No hype, Just works: How Comma reached 100M miles in autonomous driving | E2011

0:00I'm very excited about robotics, but I think we should be realistic. The big reason a lot of people went to self-driving 10 years ago, including me, is because it seemed like a great applied robotics problem that was easy. You have two-dimensional actuators, you have simple rules of the road. As far as robotics goes, that's relatively easy. And then what happened is all these companies were optimistic and ended up not reaching their goals. And now all of a sudden everyone's switching to humanoid robotics, which from the beginning we always thought was harder. So I think it's just another hype wave.

0:29I don't think there's going to be humanoid robots in your house. And we should be somewhat cautious about everything that's just a demo and is not shipping. This Week in Startups is brought to you by.techdomains. Don't miss our Jam with JCal contest. To apply and get more details, go to jamwithjcal.tech. Brought to you by.techdomains. Vanta. Compliance and security shouldn't be a deal breaker for startups to win new business. Vanta makes it easy for companies to get a SOC 2 report fast. Twist listeners can get$1 ,000 off for a limited time at vanta.com slash twist. And MicroOne. MicroOne is an AI recruitment engine to hire world-class engineers fast.

1:14Visit microone.ai slash twist to open a talent search and get a two-week free trial per hire. All right, everybody. Welcome back to the program. I'm very excited today to talk about self-driving cars and autonomy. It feels to me like the autonomy endgame is upon us. We're seeing it in VTOLs, vertical takeoff and landing companies. We're seeing it with Waymo, Tesla, and today's guest, Comma AI's CTO, Harold Schaefer. Welcome to the program, Harold. How are you? Thank you. Yeah, I'm doing great. All right. so um i had george on the program i'm trying to remember what episode that was oh gosh it was a while ago uh eight years ago or something eight years ago uh for the audience who doesn't know explain what comma dot ai is doing in the autonomous space and how it's different than waymo and tesla the other and cruise the other major players in the space right so our goal is to solve robotics, general purpose robotics.

2:22And in the meantime, you know, ship useful products to people that we can sell them for money that add value to their lives. And so today, what that means is we sell a kit that runs software called OpenPilot, that's completely open source, and it's an ADAS upgrade for your car. So basically, it will take over the internal messaging of your car, and it can send gas commands, brake commands and steering commands, and it can make it drive itself on the highway. So it's a bit like, you know, Tesla Autopilot slash FSD. Today, from our users, over 50 % of the miles are driven by OpenPilot. So it kind of gives you an idea of, you know, how much of the driving it does.

3:00It's a level two system, it's not fully autonomous, it just makes your drive more comfortable, and it's kind of a value add. And, you know, as we progress with the technology, we want to, you know, increasingly make these things autonomous and make robotic products that we can sell. Got it. So the mission of the company is general robotics. The first product is this level two autonomy. Level two, I believe, correct me if I'm wrong here, is taking over two functions. And I believe the two functions that you tackled first with Kama AI's kit is staying in the lane and adaptive cruise control. Am I correct?

3:39Yeah, exactly. But I mean, it's a bit more general than that. Like it'll work if there's no lane lines, it'll work if there's no lead, that sort of stuff. It's just a gradual process to become more reliable and eventually it will do everything and drive perfectly. But it's just an incremental game. But yeah, the goal is to do general purpose robotics. It's just that self-driving right now, especially partial autonomy is a very sensible place to make a product. It's something people are willing to pay for and something that's valuable even if it's not perfect. And so what does it cost to add this to your Toyota, your Honda and how does that work for people who don't know about you know the different ports and and how modern cars work in terms of controlling steering and speed maybe you could give us a little primer on that yeah so it's$1 ,450 we'll get you a kit that is a device that has cameras compute and sensors and then a wiring harness that plugs into your car so that wiring harness is specific to a certain brand or a certain model and it basically you know connects to the CAN bus which is your car's internal network and on that network we can send the same messages that the car already accepts from the factory and those messages can apply torque to the steering wheel they can apply gas and they can apply brake and when you can control those three axes you can basically uh you know fully control the car so you can see in this video kind of how that works there's you know connectors that connect to the scan bus we can just intercept it and we can send the same messages that the car is designed to receive and that the stock ADAS system of the car would have sent.

