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Speaker 1: Pushkin.

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Speaker 2: If you live in the Dallas Fort Worth area, there

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Speaker 2: is a good chance that right now you can open

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Speaker 2: up an app on your phone and order a cup

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Speaker 2: of coffee or a bottle of ibuprofen from a nearby Walmart,

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Speaker 2: and then about fifteen minutes later, a drone will appear

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Speaker 2: hovering in the sky above your yard. The drone will

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Speaker 2: lower down a rope that holds a box that has

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Speaker 2: your ibuprofen in it. Then the drone will leave the

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Speaker 2: box on the ground, pull up the rope and fly away.

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Speaker 2: People have been talking about drone delivery for a long

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Speaker 2: time now. There have been pilot programs and test sites,

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Speaker 2: but this thing in Dallas is big. Millions of people

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Speaker 2: live in the delivery zone. It's the first place in

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Speaker 2: the US where for lots and lots of people, drone

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Speaker 2: delivery seems set to become a normal, everyday thing. I'm

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Speaker 2: Jacob Goldstein and this is What's Your Problem, the show

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Speaker 2: where I talk to people who are trying to make

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Speaker 2: technological progress. My guest today is Adam Woodworth. Adam is

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Speaker 2: the CEO of Wing. Wing is owned by Alphabet and

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Speaker 2: it's one of the two drone companies doing deliveries for

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Speaker 2: Walmart in Dallas. Wing has also been making deliveries in

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Speaker 2: Australia for several years now. Adam's problem is this, how

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Speaker 2: do you turn a delivery drone into something as boring

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Speaker 2: and ubiquitous as a shopping cart? To start, I asked

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Speaker 2: Adam to make the case for his project, like, why

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Speaker 2: should I be happy to learn that delivery drones may

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Speaker 2: soon be coming to a sky near me delivering coffee

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Speaker 2: and burritos to my neighbors.

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Speaker 3: I've caught a lot of flack over the years for

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Speaker 3: the burrito copter, and like, oh, you're just using drones

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Speaker 3: to fire around and deliver cups coffee and stuff. But

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Speaker 3: at the core of it, like people eat food every day,

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Speaker 3: Like if you look at it from a holistic transportation perspective,

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Speaker 3: like people are not going to stop ordering things, Like

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Speaker 3: that's not like it's in fact the opposite. People are

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Speaker 3: ordering more stuff every day. And it just does not

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Speaker 3: make sense that we are moving around like burritos and

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Speaker 3: cups of coffee in cars, Like it just does not

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Speaker 3: make sense.

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Speaker 2: To what extent are people ordering coffee delivered by somebody

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Speaker 2: in a car? Is that a thing?

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Speaker 3: And I just don't know it. It is a thing.

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Speaker 3: It is a thing like you can go sort of

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Speaker 3: look up. There's been a myriad of different studies about

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Speaker 3: sort of what actual sort of like dipler use cases are,

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Speaker 3: and it's a lot of small items. I can I

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Speaker 3: can talk about a bunch of aviation math, but I

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Speaker 3: think the simplest way to look at it is we

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Speaker 3: are designing systems like to be able to fly in

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Speaker 3: the national airspace. This is the same for everybody who's

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Speaker 3: sort of in here to be building systems that are

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Speaker 3: like sort of equivalent level of safety to like airliners.

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Speaker 3: So if you take that and you abstract it down

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Speaker 3: to things that people can sort of internalize in terms

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Speaker 3: of sort of risk, it is safer to fly the

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Speaker 3: package via drone than it is to walk the package

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Speaker 3: in your hand down the sidewalk.

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Speaker 2: That's good, that's compelling, that's fun. Non intuitive, it's very

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Speaker 2: non intuitive. I thought you were gonna say safer than

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Speaker 2: to drive, and I'd be like, sure.

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Speaker 3: Everything everything, but like safer than to hand carry it.

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Speaker 2: The risk of hand caring is getting hit by a car.

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Speaker 3: Yes, that's it's usually serve pedestrian road risk. And so

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Speaker 3: you have this form of transportation which is possible and

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Speaker 3: real and financially viable. That is many orders of magnitude

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Speaker 3: safer than the incumbent. If you look at on every

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Speaker 3: metric from safety to emissions, sort of impact on infrastructure,

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Speaker 3: It's like, it is silly that we are moving around

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Speaker 3: these boxes and the way we do today. This is

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Speaker 3: a fundamentally better way to do it.

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Speaker 2: So if I want to order something, I live near

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Speaker 2: Walmart in Dallas and I want to order something from you, Like,

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Speaker 2: how does that part work?

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Speaker 3: So basically like we built a pretty traditional looking marketplace

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Speaker 3: where the order flow is very traditional until you get

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Speaker 3: to the part at the end, which is the drone part.

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Speaker 2: So I use your app. I don't use like the

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Speaker 2: Walmart app.

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Speaker 3: So it depends on which region you're in. So in

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Speaker 3: Australia we're integrated into the door Dash app, So use

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Speaker 3: the front end of door Dash. In the US right

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Speaker 3: now we're integrate. We're using our own app. Okay, So

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Speaker 3: you say what you want ordered, and then before you

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Speaker 3: even get to that step, the back end will say

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Speaker 3: is your address deliverable? Right? Like it is the place

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Speaker 3: that you are, a place that the plane can get

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Speaker 3: to just to be.

