WEBVTT 00:00.000 --> 00:03.120 The following is a conversation with Chris Sampson. 00:03.120 --> 00:06.000 He was a CTO of the Google self driving car team, 00:06.000 --> 00:08.880 a key engineer and leader behind the Carnegie Mellon 00:08.880 --> 00:12.000 University autonomous vehicle entries in the DARPA Grand 00:12.000 --> 00:16.160 Challenges and the winner of the DARPA Urban Challenge. 00:16.160 --> 00:20.100 Today, he's the CEO of Aurora Innovation, an autonomous 00:20.100 --> 00:21.360 vehicle software company. 00:21.360 --> 00:23.600 He started with Sterling Anderson, 00:23.600 --> 00:25.960 who was the former director of Tesla Autopilot, 00:25.960 --> 00:30.120 and drew back now, Uber's former autonomy and perception lead. 00:30.120 --> 00:32.880 Chris is one of the top roboticists and autonomous 00:32.880 --> 00:36.320 vehicle experts in the world, and a longtime voice 00:36.320 --> 00:38.840 of reason in a space that is shrouded 00:38.840 --> 00:41.320 in both mystery and hype. 00:41.320 --> 00:43.600 He both acknowledges the incredible challenges 00:43.600 --> 00:46.480 involved in solving the problem of autonomous driving 00:46.480 --> 00:49.760 and is working hard to solve it. 00:49.760 --> 00:52.400 This is the Artificial Intelligence podcast. 00:52.400 --> 00:54.720 If you enjoy it, subscribe on YouTube, 00:54.720 --> 00:57.920 give it five stars on iTunes, support it on Patreon, 00:57.920 --> 00:59.720 or simply connect with me on Twitter 00:59.720 --> 01:03.240 at Lex Friedman, spelled F R I D M A N. 01:03.240 --> 01:09.120 And now, here's my conversation with Chris Sampson. 01:09.120 --> 01:11.960 You were part of both the DARPA Grand Challenge 01:11.960 --> 01:13.880 and the DARPA Urban Challenge teams 01:13.880 --> 01:17.040 at CMU with Red Whitaker. 01:17.040 --> 01:19.720 What technical or philosophical things 01:19.720 --> 01:22.240 have you learned from these races? 01:22.240 --> 01:26.600 I think the high order bit was that it could be done. 01:26.600 --> 01:30.200 I think that was the thing that was 01:30.200 --> 01:34.880 incredible about the first of the Grand Challenges, 01:34.880 --> 01:38.160 that I remember I was a grad student at Carnegie Mellon, 01:38.160 --> 01:45.360 and there was kind of this dichotomy of it 01:45.360 --> 01:46.720 seemed really hard, so that would 01:46.720 --> 01:48.800 be cool and interesting. 01:48.800 --> 01:52.800 But at the time, we were the only robotics institute around, 01:52.800 --> 01:55.560 and so if we went into it and fell on our faces, 01:55.560 --> 01:58.360 that would be embarrassing. 01:58.360 --> 02:01.120 So I think just having the will to go do it, 02:01.120 --> 02:02.880 to try to do this thing that at the time 02:02.880 --> 02:05.000 was marked as darn near impossible, 02:05.000 --> 02:06.960 and then after a couple of tries, 02:06.960 --> 02:08.420 be able to actually make it happen, 02:08.420 --> 02:12.320 I think that was really exciting. 02:12.320 --> 02:15.040 But at which point did you believe it was possible? 02:15.040 --> 02:16.960 Did you from the very beginning? 02:16.960 --> 02:18.000 Did you personally? 02:18.000 --> 02:19.800 Because you're one of the lead engineers. 02:19.800 --> 02:21.800 You actually had to do a lot of the work. 02:21.800 --> 02:23.880 Yeah, I was the technical director there, 02:23.880 --> 02:26.120 and did a lot of the work, along with a bunch 02:26.120 --> 02:28.420 of other really good people. 02:28.420 --> 02:29.760 Did I believe it could be done? 02:29.760 --> 02:31.080 Yeah, of course. 02:31.080 --> 02:32.760 Why would you go do something you thought 02:32.760 --> 02:34.800 was completely impossible? 02:34.800 --> 02:36.260 We thought it was going to be hard. 02:36.260 --> 02:37.800 We didn't know how we were going to be able to do it. 02:37.800 --> 02:42.880 We didn't know if we'd be able to do it the first time. 02:42.880 --> 02:45.960 Turns out we couldn't. 02:45.960 --> 02:48.400 That, yeah, I guess you have to. 02:48.400 --> 02:52.960 I think there's a certain benefit to naivete, right? 02:52.960 --> 02:55.440 That if you don't know how hard something really is, 02:55.440 --> 02:59.600 you try different things, and it gives you an opportunity 02:59.600 --> 03:04.120 that others who are wiser maybe don't have. 03:04.120 --> 03:05.720 What were the biggest pain points? 03:05.720 --> 03:08.880 Mechanical, sensors, hardware, software, 03:08.880 --> 03:11.800 algorithms for mapping, localization, 03:11.800 --> 03:13.680 just general perception, control? 03:13.680 --> 03:15.320 Like hardware, software, first of all? 03:15.320 --> 03:20.120 I think that's the joy of this field, is that it's all hard 03:20.120 --> 03:25.360 and that you have to be good at each part of it. 03:25.360 --> 03:32.360 So for the urban challenges, if I look back at it from today, 03:32.360 --> 03:38.960 it should be easy today, that it was a static world. 03:38.960 --> 03:40.800 There weren't other actors moving through it, 03:40.800 --> 03:42.480 is what that means. 03:42.480 --> 03:47.080 It was out in the desert, so you get really good GPS. 03:47.080 --> 03:51.400 So that went, and we could map it roughly. 03:51.400 --> 03:55.160 And so in retrospect now, it's within the realm of things 03:55.160 --> 03:57.840 we could do back then. 03:57.840 --> 03:59.720 Just actually getting the vehicle and the, 03:59.720 --> 04:00.680 there's a bunch of engineering work 04:00.680 --> 04:04.760 to get the vehicle so that we could control it and drive it. 04:04.760 --> 04:09.600 That's still a pain today, but it was even more so back then. 04:09.600 --> 04:14.280 And then the uncertainty of exactly what they wanted us to do 04:14.280 --> 04:17.040 was part of the challenge as well. 04:17.040 --> 04:19.440 Right, you didn't actually know the track heading in here. 04:19.440 --> 04:21.480 You knew approximately, but you didn't actually 04:21.480 --> 04:23.520 know the route that was going to be taken. 04:23.520 --> 04:24.920 That's right, we didn't know the route. 04:24.920 --> 04:28.600 We didn't even really, the way the rules had been described, 04:28.600 --> 04:29.800 you had to kind of guess. 04:29.800 --> 04:33.360 So if you think back to that challenge, 04:33.360 --> 04:36.960 the idea was that the government would give us, 04:36.960 --> 04:40.320 the DARPA would give us a set of waypoints 04:40.320 --> 04:43.520 and kind of the width that you had to stay within 04:43.520 --> 04:46.800 between the line that went between each of those waypoints. 04:46.800 --> 04:49.280 And so the most devious thing they could have done 04:49.280 --> 04:53.280 is set a kilometer wide corridor across a field 04:53.280 --> 04:58.280 of scrub brush and rocks and said, go figure it out. 04:58.520 --> 05:01.920 Fortunately, it really, it turned into basically driving 05:01.920 --> 05:05.000 along a set of trails, which is much more relevant 05:05.000 --> 05:07.920 to the application they were looking for. 05:08.760 --> 05:12.080 But no, it was a hell of a thing back in the day. 05:12.080 --> 05:16.640 So the legend, Red, was kind of leading that effort 05:16.640 --> 05:19.120 in terms of just broadly speaking. 05:19.120 --> 05:22.040 So you're a leader now. 05:22.040 --> 05:25.000 What have you learned from Red about leadership? 05:25.000 --> 05:26.200 I think there's a couple things. 