A decade ago, there was a lot of hype about self driving cars. In fact, there was more interest in self-driving cars than there was in electric vehicles, in terms of the future of the auto industry. But progress in developing these robotic cars has turned out to be slow, and many tricky challenges still have not been solved. But is the technology finally ready for prime time? On this episode of the Odd Lots podcast, we speak with long-time technology journalist and analyst Tim Lee, the author of the
Understanding AI
newsletter, about why he believes self-driving cars are here and why they're finally about to make serious commercial inroads.
Key insights from the pod
:
Why the last wave of hype fizzled out — 5:23
The main impediment to self-driving car adoption — 8:16
Why are things changing now? — 10:03
How companies are dealing with edge cases — 12:35
Who are the big players in self-driving cars? — 16:19
What is the business model of self-driving cars? — 19:18
Will these cars change cities? — 22:43
AV safety vs human safety — 24:42
When will see mass adoption? — 29:55
Joe Weisenthal: (00:10)
Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.
Tracy Alloway: (00:14)
And I'm Tracy Alloway.
Joe: (00:16)
Tracy, remember the hype about self-driving cars from like 10 years ago? That really died out.
Tracy: (00:21)
Can I tell you something? I'm still holding out hope for the self-driving cars 'cause I can't drive. It was kind of acceptable when I was in my twenties, but now it's starting to get a little embarrassing. So I really need the self-driving cars to, um, become viable options.
Joe: (00:40)
So when we go on the road and like do podcasts like in another city...
Tracy: (00:44)
You have to drive.
Joe: (00:45)
I have to drive all the time, don't I? I'm like, “Oh, Tracy, you're renting a car” and then you like, sort of change the discussion or you bring up something else like, “Oh, I think there's Ubers in that town or something.” But this is the real reason, isn't it.
Tracy: (00:57)
Well, I mean, there are Ubers everywhere. You know what we should talk about whether or not Ubers have a decreased enthusiasm for self-driving cars as a business model.
Joe: (01:05)
Remember when people used to say Uber would never make any money if they still had to pay humans, but now they're making a little money.
Tracy: (01:11)
It's true.
Joe: (01:11)
But I do think like, generally, like when people talk about like tech that didn't live up to the hype. And that you see it now with like chatbots and stuff like that and whether they're really gonna change world. Like people go back to the self-driving cars. Like to me that's the sort of quintessential example of the like modern times. Maybe 3D printing. You don't really hear that much about that either.
Tracy: (01:31)
But don't you also find it weird to imagine a future in two or 300 years where there wouldn't be self-driving cars? It feels at once both inevitable and like hype, if that makes sense.
Joe: (01:45)
No, I mean I definitely, I definitely agree. 200, 300 years. That's a long time. Like 50 years from now I've kind of...
Tracy: (01:53)
You think 50 years from now. Well...
Joe: (01:55)
So this is the question. And this is not an area that I know well. But my impression is it's like a sort of classic thing where like tech got us 95% of the way there and then there are some edge cases that make self-driving cars difficult. I don't know exactly what they are, but getting that last 5% or whatever is so hard that it renders the whole thing very difficult. And that whatever that last percent is, is the difference between the tech being like “Wow” versus actually changing the world.
Tracy: (02:24)
We are so close and yet so far.
Joe: (02:26)
It's one of those things. And I feel like again, with chatbots and some of these other like current artificial intelligence applications, it comes back to this question of like, “Yes, it's really great and it sort of blows your mind, but there are these hallucinations.” If it’s not...
Tracy: (02:41)
Hundred percent reliable.
Joe: (02:42)
Yeah, if it’s not a hundred percent reliable, does that mean it really won't be as disruptive as people expect?
Tracy: (02:46)
The other thing I'm curious about is whether or not that sort of last 5% that you're describing, whether that's on the software or the hardware side.
Joe: (02:54)
Yeah.
Tracy: (02:55)
Because I think that has implications for, you know, if we do make huge leaps in artificial intelligence, maybe that solves a software problem. But maybe the issue is actually that the sensors are too basic. Or too expensive. That sort of thing.
Joe: (03:10)
I don't know the answer to any of these questions. The one other thing I'll say too is like, there is a lot of car talk these days.