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Speaker 2: Clear that is you checking it out. You're using basically

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Speaker 2: satellite data to say does this address work? Or that's

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Speaker 2: you asking music. No, that's you just checking.

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Speaker 3: So it's just basic. And some of it is even

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Speaker 3: like like if there's a big hill that the plane

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Speaker 3: has to spend more energy climbing over, like you might

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Speaker 3: be within the radius, but like your particular house like

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Speaker 3: may be undeliverable, or you might be slightly outside of

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Speaker 3: the radius because there's no there's no power lines or

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Speaker 3: hills to get there, so the plane go slightly farther.

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Speaker 3: So everybody thinks about a delivery area as a circle,

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Speaker 3: but it's really like a weird amiba.

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Speaker 2: With lots of variables affecting where you can go.

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Speaker 3: Yeah, and so there's a there's a sort of there's

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Speaker 3: an address checker that'll run that like just GPS coordinate

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Speaker 3: through a terrain database to be like can the plane

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Speaker 3: get there? And then once you get to check out,

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Speaker 3: you'll be presented with either one delivery zone of like okay,

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Speaker 3: this is the place on your property where the box

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Speaker 3: can be dropped off, or a choice like if there's

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Speaker 3: multiple spots, it'll be like okay, which one of these three,

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Speaker 3: do you want it in the left side of your

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Speaker 3: yards sell the ardor in the backyard the personal pick that.

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Speaker 3: Then the order will process, the plane will be dispatched,

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Speaker 3: and then it'll go to like a sort of countdown

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Speaker 3: of like, Okay, the plane is on its way and

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Speaker 3: it'll be here in three minutes and forty two seconds.

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Speaker 2: So uh, and and what's the cost?

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Speaker 3: It depends it's uh, it's sort of uh. That's that's

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Speaker 3: that's more of a partner question.

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Speaker 2: What's it what's it cost you?

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Speaker 3: That's a that's an unanswerable question.

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Speaker 2: A lot right, now, A lot right?

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Speaker 3: No, I mean I think, uh, I think less than

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Speaker 3: less than what folks would assume.

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Speaker 2: I mean, the marginal cost is low, right, but it's

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Speaker 2: not that many deliveries against a large fixed costs.

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Speaker 3: That's fair. But the marginal metrics are all sort of

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Speaker 3: you know, favorable or in the direction of favorable. Yeah. So,

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Speaker 3: like you know, people are well accustomed to getting stuff

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Speaker 3: delivered today, and so like those costs are well understood,

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Speaker 3: and the sort of costs per delivery that you know,

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Speaker 3: either is either the partner is charging they're sort of

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Speaker 3: all in line with that, depending on sort of which

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Speaker 3: region you're in. But that's that's ultimately up to the partner.

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Speaker 2: A few bucks, I mean, is is that what that means?

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Speaker 2: Reason which you know it can't be more than that

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Speaker 2: if people are out in coffee, right though, it is

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Speaker 2: amazing how much people spend on, you know, on the

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Speaker 2: marginal thing. So so that's how it works from the

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Speaker 2: consumer's point of view, How does it work from you know,

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Speaker 2: from the drones point of view. From from the company's point.

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Speaker 3: Of view, what happens every every morning the service turns on,

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Speaker 3: Folks can can order the stuff. Planes will get automatically

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Speaker 3: tasked to go take off, pick up the box and go.

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Speaker 2: How many deliveries what they do in a day?

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Speaker 3: Like our high water mark right now is around for

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Speaker 3: one store was about like one hundred and thirty deliveries, okay,

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Speaker 3: So it's like these are like, these are real numbers.

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Speaker 3: This isn't like like, oh okay, like three people ordered

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Speaker 3: stuff today, And I think that that's the that's I

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Speaker 3: think sort of the phase that the industry is moving

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Speaker 3: into now is it's it's these aren't like pilot programs

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Speaker 3: and trials. These are like, okay, this store opened up

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Speaker 3: offering this service and all the people in the area

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Speaker 3: expect to get that service.

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Speaker 2: How how big and how heavy can something be?

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Speaker 3: So you know, we carry about a little bit over

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Speaker 3: a kilo of of of good, so you know, two

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Speaker 3: point two pounds of stuff, and in.

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Speaker 2: Terms of volume, like.

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Speaker 3: Like I think about like a shoe box, shoe box

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Speaker 3: ish shoe box, okay, And a lot of it ends

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Speaker 3: up being you know, prepared food, drinks like you know,

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Speaker 3: soft drinks, you know, grocery items. And I think the

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Speaker 3: one of the interesting observations I've always had on this is, uh,

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Speaker 3: back back to the sort of original like did we

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Speaker 3: pick the right use case piece. We did a bunch

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Speaker 3: of surveys sort of early on in the program of

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Speaker 3: you know, what would you want delivered by drone if

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Speaker 3: you if you had the option, and you know, there

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Speaker 3: were dozens of different options sort of from food all

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Speaker 3: the way to medicine, clothing, all these other things, and

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Speaker 3: overwhelming the responses were always like, you know, drones should

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Speaker 3: only be used for medical delivery, like they should only

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Speaker 3: be used for medicine first aid bits like that. And

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Speaker 3: then we went and offered the service in Australia. We

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Speaker 3: had we had all those goods in there. We had

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Speaker 3: like a lot of you know, like type of you know,

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Speaker 3: over the counters, pharmacy items, sort of food, clothing, a

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Speaker 3: bunch of different local restaurants, and like eighty percent of

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Speaker 3: people ordered coffee. Like that was the overwhelming sort of

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Speaker 3: thing because it's like that's something that people got every day,

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Speaker 3: and it made.