05:26.200 --> 05:31.080 One is go and try those really hard things. 05:31.080 --> 05:34.480 That's where there is an incredible opportunity. 05:34.480 --> 05:36.560 I think the other big one, though, 05:36.560 --> 05:40.680 is to see people for who they can be, not who they are. 05:41.720 --> 05:43.720 It's one of the things that I actually, 05:43.720 --> 05:46.080 one of the deepest lessons I learned from Red 05:46.080 --> 05:50.200 was that he would look at undergraduates 05:50.200 --> 05:55.200 or graduate students and empower them to be leaders, 05:56.120 --> 06:00.320 to have responsibility, to do great things 06:00.320 --> 06:04.480 that I think another person might look at them 06:04.480 --> 06:06.600 and think, oh, well, that's just an undergraduate student. 06:06.600 --> 06:07.720 What could they know? 06:08.680 --> 06:12.720 And so I think that kind of trust but verify, 06:12.720 --> 06:14.480 have confidence in what people can become, 06:14.480 --> 06:16.680 I think is a really powerful thing. 06:16.680 --> 06:20.440 So through that, let's just fast forward through the history. 06:20.440 --> 06:24.160 Can you maybe talk through the technical evolution 06:24.160 --> 06:26.200 of autonomous vehicle systems 06:26.200 --> 06:29.960 from the first two Grand Challenges to the Urban Challenge 06:29.960 --> 06:33.560 to today, are there major shifts in your mind 06:33.560 --> 06:37.240 or is it the same kind of technology just made more robust? 06:37.240 --> 06:39.840 I think there's been some big, big steps. 06:40.880 --> 06:43.720 So for the Grand Challenge, 06:43.720 --> 06:48.720 the real technology that unlocked that was HD mapping. 06:51.400 --> 06:54.200 Prior to that, a lot of the off road robotics work 06:55.160 --> 06:58.480 had been done without any real prior model 06:58.480 --> 07:01.400 of what the vehicle was going to encounter. 07:01.400 --> 07:04.880 And so that innovation that the fact that we could get 07:05.960 --> 07:10.960 decimeter resolution models was really a big deal. 07:13.440 --> 07:18.200 And that allowed us to kind of bound the complexity 07:18.200 --> 07:19.680 of the driving problem the vehicle had 07:19.680 --> 07:21.040 and allowed it to operate at speed 07:21.040 --> 07:23.800 because we could assume things about the environment 07:23.800 --> 07:25.360 that it was going to encounter. 07:25.360 --> 07:29.720 So that was the big step there. 07:31.280 --> 07:35.280 For the Urban Challenge, 07:37.240 --> 07:39.280 one of the big technological innovations there 07:39.280 --> 07:41.040 was the multi beam LIDAR 07:41.960 --> 07:45.760 and being able to generate high resolution, 07:45.760 --> 07:48.680 mid to long range 3D models of the world 07:48.680 --> 07:53.680 and use that for understanding the world around the vehicle. 07:53.680 --> 07:56.600 And that was really kind of a game changing technology. 07:58.600 --> 08:00.000 In parallel with that, 08:00.000 --> 08:04.360 we saw a bunch of other technologies 08:04.360 --> 08:06.120 that had been kind of converging 08:06.120 --> 08:08.440 half their day in the sun. 08:08.440 --> 08:12.560 So Bayesian estimation had been, 08:12.560 --> 08:17.560 SLAM had been a big field in robotics. 08:17.840 --> 08:20.760 You would go to a conference a couple of years before that 08:20.760 --> 08:24.880 and every paper would effectively have SLAM somewhere in it. 08:24.880 --> 08:29.320 And so seeing that the Bayesian estimation techniques 08:30.720 --> 08:33.400 play out on a very visible stage, 08:33.400 --> 08:36.520 I thought that was pretty exciting to see. 08:38.080 --> 08:41.560 And mostly SLAM was done based on LIDAR at that time. 08:41.560 --> 08:44.560 Yeah, and in fact, we weren't really doing SLAM per se 08:45.600 --> 08:47.480 in real time because we had a model ahead of time, 08:47.480 --> 08:51.040 we had a roadmap, but we were doing localization. 08:51.040 --> 08:53.560 And we were using the LIDAR or the cameras 08:53.560 --> 08:55.400 depending on who exactly was doing it 08:55.400 --> 08:57.560 to localize to a model of the world. 08:57.560 --> 09:00.160 And I thought that was a big step 09:00.160 --> 09:05.160 from kind of naively trusting GPS, INS before that. 09:06.640 --> 09:09.840 And again, lots of work had been going on in this field. 09:09.840 --> 09:13.040 Certainly this was not doing anything 09:13.040 --> 09:16.840 particularly innovative in SLAM or in localization, 09:16.840 --> 09:20.200 but it was seeing that technology necessary 09:20.200 --> 09:21.800 in a real application on a big stage, 09:21.800 --> 09:23.080 I thought was very cool. 09:23.080 --> 09:24.000 So for the urban challenge, 09:24.000 --> 09:28.600 those are already maps constructed offline in general. 09:28.600 --> 09:30.920 And did people do that individually, 09:30.920 --> 09:33.600 did individual teams do it individually 09:33.600 --> 09:36.440 so they had their own different approaches there 09:36.440 --> 09:41.440 or did everybody kind of share that information 09:41.720 --> 09:42.880 at least intuitively? 09:42.880 --> 09:47.880 So DARPA gave all the teams a model of the world, a map. 09:49.640 --> 09:53.240 And then one of the things that we had to figure out 09:53.240 --> 09:56.080 back then was, and it's still one of these things 09:56.080 --> 09:57.280 that trips people up today 09:57.280 --> 10:00.280 is actually the coordinate system. 10:00.280 --> 10:03.080 So you get a latitude longitude 10:03.080 --> 10:05.040 and to so many decimal places, 10:05.040 --> 10:07.360 you don't really care about kind of the ellipsoid 10:07.360 --> 10:09.560 of the earth that's being used. 10:09.560 --> 10:12.240 But when you want to get to 10 centimeter 10:12.240 --> 10:14.400 or centimeter resolution, 10:14.400 --> 10:18.520 you care whether the coordinate system is NADS 83 10:18.520 --> 10:23.520 or WGS 84 or these are different ways to describe 10:24.200 --> 10:26.760 both the kind of non sphericalness of the earth, 10:26.760 --> 10:31.080 but also kind of the, I think, 10:31.080 --> 10:32.080 I can't remember which one, 10:32.080 --> 10:33.600 the tectonic shifts that are happening 10:33.600 --> 10:37.000 and how to transform the global datum as a function of that. 10:37.000 --> 10:41.020 So getting a map and then actually matching it to reality 10:41.020 --> 10:42.880 to centimeter resolution, that was kind of interesting 10:42.880 --> 10:44.040 and fun back then. 10:44.040 --> 10:46.760 So how much work was the perception doing there? 10:46.760 --> 10:51.760 So how much were you relying on localization based on maps 10:52.480 --> 10:55.760 without using perception to register to the maps? 10:55.760 --> 10:58.000 And I guess the question is how advanced 10:58.000 --> 10:59.800 was perception at that point? 10:59.800 --> 11:01.960 It's certainly behind where we are today, right? 11:01.960 --> 11:05.840 We're more than a decade since the urban challenge. 11:05.840 --> 11:08.640 But the core of it was there. 11:08.640 --> 11:13.120 That we were tracking vehicles. 11:13.120 --> 11:15.640 We had to do that at 100 plus meter range 11:15.640 --> 11:18.320 because we had to merge with other traffic. 11:18.320 --> 11:21.240 We were using, again, Bayesian estimates 11:21.240 --> 11:23.860 for state of these vehicles. 