We've been doing more and more on the podcast. It's entirely like on the sort of EV charging side and EV production and batteries, like how are they going to reshape the industry or Chinese exports? How are they gonna reshape the industry? It does not seem like, again, 10 years ago, the big question was like, who's ahead in the auto-driving car race, Google, GM or Ford? There was much less talk then about EVs as the big disruptor.
Tracy: (03:41)
Right. So I think it is time for a checkup right. On what's going on with self-driving cars.
Joe: (03:46)
Time for a checkup and our guest says they're back, that they're happening for real. And I do believe him to some extent because I follow some people who live in San Francisco and they're tweeting about it more and more that they see them on the road. And sometimes when I'm up at 4 AM to read the internet in the dark and drink coffee, I see like people who are still out at night in San Francisco talking about all the self-driving cars around them. So there might actually be… they might be back.
Tracy: (04:13)
Well, the things I see on the internet about self-driving cars are those edge cases where it's like a car flummoxed by a traffic cone in the middle of the street. Yeah. Which they're simultaneously like impressive and amusing and disappointing all at the same time if that makes sense.
Joe: (04:30)
Interesting, you're very pro self-driving cars. I didn't, I it hadn't clicked like, you really want this to happen.
Tracy: (04:35)
I have a personal self-interest in not having to learn how to drive. I figure if I'm super optimistic, maybe, maybe if I just hang on for like another 10 years. Maybe. I don't know. Let's ask our guests.
Joe: (04:48)
Let's ask our guest. We have the perfect guest, longtime tech journalist, a tech understander, someone who really deep delves deep into technology to understand like how things work and what's really happening. I followed his work for a long time. We're actually like, we're colleagues together 18 years ago I think at a site called TechDirt. Tim Lee, he is the author of the understandingai.org newsletter, longtime tech journalist. And he recently wrote a piece, The Death of Self-driving Cars is Greatly Exaggerated. So, Tim, great to have you on the show.
Tim Lee: (05:21)
Hey, I'm great to be on. I'm a fan of the podcast.
Joe: (05:23)
Thank you very much. Appreciate that.
Let's start 10 years ago and you know, I think 10 years ago there was a lot of self-driving car hype. And my impression was, and this is so vague and fuzzy, “it's like, oh, most of it's solved, but this last part's really hard.” Is that true? What was that last part? That has proven to be very challenging to like turn these from like prototypes on a track or a very like organized grid-like suburb in Arizona to something that could actually be used on the road.
Tim: (05:53)
So it is true that about 10 years ago, Google was the leading company and they had vehicles that could go on certain routes with a fair amount of kind of preparation. And about six years ago, Google rebranded itself as Waymo, its self-driving car project as Waymo and started testing a taxi service in Phoenix.
And they've been plugging away at that ever since. There were a bunch of other startups that were started between about 2014 and 2018 say. And a lot of those failed or were forced to sell to some of the tech giants. And so there's many fewer companies operating in this space than there were five or six years ago in, in terms of what the last little bit is. It's just a lot of little things. I mean that's a thing about a long tail is there's a lot of stuff out in the long tail.
One thing for example, that Waymo and Cruise the kind of industry leaders have been struggling with is when you deal with first responders, for example, if you come up to an active fire site, you're not supposed to drive over the hoses that firefighters are using.
I mean, that's something you might only encounter every a hundred thousand miles or something. But it's a really big deal when you do it. There's another case where a Cruise vehicle like drove through police tape and a crime scene. So there's lots of little things. I saw a headline, I haven't actually looked into this yet, but apparently a Cruise like drove into wet concrete. So the real world is complicated and there's just lots of weird situations that a human being because we kind of understand how the world works, right. You see, oh, that looks like wet concrete. I shouldn't drive on that, but you just have to like, it's like whack-a-mole. You have to like hit every single like bad thing a vehicle could do it. That just takes a lot of work.
Tracy (7:27)
I don't know why, but I find all the stories of like robotic self-driving cars behaving badly absolutely hilarious. And not the ones where they hurt people, I should just caveat that. But the ones where, you know, something that we wouldn't even think about, you know, there's an object in the road just go around it and they seem to really struggle with.