5:10It's just that the stock ADAS systems generally suck and we can make one that is actually usable. All modern Toyotas, even from 2017 onwards, ship with ADAS with the ability to control gas, brake, steering electronically, but they're just not very good and people tend not to use them. But when you use good software like OpenPilot, you can make actually a very enjoyable partial autonomy experience. And so I guess the, well, one question is, how does Toyota, Honda, you know, these, you know, car manufacturers, how do they look at what you're doing? Do they try to stop you? Are they excited about it?

5:48Or are they indifferent? Well, they haven't tried to stop us. People that work in kind of the ADAS development there tend to like us. You know, we know quite a few people that work in kind of the research labs and their ADAS. Generally speaking, they like us. they wish their companies would move a lot faster when it comes to this sort of stuff. You know, it's not lost on those engineers that their ADAS solutions are terrible. And that compared to something like Tesla or OpenPilot, they're very, very far behind. So generally speaking, they like us. And so$1 ,500, you put this into your car, you can either install it yourself or there are third party installers, I understand, who will do this for you?

6:27No, well, there might be, but not any that we're affiliated with. It's kind of a DIY thing. It's not that hard. It's like kind of working on your own computer. It's not the hardest thing, but it is a project. Wow, this Jam with JCal contest has been a blast. So far, I've had the opportunity to meet with four great founders from companies like CorePod, Ulama, Uptrends.ai, and the Roam app, all because they all use.tech domains. And we have room for one more. Do you want to come on the pod and tell me what you're building? Well, you only need two things to answer. You got to be a founder with under$2 million in funding, and you got to have one of those awesome.tech domains.

7:03So head to JamWithJakeAl.tech and tell me what you're building. And if you win, I will invite you onto This Week in Startups, and you'll get to share your vision with me and the world. I'm working with.tech domains because killer startups use them. You know, 1x.tech, Rabbit.tech, so many others. And guess what? We use it too. That's right. .tech powers our Founder Friday program. So tell me about your awesome.tech domain and startup. apply for the jam with jcal contest today at jam with jcal.tech we're picking the final winner soon okay so the thing i really wanted to talk to you about is the open source approach that you've taken it seems to me that open source has won so much of the problem space in computing that it's odd to me that all of the uh self-driving companies and projects are closed whether it's tesla cruz waymo um or any number of them so how is the open source project going are there many other people contributing to it and do you see interest or engineers from these other major projects looking at the work you're doing talk to me a little bit about how that space is shaping up and if you believe open source is going to win the day here okay so just to start off i mean i have dozens of great things to say about open source but i think the biggest thing it does for us is it keeps us honest and it prevents us from being able to rent seek.

8:28If we make hardware that's quite overpriced or worse than a previous version, someone can just come in, undercut us and run open pilot. If we make changes to the software that makes it just the experience, like we can run ads while you're stationary, stuff like that, people will run a fork and they'll make changes to undo the things that we did. So it really forces us to make a good product, both in software and in hardware. So that's, I think, the biggest thing that's good about open source for that. And then are there a lot of people contributing? So because we support so many different cars, it is useful for the community to be able to port new cars to port their own car.

9:05There's definitely a lot of contribution there. When it comes to like improving the core driving experience, you know, it's not really feasible for for external people to contribute there. It's mostly for this like kind of small stuff. Some people make forks that have kind of different uys or small changes that can kind of inspire us to look at maybe something we can change or changes we can we can take over talk to me about the approach i saw in you know our notes here uh for our discussion the different approaches people are taking to autonomy and a lot of the the work that's being done in language models is supposedly becoming applicable here maybe you could just educate the audience on how this technology was working originally and then how this is starting to evolve over time with the advances in AI and compute.