11:23.860 --> 11:25.580 We had to deal with a bunch of the problems 11:25.580 --> 11:26.920 that you think of today, 11:26.920 --> 11:29.820 of predicting where that vehicle's going to be 11:29.820 --> 11:31.060 a few seconds into the future. 11:31.060 --> 11:32.380 We had to deal with the fact 11:32.380 --> 11:35.320 that there were multiple hypotheses for that 11:35.320 --> 11:37.660 because a vehicle at an intersection might be going right 11:37.660 --> 11:38.780 or it might be going straight 11:38.780 --> 11:40.620 or it might be making a left turn. 11:41.500 --> 11:44.120 And we had to deal with the challenge of the fact 11:44.120 --> 11:47.600 that our behavior was going to impact the behavior 11:47.600 --> 11:48.960 of that other operator. 11:48.960 --> 11:53.480 And we did a lot of that in relatively naive ways, 11:53.480 --> 11:54.820 but it kind of worked. 11:54.820 --> 11:57.080 Still had to have some kind of solution. 11:57.080 --> 11:59.960 And so where does that, 10 years later, 11:59.960 --> 12:01.520 where does that take us today 12:01.520 --> 12:04.260 from that artificial city construction 12:04.260 --> 12:07.000 to real cities to the urban environment? 12:07.000 --> 12:09.160 Yeah, I think the biggest thing 12:09.160 --> 12:14.160 is that the actors are truly unpredictable. 12:15.720 --> 12:18.800 That most of the time, the drivers on the road, 12:18.800 --> 12:23.800 the other road users are out there behaving well, 12:24.080 --> 12:25.880 but every once in a while they're not. 12:27.080 --> 12:32.080 The variety of other vehicles is, you have all of them. 12:32.080 --> 12:35.840 In terms of behavior, in terms of perception, or both? 12:35.840 --> 12:36.680 Both. 12:38.740 --> 12:40.520 Back then we didn't have to deal with cyclists, 12:40.520 --> 12:42.800 we didn't have to deal with pedestrians, 12:42.800 --> 12:44.800 didn't have to deal with traffic lights. 12:46.260 --> 12:49.400 The scale over which that you have to operate is now 12:49.400 --> 12:51.120 is much larger than the air base 12:51.120 --> 12:52.720 that we were thinking about back then. 12:52.720 --> 12:55.420 So what, easy question, 12:56.280 --> 12:59.720 what do you think is the hardest part about driving? 12:59.720 --> 13:00.560 Easy question. 13:00.560 --> 13:02.560 Yeah, no, I'm joking. 13:02.560 --> 13:07.440 I'm sure nothing really jumps out at you as one thing, 13:07.440 --> 13:12.440 but in the jump from the urban challenge to the real world, 13:12.920 --> 13:15.320 is there something that's a particular, 13:15.320 --> 13:18.480 you foresee as very serious, difficult challenge? 13:18.480 --> 13:21.080 I think the most fundamental difference 13:21.080 --> 13:25.340 is that we're doing it for real. 13:26.760 --> 13:28.960 That in that environment, 13:28.960 --> 13:31.880 it was both a limited complexity environment 13:31.880 --> 13:33.240 because certain actors weren't there, 13:33.240 --> 13:35.380 because the roads were maintained, 13:35.380 --> 13:37.360 there were barriers keeping people separate 13:37.360 --> 13:39.400 from robots at the time, 13:40.840 --> 13:43.300 and it only had to work for 60 miles. 13:43.300 --> 13:46.160 Which, looking at it from 2006, 13:46.160 --> 13:48.960 it had to work for 60 miles, right? 13:48.960 --> 13:50.940 Looking at it from now, 13:51.880 --> 13:53.720 we want things that will go and drive 13:53.720 --> 13:57.160 for half a million miles, 13:57.160 --> 14:00.020 and it's just a different game. 14:00.940 --> 14:03.480 So how important, 14:03.480 --> 14:06.080 you said LiDAR came into the game early on, 14:06.080 --> 14:07.880 and it's really the primary driver 14:07.880 --> 14:10.240 of autonomous vehicles today as a sensor. 14:10.240 --> 14:11.920 So how important is the role of LiDAR 14:11.920 --> 14:14.800 in the sensor suite in the near term? 14:14.800 --> 14:16.740 So I think it's essential. 14:17.920 --> 14:20.480 I believe, but I also believe that cameras are essential, 14:20.480 --> 14:22.120 and I believe the radar is essential. 14:22.120 --> 14:26.280 I think that you really need to use 14:26.280 --> 14:28.720 the composition of data from these different sensors 14:28.720 --> 14:32.640 if you want the thing to really be robust. 14:32.640 --> 14:34.360 The question I wanna ask, 14:34.360 --> 14:35.600 let's see if we can untangle it, 14:35.600 --> 14:39.320 is what are your thoughts on the Elon Musk 14:39.320 --> 14:42.340 provocative statement that LiDAR is a crutch, 14:42.340 --> 14:47.340 that it's a kind of, I guess, growing pains, 14:47.760 --> 14:49.920 and that much of the perception task 14:49.920 --> 14:52.120 can be done with cameras? 14:52.120 --> 14:55.440 So I think it is undeniable 14:55.440 --> 14:59.360 that people walk around without lasers in their foreheads, 14:59.360 --> 15:01.880 and they can get into vehicles and drive them, 15:01.880 --> 15:05.600 and so there's an existence proof 15:05.600 --> 15:09.600 that you can drive using passive vision. 15:10.880 --> 15:12.720 No doubt, can't argue with that. 15:12.720 --> 15:14.680 In terms of sensors, yeah, so there's proof. 15:14.680 --> 15:16.000 Yeah, in terms of sensors, right? 15:16.000 --> 15:20.200 So there's an example that we all go do it, 15:20.200 --> 15:21.380 many of us every day. 15:21.380 --> 15:26.380 In terms of LiDAR being a crutch, sure. 15:28.180 --> 15:33.100 But in the same way that the combustion engine 15:33.100 --> 15:35.260 was a crutch on the path to an electric vehicle, 15:35.260 --> 15:39.300 in the same way that any technology ultimately gets 15:40.840 --> 15:44.380 replaced by some superior technology in the future, 15:44.380 --> 15:47.740 and really the way that I look at this 15:47.740 --> 15:51.460 is that the way we get around on the ground, 15:51.460 --> 15:53.920 the way that we use transportation is broken, 15:55.280 --> 15:59.740 and that we have this, I think the number I saw this morning, 15:59.740 --> 16:04.060 37,000 Americans killed last year on our roads, 16:04.060 --> 16:05.380 and that's just not acceptable. 16:05.380 --> 16:09.460 And so any technology that we can bring to bear 16:09.460 --> 16:12.860 that accelerates this self driving technology 16:12.860 --> 16:14.640 coming to market and saving lives 16:14.640 --> 16:17.320 is technology we should be using. 16:18.280 --> 16:20.840 And it feels just arbitrary to say, 16:20.840 --> 16:25.840 well, I'm not okay with using lasers 16:26.240 --> 16:27.820 because that's whatever, 16:27.820 --> 16:30.720 but I am okay with using an eight megapixel camera 16:30.720 --> 16:32.880 or a 16 megapixel camera. 16:32.880 --> 16:34.640 These are just bits of technology, 16:34.640 --> 16:36.360 and we should be taking the best technology 16:36.360 --> 16:41.360 from the tool bin that allows us to go and solve a problem. 16:41.360 --> 16:45.160 The question I often talk to, well, obviously you do as well, 16:45.160 --> 16:48.280 to sort of automotive companies, 16:48.280 --> 16:51.360 and if there's one word that comes up more often 16:51.360 --> 16:55.280 than anything, it's cost, and trying to drive costs down. 16:55.280 --> 17:00.280 So while it's true that it's a tragic number, the 37,000, 17:01.400 --> 17:04.880 the question is, and I'm not the one asking this question 17:04.880 --> 17:05.820 because I hate this question, 17:05.820 --> 17:09.960 but we want to find the cheapest sensor suite 17:09.960 --> 17:13.280 that creates a safe vehicle. 