I wanna ask you more about why that seems to be an issue and sort of get into some of the edge cases that, that Joe mentioned in the intro. But before we do, why, here's a basic question. Why have a lot of these self-driving car companies struggled? Because on the face of it would appear that there is a lot of money floating out there in venture capital land that often goes into, um, unrealistic or unprofitable unprofitable projects. So why has this been an issue for self-driving cars in particular?
Tim (8:16)
I mean, I think on some level the basic issue is safety.
A lot of other areas of tech, you kind of build a minimum viable product and you put it out in the world and you know, it breaks sometimes, but that's fine. Like that gives you more feedback. And because you can kind of iterate rapidly, you can like scale up very quickly and get to a profitable scale pretty quickly.
That obviously doesn't work if, if the moving face of breaking things is like literally breaking things and killing people. And so you have to be very close to perfect before you can launch a commercial service and start making money. And so you had a bunch of startups that were trying to do this. They had all sorts of strategies to do that. Some were trying to operate in retirement communities or do like package delivery. They try to find kind of less demanding applications than like “drive anywhere, anytime.”
But it was just really, really hard. And so the companies that have, uh, sustained are the ones that have Amazon, Google, GM, like big companies behind them who are willing to put like a billion dollars a year behind them for several years in a row while they kind of try to iron out these final little wrinkles.
Joe: (09:16)
So zooming forward to today, and that makes a lot of sense. I hadn't really thought about that. It's like for many tech things it's okay if there are edge cases where it doesn't work because you just sort of like, well, you put out in the world and like, yeah, it's not a perfect product, but it's not minimum viable, it's free...
Tracy: (09:30)
And where we're refining it…
Joe: (09:32)
We're iterating, but you cannot do that when there's big safety issues. And if it's a threat to other drivers or pedestrians, it's not really an acceptable way to do product going to today. And you are more optimistic and we'll get to that about the prospects for their existence. But has there been a breakthrough in recent years or has it just been this slow iterative, grinding away at the edge cases that makes it so that there are fewer and fewer edge cases?
Tim: (10:03)
I would say the second one. I mean Waymo's technology has worked pretty well. They started doing fully driverless operations in Phoenix in the fall of 2020 and have just very gradually expanded that service. Now Waymo, just a week or two ago, they got permission from California regulators to begin operating commercially in San Francisco after a year or two of doing practice driving there.
And so yeah, they've just been plugging away at it. And it's hard to tell from the outside because they're not super transparent about all the details of, you know, how many incidents they have or how much work they have to do on the backend. But yeah, it seems like they're just very gradually making the technology better and they seem to think because they're, they're now talking about scaling up much more quickly. They seem to think that the companies seem to think that they're, that this is ready for it to be a commercial product.
Joe: (10:50)
Just a really simple question. If I were to go to San Francisco right now, could I go there and download an app or whatever and get in a self-driving taxi?
Tim: (11:01)
I haven't checked that recently. So it was literally like last week or the week before the California regulators gave them permission to do that. Okay. I think. And so until like last week, I think there's a waiting list, but it's definitely a case if you go to certain parts of Phoenix including the Phoenix airport, you can hail a taxi and it is just like Uber or Lyft. You can go try it.
Joe: (11:19)
I wanna do it. I want to do it. Tracy, let's go suburbs. Let's go to Phoenix just so that for the one ride then fly back.
Tracy: (11:25)
Sure, would love that.
Tim: (11:26)
And I've talked to people there. I mean, it works. It works quite well. I mean the people I've talked to several people who've ridden in those vehicles and at least in most rides they say it's flawless. It drives very comfortably and yeah, the service, they, there just aren't that many refuges.
Tracy: (11:39)
Can we talk a little bit more about the edge stuff? Because my my impression is that okay, computers learn from repetition and from modeling out various scenarios, but driving is such an infinitely unpredictable experience. Especially if you're in New York...
Joe: (11:59)
It's not that hard Tracy. You could get it. I have confidence you could it.
Tracy: (12:03)
I don't know, I think I've missed the boat on that one, but anyway. Okay. But there are all these different possibilities that a self-driving car could be grappling with. So for instance, an animal runs out in the middle of the street and you know, maybe after that happens several times, the self-driving car starts to realize, well, it's this animal and then it's gonna behave in this way and keep moving or stop and I need to respond to it in a certain way. But that kind of seems to be the issue here as far as I understand it.
