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Kyle Vogt: Cruise Automation | Lex Fridman Podcast #14

Lex Fridman and Kyle Vogt on kyle Vogt on Cruise, startups, and building safe self-driving cars.

Lex FridmanhostKyle Vogtguest
Feb 7, 201955mWatch on YouTube ↗

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  1. 0:0015:00

    The following is a…

    1. LF

      The following is a conversation with Kyle Vogt. He's the president and the CTO of Cruise Automation, leading an effort to solve one of the biggest robotics challenges of our time, vehicle automation. He's a co-founder of two successful companies, Twitch and Cruise, that have each sold for a billion dollars, and he's a great example of the innovative spirit that flourishes in Silicon Valley, and now is facing an interesting and exciting challenge of matching that spirit with the mass production and the safety-centric culture of a major automaker, like General Motors. This conversation is part of the MIT Artificial General Intelligence series and the Artificial Intelligence Podcast. If you enjoy it, please subscribe on YouTube, iTunes, or simply connect with me on Twitter at lexfridman, spelled F-R-I-D. And now, here's my conversation with Kyle Vogt. You grew up in Kansas, right?

    2. KV

      Yeah. And I just saw that picture you had hidden-

    3. LF

      Oh, boy.

    4. KV

      ... under there, so I'm a little bit- a little bit worried about that now.

    5. LF

      Nervous.

    6. KV

      Yeah.

    7. LF

      So in high school, in Kansas City, you joined Shawnee Mission North High School robotics team.

    8. KV

      Yeah.

    9. LF

      Now, that wasn't your high school.

    10. KV

      That's right. That was- that was, uh, the only high school in the area that had a f- like, a- a teacher who was willing to sponsor our first robotics team.

    11. LF

      I was gonna troll you a little bit, jog your memory-

    12. KV

      Yep.

    13. LF

      ... a little bit-

    14. KV

      Yep.

    15. LF

      ... about that kid.

    16. KV

      I was trying to look super cool and intense-

    17. LF

      You did.

    18. KV

      ... 'cause, you know, this was BattleBots, this is serious business, so we're standing there with a welded steel frame and looking tough.

    19. LF

      So go back there. What is it that drew you to robotics?

    20. KV

      Well, I think, I- I've been trying to figure this out for a while, but I've always liked building things with LEGOs, and when I was really, really young, I wanted the- the LEGOs that had motors and other things. And then, you know, LEGO MINDSTORMS came out, and for the first time, you could program LEGO contraptions. And I think, uh, things just sort of snowballed from that. But I remember, um, seeing, you know, the BattleBots TV show on Comedy Central and thinking, "That is the coolest thing in the world. I wanna be a part of that," and, uh, not knowing a whole lot about how to build these 200-pound fighting robots. So I sort of obsessively pored over the, uh, internet forums where all the creators for BattleBots would sort of hang out and talk about, you know, document their build progress and everything. And, uh, I think I read- I must have read like, you know, tens of thousands of forum posts from- from basically everything that was out there on what these people were doing. And eventually, like, sort of triangulated how to- how to put some of these things together, and- and, uh- uh, ended up doing BattleBots, which was, you know, I was like 13 or 14, which was pretty awesome.

    21. LF

      I'm not sure if the show's still running, but s- so BattleBots is, uh, so there's not an artificial intelligence component. It's remotely controlled, and you- it's a m- almost like a mechanical engineering challenge of-

    22. KV

      Yeah.

    23. LF

      ... building things that can't be broken.

    24. KV

      They're- they're radio controlled. So-

    25. LF

      Okay.

    26. KV

      Uh, and I think that they allowed some limited form of autonomy. But, you know, in a two-minute match, you're- you're i- in the way these things ran, you're really doing yourself a disservice by trying to automate it versus just, you know, do the practical thing, which is drive it yourself.

    27. LF

      And there's an entertainment aspect, uh, just- just going on YouTube, there's like an- some of them wield an ax, some of them... I mean, there's that fun. So what drew you to that aspect? Was it the mechanical engineering? Was it the dream to create, like, uh, Frankenstein and tell- sentient being, or was it just like the LEGO, you like tinkering with stuff?