9:58I'll just add one file note about the open source discussion, which is that companies that are closed source, it's most likely because they're trying to hide their lack of capabilities. In Silicon Valley, it's pretty common that a lack of transparency means that, you know, they're not maybe not as great as they claim um but yeah to answer your other question we've been very big on end-to-end machine learning since the beginning which means we can take data to see how humans drive it's very easy to collect data on this you can record their steering gas brake inputs you can see the video of the road and you can then learn um a machine learning model you can teach a machine learning mold and teach it to drive like that we've said that since the beginning you know when we started this company eight years ago, this wasn't really a big thing.

10:41Nobody was thinking this way. People had perception systems that would detect all sorts of things about the world with all sorts of sensors. They would then go into some planning logic that makes decisions based on that, based on some rules, and then take driving action. Whereas we've, in contrast, always said, just learn how to do everything like a human. Waymo is a good example of something that has this very classical stack where they detect things, then they have this classical planning algorithm, then they make decisions. But now multiple companies are kind of coming around. Tesla talks a lot about doing end to end learning.

11:14There's companies like Wave, and a few more that are, this is kind of gaining traction. I think your final point was about the generative AI models, how those, you know, become relevant. So to learn how to drive like a human, one of the best ways to do this is to learn in a simulator. So what we do is, you have a simulator that can simulate driving and you can then let your student that is learning how to drive drive in it and it will deviate from what a human would have done and then you can tell it to recover to what the human was doing so that's basically how our system works but that requires a simulator of driving and one really good way to make a simulator is with these generative ai models that can generate arbitrary video they can simulate the world they can simulate physics and i've got some clips.

12:01I don't know if we want to show those now. Let's take a look at this. I mean, I think this is sort of the fascinating turn, so to speak, that this is taking, which is in a simulator here that we're seeing. For those of you who are listening, we see a simulated road on top and a actual road on the bottom. Explain what we're seeing. So those are both simulated roads. They're completely generated by a machine learning model. They're just two different perspectives. One is kind of zoomed in, the other is kind of zoomed out. And then that machine learning model that's simulating the world is also telling you what it thinks a human would do over the next 10 seconds.

12:36And so what we can do is we can let this agent drive. And by giving action inputs like turn left, turn right, the world model will simulate that deviation and then try to get back to what the human would have done. So this is fully simulated, fully in the imagination of a machine learning model, and we can let a student kind of play and kind of drive around, make mistakes, and we can tell it to recover from those mistakes. And so this is what we're working on today. We've been working on that for a little over a year now with these generative models, and we hope to ship that very soon. so this model has information on what roads look like nighttime versus daytime rain versus snow versus clear skies and it will create simulations let the driver attempt to do that and then how do you know if it's making a mistake and then how do you know to intervene um and how do you know it doesn't hallucinate right because that's like one of the things that we all experience using chat gpt is hey sometimes it's pulling information from maybe a website that has bad data so how do you know like yeah it's it's not producing you know something that is incongruous to the real world yeah i mean that's that makes sense so basically these models are seeded with some real video so we give them some context that is real video and then we ask them to basically go from there and simulate and we can give it you know actions and then that then you basically have a simulator And yeah, I mean, the hallucinating, it's kind of the same thing as just general inaccuracy.

14:08These models, when they're very accurate, they produce realistic looking rollouts. When they're inaccurate, they can deviate from the real world. And that's definitely a real failure mode. You can diverge from what looks like a realistic road. Lane lines can cross in unrealistic ways. And that's kind of the project of making these models better. It's just bringing that error rate down and the videos look better and better. Waymo seems to be the one player that has full autonomous vehicles on the road at scale um their approach is the old school approach it's taking all this input and it's saying you know if this then that and and you know it's got a a rule set there that it's following so maybe you could tell me why they've been so successful and you know what what you think of their rollout limitations on what they're doing and or things they're doing that are causing them to hit 100 ,000 paid rides a week.

15:05Right. Well, let me start by saying, you know, what Waymo's done is incredibly cool. They're probably the coolest service that you can get today as a normal user. That's like an actual robotic thing of something interacting with the real world that is actually to some degree autonomous. With that said, I think their strategy doesn't really make sense from a business perspective. I think, you know, that they don't have unit economics at all. And a part of that is because of this strategy that they're using, which requires, you know, mapping all the areas that they drive in. It requires a lot of remote supervision.