Tim: (12:35)
Yes, absolutely.
And there's a bunch of ways that the companies have tried to do this. So for example, Google has long had a big test track facility out in California. I went out there a few years ago where they have some fake roads and they'll create kind of fake scenarios. They'll have cars cut other cars off or have somebody like moving boxes across the street, people in Halloween costumes, something like that.
And so they try to think of what are all the situations that a self-driving car could run into and kinda anticipate that, and this is also why they started in Phoenix, is one of their strategies was, “Okay, there's so many edge cases, we can't do them all right at what all at once. And so let's start a kind of easy mode.” And so Phoenix has very nice weather, nice wide streets, um, well marked, you know, not a lot of pedestrians, not a lot of bicyclists.
And so that was kind of way most theory was that we'll do the easiest one first. The issue with that is that the economics of running a taxi service in Phoenix are not that great 'cause most people already have cars. And so Cruise has kind of had the opposite approach, which is we wanna see these cases as fast as possible, so let's start in downtown San Francisco because that's where there's a ton of crazy situations.
And so we'll kind of be harder in the first place, but we gathering data very quickly and maybe we'll master it and is not yet clear yet. I mean, both, both companies now seem to think they're ready, but I don't think we've, we've seen them in the wild long enough to have a sense for kind of which of those strategies are working better. But yeah, it's really tough.
So I should say like for the first few years, both of these companies had safety drivers behind the wheel of every vehicle. And so the vehicle was mostly driving itself, but if it got stuck, the safety driver would have to, um, take over. And the kind of big switching, the big risky point is when they take the first drivers out of the car, which Waymo did about two years ago and Cruise did I think maybe a year ago. And then, you know, and then it becomes much trickier because if the vehicle screws up it's a big deal.
Tracy: (14:17)
I love the idea of having to train the self-driving cars by like putting people in Halloween costumes in front of them. And it reminds me a lot of socializing my dog. Because we used to have to like wear weird hats, right? Or like bring balloons into the house so that he would get used to them and not freak out.
But this goes back to something that I mentioned earlier, which is, is the issue here the software? So like the actual modeling of the reaction to an unknown or unfamiliar, um, event or stimulus? Or is it more on the hardware side where maybe you need better sensors that are better able to appreciate the things in front of you?
Tim: (14:58)
I would say it's more software and particularly more data. But yeah, the hardware has stayed pretty constant. I mean the trio of sensors most of these vehicles have are cameras, radar, and then lidar, which is like laser range finding technology that gives you kind of a 3D map of your environment.
And so 10 years ago Google's cars had those three sensors and I think now those sensors are better. But I don't think anybody thinks that the main issue is that we need to upgrade in the quality to lidar. Really, they just need, they need examples of every possible edge case and they, you know, it's hard to get enough of that data because some edge cases happen very rarely, but could be very serious if you encounter them.
Joe: (15:49)
Can you give us a quick industry overview? You know, you mentioned Waymo, it, so Waymo's, Google. Cruise is GM...
And then obviously Tesla and Elon's, like if you just like read Elon's Twitter feed, you would think that they've already had self-driving cars, like in the wild. And I don't really think that's true, but I don't really understand what's going on. Can you give like a really just sort of quick like, overview of who the big players are? Yeah. And like who owns them and just sort of like what their status is.
Tim: (16:19)
Yes, absolutely. So Waymo is mainly owned by Google. Cruise is mainly owned by GM. I consider Tesla to be in a different market. And some of the Tesla fans get mad at me when I say this. But Tesla is building a driver assistance product.
So pretty much any car you drive now they have advanced cruise control where it stays in your lane and doesn't hit the car in front of you. In some ways I think Tesla has a more advanced version of that, although also in some ways I think it's, you must just Tesla low or risk tolerance. And so he is kind of pushing a technology that's… but the key thing about the Tesla product is you are not supposed to like crawl in the backseat and take a nap, right? You're supposed to be there making sure it doesn't break and say has
Joe: (16:55)
People crawled in the backseat and taking a nap?