17:13.280 --> 17:18.220 So in that uncomfortable trade off, 17:18.220 --> 17:23.220 do you foresee LiDAR coming down in cost in the future, 17:23.680 --> 17:26.680 or do you see a day where level four autonomy 17:26.680 --> 17:29.880 is possible without LiDAR? 17:29.880 --> 17:32.880 I see both of those, but it's really a matter of time. 17:32.880 --> 17:36.040 And I think really, maybe I would talk to the question 17:36.040 --> 17:37.840 you asked about the cheapest sensor. 17:37.840 --> 17:40.360 I don't think that's actually what you want. 17:40.360 --> 17:45.360 What you want is a sensor suite that is economically viable. 17:45.680 --> 17:49.440 And then after that, everything is about margin 17:49.440 --> 17:52.120 and driving costs out of the system. 17:52.120 --> 17:55.360 What you also want is a sensor suite that works. 17:55.360 --> 17:58.200 And so it's great to tell a story about 17:59.600 --> 18:03.260 how it would be better to have a self driving system 18:03.260 --> 18:08.040 with a $50 sensor instead of a $500 sensor. 18:08.040 --> 18:10.520 But if the $500 sensor makes it work 18:10.520 --> 18:14.760 and the $50 sensor doesn't work, who cares? 18:15.680 --> 18:20.020 So long as you can actually have an economic opportunity, 18:20.020 --> 18:21.520 there's an economic opportunity there. 18:21.520 --> 18:23.760 And the economic opportunity is important 18:23.760 --> 18:27.760 because that's how you actually have a sustainable business 18:27.760 --> 18:31.120 and that's how you can actually see this come to scale 18:31.120 --> 18:32.400 and be out in the world. 18:32.400 --> 18:34.780 And so when I look at LiDAR, 18:35.960 --> 18:38.880 I see a technology that has no underlying 18:38.880 --> 18:42.420 fundamentally expense to it, fundamental expense to it. 18:42.420 --> 18:46.080 It's going to be more expensive than an imager 18:46.080 --> 18:50.360 because CMOS processes or FAP processes 18:51.360 --> 18:55.080 are dramatically more scalable than mechanical processes. 18:56.200 --> 18:58.320 But we still should be able to drive costs down 18:58.320 --> 19:00.120 substantially on that side. 19:00.120 --> 19:04.840 And then I also do think that with the right business model 19:05.880 --> 19:07.560 you can absorb more, 19:07.560 --> 19:09.480 certainly more cost on the bill of materials. 19:09.480 --> 19:12.600 Yeah, if the sensor suite works, extra value is provided, 19:12.600 --> 19:15.480 thereby you don't need to drive costs down to zero. 19:15.480 --> 19:17.100 It's the basic economics. 19:17.100 --> 19:18.820 You've talked about your intuition 19:18.820 --> 19:22.200 that level two autonomy is problematic 19:22.200 --> 19:25.920 because of the human factor of vigilance, 19:25.920 --> 19:28.040 decrement, complacency, over trust and so on, 19:28.040 --> 19:29.600 just us being human. 19:29.600 --> 19:31.120 We over trust the system, 19:31.120 --> 19:34.240 we start doing even more so partaking 19:34.240 --> 19:37.180 in the secondary activities like smartphones and so on. 19:38.680 --> 19:43.000 Have your views evolved on this point in either direction? 19:43.000 --> 19:44.800 Can you speak to it? 19:44.800 --> 19:47.480 So, and I want to be really careful 19:47.480 --> 19:50.380 because sometimes this gets twisted in a way 19:50.380 --> 19:53.040 that I certainly didn't intend. 19:53.040 --> 19:58.040 So active safety systems are a really important technology 19:58.040 --> 20:00.680 that we should be pursuing and integrating into vehicles. 20:02.080 --> 20:04.280 And there's an opportunity in the near term 20:04.280 --> 20:06.520 to reduce accidents, reduce fatalities, 20:06.520 --> 20:10.320 and we should be pushing on that. 20:11.960 --> 20:14.680 Level two systems are systems 20:14.680 --> 20:18.080 where the vehicle is controlling two axes. 20:18.080 --> 20:21.720 So braking and throttle slash steering. 20:23.480 --> 20:25.680 And I think there are variants of level two systems 20:25.680 --> 20:27.280 that are supporting the driver. 20:27.280 --> 20:31.080 That absolutely we should encourage to be out there. 20:31.080 --> 20:32.880 Where I think there's a real challenge 20:32.880 --> 20:37.640 is in the human factors part around this 20:37.640 --> 20:41.240 and the misconception from the public 20:41.240 --> 20:43.600 around the capability set that that enables 20:43.600 --> 20:45.640 and the trust that they should have in it. 20:46.640 --> 20:50.000 And that is where I kind of, 20:50.000 --> 20:52.920 I'm actually incrementally more concerned 20:52.920 --> 20:54.440 around level three systems 20:54.440 --> 20:58.440 and how exactly a level two system is marketed and delivered 20:58.440 --> 21:01.840 and how much effort people have put into those human factors. 21:01.840 --> 21:05.640 So I still believe several things around this. 21:05.640 --> 21:09.440 One is people will overtrust the technology. 21:09.440 --> 21:11.440 We've seen over the last few weeks 21:11.440 --> 21:14.040 a spate of people sleeping in their Tesla. 21:14.920 --> 21:19.920 I watched an episode last night of Trevor Noah 21:19.920 --> 21:23.920 talking about this and him, 21:23.920 --> 21:26.720 this is a smart guy who has a lot of resources 21:26.720 --> 21:30.720 at his disposal describing a Tesla as a self driving car 21:30.720 --> 21:33.480 and that why shouldn't people be sleeping in their Tesla? 21:33.480 --> 21:36.560 And it's like, well, because it's not a self driving car 21:36.560 --> 21:38.840 and it is not intended to be 21:38.840 --> 21:43.840 and these people will almost certainly die at some point 21:46.400 --> 21:48.040 or hurt other people. 21:48.040 --> 21:50.080 And so we need to really be thoughtful 21:50.080 --> 21:51.840 about how that technology is described 21:51.840 --> 21:53.280 and brought to market. 21:54.240 --> 21:59.240 I also think that because of the economic challenges 21:59.240 --> 22:01.240 we were just talking about, 22:01.240 --> 22:05.160 that these level two driver assistance systems, 22:05.160 --> 22:07.280 that technology path will diverge 22:07.280 --> 22:10.200 from the technology path that we need to be on 22:10.200 --> 22:14.080 to actually deliver truly self driving vehicles, 22:14.080 --> 22:16.920 ones where you can get in it and drive it. 22:16.920 --> 22:20.800 Can get in it and sleep and have the equivalent 22:20.800 --> 22:24.680 or better safety than a human driver behind the wheel. 22:24.680 --> 22:27.520 Because again, the economics are very different 22:28.480 --> 22:30.880 in those two worlds and so that leads 22:30.880 --> 22:32.800 to divergent technology. 22:32.800 --> 22:34.680 So you just don't see the economics 22:34.680 --> 22:38.560 of gradually increasing from level two 22:38.560 --> 22:41.600 and doing so quickly enough 22:41.600 --> 22:44.480 to where it doesn't cause safety, critical safety concerns. 22:44.480 --> 22:47.680 You believe that it needs to diverge at this point 22:48.680 --> 22:50.800 into basically different routes. 22:50.800 --> 22:55.560 And really that comes back to what are those L2 22:55.560 --> 22:57.080 and L1 systems doing? 22:57.080 --> 22:59.840 And they are driver assistance functions 22:59.840 --> 23:04.400 where the people that are marketing that responsibly 23:04.400 --> 23:08.000 are being very clear and putting human factors in place 23:08.000 --> 23:12.440 such that the driver is actually responsible for the vehicle 23:12.440 --> 23:15.160 and that the technology is there to support the driver. 