    28. KV

      I mean, that- that was just building something... I- I think the- the idea of, you know, this- this radio controlled machine that- that can do various things if it has like a weapon or something was pretty interesting. I agree, it's- it doesn't have the same appeal as, you know, autonomous robots, which I- which I, you know, sort of gravitated towards later on. But it was definitely an engineering challenge, because everything you did in- in that competition was pushing components to their limits. So we would buy, like, these $40 DC motors that came out of a- a winch, like on the front of a pickup truck or something, and we'd power the car with those, and we'd run them at, like, double or triple their rated voltage. So they immediately start overheating, but for that two-minute match, you can get, you know, a significant increase in the power output of those motors before they burn out. And so you're doing the same thing for your battery packs, all the materials in the system. And I think there is something- something, uh- uh, intrinsically interesting about just seeing, like, where things break.

    29. LF

      And did you offline see where they break? Did you take it to the testing point? Like, how did you know two minutes, or was it a reckless, "Let's just go with it and- and see?"

    30. KV

      Uh, we- we weren't very good at BattleBots. We lost all of our matches before-

  2. 15:0030:00

    So let me jump…

    1. KV

      money, dollar for dollar, that I've seen. You know, because that, that small sort of initiative that DARPA put, uh, put out, sort of, in, in my view, was the catalyst or, or the tipping point for this, this whole next wave of autonomous vehicle development. So th- that was pretty cool.

    2. LF

      So let me jump around a little bit on that point. S- they also did the Urban Challenge-

    3. KV

      Mm-hmm.

    4. LF

      ... where it was in the city. But it was very artificial and there was no pedestrians and there was very little human involvement except the, a few professional drivers.

    5. KV

      Yeah.

    6. LF

      Do you think there's room... and then there was the Robotics Challenge with humanoid robots.

    7. KV

      Right.

    8. LF

      So in your now role as looking at this, you're trying to solve one of the... you know, u- autonomous driving in one of the harder, more difficult places in San Francisco. Is there a role for DARPA to step in to also kind of help out, like challenge with new ideas, specifically, yeah, pedestrians and so on, all these kinds of interesting things?

    9. KV

      Well, I haven't, I haven't thought about it from that perspective. Is there anything DARPA could do today to further accelerate things? And I would say, my instinct is that that's maybe not the highest and best use of their resources and time.

    10. LF

      Right.

    11. KV

      Because, like, kickstarting and, and spinning up the flywheel is, I think, what, what they-

    12. LF

      Mm-hmm.

    13. KV

      ... did in this case for very, very little money. But today this has become, this has become, like, commercially interesting to very large companies. And the amount of money going into it and the amount of people, like going through your class and learning about these things and developing new skills is just, you know, orders of magnitude more than it was back then. And so there's enough momentum and inertia and energy and investment dollars into this space right now that, uh, I don't, I don't, um... I think they're, I- I think they're, they- they can just say mission accomplished and move on to the next, uh-

    14. LF

      Success.

    15. KV

      ... area of technology that, that needs help.

    16. LF

      So then stepping back to MIT, you left MIT during your junior year. What was that decision like?

    17. KV

      As I said, I had always wanted to do a company in, uh, or start a company and this opportunity landed in my lap, which was a couple guys from Yale. Uh, we're starting a new company and I Googled them and found that they had started a company previously and sold it actually on eBay for about a quarter million bucks, which was a pretty interesting story. But, so I thought to myself, "These guys are, you know, rockstar entrepreneurs. They've done this before. They must be driving around in Ferraris 'cause they sold their company." And, uh, you know, I, I thought I could learn a lot from them. So I, I teamed up with those guys and, and, you know, went out during... went out to California during IAP, which is MIT's-

    18. LF

      Mm-hmm.

    19. KV

      ... uh, month off, uh, on a, on a one-way ticket and basically never went back.

    20. LF

      (laughs)

    21. KV

      We were having so much fun. We felt like we were building something and creating something and it was gonna be interesting that, you know, I was just all in and, and, and got completely hooked. And that, that business was Justin.tv, which was originally a reality show about a guy named Justin, which morphed into a live video streaming platform, which then morphed into what is Twitch today. So that was, that was quite a, an unexpected journey.

    22. LF

      S- so no regrets?

    23. KV

      No.

    24. LF

      Looking back, it was just an obvious, I mean, one-way ticket. I mean, if we just pause on that for a second, there was no...How did you know these were the right guys, this is the right decision? You didn't think? It was just follow the heart kind of thing?

    25. KV

      Well, I didn't know. But, you know, just trying something for a month during IAP seems pretty low risk, right?