15:41Not sure how many remote supervisors they have now, but I'm guessing it's on the order of a half to one per car. You know, I just don't think this scales nearly as well as the strategy that we're using, which is far more end to end. What do you mean by remote supervisors? So it's hard to get exact numbers on this sort of stuff, but I would guess that they have interventions by remote operators that take some amount of action to fix mistakes, at least once every 10 rides. And so it's not clear to me that their strategy that they're applying now, even though they do not have drivers in the car, necessarily scales that easily to actually having a, you know, really, really autonomous fleet that doesn't require humans in the loop, essentially.

16:24so there are humans somewhere looking at the cars driving in your mind it might be one-to-one per vehicle or one to two vehicles that would be my guess yes uh and they are not driving the cars obviously we actually recently had a startup on that is doing remote driving of cars like a video game with over 5g pretty clever um if you've got good connections and seems to work pretty well for dropping off a uh dropping off and also training you know like a hertz car or something like that um but with waymo you think there's a large number of people obviously that would be very expensive to have you know a human being you know split watching two cars that's just like having the driver essentially because he's probably well-paid people in an office somewhere uh so you have that overhead so and then they use lidar as well which adds a certain expense what do you think the economics are in terms of running one of these way more vehicles i mean from my understanding they've got over a billion dollars in burn rate and less than a thousand cars so that's over a million dollars per car per year now revenue probably looks on the order of 100 to 150 000 a year so it's very far off from something that makes sense and I think some you know obviously they can get that down pretty quickly but I think some of those things will be hard to remove especially the remote operators the costs in developing new mapping for all these new areas I think there are just several issues that will come up that are costly like I don't know what happens now if someone leaves the door open does the door auto close that's that sort of stuff I think will make the unit economics essentially not realistically come down to the you know hundred thousand a year that is required anytime soon i've been using tesla's autopilot and fsd since inception uh and was using this morning um i get an intervention i would say in the back roads here in texas or on the highway once every i don't know 20 to 30 minutes uh so So it feels like it's doing a pretty great job on straightaways, easy turns, roundabouts.

18:39It feels like it's a little jittery. Left turns into traffic feels a little jittery, like it's figuring some stuff out. But it does feel like it's getting more confident every year. Maybe you could talk a little bit about Waymo's approach versus Tesla FSD versus what you're doing at Combo. I mean, so Tesla is definitely a lot more similar to us. And if I were to place a bet on anyone, it would be them. They're recently very focused on end-to-end machine learning, just like we are. I think they've not quite rolled out as end-to-end of a strategy as we have. I think they've got some more classical stuff in there.

19:11But to be fair, they also have capabilities that our system does not have. And I think it is harder to switch to end-to-end when you have these more capabilities, like they can do left and right hand turns and stuff like that, new turns, stuff that we cannot yet do. But they're a little bit less end-to-end than us. our system is completely end-to-end that we ship today and tesla is also working on generative ai simulation presumably to one day train in i don't think they do that yet i think we would have heard about that if they did there is a lot of similarity to our approach there you know they also have a product they have a very large fleet um you know tesla has the most miles collected on any kind of autonomous system we have the second and then way more actually has quite a bit less than than any any of us.

19:55So yeah, I think we're much more similar to Tesla in that sense, much more end-to-end. Waymo has really seemed to have pigeonholed themselves in this LiDAR sensor strategy. They don't seem to have any interest in moving away from LiDAR, which I think is a mistake. The world is made for eyes. Why is it a mistake? The arguments they often use is that it's more redundancy. It gives you information about the world that cameras could never do. But ultimately, the roads are designed for human eyes and good modern cameras can do everything human eyes can do if not more and so there's absolutely no reason you can't perfectly drive a car at least safer than most humans with cameras it is all a software machine learning problem and i think using things like lidars gives you short-term gains but are long-term uh essentially bottlenecks um so i think it's a detour I think they'll regret that.