Tim: (16:57)
I'm sure somebody has done that. There are videos of people doing inappropriate things while behind the wheel of the Tesla. But you're definitely not supposed to, and you know, the vehicles, they have ways of monitoring the driver so that that doesn't happen.
But anyway, so theoretically Elon Musk thinks they're gonna at some point get to the point where you don't have to be behind the wheel, but I do not think they're close to that or really laying groundwork. Because one of the things for any service like that is you need an operations staff. Because a vehicle is occasionally gonna get stuck. And when that happens, it needs to be able to phone home and get kind of remote guidance about how to deal with it. And as far as I know, Tesla's not doing it. So that's Tesla.
And then the other two companies there, there are a few other companies that I would say are a little behind. So Amazon has a company called Zoox that used to be a startup, but got acquired by Amazon a couple years ago. And there's a company called Motional that is also, I think close to being ready for driverless, but not to driverless. And then there's a company called MobileEye that supplies the hardware for most of these driver assistance systems. And they have been working on this technology. So that's another company. But yes, I say those four or five companies are the kind of the remaining players.
Joe: (17:55)
Am I hallucinating this memory or was there a situation in which Uber hired every single member of the Carnegie Mellon University Robotics Department to work on self-driving cars for them?
Tim: (18:09)
Yes, absolutely. So Uber was one…
Joe: (18:11)
That's the real thing that actually happened.
Tim: (18:13)
Yes. That was in, I mean, I don't dunno if it was every member, but yes, Uber hired a bunch of talent in 2016, 2017, and then one of their vehicles struck and killed somebody in Tempe, Arizona in 2018. And that basically destroyed their program.
And so I think the remnants… so actually I should just say there's a startup called Aurora that is doing trucking. I think they acquired Uber's thing, but anyway, yeah. So Uber is now not a player because in large part because they're really the only, only one of these fully self-driving programs that have had a fatality with their, with their testing.
Tracy: (18:45)
So let's assume that self-driving cars become a realistic thing. How viable is that as a business model? Because on a first reading, it seems extremely expensive to develop, possibly extremely expensive to maintain if you have to provide operational support to all these, you know, robot cars out in the field. And then thirdly, it does seem like there's a big regulatory slash safety slash maybe legal liability risk if something were to happen.
Tim: (19:18)
I mean, I'm pretty optimistic about it because you think about, if you think about Uber and Lyft, about half of the cost of running Uber and Lyft is the labor of the human driver.
And so if you take that out, then Waymo/Cruise need to get the new cost, the cost of the sensors plus whatever operational stuff in R&D to be less than half the cost of the driver. And that's a pretty significant amount of money.
And so I think it'll take them a while to get to the scale where it's profitable because certainly, you know, way Waymo and crew both have, I I think hundreds or maybe thousands of people working on this technology and the sensors are currently pretty expensive. But one of the most predictable things in business is that mass manufactured technologies like LIDAR sensors and computer chips get cheaper at scale.
And so I have no doubt that in the long run, this is going to be a viable business. And it's really, I think, a question of how much patience big companies backing, you know, Google, GM and Amazon companies like that, how many billions of dollars they wanna spend to get to this. But I think that in the long run, I think that the taxi industry will be operated by self-driving cars. And I think that in the long run, I also think it'll be cheaper and probably expand the market a lot. So my my long run expectation is that this is gonna be a big and profitable industry.
Tracy
:
(20:29)
Do you envision it just, or primarily for taxis or could you have a situation where people like, like me are buying self-driving cars?
Joe: (20:38)
And just to add on to Tracy's question, because this, it sort of dovetails, could Tracy drive to work and then make some extra money by during the day when it would be parking for eight hours, have it be a taxi, and then could that impair total volume sales for the automakers? Because basically Tracy takes her self-driving car to work, but then also is serving the taxi industry at the same time.
Tracy: (21:03)
A self-driving car capitalist...
Joe: (21:06)
Rather than having the car sit for eight hours in the parking lot or 10 hours.
Tracy: (21:09)
Smart.
Tim: (21:10)
Right. So I think certainty the initial product is gonna be a taxi service. That's what all the people doing passenger, you know, nobody's talking about selling them in the short run. Obviously people like owning cars.