    26. LF

      Right.

    27. KV

      And then, you know, well, maybe I'll take a semester off. MIT's pretty flexible about that. You can always go back, right? And then after two or three cycles of that, I eventually threw in the towel. But, uh, you know, I think it's, um... I guess in that case, I felt like I could always hit the undo button if I had to.

    28. LF

      Right. But nevertheless, from, from, uh, when you look in retrospect, I mean, it's, it seems like a brave decision that, you know, is, is difficult... it would be difficult for a lot of people to make.

    29. KV

      It, it wasn't as popular. I'd say the, the general, you know, flux of people out of MIT at the time was mostly into, you know, finance or consulting jobs in Boston or New York. And very few people were going to California to start companies. But today, I'd say that's, it's probably inverted, which is just a sign of, uh, a sign of the times, I guess.

    30. LF

      Yeah. So there's a story about midnight of March 18, 2007, where, uh, where TechCrunch, I guess, announced Justin.tv earlier than it was supposed to, a few hours. The site didn't work. I don't know if any of this is true. You can tell me.

  3. 30:0045:00

    Mm-hmm. …

    1. LF

      in terms of applying AI. And so how, how do those... You've t- you've talked about it a little bit before, but it's also just fascinating to me. We work with a lot of automakers.

    2. KV

      Mm-hmm.

    3. LF

      Uh, you know, the difference between the gap between Detroit and Silicon Valley, let's say. Just to be sort of poetic about it, I guess. Uh, wh- how do you close that gap? How do you take GM into the future where a large part of the fleet will be autonomous perhaps?

    4. KV

      I wanna start by acknowledging that, that GM is made up of, you know, tens of thousands of really brilliant, motivated people who wanna be a part of the future. And, uh, so it's, it's pretty fun to, to work with them. The attitude inside a car company like that is, you know, uh, embracing this, this transformation and change rather than fearing it. And I think that's a testament to the leadership at GM, and that's flown all the way through to, to everyone you talk to, even the people in the assembly plants working on these cars.

    5. LF

      Right.

    6. KV

      So, that's really great. So that, starting from that position makes it a lot easier. So then when the, the people in San Francisco at Cruise interact with the people at GM, at least we have this common set of values, which is that we really want this stuff to work 'cause we think it's important and we think it's the future. That's not to say, you know, those two cultures don't clash. They absolutely do. There's different, different sort of value systems. Like, in a car company, the thing that gets you promoted and, and sort of the reward system is following the processes, delivering the, the, the program on time and on budget. So, any sort of risk-taking is, uh, discouraged in many ways because if a program is late or if you shut down the plant for a day, it's, you know, you can count the millions of dollars that, that burn by pretty quickly. Whereas I think in a, uh, most Silicon Valley companies and, and in, in, in Cruise and the methodology we were employing, especially around the time of the acquisition, the reward structure is about trying to solve these complex problems in any way, shape, or form, or coming up with crazy ideas that, you know, 90% of them won't work. And, uh, and so, so meshing that culture of sort of continuous improvement and experimentation with one where everything needs to be, you know, rigorously defined upfront so that you never slip a, a deadline or, or miss a budget was a pretty big challenge. And that, we're, we're over three years in now, uh, after the acquisition, and I'd say, like, you know, the investment we made in figuring out how to work together successfully and who should do what and, uh, how, how we bridge the gaps between these very different systems and way of doing engineering work, uh, is now one of our greatest assets 'cause I think we have this really powerful thing. But for a while, it was both, both GM and Cruise were, were very steep on a learning curve.

    7. LF

      Yes, I'm sure it was very stressful. It's really important work 'cause that's, that's how to revolutionize the transportation, uh, really to revolutionize any system. You know, you look at the healthcare system or you look at the legal system. I have people, like lawyers come up to me all the time, like, everything they're working on can easily be automated. But then that's not-

    8. KV

      That's not a good feeling, yeah.

    9. LF

      Well, it's not a good feeling, but also there's no way to automate because the, the, the entire infrastructure is really, uh, you know, based, is, is older and it moves very slowly. And so, so how do you close the gap between I haven't ... Uh, how can I replace ... Of course, lawyers don't want to be replaced with an app, but you could replace-

    10. KV

      Mm-hmm.