20:51What does it cost, do you think, for them to put LiDAR on these cars? I had heard in the early days$20 ,000,$30 ,000 per car. I don't know if that's still accurate. Last I heard, they're paying$120 ,000 for their cars. And I think the cars themselves cost about half that. So I think the entire upgrade must be on the order of$50 ,000, I think. and then tesla's you think is a couple of thousand dollars and yours obviously is fifteen hundred dollars uh so yes it can be done for a lot less yes i mean also fifteen hundred is what we sell it for you know we build the devices for half that and you know same for tesla tell me about the cameras you use versus tesla's because when you say like hey we should be able to be as good or better than a human driver humans only see in one direction they get tired uh they have glasses you know there's blind spots if you have cameras all over the car you're literally could be behaving like maybe six seven eight human beings in terms of your field of view um and then in terms of accuracy the fidelity of cameras is better than human eyes now and um i would think it's obviously more vigilant than humans maybe doesn't need a cup of coffee it's late at night yeah i mean not being distracted definitely you know when we start comparing safety when we get actual competent self-driving systems uh you know that's that's where the advantage is going to be no distraction no drunk driving no sleeping um i think we're not even quite there yet we need we need higher capabilities before we can really improve on that and as to your comments on cameras i think it's a distraction to talk about cameras even this this webcam that i'm using now which is not a great camera uh you know can let you drive a car pretty well if a competent human was operating behind the wheel with that camera view um there are some things that more cameras will help you with uh and you know for a company like tesla i think it completely makes sense to install those cameras for a company like us the added hassle of installing more cameras around the car is never going to give the upgrade in performance uh to make that how many do you use when you do it just the front facing one or so we have two cameras facing the actually have a device here that i can show you maybe so this is the device here and so we've got a narrow camera and a wide camera to the front so it's 180 degrees and 40 degrees and then on the other side we have a driver facing camera that makes sure that you're paying attention so three cameras total and uh what about like on the sides of the vehicle and the reverse cameras those could help with changing lanes etc So how do you think about lane changing and the next version of your software?

23:36So our device has, you know, with the two 180 degree lenses has 360 degrees. So you can see the blind spots. But currently the lane changes are supervised. So you initiate the lane change. You're expected to check the blind spot. And most cars that we support have a blind spot sensor that we can also look at. And so when there's a car in your blind spot detected by the blind spot radar, it will prevent the lane change. But it is a supervisor expected to look as well. Listen, a strong sales team can make all the difference for a B2B startup. But if you're going to hire sharks, you need to let them hunt and you can't slow them down with compliance hurdles like SOC 2.

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24:48Stop slowing your sales team down and use Vanta. Get$1 ,000 off at vanta.com slash twist. That's vanta.com slash twist for$1 ,000 off your SOC 2. What is your handicapping of the space? When will we see this rollout, you know, in a major way with multiple vendors in many cities? You're talking about like a Waymo type taxi solution? let's say no human in the in the driver's seat we've established now that the majority of miles can be driven safely or safer with a human plus a level two three system or system whatever it is i guess the question for everybody is when do we remove the expense of the driver and have you know these fleets of cars everywhere driving people and burritos to their destinations without the expense of a driver?

25:43So I'm generally a lot more pessimistic than I would say the average. I think there's a lot of hype in the space. I think most of these things are generally overhyped. I think the best thing to do is to look at the orders of magnitude of mistakes and kind of see how that's been trending and extrapolate that. I think exactly what you're talking about is relevant. You have a disengagement that, you know, maybe safety critical, maybe not every few drives, let's say. I think the Waymos are similar. They have a bit of a different strategy, but they have remote supervision, remote intervention, let's say a disengagement that is necessary every 10, 20 drives, you know, that's very far away from a system that can drive reliably day after day with absolutely no supervision.