And so in the long run, I think there will be a business model where you'll be able to have a car. My guess is that it's gonna be something more like a long-term lease than actual outright ownership, but partly for liability reasons. I mean, if you imagine if you own the car and the brake needs a replacement and you don't replace it and the car crashes to kill somebody, the people who made the software gonna get sued for that.
And so I think they're gonna be reluctant to sell people self-driving cars outright. But you might be able to have something that's a long-term lease that's effectively the same as ownership.
I'm not sure it would make that much sense. I mean, if you're the kind of person who wants to share a car with other people, then probably you would just take a taxi. So I'm not sure, I mean, there's a lot of ways the economics could work out, but my guess is that you'll have some people who will lease a self-driving car long term and other people who will just take taxis.
And I think that hopefully, like in the long run, if the economy still bring costs down, it'll be much cheaper than a taxi today. Like roughly half the price if you figure that that half is labor. And so then that'll allow lots of people, especially in cities, to own fewer cars and, and take more taxi rides.
Joe: (22:20)
But I was just gonna say, even if you didn't, I mean I know other people have said this before, but maybe Tracy doesn't want to share her car with other people during the day, but it could mean less need for parking, right? The car could drive home and back, go back into your driveway or garage while you're at work. And then pick you up. And then the amount of space that a city or a neighborhood needs for parking probably could be significantly diminished.
Tim: (22:43)
Yes, absolutely. And I think, I think one underestimated benefit of this from an urban planning perspective is it'll be much easier to do congestion charging because the vehicles will all be up connected. And so I could imagine more kind of complicated pricing where you give people a strong incentive not to drive their car into downtown.
Like if you're going to go downtown, take a taxi or maybe some kind of shared, you know, vehicle. So there's a lot of... I think self-driving cars will open up a lot of new options for the way you kind of organize, especially commutes because yeah, you can have different kinds of vehicles and different kinds of business models for how people pay for them.
Tracy: (23:15)
Could I use myself driving car to deliver packages as a sort of gig FedEx worker or something? I hear UPS drivers cost a nowadays.
Tim: (23:25)
I mean, again, I think that'll be a different market. So there's a company called Neuro that is trying to do this. Several companies actually, but I think they're the market leader. So I think it's possible. I mean, one of the issues is, you know, with a FedEx driver, the FedEx driver physically gets out of the car, out of the truck and carries the package to your front door.
And obviously your self-driving car is gonna be able to do that. So I'm not sure exactly what that market will look like, but my guess is that there'll be customized delivery vehicles that are much smaller and lighter and cheaper than a full-sized car. Because there's no reason you need a full car if there's nobody in the vehicle.
Joe: (23:55)
Can I ask a question about safety? You know, you mentioned that Uber self-driving car pilot program ended basically because a car struck and killed a pedestrian. It is also true that human driven cars are killing people every day. I believe there's tens of thousands of people every year who die in auto accidents. Do we have meaningful apples-to-apples statistics, or is it that still so far that the test that the self-driving car universe is too narrow or in too ideal conditions to actually do a safety comparison?
Tim: (24:31)
It's actually just that the raw number of miles is not high enough. Ok it’s true that humans kill 30,000 to 40,000 people a year.
Joe: (24:39)
I mean that's a staggering number.
Tim: (24:42)
Humans drive billions or trillions of miles every year. And so it's like one, there's a fatality once every hundred million miles roughly on the roads and self-driving cars are in the tens of millions of miles. So if there were as safe as a human, you would expect about one less than one death so far. And so the fact that there has been only one death doesn't really tell you that much about.
You know, is it, is it more or less safe? Um, I mean, so far the Waymo/Cruise, the leaders, have had zero deaths, but they've gotten less than a hundred million miles. So you just, I think it's just too soon to say for sure.
Tracy: (25:16)
How much does the business model or the eventual profitability of a lot of these self-driving car companies depend on the way the insurers react? Because I imagine, you know, if there is an accident involving a self-driving car and there's negligence involved, or you know, something's wrong with the model, the, the legal liability is almost infinite at that point. Potentially millions and millions of dollars of payouts if there are actual fatalities. And I guess my question is, a lot of this is gonna depend on the insurers being willing to take on that risk, right?