23:15.160 --> 23:19.880 And the safety cases that are built around those 23:19.880 --> 23:24.040 are dependent on that driver attention and attentiveness. 23:24.040 --> 23:28.000 And at that point, you can kind of give up 23:29.160 --> 23:31.240 to some degree for economic reasons, 23:31.240 --> 23:33.480 you can give up on say false negatives. 23:34.800 --> 23:36.200 And the way to think about this 23:36.200 --> 23:39.320 is for a four collision mitigation braking system, 23:39.320 --> 23:43.960 if it half the times the driver missed a vehicle 23:43.960 --> 23:46.080 in front of it, it hit the brakes 23:46.080 --> 23:47.680 and brought the vehicle to a stop, 23:47.680 --> 23:51.640 that would be an incredible, incredible advance 23:51.640 --> 23:53.040 in safety on our roads, right? 23:53.040 --> 23:55.000 That would be equivalent to seat belts. 23:55.000 --> 23:56.600 But it would mean that if that vehicle 23:56.600 --> 23:59.440 wasn't being monitored, it would hit one out of two cars. 24:00.600 --> 24:05.120 And so economically, that's a perfectly good solution 24:05.120 --> 24:06.280 for a driver assistance system. 24:06.280 --> 24:07.240 What you should do at that point, 24:07.240 --> 24:09.240 if you can get it to work 50% of the time, 24:09.240 --> 24:10.520 is drive the cost out of that 24:10.520 --> 24:13.320 so you can get it on as many vehicles as possible. 24:13.320 --> 24:14.760 But driving the cost out of it 24:14.760 --> 24:18.800 doesn't drive up performance on the false negative case. 24:18.800 --> 24:21.440 And so you'll continue to not have a technology 24:21.440 --> 24:25.680 that could really be available for a self driven vehicle. 24:25.680 --> 24:28.440 So clearly the communication, 24:28.440 --> 24:31.600 and this probably applies to all four vehicles as well, 24:31.600 --> 24:34.440 the marketing and communication 24:34.440 --> 24:37.040 of what the technology is actually capable of, 24:37.040 --> 24:38.400 how hard it is, how easy it is, 24:38.400 --> 24:41.000 all that kind of stuff is highly problematic. 24:41.000 --> 24:45.640 So say everybody in the world was perfectly communicated 24:45.640 --> 24:48.400 and were made to be completely aware 24:48.400 --> 24:50.000 of every single technology out there, 24:50.000 --> 24:52.840 what it's able to do. 24:52.840 --> 24:54.120 What's your intuition? 24:54.120 --> 24:56.880 And now we're maybe getting into philosophical ground. 24:56.880 --> 25:00.000 Is it possible to have a level two vehicle 25:00.000 --> 25:03.280 where we don't over trust it? 25:04.680 --> 25:05.800 I don't think so. 25:05.800 --> 25:10.800 If people truly understood the risks and internalized it, 25:11.160 --> 25:14.320 then sure, you could do that safely. 25:14.320 --> 25:16.160 But that's a world that doesn't exist. 25:16.160 --> 25:17.520 The people are going to, 25:18.720 --> 25:20.760 if the facts are put in front of them, 25:20.760 --> 25:24.440 they're gonna then combine that with their experience. 25:24.440 --> 25:28.360 And let's say they're using an L2 system 25:28.360 --> 25:30.800 and they go up and down the 101 every day 25:30.800 --> 25:32.720 and they do that for a month. 25:32.720 --> 25:36.200 And it just worked every day for a month. 25:36.200 --> 25:39.000 Like that's pretty compelling at that point, 25:39.000 --> 25:41.800 just even if you know the statistics, 25:41.800 --> 25:43.400 you're like, well, I don't know, 25:43.400 --> 25:44.760 maybe there's something funny about those. 25:44.760 --> 25:46.920 Maybe they're driving in difficult places. 25:46.920 --> 25:49.840 Like I've seen it with my own eyes, it works. 25:49.840 --> 25:52.400 And the problem is that that sample size that they have, 25:52.400 --> 25:53.880 so it's 30 miles up and down, 25:53.880 --> 25:56.360 so 60 miles times 30 days, 25:56.360 --> 25:58.720 so 60, 180, 1,800 miles. 25:58.720 --> 26:03.280 Like that's a drop in the bucket 26:03.280 --> 26:07.640 compared to the, what, 85 million miles between fatalities. 26:07.640 --> 26:11.400 And so they don't really have a true estimate 26:11.400 --> 26:14.440 based on their personal experience of the real risks, 26:14.440 --> 26:15.640 but they're gonna trust it anyway, 26:15.640 --> 26:16.480 because it's hard not to. 26:16.480 --> 26:18.640 It worked for a month, what's gonna change? 26:18.640 --> 26:21.640 So even if you start a perfect understanding of the system, 26:21.640 --> 26:24.160 your own experience will make it drift. 26:24.160 --> 26:25.920 I mean, that's a big concern. 26:25.920 --> 26:28.160 Over a year, over two years even, 26:28.160 --> 26:29.440 it doesn't have to be months. 26:29.440 --> 26:32.920 And I think that as this technology moves 26:32.920 --> 26:37.760 from what I would say is kind of the more technology savvy 26:37.760 --> 26:40.880 ownership group to the mass market, 26:42.640 --> 26:44.600 you may be able to have some of those folks 26:44.600 --> 26:46.280 who are really familiar with technology, 26:46.280 --> 26:48.840 they may be able to internalize it better. 26:48.840 --> 26:50.800 And your kind of immunization 26:50.800 --> 26:53.360 against this kind of false risk assessment 26:53.360 --> 26:54.280 might last longer, 26:54.280 --> 26:58.680 but as folks who aren't as savvy about that 26:58.680 --> 27:00.880 read the material and they compare that 27:00.880 --> 27:02.160 to their personal experience, 27:02.160 --> 27:07.160 I think there it's going to move more quickly. 27:08.160 --> 27:11.280 So your work, the program that you've created at Google 27:11.280 --> 27:16.280 and now at Aurora is focused more on the second path 27:16.600 --> 27:18.480 of creating full autonomy. 27:18.480 --> 27:20.880 So it's such a fascinating, 27:20.880 --> 27:24.560 I think it's one of the most interesting AI problems 27:24.560 --> 27:25.600 of the century, right? 27:25.600 --> 27:28.280 It's, I just talked to a lot of people, 27:28.280 --> 27:29.440 just regular people, I don't know, 27:29.440 --> 27:31.720 my mom, about autonomous vehicles, 27:31.720 --> 27:34.520 and you begin to grapple with ideas 27:34.520 --> 27:38.080 of giving your life control over to a machine. 27:38.080 --> 27:40.040 It's philosophically interesting, 27:40.040 --> 27:41.760 it's practically interesting. 27:41.760 --> 27:43.720 So let's talk about safety. 27:43.720 --> 27:46.240 How do you think we demonstrate, 27:46.240 --> 27:47.880 you've spoken about metrics in the past, 27:47.880 --> 27:51.880 how do you think we demonstrate to the world 27:51.880 --> 27:56.160 that an autonomous vehicle, an Aurora system is safe? 27:56.160 --> 27:57.320 This is one where it's difficult 27:57.320 --> 27:59.280 because there isn't a soundbite answer. 27:59.280 --> 28:04.280 That we have to show a combination of work 28:05.960 --> 28:08.360 that was done diligently and thoughtfully, 28:08.360 --> 28:10.840 and this is where something like a functional safety process 28:10.840 --> 28:11.680 is part of that. 28:11.680 --> 28:14.360 It's like here's the way we did the work, 28:15.280 --> 28:17.160 that means that we were very thorough. 