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Speaker 2: Sense stated preference versus revealed preference. I mean there is

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Speaker 2: there is also the externality thing, right, Like it's one

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Speaker 2: thing to say, if a drone's going to be flying

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Speaker 2: over my house all the time, what do I want

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Speaker 2: it to be delivering to everybody? Versus if it's coming

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Speaker 2: to my house, what am I going to order today?

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Speaker 3: Right? I mean that is another way to frame that's fair.

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Speaker 2: So like what what are when you look back after

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Speaker 2: ten years of working at it and like now you're

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Speaker 2: actually doing it, Like, what are a few key things

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Speaker 2: you figured out?

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Speaker 3: I think one of the most defining moments is or

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Speaker 3: maybe one of the most defining constraints. Most sort of

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Speaker 3: disruptive or merging technologies sort of start off in a

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Speaker 3: permissive environment. So you know, one of the one of

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Speaker 3: the things that I you know, one of the questions

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Speaker 3: I've gotten asked many times sort of over the years,

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Speaker 3: is well, why didn't you take the approach that like

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Speaker 3: ride share took of. Okay, you know, offer the service

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Speaker 3: in a big metro area, build up a big customer base,

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Speaker 3: and then as the rules change, you have, like you

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Speaker 3: have customers to say, Okay, this is a valuable thing.

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Speaker 2: Why didn't you do it?

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Speaker 3: Why not just go? Why not why not just go?

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Speaker 3: Do it? And I think at the core of it,

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Speaker 3: it's because aviation does not operate that way right, Like

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Speaker 3: aviation is is is built around a preempted set of

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Speaker 3: rules where the federal government controls the airspace, so it's

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Speaker 3: not up to sort of anyone given municipality. And from

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Speaker 3: that place, you know, how do you build consumer demand,

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Speaker 3: How do you show that this thing works? How do

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Speaker 3: you even go and do a trial where the existing

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Speaker 3: regulatory frameworks are just say no, you can't fly at all.

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Speaker 2: Yes to Australia.

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Speaker 3: Yeah, So that's that's what That's what drove us to

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Speaker 3: to start in Australia because they were one of the

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Speaker 3: first markets where the National Aviation Regulator there they sort

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Speaker 3: of quantify the risk of the operation. They look at

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Speaker 3: the specifics the operation and they sort of approve on

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Speaker 3: a case by case basis of all right, like this

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Speaker 3: meets the same level of safety as an airliner, even

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Speaker 3: though it's a very different use case.

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Speaker 2: So just tell me like one thing that you know

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Speaker 2: you had to figure out. Maybe you tried something and

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Speaker 2: it didn't work, and you tried something else and it worked.

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Speaker 2: You know what I mean? Is there just one kind

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Speaker 2: of a microcosm example.

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Speaker 3: If I could do two a lot? If that's yeah.

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Speaker 3: So the first one is sort of how do you

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Speaker 3: achieve aerospace reliability with like consumer electronics costs? So you know,

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Speaker 3: we started from a place of how do you build

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Speaker 3: these planes in a way where the unit economics will work?

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Speaker 3: Not how do you build these planes and then try

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Speaker 3: to figure out how to make the unit economics work?

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Speaker 2: Right?

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Speaker 3: So what is I mean?

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Speaker 2: Obviously the cost of one is going to be a

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Speaker 2: function partly or largely of scale. But since you brought

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Speaker 2: it up, like, what has one of them got a

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Speaker 2: cost for it to work for you?

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Speaker 3: I mean it has to look like cell phones basically.

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Speaker 3: And I think that the interesting one that the sort

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Speaker 3: of specific point here is is if you looked at

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Speaker 3: just the reliability case Okay, so how many propulsion system

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Speaker 3: elements do you need in order to be able to

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Speaker 3: make the airplane sort of close all the reliability numbers.

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Speaker 3: That requires eight motors in our use case, so you know,

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Speaker 3: you need eight hover motors so that you can have

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Speaker 3: any one of them fail at any given time and

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Speaker 3: the airplane can still sort of have controlled flight. In

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Speaker 3: our cost trades, it ended up being that if you

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Speaker 3: move to twelve motors instead of eight motors, so the

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Speaker 3: reliability numbers close at eight. But if you went to twelve,

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Speaker 3: you got to use a much smaller motor that didn't

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Speaker 3: need a carbon fiber propeller. You could use a plastic propeller.

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Speaker 3: And there was a huge change in the cost of

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Speaker 3: the total propulsion system by increasing the number of motors,

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Speaker 3: which is not a thing that you would on the

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Speaker 3: surface look at and be like, okay, this is intuitively obvious.

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Speaker 2: So you're using twelve cheaper motors, so more smaller. It's

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Speaker 2: more smaller motors rather than fewer larger motors. And I

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Speaker 2: mean presumably you could keep going that way. You could

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Speaker 2: have twenty tiny motors. I mean, you find the optimum.