Tim: (25:50)
Yeah. You know, I'm not actually sure exactly what Google and and Cruise’s insurance situations are. I mean, they're big enough companies that I would guess they can self-insure. So that's actually not something they've disclosed in some regulatory filing how they're insured. But it's a different market because it's not, especially in the early years, it's not gonna be individual consumers buying insurance. And so, yeah, I'm not actually sure what the, the structure of that market is right now. And whether they have third party insurance or they're just on the hook for the liability...
Tracy: (26:17)
That'd be interesting to look at.
Joe: (26:19)
Can I just ask a really simple regulatory question. Right now, if one of these companies said “We're good, we got it. You want to get a taxi, or you wanna do Cannonball Run and you wanna go coast to coast, we'll drive you from New York to California.” Could they legally do it? Is there still some sort of like regulatory blessing that would need to happen for that to exist?
Tim: (26:42)
There's very little regulation at the federal level. There's some regulation of the design of the vehicle. For example, you still need to have a steering wheel in the car, but at the federal level, I don't think there'd be any legal barriers to do that. It's state by state. I think if you weren't charging for it and just doing as a demonstration, I don't think there'd be any issue in most states.
But as I mentioned, so California I think is one of the states that regulates these things more heavily. And they do have a fairly substantial process. They treat Waymo and Cruise similarly to the way Uber and Lyft are regulated. And they just got the approval to start doing commercial taxi rides in San Francisco. So yeah, it's state by state and Phoenix, I believe, there's, there's close to no regulation of of that kind of thing. So, yeah. And I think Texas is probably similar. So the more kind of Republican leaning states, there's very little real regulation. California has some, but, but not enough that it's really a major bottleneck.
Tracy: (27:49)
So we discussed that there are some self-driving cars available out there, but they're kind of a novelty slash experiment at the moment. How will we know when self-driving cars are a sort of viable, realistic thing? What are you watching out for?
Tim: (28:06)
I think they're running the experiment right now. So Cruise has announced I think 8 to 10 new cities, mostly in the southwest places like, um, Houston, Dallas, Miami, Atlanta, Nashville. And we'll just kind of have to see how quickly that happens or if it happens. I mean, it certainly wouldn't be the first time that a company's made an announcement in the self-driving space that hasn't panned out, but they've gone from just Phoenix to now Phoenix and San Francisco.
We'll just have to watch and see if those announcements actually turn into operating services. Like I said, right now, you can go to Phoenix, you can try it. I think in the next few weeks or months you'll be able, anybody will be able to get car in San Francisco. And then the other thing is the service territory. So right now it's not all of the Phoenix Metro. I think a couple hundred square miles.
And so yeah, you'll, we'll wanna watch what cities are they going into and how big of a service footprint and do does that service footprint grow over time? And then ultimately we'll have to see the financial results. I mean, these are both publicly traded companies, so eventually I assume they'll tell us if it's profitable. I don't think it is yet. But yeah, I think if you see them rapidly scaling up the number of vehicles and the number of cities, then that'll be a sign that it's going well. And if it's, if it doesn't, then probably isn't going as well.
Joe: (29:20)
I'm not kidding by the way, about going to Arizona just to travel. Cause we already want to do an Arizona tour anyway with all of our land and water and alfalfa and chips episodes we do there. So we gotta fly there just to take a self-driving car. I just have like one more question and it's basically, you know, here in New York, I don't think there's anything happening yet, but let's put a real timeframe on this. You say they're coming, we're gonna start seeing them more and more in some of these other cities. When can we say like, you know, when will we have them in New York and give us a year by which we could say “Tim was right or Tim was wrong.”
Tim: (29:55)
So I don't know if I'm making a strong prediction on a specific year.
So I will say what Waymo and Cruz have said, I believe Waymo has said they're planning to increase their footprint by 10 x by the end of next year. Wow. And Cruise has said they're gonna reach a billion dollars in revenue, which I think will be about 50 x increase by 2025. So I'm a little skeptical to hit those numbers, but that's, that's the scale they're talking about now.