    11. LF

      ... a lot of aspect when most of the data is still on paper. And so the same thing with, with automotive. I mean, it's fundamentally software. So it's, it's basically hiring software engineers. It's thinking in a software world. I mean, I'm pretty sure nobody in Silicon Valley has ever hit a deadline. (laughs) So and then, uh, on, on GM's-

    12. KV

      (laughs) That's, that's probably true, yeah.

    13. LF

      (laughs) On GM's side, it's probably the opposite.

    14. KV

      Yeah.

    15. LF

      Uh, so that's, that culture gap is, is really fascinating. And so you're optimistic about the future of that?

    16. KV

      Yeah, I mean, from what I've seen, uh, it's impressive. And I think, like, especially in Silicon Valley, it's easy to write off building cars because, you know, people have been doing that for over 100 years now in this country, and so it seems like that's a solved problem. But that doesn't mean it's an easy problem. And, uh, I think it would be easy to sort of overlook that and think that, you know, we're Silicon Valley engineers, we can solve any problem. You know, building a car, it's been done, therefore it's, you know, it's, it's, it's not a, it's not a real engineering challenge. But after having seen just the sheer scale and magnitude in industrialization that occurs inside of an automotive assembly plant, that is a lot of work that I am very glad that we don't have to reinvent, um, to make self-driving cars work. And so to have, you know, partners who have done that for 100 years and have these great processes and this huge infrastructure and supply base that we can tap into is just remarkable because the scope and surface area of, of the problem of deploying fleets of self-driving cars is so large that we're constantly looking for ways to do less so we can focus on the things that really matter more. And if we had to figure out how to build and assemble and, you know-

    17. LF

      Tests and s- yeah.

    18. KV

      Yeah, build the cars themselves, I mean, we, we work closely with GM on that, but if we had to develop all that capability in-house as well, you know, that, that would just make, make the problem really intractable, I think.

    19. LF

      Mm-hmm. So yeah, just like your first entry at the MIT DARPA Challenge when there was, what, the motor that failed?

    20. KV

      Mm-hmm.

    21. LF

      If somebody that knows what they're doing with a motor did it, they could just focus on the soft-

    22. KV

      It would've been nice if we could focus on the software and not the-

    23. LF

      Yeah. (laughs)

    24. KV

      ... not the hardware platform. Yeah.

    25. LF

      Right. So, uh, fr- from your perspective now, you know, there are so many ways that autonomous vehicles can impact society in the next year, five years, 10 years. What do you think is the biggest opportunity to make money in autonomous driving, uh, so- sort of make it a financially viable thing in the near term? What do you think will be the biggest, um, impact there?

    26. KV

      Well, the things that, that drive the economics for fleets of self-driving cars are, there, there's sort of a, a handful of, of variables. One is, you know, the cost to build the vehicle itself, so the material cost. How many ... you know, what's the cost of all your sensors plus the cost of the vehicle and everyth- all the other components on it? Another one is the lifetime of the vehicle. It's very different if your vehicle drives 100,000 miles and then it falls apart versus, you know, two million.

    27. LF

      Right.

    28. KV

      And then, you know, if you have a, a fleet, it's kind of like an airplane where, or, or a airline where once, um, you produce the vehicle, you want it to be in operation-

    29. LF

      Right.

    30. KV

      ... as many hours a day as possible producing revenue. And then, uh, you know, the other piece of that is-... how are you generating revenue? And I think that's kinda what you're asking. And I think the obvious things today are, you know, the ridesharing business, because that's pretty clear that there's demand for that. Uh, there's existing markets you can tap into and, um-

  4. 45:0055:08

    Right. …

    1. KV

      thing for me is I don't think that grinding ever stops-

    2. LF

      Right.

    3. KV

      ... because there's a moment in time where you, you f- you cross that threshold of, of human performance and become superhuman. But there's no reason, there's no first principles reason that AV capability will tap out anywhere near humans. Like there's no reason it couldn't be 20 times better, whether that's, you know, just better driving or safer driving or more comfortable driving, or even 1,000 times better given enough time. And we intend to basically chase that, you know, f- forever, to build the best possible product.

    4. LF

      Better and better and better and always new edge cases come up and new experiences so... And you, you wanna a- automate that process as much as possible.

    5. KV

      Mm-hmm.