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Speaker 3: What settled on twelve was really driven by noise. So

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Speaker 3: like as you get the burders smaller, they have the

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Speaker 3: you know, the frequencies go higher, they spin faster, that

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Speaker 3: discon goes up all these different effects. And so moving

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Speaker 3: to twelve let you get the sort of cost benefits

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Speaker 3: by going small motors. But you didn't sort of start

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Speaker 3: climbing up that that noise curve by having like you know,

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Speaker 3: like one hundred little half inch motors hu and even

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Speaker 3: that there isn't an off the shelf propeller solution that

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Speaker 3: sounds pleasant.

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Speaker 2: Yeah, So that the sound, the sound is a big one, right,

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Speaker 2: Like there was a good Wall Street Journal story I thought,

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Speaker 2: uh from Australia where you were doing a lot of

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Speaker 2: the early work, and the headline was delivery drones, cheer shoppers,

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Speaker 2: annoy neighbors, scare dogs. Tell me about that piece of it.

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Speaker 2: Tell me about the noise.

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Speaker 3: So that's a that's a it's a thing you have

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Speaker 3: to be conscious of. So, you know, we did a

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Speaker 3: bunch of work early on in the development of this

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Speaker 3: aircraft around sort of how do we how do we

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Speaker 3: shape the tone of the noises being generated. So it's

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Speaker 3: sort of less of like one big peak and sort

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Speaker 3: of more broad spectrum, how do we reduce the noise

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Speaker 3: of it? Like, if you look closely at our propellers,

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Speaker 3: they're they're like asymmetrics. So there's one long set of

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Speaker 3: blades and one short set of blades, and that creates

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Speaker 3: like two tip forto sees that destructively interfere and like

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Speaker 3: spread out noise. So all these things. So we did

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Speaker 3: all this work on on the hover propulsion system, and

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Speaker 3: the vast majority of of sort of noise feedback from

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Speaker 3: the communities and mind you, like, if you compare this

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Speaker 3: to the noise feedback you get about an actual airport

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Speaker 3: or you know, construction project is still like far less

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Speaker 3: than that. But it was all overflight, so it was

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Speaker 3: like people weren't complaining about the airplanes hovering. They were

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Speaker 3: complaining about them flying over overhead. And if you you

302
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Speaker 3: look at the fact that the person that ordered the goods,

303
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Speaker 3: like the plane is coming, then they asked for it, right,

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Speaker 3: Like they're like they're like, I want the service. Their

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Speaker 3: neighbors are probably also ordering things. But the thousand homes

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Speaker 3: that you flew over to get to that spot, like

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Speaker 3: may not be participating in the service.

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Speaker 2: It's a negative externality, right, you're imposing a cost on

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Speaker 2: someone who's not a party to the transaction.

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Speaker 3: So so that was that was a very interesting learning

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Speaker 3: sort of early on in our that we only would

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Speaker 3: have learned by actually operating the service.

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Speaker 2: Huh, it's that it's not it's not the next door

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Speaker 2: neighbor who hates it. It's all the people between the

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Speaker 2: store and the customer.

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Speaker 3: And in that sense, it was like, okay, well, well,

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Speaker 3: like we thought we needed to put all this development

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Speaker 3: work in the hover propulsion system, but it's actually the

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Speaker 3: crew system that they need to work.

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Speaker 2: People never get mad about what you think they're going

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Speaker 2: to get mad about, right again, I.

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Speaker 3: Think that that's the at the core of it, Like

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Speaker 3: the dron delivery space is like so full of has

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Speaker 3: been so full of what ifs for so long, and

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Speaker 3: in the absence of regulatory frameworks that let you go

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Speaker 3: and operate like you can't move out these things that

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Speaker 3: it it oftentimes like there's a lot of misconceptions about

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Speaker 3: either noise or sort of what the use cases will

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Speaker 3: be or what people want to order, and then when

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Speaker 3: you go and offer the service, sort of the cure

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Speaker 3: for the what ifs is the actuality of an operating.

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Speaker 2: So okay, so you realize that the noise complaints aren't

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Speaker 2: the noise complaints you're expecting. You had mitigated the one,

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Speaker 2: the hovering, but not the other, the flying over. So

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Speaker 2: now you have this new challenge, right that people getting

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Speaker 2: mad if a drones are flying over their house all

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Speaker 2: day long? What do you do about that?

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Speaker 3: So we we basically did the same thing we did

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Speaker 3: on the other propulsion side, So we used the same

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Speaker 3: technology as to redesign the props. We sort of set

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Speaker 3: the design target so that like basically the aircraft that

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Speaker 3: the cruise altitude would be inaudible to a to an

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Speaker 3: observer on the ground. But this is like everything in

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Speaker 3: aerospace is a trade and so you know, for us,

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Speaker 3: it was like we want to we want to address

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Speaker 3: sort of any of the noise concerns. Uh, And so

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Speaker 3: we're willing to go and do that development time and

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Speaker 3: exercise and costs, redo the propulsions, and then redo the

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Speaker 3: plane to to be able to use it. So that

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Speaker 3: that's uh, that was that was one interesting one and

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Speaker 3: the other one is just like you know, how you

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Speaker 3: get the box to the people. So early on in

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Speaker 3: the program, uh, we had basically you know, you have

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Speaker 3: the little tope that hangs below the plane, and then

355
00:19:08,316 --> 00:19:10,676
Speaker 3: it was connected to playing with a tether, and that

356
00:19:10,836 --> 00:19:13,636
Speaker 3: tether went around a school and just sort of like

357
00:19:14,236 --> 00:19:17,156
Speaker 3: you'd open up a latch and it would descend and

358
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Speaker 3: you'd leave behind the string. So it was like the

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Speaker 3: way of letting go the box was just well, there's

360
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Speaker 3: only so much string on the on the on the aircraft.