28:17.160 --> 28:20.040 So if you believe that what we said 28:20.040 --> 28:21.440 about this is the way we did it, 28:21.440 --> 28:22.720 then you can have some confidence 28:22.720 --> 28:25.200 that we were thorough in the engineering work 28:25.200 --> 28:26.920 we put into the system. 28:26.920 --> 28:28.920 And then on top of that, 28:28.920 --> 28:32.000 to kind of demonstrate that we weren't just thorough, 28:32.000 --> 28:33.800 we were actually good at what we did, 28:35.280 --> 28:38.200 there'll be a kind of a collection of evidence 28:38.200 --> 28:40.440 in terms of demonstrating that the capabilities 28:40.440 --> 28:42.920 worked the way we thought they did, 28:42.920 --> 28:45.320 statistically and to whatever degree 28:45.320 --> 28:47.280 we can demonstrate that, 28:48.160 --> 28:50.320 both in some combination of simulations, 28:50.320 --> 28:53.080 some combination of unit testing 28:53.080 --> 28:54.640 and decomposition testing, 28:54.640 --> 28:57.000 and then some part of it will be on road data. 28:58.160 --> 29:02.680 And I think the way we'll ultimately 29:02.680 --> 29:04.000 convey this to the public 29:04.000 --> 29:06.760 is there'll be clearly some conversation 29:06.760 --> 29:08.200 with the public about it, 29:08.200 --> 29:12.040 but we'll kind of invoke the kind of the trusted nodes 29:12.040 --> 29:13.880 and that we'll spend more time 29:13.880 --> 29:17.280 being able to go into more depth with folks like NHTSA 29:17.280 --> 29:19.720 and other federal and state regulatory bodies 29:19.720 --> 29:22.080 and kind of given that they are 29:22.080 --> 29:25.200 operating in the public interest and they're trusted, 29:26.240 --> 29:28.640 that if we can show enough work to them 29:28.640 --> 29:30.000 that they're convinced, 29:30.000 --> 29:33.800 then I think we're in a pretty good place. 29:33.800 --> 29:35.000 That means you work with people 29:35.000 --> 29:36.920 that are essentially experts at safety 29:36.920 --> 29:39.000 to try to discuss and show. 29:39.000 --> 29:41.720 Do you think, the answer's probably no, 29:41.720 --> 29:42.920 but just in case, 29:42.920 --> 29:44.360 do you think there exists a metric? 29:44.360 --> 29:46.320 So currently people have been using 29:46.320 --> 29:48.200 number of disengagements. 29:48.200 --> 29:50.120 And it quickly turns into a marketing scheme 29:50.120 --> 29:54.280 to sort of you alter the experiments you run to adjust. 29:54.280 --> 29:56.280 I think you've spoken that you don't like. 29:56.280 --> 29:57.120 Don't love it. 29:57.120 --> 29:59.680 No, in fact, I was on the record telling DMV 29:59.680 --> 30:01.960 that I thought this was not a great metric. 30:01.960 --> 30:05.280 Do you think it's possible to create a metric, 30:05.280 --> 30:09.440 a number that could demonstrate safety 30:09.440 --> 30:12.320 outside of fatalities? 30:12.320 --> 30:13.440 So I do. 30:13.440 --> 30:16.560 And I think that it won't be just one number. 30:17.600 --> 30:21.280 So as we are internally grappling with this, 30:21.280 --> 30:23.560 and at some point we'll be able to talk 30:23.560 --> 30:25.040 more publicly about it, 30:25.040 --> 30:28.520 is how do we think about human performance 30:28.520 --> 30:29.840 in different tasks, 30:29.840 --> 30:32.160 say detecting traffic lights 30:32.160 --> 30:36.200 or safely making a left turn across traffic? 30:37.680 --> 30:40.080 And what do we think the failure rates are 30:40.080 --> 30:42.520 for those different capabilities for people? 30:42.520 --> 30:44.760 And then demonstrating to ourselves 30:44.760 --> 30:48.480 and then ultimately folks in the regulatory role 30:48.480 --> 30:50.760 and then ultimately the public 30:50.760 --> 30:52.400 that we have confidence that our system 30:52.400 --> 30:54.760 will work better than that. 30:54.760 --> 30:57.040 And so these individual metrics 30:57.040 --> 31:00.720 will kind of tell a compelling story ultimately. 31:01.760 --> 31:03.920 I do think at the end of the day 31:03.920 --> 31:06.640 what we care about in terms of safety 31:06.640 --> 31:11.320 is life saved and injuries reduced. 31:12.160 --> 31:15.280 And then ultimately kind of casualty dollars 31:16.440 --> 31:19.360 that people aren't having to pay to get their car fixed. 31:19.360 --> 31:22.680 And I do think that in aviation 31:22.680 --> 31:25.880 they look at a kind of an event pyramid 31:25.880 --> 31:28.600 where a crash is at the top of that 31:28.600 --> 31:30.440 and that's the worst event obviously 31:30.440 --> 31:34.240 and then there's injuries and near miss events and whatnot 31:34.240 --> 31:37.320 and violation of operating procedures 31:37.320 --> 31:40.160 and you kind of build a statistical model 31:40.160 --> 31:44.440 of the relevance of the low severity things 31:44.440 --> 31:45.280 or the high severity things. 31:45.280 --> 31:46.120 And I think that's something 31:46.120 --> 31:48.200 where we'll be able to look at as well 31:48.200 --> 31:51.840 because an event per 85 million miles 31:51.840 --> 31:54.440 is statistically a difficult thing 31:54.440 --> 31:56.800 even at the scale of the U.S. 31:56.800 --> 31:59.360 to kind of compare directly. 31:59.360 --> 32:02.240 And that event fatality that's connected 32:02.240 --> 32:07.240 to an autonomous vehicle is significantly 32:07.440 --> 32:09.160 at least currently magnified 32:09.160 --> 32:12.320 in the amount of attention it gets. 32:12.320 --> 32:15.080 So that speaks to public perception. 32:15.080 --> 32:16.720 I think the most popular topic 32:16.720 --> 32:19.480 about autonomous vehicles in the public 32:19.480 --> 32:23.080 is the trolley problem formulation, right? 32:23.080 --> 32:27.000 Which has, let's not get into that too much 32:27.000 --> 32:29.600 but is misguided in many ways. 32:29.600 --> 32:32.320 But it speaks to the fact that people are grappling 32:32.320 --> 32:36.160 with this idea of giving control over to a machine. 32:36.160 --> 32:41.160 So how do you win the hearts and minds of the people 32:41.560 --> 32:44.600 that autonomy is something that could be a part 32:44.600 --> 32:45.520 of their lives? 32:45.520 --> 32:47.640 I think you let them experience it, right? 32:47.640 --> 32:50.440 I think it's right. 32:50.440 --> 32:52.800 I think people should be skeptical. 32:52.800 --> 32:55.680 I think people should ask questions. 32:55.680 --> 32:57.000 I think they should doubt 32:57.000 --> 33:00.120 because this is something new and different. 33:00.120 --> 33:01.880 They haven't touched it yet. 33:01.880 --> 33:03.640 And I think that's perfectly reasonable. 33:03.640 --> 33:07.320 And, but at the same time, 33:07.320 --> 33:09.320 it's clear there's an opportunity to make the road safer. 33:09.320 --> 33:12.440 It's clear that we can improve access to mobility. 33:12.440 --> 33:14.960 It's clear that we can reduce the cost of mobility. 33:16.640 --> 33:19.480 And that once people try that 33:19.480 --> 33:22.720 and understand that it's safe 33:22.720 --> 33:24.440 and are able to use in their daily lives, 33:24.440 --> 33:25.280 I think it's one of these things 33:25.280 --> 33:28.040 that will just be obvious. 33:28.040 --> 33:32.240 And I've seen this practically in demonstrations 33:32.240 --> 33:35.560 that I've given where I've had people come in 33:35.560 --> 33:38.840 and they're very skeptical. 