26:24So I think you should look at the trends and kind of extrapolate the orders of magnitudes of mistake. And we're still many years away, I think. Okay, so many years being three, four, five, six, seven, somewhere in that range. i think predicting past five years is so hard it's not next year it's not going to be the year after that i predict within five years there's going to be nothing that looks like a self-driving taxi solution in most cities after that i think predictions are so hard why hasn't a major car manufacturer the toyotas hondas of the world looked at what you're doing in the open source project and just said hey let's go all in on open source here that would seem to me to be a tipping point for the industry if we really want to save lives why not you know why hasn't cruise open sourced what they're doing or waymo or tesla or one of these i i had the um co-ceo of tesla at the all-in summit last week and she said open source isn't a discussion at waymo so it does seem like open source tends to win in the long term uh because of the reasons you stated but I'm just curious why there isn't a major open source project.

27:33You do have open maps as a data repository. I believe I'm not sure if you use it or if it's relevant here, but it would seem to be open street maps. Yeah. And so maybe you could explain a little bit about that project and how that helps you. And then there's all this open hardware that exists in the world now and all kinds of libraries. why hasn't an open source self-driving project kind of taken hold across many vendors yet? So first of all, like I said, I think companies don't open source their stuff because they want to overhype what they have. Open sourcing means making clear what you have.

28:11And I think companies like Waymo aren't too excited about people finding out how many interventions they actually have about people finding out how much work it actually takes to do a lot of these things, because you know that's their revenue stream is investment and if people have less of an opinion of where they really are that is not good for uh you know their financial situation tesla on the other hand they're not open source but they're relatively open and transparent about what they're doing and what the system does and you can use it at any time and you can test it in any conditions that you want so it's not open source but at least it's transparent and then as to why these legacy car manufacturers don't take our system and just implement it and ship it because it's a lot better than theirs i mean that i think is a great question but it's a question for them i think generally speaking these companies are not interested in innovation they run defensively and they act out of fear if they see that their business model is under threat they will respond and try to reduce that threat but when there is a system that is a clear upgrade to them available that doesn't seem like an immediate threat they just generally have no interest i mean it's the same thing with their infotainment systems.

29:19You know, you use infotainment system of even a modern car from a legacy car manufacturer, and it feels broken compared to your iPhone. There's no excuse for that. They could fix that. But that's just not how these companies work. I think the bigger question is, why does companies like Lucid or Rivian perhaps not, you know, they're developing their own system in-house, they have hardware that can run OpenPilot, and they're shipping solutions that are worse than OpenPilot. I think they'd be a great candidate to implement OpenPilot on their car, at least while they're developing their own solution.

29:47If they can make something better, sure, replace it. But in the meantime, why not just use our software? It's free, it's MIT licensed, they can get something better running today. Yeah, it would seem to me that if you're behind, and classically, this is what we've seen, when a corporation is behind, they embrace open source. And when they're ahead, they embrace closed source. Google is a great microcosm of that. android they were far behind on the smartphone market they open source it search they were far ahead they they kept it closed facebook the the social graph is closed because they're so far ahead and they have locked in and then they just open source llama and they're so far behind on ai that they decided to open source it's not key to the business so it would seem to me like a rivian a niche provider of vehicles would do so much better to partner with you have you have you talked to them or reached out to them?

30:38I mean, we're not really interested, like we have very limited resources. We don't want to invest resources into partnering with anyone. We do everything we can to make our stuff accessible, open source, and a company like Rivian, if they invested the time, could easily port it to their hardware. I think it's like a stuff made here kind of thing. They want stuff built in-house. That's what I think. There are some limitations to our software too that they may not like. We don't do A, B yet. They might not be interested in a solution that doesn't do A, B as well. That's something that we're working on.

31:08But you know, we've talked to some of these people, there is some interest, we've talked to legacy car manufacturers, there is interest. But it just doesn't align with our goals. We're really focused on solving robotics. And we just want to make money and have a product in the meantime. And anything that distracts from that is just not worth it for us. All right, scaling product is one of the hardest challenges we as founders face. Knowing what to build is obviously only half the battle. You also need the resources at exactly the right time. You might want a little help now, you might not need it later.

31:40And that's where Micro One comes in. They're going to help you scale your product with a team of developers in days, not weeks. When you're handling the search process, when you're trying to get great developers, the vetting and the onboarding and the paperwork, that's going to take weeks for each one. It's painful. It's one of the hardest parts about being an entrepreneur. Well, imagine if you just tell AI what you need on an engineering basis, and then AI delivers with the team at Micro One exactly what you need, you're going to be in great shape. And Micro One built this incredible AI engine.