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Speaker 2: So so the customer would get a box with a

362
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Speaker 2: long string.

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00:19:30,116 --> 00:19:33,876
Speaker 3: Not a great user experience, but very simple, like super simple.

364
00:19:34,516 --> 00:19:38,956
Speaker 3: And uh, we spent a huge amount of time around

365
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Speaker 3: how do you drop off the box without a bunch

366
00:19:43,836 --> 00:19:47,236
Speaker 3: of mechanical complexity? So how do you how do you

367
00:19:47,316 --> 00:19:50,276
Speaker 3: lower down the box, make sure that it lets go

368
00:19:50,316 --> 00:19:53,036
Speaker 3: of the box one hundred percent of the time. Make

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Speaker 3: sure that that little hook at the bottom doesn't get

370
00:19:56,156 --> 00:19:59,276
Speaker 3: snagged on anything else as it's getting pulled back up. Uh.

371
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Speaker 3: Making sure that that whole system could operate reliably, you know,

372
00:20:03,956 --> 00:20:08,076
Speaker 3: thousands of times with dirt and leaves and stuff. Uh.

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Speaker 3: And so like this is little, that little yellow bit

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Speaker 3: of plastic. So you're just.

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Speaker 2: Talking about the hook at the end of the line

376
00:20:15,476 --> 00:20:18,716
Speaker 2: that holds the box. Like that is like a nightmare

377
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Speaker 2: to get.

378
00:20:19,596 --> 00:20:21,476
Speaker 3: Just right, nightmare to get just right. And it is

379
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Speaker 3: probably one of the most iterated components on the whole aircraft.

380
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Speaker 2: Still to come on the show. Why despite all that

381
00:20:30,436 --> 00:20:34,316
Speaker 2: work on the hook and on everything else, drone delivery

382
00:20:34,436 --> 00:20:38,596
Speaker 2: may never really take off. Also, what the world will

383
00:20:38,636 --> 00:20:53,556
Speaker 2: look like if drone delivery does work? So what like

384
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Speaker 2: what's the frontier for you? Like, what are you trying

385
00:20:55,716 --> 00:20:58,876
Speaker 2: to figure out that you haven't figured out yet?

386
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Speaker 3: Yeah, I think that for us right now. A couple

387
00:21:04,596 --> 00:21:06,996
Speaker 3: of years ago in Australia when we were sort of

388
00:21:07,076 --> 00:21:12,236
Speaker 3: ramping up volumes there, we demonstrated what scale looked like

389
00:21:12,436 --> 00:21:16,596
Speaker 3: for a sort of confined geographic area. So, you know,

390
00:21:16,676 --> 00:21:19,676
Speaker 3: one of the common I think misconceptions about drones is,

391
00:21:19,716 --> 00:21:21,516
Speaker 3: you know, folks like, well, when drone delivery is real,

392
00:21:21,556 --> 00:21:23,116
Speaker 3: I'll look up at the sky and all I see

393
00:21:23,116 --> 00:21:25,476
Speaker 3: is drones. And I was like, well, no, when you

394
00:21:25,516 --> 00:21:27,836
Speaker 3: when you actually do it, when you actually offer sort

395
00:21:27,836 --> 00:21:29,756
Speaker 3: of the scaled out service to like a you know,

396
00:21:29,796 --> 00:21:34,316
Speaker 3: one hundred square kilometer piece of the Earth, even when

397
00:21:34,316 --> 00:21:38,876
Speaker 3: there's even then when there's a thousand deliveries happening in

398
00:21:38,876 --> 00:21:41,076
Speaker 3: one day, and that that little space you can look

399
00:21:41,156 --> 00:21:44,156
Speaker 3: up and not see any planes for a while. And

400
00:21:44,276 --> 00:21:46,676
Speaker 3: so for the last couple of years that's what we

401
00:21:46,676 --> 00:21:49,716
Speaker 3: were focused on was Okay, how do we demonstrate the

402
00:21:49,916 --> 00:21:53,196
Speaker 3: unit scale of Okay, this is what drune delivery looks

403
00:21:53,236 --> 00:21:57,596
Speaker 3: like at scale for one one small space. Now I

404
00:21:57,636 --> 00:22:02,276
Speaker 3: think with the DFW expansion, we have the opportunity to

405
00:22:02,276 --> 00:22:05,236
Speaker 3: do that at a whole sort of metro wide scale.