33:38.840 --> 33:40.440 Again, in a vehicle, my favorite one 33:40.440 --> 33:42.560 is taking somebody out on the freeway 33:42.560 --> 33:46.000 and we're on the 101 driving at 65 miles an hour. 33:46.000 --> 33:48.400 And after 10 minutes, they kind of turn and ask, 33:48.400 --> 33:49.480 is that all it does? 33:49.480 --> 33:52.080 And you're like, it's a self driving car. 33:52.080 --> 33:54.840 I'm not sure exactly what you thought it would do, right? 33:54.840 --> 33:57.920 But it becomes mundane, 33:58.840 --> 34:01.480 which is exactly what you want a technology 34:01.480 --> 34:02.720 like this to be, right? 34:02.720 --> 34:07.280 We don't really, when I turn the light switch on in here, 34:07.280 --> 34:12.000 I don't think about the complexity of those electrons 34:12.000 --> 34:14.200 being pushed down a wire from wherever it was 34:14.200 --> 34:15.240 and being generated. 34:15.240 --> 34:19.080 It's like, I just get annoyed if it doesn't work, right? 34:19.080 --> 34:21.400 And what I value is the fact 34:21.400 --> 34:23.080 that I can do other things in this space. 34:23.080 --> 34:24.560 I can see my colleagues. 34:24.560 --> 34:26.160 I can read stuff on a paper. 34:26.160 --> 34:29.200 I can not be afraid of the dark. 34:30.360 --> 34:33.320 And I think that's what we want this technology to be like 34:33.320 --> 34:34.640 is it's in the background 34:34.640 --> 34:37.120 and people get to have those life experiences 34:37.120 --> 34:38.440 and do so safely. 34:38.440 --> 34:42.160 So putting this technology in the hands of people 34:42.160 --> 34:46.320 speaks to scale of deployment, right? 34:46.320 --> 34:50.880 So what do you think the dreaded question about the future 34:50.880 --> 34:53.560 because nobody can predict the future, 34:53.560 --> 34:57.240 but just maybe speak poetically 34:57.240 --> 35:00.880 about when do you think we'll see a large scale deployment 35:00.880 --> 35:05.880 of autonomous vehicles, 10,000, those kinds of numbers? 35:06.680 --> 35:08.240 We'll see that within 10 years. 35:09.240 --> 35:10.240 I'm pretty confident. 35:14.040 --> 35:16.040 What's an impressive scale? 35:16.040 --> 35:19.200 What moment, so you've done the DARPA challenge 35:19.200 --> 35:20.440 where there's one vehicle. 35:20.440 --> 35:23.960 At which moment does it become, wow, this is serious scale? 35:23.960 --> 35:26.520 So I think the moment it gets serious 35:26.520 --> 35:31.520 is when we really do have a driverless vehicle 35:32.240 --> 35:34.120 operating on public roads 35:35.000 --> 35:37.960 and that we can do that kind of continuously. 35:37.960 --> 35:38.880 Without a safety driver. 35:38.880 --> 35:40.440 Without a safety driver in the vehicle. 35:40.440 --> 35:41.560 I think at that moment, 35:41.560 --> 35:44.400 we've kind of crossed the zero to one threshold. 35:45.920 --> 35:50.200 And then it is about how do we continue to scale that? 35:50.200 --> 35:53.960 How do we build the right business models? 35:53.960 --> 35:56.320 How do we build the right customer experience around it 35:56.320 --> 35:59.960 so that it is actually a useful product out in the world? 36:00.960 --> 36:03.600 And I think that is really, 36:03.600 --> 36:05.920 at that point it moves from 36:05.920 --> 36:09.200 what is this kind of mixed science engineering project 36:09.200 --> 36:12.360 into engineering and commercialization 36:12.360 --> 36:15.840 and really starting to deliver on the value 36:15.840 --> 36:20.680 that we all see here and actually making that real in the world. 36:20.680 --> 36:22.240 What do you think that deployment looks like? 36:22.240 --> 36:26.440 Where do we first see the inkling of no safety driver, 36:26.440 --> 36:28.600 one or two cars here and there? 36:28.600 --> 36:29.800 Is it on the highway? 36:29.800 --> 36:33.160 Is it in specific routes in the urban environment? 36:33.160 --> 36:36.920 I think it's gonna be urban, suburban type environments. 36:37.880 --> 36:41.560 Yeah, with Aurora, when we thought about how to tackle this, 36:41.560 --> 36:45.040 it was kind of in vogue to think about trucking 36:46.040 --> 36:47.800 as opposed to urban driving. 36:47.800 --> 36:51.280 And again, the human intuition around this 36:51.280 --> 36:55.400 is that freeways are easier to drive on 36:57.080 --> 36:59.280 because everybody's kind of going in the same direction 36:59.280 --> 37:01.560 and lanes are a little wider, et cetera. 37:01.560 --> 37:03.320 And I think that that intuition is pretty good, 37:03.320 --> 37:06.040 except we don't really care about most of the time. 37:06.040 --> 37:08.400 We care about all of the time. 37:08.400 --> 37:10.880 And when you're driving on a freeway with a truck, 37:10.880 --> 37:13.440 say 70 miles an hour, 37:14.600 --> 37:16.240 and you've got 70,000 pound load with you, 37:16.240 --> 37:18.880 that's just an incredible amount of kinetic energy. 37:18.880 --> 37:21.440 And so when that goes wrong, it goes really wrong. 37:22.640 --> 37:27.640 And those challenges that you see occur more rarely, 37:27.800 --> 37:31.120 so you don't get to learn as quickly. 37:31.120 --> 37:34.720 And they're incrementally more difficult than urban driving, 37:34.720 --> 37:37.440 but they're not easier than urban driving. 37:37.440 --> 37:41.640 And so I think this happens in moderate speed 37:41.640 --> 37:45.280 urban environments because if two vehicles crash 37:45.280 --> 37:48.120 at 25 miles per hour, it's not good, 37:48.120 --> 37:50.120 but probably everybody walks away. 37:51.080 --> 37:53.720 And those events where there's the possibility 37:53.720 --> 37:55.800 for that occurring happen frequently. 37:55.800 --> 37:58.000 So we get to learn more rapidly. 37:58.000 --> 38:01.360 We get to do that with lower risk for everyone. 38:02.520 --> 38:04.360 And then we can deliver value to people 38:04.360 --> 38:05.880 that need to get from one place to another. 38:05.880 --> 38:08.160 And once we've got that solved, 38:08.160 --> 38:11.320 then the freeway driving part of this just falls out. 38:11.320 --> 38:13.080 But we're able to learn more safely, 38:13.080 --> 38:15.200 more quickly in the urban environment. 38:15.200 --> 38:18.760 So 10 years and then scale 20, 30 year, 38:18.760 --> 38:22.040 who knows if a sufficiently compelling experience 38:22.040 --> 38:24.400 is created, it could be faster and slower. 38:24.400 --> 38:27.160 Do you think there could be breakthroughs 38:27.160 --> 38:29.920 and what kind of breakthroughs might there be 38:29.920 --> 38:32.400 that completely change that timeline? 38:32.400 --> 38:35.360 Again, not only am I asking you to predict the future, 38:35.360 --> 38:37.360 I'm asking you to predict breakthroughs 38:37.360 --> 38:38.360 that haven't happened yet. 38:38.360 --> 38:41.440 So what's the, I think another way to ask that 38:41.440 --> 38:44.320 would be if I could wave a magic wand, 38:44.320 --> 38:46.720 what part of the system would I make work today 38:46.720 --> 38:49.480 to accelerate it as quickly as possible? 38:52.120 --> 38:54.200 Don't say infrastructure, please don't say infrastructure. 38:54.200 --> 38:56.320 No, it's definitely not infrastructure. 38:56.320 --> 39:00.600 It's really that perception forecasting capability. 39:00.600 --> 39:04.840 So if tomorrow you could give me a perfect model 39:04.840 --> 39:06.960 of what's happened, what is happening 39:06.960 --> 39:09.200 and what will happen for the next five seconds 39:10.360 --> 39:13.040 around a vehicle on the roadway, 39:13.040 --> 39:15.360 that would accelerate things pretty dramatically. 