    6. LF

      So what do you think in general in society, w- when do you think we may have hundreds of thousands of fully autonomous vehicles driving around? So first of all, predictions, nobody knows the future. You're a part of, uh, the leading people trying to define that future, but even then, you still don't know. But if you l- think about a hu- hundreds of thousands of vehicles, so a significant fraction of vehicles in major cities are autonomous, do you think... Are, are you with Rodney Brooks, who is 2050 and beyond, or are you more with Elon Musk, who is we should've had that two years ago?

    7. KV

      Well, I mean, I- I would've loved-

    8. LF

      I, I don't mean to use those people.

    9. KV

      ... to have it two years ago, but-

    10. LF

      (laughs)

    11. KV

      ... um, (laughs) we're not there yet. So I guess the, the way I would think about that is let's, let's, uh, flip that question around. So what would prevent you to reach hundreds of thousands of vehicles? And-

    12. LF

      That's a good, that's a good, uh, rephrasing it.

    13. KV

      Yeah, so the... I'd say the... It seems the consensus among the, the people developing self-driving cars today is to sort of start with some form of an easier environment, whether it means, you know, lacking inclement weather or, you know, mostly sunny or whatever it is. And then add, add capability for more complex situations over time. And so if you're only able to deploy in areas that, that meet sort of your, your criteria or the, the current domain- you know, operating domain of, of the software you developed, uh, that may put a cap on how many cities you could deploy in. But then as those restrictions start to fall away, like maybe you add, you know, capability to drive really well and, and safely in heavy rain or snow, you know, that, that probably opens up the market by two, two or threefold in terms of the cities you can expand into and so on. And so the real question is, you know, I, I know today, if we wanted to, we could produce that, that many autonomous vehicles-

    14. LF

      Mm-hmm.

    15. KV

      ... but we wouldn't be able to make use of all of them yet 'cause we would sort of saturate the demand, um, in the cities in which we would want to operate initially. So if I were to guess like what the timeline is for those things falling away and reaching hundreds of thousands of vehicles-

    16. LF

      Maybe a range is better?

    17. KV

      ... I would, I would say less than five years.

    18. LF

      Less than five years?

    19. KV

      Yeah.

    20. LF

      And, of course, you're working hard to make that happen. So you started two companies that were eventually acquired for, each for a billion dollars. So you're a pretty good person to ask, what does it take to build a successful startup?

    21. KV

      Hmm. I think, uh, there's, there's sort of survivor bias here a little bit, but I can try to find some common threads for the, the things that worked for me, which is, you know, I... In, in both of these companies, I was really passionate about the core technology. I actually like, you know, lay awake at night thinking about these problems and, and how to solve them. And I think that's helpful because when you start a business, there are, like to this day, there are, there are-... these crazy ups and downs. Like one day you think the business is just on, you're, you're just on top of the world and unstoppable, and the next day you think, "Okay, this is all gonna end." You know, it's, it's just, it's just going south and it's gonna be over tomorrow. Um, and, uh, and so I think, like, having a, a true passion that you can fall back on and knowing that you would be doing it even if y- you weren't getting paid for it helps you weather those, those tough times. So that's one thing. I think the other one is really good people. So I've always, uh, been surrounded by really good co-founders that are logical thinkers, um, are always pushing their limits, and have very high levels of integrity. So that's Dan Kohn in my current company and actually his brother and a couple other guys for Justin.tv and Twitch. And then I think the last thing is just, uh, I guess persistence or perseverance. Like, and, and that, that can apply to sticking to sort of a, the, or, or having conviction around the original premise of your idea, and, and sticking around to do all the, you know, the unsexy work to actually make it come to fruition-

    22. LF

      Yeah.

    23. KV

      ... including dealing with, you know, whatever it is that you, that you're not passionate about, whether that's finance or, or HR or, or operations or those things. As long as you are grinding away and working towards, you know, that north star for your business, whatever it is, and you don't give up, and you're making progress every day, i- it seems like eventually you'll end up in a good place. And the only things that can slow you down are, you know, running out of money, or I suppose your competitors destroying you. But I think most of the time, it's, it's people, uh, giving up or, or somehow destroying-

    24. LF

      Right.

    25. KV

      ... things themselves rather than being beaten by their competition or running out of money.

    26. LF

      Yeah, if you never quit, eventually you'll arrive. S- so, uh-

    27. KV

      That was a much more concise version of what I was trying to say.

    28. LF

      (laughs)

    29. KV

      That was good.

    30. LF

      So you went the Y Combinator route twice.

Episode duration: 55:23

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