406
00:22:05,316 --> 00:22:08,476
Speaker 3: So I think that the ability to offer the service

407
00:22:08,596 --> 00:22:12,196
Speaker 3: across a big metro to like, you know, where you're

408
00:22:12,196 --> 00:22:16,756
Speaker 3: gonna cover millions of people. Let's you answer, let's you

409
00:22:16,836 --> 00:22:19,996
Speaker 3: sort of validate that those assumptions that have been proven

410
00:22:20,036 --> 00:22:23,716
Speaker 3: out at smaller operational scales hold as you go up

411
00:22:23,756 --> 00:22:26,396
Speaker 3: and so looking at things like how frequently do people order,

412
00:22:26,876 --> 00:22:30,316
Speaker 3: like is it is it a novelty that people order

413
00:22:30,356 --> 00:22:32,036
Speaker 3: once and then they're like, okay, well I got my

414
00:22:32,156 --> 00:22:34,756
Speaker 3: cool TikTok video of a drown delivering me something or

415
00:22:34,796 --> 00:22:37,996
Speaker 3: do they find value in it? You know, do you

416
00:22:38,116 --> 00:22:41,876
Speaker 3: start to get to the place where you know, for us, like,

417
00:22:42,436 --> 00:22:47,236
Speaker 3: you know, is one operator able to you know, do

418
00:22:47,316 --> 00:22:49,556
Speaker 3: we have the permissions and is it working to have

419
00:22:49,636 --> 00:22:53,756
Speaker 3: one operator do multiple locations and you know, many aircraft

420
00:22:53,796 --> 00:22:57,076
Speaker 3: in the sky at once looking less and less like

421
00:22:57,716 --> 00:23:01,516
Speaker 3: sort of a one to one relationship between sort of

422
00:23:01,596 --> 00:23:04,276
Speaker 3: the person the operation to like more of a sort

423
00:23:04,316 --> 00:23:06,796
Speaker 3: of dispatcher view of the world of like, okay, this

424
00:23:06,836 --> 00:23:09,516
Speaker 3: person is managing a fleet of airplanes rather than energing

425
00:23:09,596 --> 00:23:10,636
Speaker 3: sort of anyone flight.

426
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Speaker 2: So in the in the current service as it exists, Now,

427
00:23:16,396 --> 00:23:19,396
Speaker 2: what what is the role of human beings?

428
00:23:19,956 --> 00:23:23,676
Speaker 3: It's it's really is like, uh, you know, a person

429
00:23:23,716 --> 00:23:25,676
Speaker 3: has to put the stuff in the box. A person

430
00:23:25,716 --> 00:23:27,556
Speaker 3: has to bring the box to where the plane is

431
00:23:27,556 --> 00:23:30,556
Speaker 3: going to be, and you know, the plane hovers and

432
00:23:30,596 --> 00:23:32,756
Speaker 3: lowers down the little hook and they hook the box

433
00:23:32,756 --> 00:23:36,276
Speaker 3: on it and it takes it up. And then you know,

434
00:23:36,436 --> 00:23:38,836
Speaker 3: somebody in the morning needs to take the planes and

435
00:23:38,876 --> 00:23:41,236
Speaker 3: put them out on the pads, and at night take

436
00:23:41,276 --> 00:23:43,956
Speaker 3: them and put them back in the shipping container. And

437
00:23:43,996 --> 00:23:46,436
Speaker 3: then our pilots are sort of monitoring the operation.

438
00:23:46,636 --> 00:23:50,436
Speaker 2: I mean, just to be clear, they're not flying the planes, right.

439
00:23:50,436 --> 00:23:51,716
Speaker 2: The planes are flying themselves.

440
00:23:51,716 --> 00:23:54,796
Speaker 3: Planes are the planes are flying themselves, but they're responsible

441
00:23:54,796 --> 00:23:57,236
Speaker 3: for the operation, right. So like if if you look

442
00:23:57,316 --> 00:23:59,036
Speaker 3: at the sort of like some of the core tenets

443
00:23:59,076 --> 00:24:03,236
Speaker 3: of aviation, like the pilot is responsible for the airliner

444
00:24:03,276 --> 00:24:06,036
Speaker 3: flight or for the charter flight. Like they're responsible for

445
00:24:06,036 --> 00:24:11,236
Speaker 3: the operation. And so what does that mean when things

446
00:24:11,276 --> 00:24:15,316
Speaker 3: get very highly automated, it's okay, well they're looking for

447
00:24:16,436 --> 00:24:19,116
Speaker 3: other air traffic. They're looking for sort of is the

448
00:24:19,156 --> 00:24:21,996
Speaker 3: system performing as we expect it to? Is there is

449
00:24:22,036 --> 00:24:24,556
Speaker 3: there weather that's rolling in? Is there something else like that?

450
00:24:24,876 --> 00:24:26,636
Speaker 2: So just so I can see, just so I can

451
00:24:26,756 --> 00:24:31,476
Speaker 2: like visualize it, is there like at each place where

452
00:24:31,516 --> 00:24:33,236
Speaker 2: you have a nest, like at each Walmart, is there

453
00:24:33,276 --> 00:24:34,956
Speaker 2: like a room where there's a guy sitting or do

454
00:24:34,996 --> 00:24:36,516
Speaker 2: you guys have like an office.

455
00:24:36,396 --> 00:24:38,796
Speaker 3: There's an office where the folks are sitting.

456
00:24:39,076 --> 00:24:41,276
Speaker 2: I mean you said there's a pilot, Like do they

457
00:24:41,436 --> 00:24:43,236
Speaker 2: So what do they have like a little radar thing?

