The Exchanges

Q can handle the San Francisco road. Um, they, if they can do this, they can do anything. And I'd love to hear from your perspective, like, you know, um, You know, how much is it, how much is it that they've just learned San Francisco in particular? I think you got to this or that they've learned like how to drive and can, and, and those skills are applicable elsewhere.

A Yeah. So, um, I'll break it down into two things, like sort of the, um, uh, I guess road layout and traffic infrastructure, like traffic lights and other things, those, those vary slightly from city to city. Like in Austin, there's horizontal traffic lights, which we don't see, uh, in San Francisco and some local differences like that, that take a little bit of work to adapt to. But I think that the part that we were more concerned about initially, or at least just wanted to validate was that the driving behavior we had seen in San Francisco and the pedestrian behavior and the cyclist behavior Does that translate well to other cities? Um, and the answer is it mostly does, uh, out, out of the gate, you take a system that's designed to operate safely in San Francisco and put it in Austin or Phoenix, uh, and it performs extremely well. Now there's some local differences, uh, that are related to, you know, the width of the roads or how people, you know, some of these more unique per city situations. And so we have a process by which we very quickly, um, when we have Basically ways when the avias drive around, if they see something unusual or something that doesn't match what they expect, they can log it, transmit it back to our, you know, data, data centers.

AI assessment note: “and the answer is it mostly does, uh, out, out of the gate”

Q So would you say the floodgates are open now?

A They are, uh, at this point, well, I, I shouldn't say completely open. They're, they're open in ways where we can launch in, you know, some cities of the U S in some areas. So we put limits on our technology today, things like top speed, uh, the weather that it will operate in, and those are tightly validated and controlled, you know, the ability to manage our fleet within those constraints. Um, but that actually opens up a lot of cities in the U S where we can operate a reasonably sized fleet. And as new technologies and improvements come along, like the ability to operate at higher speeds or in tougher weather, that will just further open up the areas in which you'll see these vehicles operate.

AI assessment note: “They are, uh, at this point, well, I, I shouldn't say completely open.”

Q use those ride hailing apps, which have mapped out the cities and routes so well to be able to get your cars and, but, and, and get to where you need to go. But right now with the cruise app or the Waymo app, it's very, it's becoming very clear, very quickly that that stuff is unnecessary. So what's your reaction to that? Is it something that replaces those apps?

A I mean, at this point, it's hard to say. There's a lot of, um, there's a lot of nuance and complexity in, you know, existing ride hailing apps and services. Um, but I think that the I think the consensus view on how the industry would evolve over the last few years, um, has evolved. Like originally there, you know, at one point there were like, 60 companies in the state of California testing AVs, and so the view was that, you know, maybe half of those or a third of those will start shipping robo taxis, and you'll have 30 different robo taxis, just like there's 30 different, you know, brands of cars, you know, often sold in the US. And then something like, you know, a rideshare app would be this nice way to have one interface to all of those. Um, what has actually happened is this problem has turned out to be way more complicated to get to do right. Uh, way more expensive, way more time consuming. And the, the, the field has thinned down to, you know, one or two or maybe three players. Um, and at this point, I think, you know, that, that assumption that you need an app to sort of like fan out to all the different types of robotaxis is, is less of a, less of a guarantee. And so I, I think it, it, it remains to be seen, you know, whether AB companies and ride share companies end up partnering or mixing and matching together, uh, to form alliances and whatnot. Uh, but I certainly t…

AI assessment note: “assumption that you need an app to sort of like fan out... is less of a guarantee”

Q company that talks about full self-driving and that's Tesla. You've mentioned there's one, two, three companies. I mean, two I can think of right off the bat is you and Google, uh, with the Waymo, but Tesla is an interesting case because, okay, their full self-driving isn't exactly full self-driving, but they have more cars driving more miles autonomously than I think anybody. So how do you view their efforts?

A Well, I think that's a, that's a common misconception. And I think one that, um, has been played up quite a bit to, to sell more cars, frankly, and that, you know, I understand why that is, but there's a huge distinction between a driverless car, as in you can sit in the backseat or it can go pick you up without anyone inside or go pick up your kids from school or whatever it is. And one where you have to sit behind the wheel and you're constantly monitoring and ready to take over at a moment's notice in this like high alert mode. And so I, I describe it as look, Either the car works for you. That's a robot taxi. That's driverless car, or you work for the car. That's what you're doing when you're sitting behind the wheel of a driverless system.

AI assessment note: “I think that's a, that's a common misconception. And I think one that”

Q Now the origin, so the origin basically looks like this pod, um, really right out of science fiction movies, two benches facing each other. And is that something that you're going to have one person ride in or is your vision for it to be rideshare?

A Well, um, so talk about another social experiment going wrong. Pooled rides, uh, for human driven ride share is totally awkward. You sit in the backseat of like, you know, a Toyota Camry shoulder to shoulder with someone you've never met. Uh, and it can be pretty jarring, pretty uncomfortable. And you do that to save a couple bucks, you know, on your fare. Um, with the origin, the seats that face it, first of all, they're facing each other. So there's no worry about like someone sitting behind you and you can't see what they're doing. That was something we heard loud and clear from. Uh, customers when we sell you this. And then, um, if you're sitting opposite each other, there's more like leg room than a, like a first class airline seat. So you can, you have plenty of space to be physically distant from someone else, even though you're sharing the same vehicle, which I think will make, uh, will fix a lot of the flaws that were in pooled rides or shared rides. Um, you know, in, in the first generation of that. And so as a result, I think you'll see Um, increased engagement in that, which helps with throughput, lowers congestion, all these good secondary benefits, not to mention lower cost rides to consumers, um, you know, for this vehicle. So it's designed with that in mind.

AI assessment note: “fix a lot of the flaws that were in pooled rides or shared rides”

Q and less, it takes less of a lift to deploy in a new city for each, each time you do it. I mean, you've gone from, what, one to seven cities this year, and, and what, what are we, what can we expect by the end of the year? We're about to, you're about to go into, I think, an eighth, but correct me on the numbers if I'm wrong.

A Yeah, we're not done. Uh, there'll be more this year. Um, uh, and, uh, you know, that that's because next year we're going to be manufacturing a lot of vehicles and, um, you know, that's, that's our biggest limitation to scale right now. We just don't have the vehicles, but we're going to be building more. And, um, we we've learned from San Francisco and other cities that, um, it takes time for communities to acclimate to this new mode of transportation. You know, the first time that people see a driverless car in their neighborhood, there's a lot of double takes and surprise and a lot of thumbs up. They're filming as you got a range of reactions. And so what we don't want to do is drop like, you know, thousands of cars into a city overnight, uh, and catch people off guard. And so by having lots of cities, we can actually make a lot of vehicles and spread them out, deploy them across many places. So there's no abrupt change in any one city that would catch people off guard. We want to deploy with communities and not at them. And so part of that is making sure that, uh, you manage the rate of change and the expectations.

AI assessment note: “Yeah, we're not done. Uh, there'll be more this year.”