39:15.360 --> 39:17.600 Are you, in terms of staying up at night, 39:17.600 --> 39:21.760 are you mostly bothered by cars, pedestrians or cyclists? 39:21.760 --> 39:25.960 So I worry most about the vulnerable road users 39:25.960 --> 39:28.480 about the combination of cyclists and cars, right? 39:28.480 --> 39:31.960 Or cyclists and pedestrians because they're not in armor. 39:31.960 --> 39:36.480 The cars, they're bigger, they've got protection 39:36.480 --> 39:39.440 for the people and so the ultimate risk is lower there. 39:41.080 --> 39:43.240 Whereas a pedestrian or a cyclist, 39:43.240 --> 39:46.480 they're out on the road and they don't have any protection 39:46.480 --> 39:49.720 and so we need to pay extra attention to that. 39:49.720 --> 39:54.120 Do you think about a very difficult technical challenge 39:55.720 --> 39:58.520 of the fact that pedestrians, 39:58.520 --> 40:00.240 if you try to protect pedestrians 40:00.240 --> 40:04.560 by being careful and slow, they'll take advantage of that. 40:04.560 --> 40:09.040 So the game theoretic dance, does that worry you 40:09.040 --> 40:12.480 of how, from a technical perspective, how we solve that? 40:12.480 --> 40:14.560 Because as humans, the way we solve that 40:14.560 --> 40:17.240 is kind of nudge our way through the pedestrians 40:17.240 --> 40:20.000 which doesn't feel, from a technical perspective, 40:20.000 --> 40:22.300 as a appropriate algorithm. 40:23.200 --> 40:25.920 But do you think about how we solve that problem? 40:25.920 --> 40:30.920 Yeah, I think there's two different concepts there. 40:31.360 --> 40:35.820 So one is, am I worried that because these vehicles 40:35.820 --> 40:37.600 are self driving, people will kind of step in the road 40:37.600 --> 40:38.640 and take advantage of them? 40:38.640 --> 40:43.640 And I've heard this and I don't really believe it 40:43.760 --> 40:45.960 because if I'm driving down the road 40:45.960 --> 40:48.400 and somebody steps in front of me, I'm going to stop. 40:50.600 --> 40:53.660 Even if I'm annoyed, I'm not gonna just drive 40:53.660 --> 40:56.400 through a person stood in the road. 40:56.400 --> 41:00.400 And so I think today people can take advantage of this 41:00.400 --> 41:02.560 and you do see some people do it. 41:02.560 --> 41:04.180 I guess there's an incremental risk 41:04.180 --> 41:05.880 because maybe they have lower confidence 41:05.880 --> 41:07.720 that I'm gonna see them than they might have 41:07.720 --> 41:10.400 for an automated vehicle and so maybe that shifts 41:10.400 --> 41:12.040 it a little bit. 41:12.040 --> 41:14.360 But I think people don't wanna get hit by cars. 41:14.360 --> 41:17.080 And so I think that I'm not that worried 41:17.080 --> 41:18.760 about people walking out of the 101 41:18.760 --> 41:23.760 and creating chaos more than they would today. 41:24.400 --> 41:27.040 Regarding kind of the nudging through a big stream 41:27.040 --> 41:30.040 of pedestrians leaving a concert or something, 41:30.040 --> 41:33.520 I think that is further down the technology pipeline. 41:33.520 --> 41:36.960 I think that you're right, that's tricky. 41:36.960 --> 41:38.620 I don't think it's necessarily, 41:40.360 --> 41:43.600 I think the algorithm people use for this is pretty simple. 41:43.600 --> 41:44.800 It's kind of just move forward slowly 41:44.800 --> 41:46.800 and if somebody's really close then stop. 41:46.800 --> 41:50.880 And I think that that probably can be replicated 41:50.880 --> 41:54.040 pretty easily and particularly given that 41:54.040 --> 41:55.720 you don't do this at 30 miles an hour, 41:55.720 --> 41:59.080 you do it at one, that even in those situations 41:59.080 --> 42:01.200 the risk is relatively minimal. 42:01.200 --> 42:03.640 But it's not something we're thinking about 42:03.640 --> 42:04.560 in any serious way. 42:04.560 --> 42:07.920 And probably that's less an algorithm problem 42:07.920 --> 42:10.160 and more creating a human experience. 42:10.160 --> 42:14.300 So the HCI people that create a visual display 42:14.300 --> 42:16.260 that you're pleasantly as a pedestrian 42:16.260 --> 42:20.760 nudged out of the way, that's an experience problem, 42:20.760 --> 42:22.000 not an algorithm problem. 42:22.880 --> 42:25.480 Who's the main competitor to Aurora today? 42:25.480 --> 42:28.640 And how do you outcompete them in the long run? 42:28.640 --> 42:31.200 So we really focus a lot on what we're doing here. 42:31.200 --> 42:34.480 I think that, I've said this a few times, 42:34.480 --> 42:37.960 that this is a huge difficult problem 42:37.960 --> 42:40.320 and it's great that a bunch of companies are tackling it 42:40.320 --> 42:42.320 because I think it's so important for society 42:42.320 --> 42:43.800 that somebody gets there. 42:43.800 --> 42:48.800 So we don't spend a whole lot of time 42:49.120 --> 42:51.600 thinking tactically about who's out there 42:51.600 --> 42:55.240 and how do we beat that person individually. 42:55.240 --> 42:58.720 What are we trying to do to go faster ultimately? 42:59.760 --> 43:02.640 Well part of it is the leadership team we have 43:02.640 --> 43:04.200 has got pretty tremendous experience. 43:04.200 --> 43:06.440 And so we kind of understand the landscape 43:06.440 --> 43:09.160 and understand where the cul de sacs are to some degree 43:09.160 --> 43:10.980 and we try and avoid those. 43:10.980 --> 43:14.260 I think there's a part of it, 43:14.260 --> 43:16.260 just this great team we've built. 43:16.260 --> 43:19.080 People, this is a technology and a company 43:19.080 --> 43:22.320 that people believe in the mission of 43:22.320 --> 43:23.740 and so it allows us to attract 43:23.740 --> 43:25.740 just awesome people to go work. 43:26.800 --> 43:29.320 We've got a culture I think that people appreciate 43:29.320 --> 43:30.460 that allows them to focus, 43:30.460 --> 43:33.120 allows them to really spend time solving problems. 43:33.120 --> 43:35.900 And I think that keeps them energized. 43:35.900 --> 43:38.940 And then we've invested hard, 43:38.940 --> 43:43.500 invested heavily in the infrastructure 43:43.500 --> 43:46.540 and architectures that we think will ultimately accelerate us. 43:46.540 --> 43:50.660 So because of the folks we're able to bring in early on, 43:50.660 --> 43:53.540 because of the great investors we have, 43:53.540 --> 43:56.780 we don't spend all of our time doing demos 43:56.780 --> 43:58.660 and kind of leaping from one demo to the next. 43:58.660 --> 44:02.820 We've been given the freedom to invest in 44:03.940 --> 44:05.500 infrastructure to do machine learning, 44:05.500 --> 44:08.600 infrastructure to pull data from our on road testing, 44:08.600 --> 44:11.500 infrastructure to use that to accelerate engineering. 44:11.500 --> 44:14.480 And I think that early investment 44:14.480 --> 44:17.340 and continuing investment in those kind of tools 44:17.340 --> 44:19.780 will ultimately allow us to accelerate 44:19.780 --> 44:21.940 and do something pretty incredible. 44:21.940 --> 44:23.420 Chris, beautifully put. 44:23.420 --> 44:24.660 It's a good place to end. 44:24.660 --> 44:26.500 Thank you so much for talking today. 44:26.500 --> 44:47.940 Thank you very much. Really enjoyed it.