32:11This is why I invested. They interview 20 ,000 engineers every month. They pick the top 1%. And then they help onboard them into your company. It's simple and it's effective. They do all the legal, they do the compliance, they do the search. You don't have to do a mountain of resumes. You don't have to worry about somebody flaking out you don't have to budget a huge recruiting bill micro one's got you covered and you'll find your next engineer in 48 hours or less that's the promise micro one has for you so here's the call to action micro one dot ai slash twist m-i-c-r-o one dot ai slash twist to instantly ramp up your product team and if you make a hire before october 1st they're going to give you two weeks of free development per hire have you been tracking what's going on in china there are some places in the world where they might look at self-driving and say hey even with one intervention every 10 or 20 rides that's safe enough for how we look at safety in let's say beijing or china where like you know let's face it people in factories there might have um you know osha in america might be a very fine filter you know in terms of working conditions and in china other places maybe they're just like you know people are a little bit more expendable we don't we want to have a society move faster and rather uh than you know have very niche safety needs i'm trying to be generous here but they've got six or seven different players on the road with technology that i think is similar to yours and tesla's yes uh i'm not super familiar with uh what's going on in china in terms of self-driving i think when you're talking about things like rolling out these these systems with the technology where it's at today you cannot make a profitable taxi service that's just a fact today and i think we're pretty far away from that and so companies like waymo when they grow they cost more money and that that's just not a that to me seems like a terrible strategy and so i'm not sure what the benefit would be of doing this in china even if they're okay with the additional risk it's not clear to me that that accelerates progress i think these technical strides need to be made and they don't need that much data or they don't like we have more data than waymo yeah what do you think the tesla announcement will be you think elon will show kind of a two-seater that people there are some leaked photos on social of like hey maybe there's going to be a specific physical robo taxi debuted um that seems to be the case and then do you think it will have a safety driver when they roll it out or is their technology ready to do autonomous rides like wayne most does i think your experience with fsd is probably very reflective of how good tesla autonomous software is i very much doubt that all of a sudden there's some secret project that is capable of doing actual taxi service you know elon said in 2016 that they were going to drive you know coast to coast self-driving uh at the end of the year that didn't happen i think generally speaking elon's a bit optimistic i think this is probably along those lines so when do you think if you had to take a guess they would be able to take the steering wheel out with fsd just to make a wild guess i'd say again over five years under five years five plus years i would say yes uh as we wrap up here tell me what your vision is for robotics obviously you have humane you got tessa doing optimus we just had sergey at the all-in summit you know sort of i think it was lamenting a little bit they were early into robotics before ai was there um you know cars go very fast they can cause a lot of damage but a robot you know if it's weighs 50 pounds or 100 pounds not going to do a lot of damage if it falls over uh it's not going to certainly be going 65 or 75 miles an hour when it makes a mistake so tell me a little bit about what you think the future of robotics is given what you've learned in AI and what's your approach for that?

36:11I mean, I'm very excited about robotics. That's, you know, having robots in your house that could do your laundry or anything like that, that is the coolest thing ever. And, you know, I think about that all the time, but I think we should be realistic. The big reason a lot of people went to self-driving 10 years ago, including me, is because it seemed like a great applied robotics problem that was easy. You have two-dimensional actuators, you have simple rules of the road. As far as robotics goes, that's relatively easy. And then what happened is all these companies were optimistic and ended up not reaching their goals.

36:41And now all of a sudden, everyone's switching to humanoid robotics, which from the beginning, we always thought was harder. So I think it's just another hype wave. I don't think there's going to be humanoid robots in your house. You know, I have a robot vacuum. I think that's kind of the state of the art robots you can buy in your house today. And they get better every year, not super fast. But I think seeing that trend is what you should be thinking about, about realistically what's going to happen. Those things will get better, but you're not going to have humanoid robotics in a couple of years.