That would still be a small fraction of the overall taxi industry and I think one of the things you'll see is that they haven't entirely figured out the weather situation. And to some extent they're like really dense infrastructure. So if this question of when will we be able to hail a vehicle in Manhattan, I could still see that being five to 10 years away. But I would not be surprised if Los Angeles, Houston, Dallas, Miami, those kind of cities, you know, southwestern kind of suburban cities, if three to five years from now it's very common to see self-driving taxis as as just like a on par with Uber and Lyft in terms of popularity.
Joe: (30:55)
Similarly, Tim Lee we’ll have you back in five years and we'll see if all of this born out. Really appreciate you coming on the podcast.
Tim: (31:03)
Sounds good. Thank you.
Joe: (31:17)
I am telling you, Tracy, it always comes back to Arizona. for US chips, . Seriously, we were getting chips, water, alfalfa and cars and now self, self-driving. I’m serious.
Tracy: (31:29)
Okay.
Joe: (31:31)
I’m serious.
Tracy: (31:31)
It's not that many things.
Joe: (31:33)
I'm telling you, we gotta take a trip. I'm not being facetious.
Tracy: (31:38)
Okay. Well I would happily go to Arizona. I think that'd be fun, but I don't know I'm just gonna go back to what I said earlier, which is like self-driving cars at once feel far away and very close and sort of inevitable and also quite difficult. If that makes sense.
Joe: (31:53)
You know what I thought was really fascinating and I hadn't really appreciated this, his point about one of the companies starting in Phoenix where they're driving is super easy. And then you sort of like progressively get better, just go to more complicated places. And then the other one starting or mainly operating in San Francisco where the driving is really difficult and it's like if you can master San Francisco, you can probably master anyway. I wonder what the better approach is. Like getting progressively, you know, progressively better or just like really taking all the hard stuff on day one.
Tracy: (32:26)
You know what, I don't get just thinking about that conversation. You know how all CAPTCHAs to identify robots Yeah. Are like identify the motorcycles Yeah. In this photo or identify the buses. That doesn't bode well for self-driving cars does it?
Joe: (32:40)
Wait why?
Tracy: (32:40)
Well, because it seems like robots struggle to identify motorcycles on the road. Humans don’t.
Joe: (32:46)
I see what you're saying. Right. Like our whole approach to even identifying whether someone is inhuman
Tracy: (32:51)
Or not, it's always traffic lights. Yeah. It's always. Or cars or motorcycles. So maybe, yeah, bicycles maybe actually self-driving cars are ultimately a threat to our existing CAPTCHA systems that
Joe: (33:00)
Wow. Yeah. Right. Like if we could solve self-driving cars that guarantees that we're gonna have spam and other internet attacks. I hadn't really thought about that.
Tracy: (33:09)
Well I mean I think we didn't touch on it much there, but there are also obviously societal implications of this. We talked a little bit about the notion that well maybe companies could just replace all the taxi or the Uber drivers, maybe even some mail delivery drivers get replaced. That seems to be an issue as well. And then the other thing, actually, I wanna look into this after this conversation, but I am really curious what the insurance is like on these things and who's providing
Joe: (33:35)
Yeah. Who has to pay and how. I do think there are a lot of big questions like that are like who's ultimately responsible when, when these malfunction? I think in San Francisco recently there was something where a bunch of them all shut down at the same time and they created all these traffic problems, which is also not something that comes up with human drivers.
I also think like the political debates are gonna get like super weird. Cause Tim mentioned congestion taxes. But what if they say, oh, like you can't even do that route because the computer is determined that that would like use too much energy. It’s interesting like the red states as mentioned, have been a bit more liberal about allowing them, but then there's all, in 20 years will you be allowed to be a human driver?
Will you allowed to be like go sightseeing? Like all these things, like kind of some like big interesting questions that could reshape society and then the reshaping like sort of of our physical space, maybe less need for parking if these actually take off. I think it will change the world in ways we don't really anticipate.
Tracy: (34:36)
Yeah. Maybe we need to do a self-driving cars episode from the perspective of a city planner or something like that.
Joe: (34:41)
That's a good idea.
Tracy: (34:41)
Alright, well shall we leave it there for now?
Joe: (34:44)
Let's leave it there.
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