458
00:24:43,396 --> 00:24:46,436
Speaker 3: Like pretty much like if you think about like sort

459
00:24:46,436 --> 00:24:49,556
Speaker 3: of what what an aircraftic controller station would look like,

460
00:24:49,716 --> 00:24:52,036
Speaker 3: or what a sort of train dispatcher station look like,

461
00:24:52,076 --> 00:24:54,236
Speaker 3: that's more or less what the pilot interface looks like.

462
00:24:54,756 --> 00:24:57,836
Speaker 3: So there is there's no live video feed from the aircraft.

463
00:24:58,036 --> 00:25:02,436
Speaker 3: So like the airplanes sort of get their assigned flight

464
00:25:02,596 --> 00:25:04,876
Speaker 3: when somebody places an order, because like we don't know

465
00:25:04,916 --> 00:25:06,596
Speaker 3: where the next order is going to come from. So

466
00:25:06,636 --> 00:25:08,996
Speaker 3: there's this whole route planning algorithm in the background that

467
00:25:09,276 --> 00:25:11,436
Speaker 3: when somebody orders something, it's like, okay, I need to

468
00:25:11,436 --> 00:25:13,356
Speaker 3: go fly this way, and here are the other flights

469
00:25:13,356 --> 00:25:18,636
Speaker 3: in the space. They'll see those tracks like so they'll see, okay,

470
00:25:18,956 --> 00:25:22,516
Speaker 3: I've got you know this many airplanes that are sort

471
00:25:22,516 --> 00:25:24,916
Speaker 3: of active right now, I've got this many airplanes that

472
00:25:24,956 --> 00:25:28,836
Speaker 3: are on the ground waiting getting assigned in order. And

473
00:25:28,876 --> 00:25:31,116
Speaker 3: they're just little icons moving around the screen. So it's

474
00:25:31,156 --> 00:25:33,396
Speaker 3: not like there's not some video feed. There's not like

475
00:25:34,116 --> 00:25:36,916
Speaker 3: and then they've got like a view of the individual nests.

476
00:25:36,916 --> 00:25:39,116
Speaker 3: So there's a little security camera looking down on it.

477
00:25:39,116 --> 00:25:41,436
Speaker 3: It's like, oh, okay, there's here all the airplanes, like

478
00:25:41,956 --> 00:25:45,876
Speaker 3: you know, so it really is it is that sort

479
00:25:45,876 --> 00:25:49,316
Speaker 3: of like supervisor interface. I think it's probably the easiest

480
00:25:49,316 --> 00:25:51,196
Speaker 3: way to think about it, rather than like there's no

481
00:25:51,356 --> 00:25:55,196
Speaker 3: like sort of controls and handles that people are manipulating

482
00:25:55,236 --> 00:25:56,236
Speaker 3: to fly the planes around.

483
00:25:57,036 --> 00:25:59,236
Speaker 2: I mean, is there like a button they can push

484
00:25:59,276 --> 00:26:02,756
Speaker 2: if the plane needs to turn around or like whatever

485
00:26:02,956 --> 00:26:04,076
Speaker 2: bail in some way?

486
00:26:04,196 --> 00:26:07,276
Speaker 3: Yeah, there's a button. So one of the things they

487
00:26:07,276 --> 00:26:09,876
Speaker 3: could do is they can pause the whole operation, so

488
00:26:09,916 --> 00:26:12,436
Speaker 3: they can say like Okay, you know we're outside of

489
00:26:12,436 --> 00:26:16,196
Speaker 3: our weather limits, or there's a airspace conflict that has

490
00:26:16,196 --> 00:26:18,996
Speaker 3: gone through. Stop receiving orders.

491
00:26:19,396 --> 00:26:22,116
Speaker 2: That's the easy one, don't any more planes out.

492
00:26:22,356 --> 00:26:25,676
Speaker 3: The other one is they have a they have a

493
00:26:25,716 --> 00:26:28,716
Speaker 3: button where they can tell the plane to land, and

494
00:26:28,756 --> 00:26:34,276
Speaker 3: that's basically the plane is following like a four D trajectory,

495
00:26:34,316 --> 00:26:36,436
Speaker 3: so it's got a like a three D path plus

496
00:26:36,476 --> 00:26:38,516
Speaker 3: time where it's like, Okay, I'm supposed to be in

497
00:26:38,556 --> 00:26:43,116
Speaker 3: this airspace at this time, and it'll it'll keep flying

498
00:26:43,116 --> 00:26:45,556
Speaker 3: on that path until it gets to a place that

499
00:26:45,676 --> 00:26:48,956
Speaker 3: sort of has been procedurally generated as like okay to land,

500
00:26:49,076 --> 00:26:52,236
Speaker 3: so like you know, open fields and like trees and

501
00:26:52,236 --> 00:26:57,276
Speaker 3: stuff like, not roads, not like sidewalks, and so the

502
00:26:57,276 --> 00:26:58,836
Speaker 3: plane will keep flying until it gets to one of

503
00:26:58,836 --> 00:27:01,476
Speaker 3: those places and it'll sort of slow down to a hover,

504
00:27:01,636 --> 00:27:04,996
Speaker 3: come down, and land and that those are really the

505
00:27:05,356 --> 00:27:06,916
Speaker 3: those are the two commands.

506
00:27:07,356 --> 00:27:09,036
Speaker 2: How often does that one happen?

