismiss the former 10 years. This is a reasonably long time and things can happen non-linearly.
SPEAKER_02: So final question for you. So if the future is autonomous, and I think it is, I think I really do, I'm convinced. I think anybody who uses one of these taxis will see it. It's so clear, at least to me. You go in and it's a clean car, it's a very good driver, it's a defensive driver, but it's also not overly defensive, so it's not timid. It's like a very good taxi driver, better. So that I think is the future. So Dimitri, I know that there are plenty of people who love driving, who love the experience of controlling their car. And those people will continue to want to have that ability, and they will. But in your view, are we looking at a future where most people are going to be driven by their cars?
SPEAKER_04: In the long term future, I think, yes. I think that that's where we're heading. Maybe taking your car in the future to a racetrack and driving it manually, that's going to be the novel and exciting thing, rather than the mundane, boring task of driving and commuting. And if you imagine a future where a large fraction of your cars on the road are fully autonomous or at least smart enough, then you can start doing things where you're optimizing more globally. They can coordinate their speed, you can connect them to smarter infrastructure and actually overall increase the throughput of your roads and could increase the throughput of your transportation system. And farther out in the future, if you look there today, personally owned vehicles can sit around for 90% of their lifetime. You take them home or work and then you park it and then nine out of 10 hours is just sitting there. So if that changes, if you no longer have to have your car just sitting there for you, it just opens up. There's a lot more space that can be used in cities for other more interesting things.
SPEAKER_02: Dimitri, thank you so much. It was a pleasure.
SPEAKER_04: Thank you, Guy. That's Dimitri Dolgov, co-CEO of Waymo.
SPEAKER_02: Hey, thanks so much for listening to the show this week. Please make sure to click the follow button on your podcast app so you never miss a new episode of the show. And as always, it's free. This episode was produced by Kerry Thompson with editing by John Isabella and research help from Chris Mussini. Their music was composed by Ramtin Arablui. Our audio engineer was Neil Rausch. Our production team at How I Built This includes Alex Chung, Carla Estevez, Casey Herman, Chris Mussini, Elaine Coates, JC Howard, Malia Agudelo, Neva Grant, Sam Paulson, and Katherine Seifer. I'm Guy Raz and you've been listening to How I Built This Lab. If you like How I Built This, you can listen early and ad-free right now by joining Wondery Plus in the Wondery app or on Apple podcasts. Prime members can listen ad-free on Amazon Music. Before you go, tell us about yourself by filling out a short survey at wondery.com slash survey.