507
00:27:09,796 --> 00:27:13,636
Speaker 3: Very land, Yeah, very infrequently. And I think it's more

508
00:27:14,036 --> 00:27:17,116
Speaker 3: I think it's more akin to like like if you

509
00:27:17,356 --> 00:27:19,076
Speaker 3: pulled your car over to the side of the road

510
00:27:19,196 --> 00:27:23,036
Speaker 3: with a check engine light it's it's not like it's

511
00:27:23,036 --> 00:27:26,036
Speaker 3: not like sort of anything is like fundamentally broken. It's

512
00:27:26,436 --> 00:27:29,916
Speaker 3: more like a precautionary step. And I think that's that's

513
00:27:29,956 --> 00:27:32,476
Speaker 3: one of the pieces that sort of underpins this whole

514
00:27:32,556 --> 00:27:35,516
Speaker 3: sort of operational cases, like all these layers of redundancy.

515
00:27:36,436 --> 00:27:38,476
Speaker 3: The plane can either the plane can go to the

516
00:27:38,516 --> 00:27:40,636
Speaker 3: delivery zone and say like, well, I don't think I

517
00:27:40,676 --> 00:27:42,676
Speaker 3: should deliver the package because there's an obstacle and they'll

518
00:27:42,716 --> 00:27:44,956
Speaker 3: come back. The plane can go and deliver the box

519
00:27:44,996 --> 00:27:47,076
Speaker 3: and say I delivered it, but I had to move

520
00:27:47,556 --> 00:27:49,916
Speaker 3: two meters over because there was an obstacle, like disable

521
00:27:50,036 --> 00:27:53,876
Speaker 3: this delivery zone. The plane can come back and say, hey,

522
00:27:53,956 --> 00:27:56,676
Speaker 3: I was doing that, and when I was on my

523
00:27:56,716 --> 00:27:59,556
Speaker 3: way back, I noticed that I was using slightly more

524
00:27:59,596 --> 00:28:02,636
Speaker 3: power than I usually use, like I'm gonna ground myself.

525
00:28:03,476 --> 00:28:06,196
Speaker 3: And sort of there's all these layers, and one of

526
00:28:06,236 --> 00:28:09,196
Speaker 3: those layers is the plane or the pilot can say, hey, like,

527
00:28:09,236 --> 00:28:10,676
Speaker 3: why don't you pull over the side of the road

528
00:28:10,996 --> 00:28:12,356
Speaker 3: so we can we could check on you.

529
00:28:14,036 --> 00:28:16,236
Speaker 2: Uh is there a camera on the plane?

530
00:28:16,436 --> 00:28:17,156
Speaker 3: Yeah, surely.

531
00:28:17,196 --> 00:28:20,516
Speaker 2: Something many people ask you, like, is the drone looking

532
00:28:20,596 --> 00:28:20,796
Speaker 2: at me?

533
00:28:21,156 --> 00:28:24,196
Speaker 3: So the drone is not looking at you. Again, I

534
00:28:24,236 --> 00:28:27,236
Speaker 3: think it's like there's no uh, there's no live feed,

535
00:28:27,516 --> 00:28:29,756
Speaker 3: so it's not like there's like an operator sort of

536
00:28:29,956 --> 00:28:34,156
Speaker 3: interfacing that video. But the aircraft has two sets of

537
00:28:34,356 --> 00:28:38,116
Speaker 3: stereo cameras on the back of it that are used

538
00:28:38,156 --> 00:28:42,716
Speaker 3: for uh so both visual odometry so like a backup

539
00:28:42,756 --> 00:28:47,596
Speaker 3: to GPS, and for like sort of broad scene understanding,

540
00:28:47,636 --> 00:28:49,716
Speaker 3: so like building a depth map of sort of what

541
00:28:49,716 --> 00:28:51,556
Speaker 3: you're flying over. But those are all like that's a

542
00:28:51,596 --> 00:28:55,036
Speaker 3: point cloud, that's not like images of stuff. You know.

543
00:28:55,156 --> 00:28:59,956
Speaker 3: One of the biggest challenges of like residential drone delivery

544
00:29:00,076 --> 00:29:03,196
Speaker 3: is like you're going to you're going from a very

545
00:29:03,236 --> 00:29:07,516
Speaker 3: structured environment to a very unstructured environment. So like like

546
00:29:07,796 --> 00:29:11,276
Speaker 3: the sky is like usually it's very clear, clear of obstacles.

547
00:29:11,316 --> 00:29:14,636
Speaker 3: Somebody's backyard like may not be clear obstacles. There may

548
00:29:14,676 --> 00:29:17,516
Speaker 3: be there may be a tree branch that has grown

549
00:29:18,076 --> 00:29:20,636
Speaker 3: sort of since the last time that sort of satellite

550
00:29:20,676 --> 00:29:24,436
Speaker 3: imagery was refreshed. And so the cameras on board the

551
00:29:24,476 --> 00:29:27,756
Speaker 3: aircraft are used mostly for the reason they're used for

552
00:29:27,876 --> 00:29:31,556
Speaker 3: navigation and for sort of obstacle detection. They run what's

553
00:29:31,956 --> 00:29:34,276
Speaker 3: what are what's called like a bunch of semantic modeling.

554
00:29:34,516 --> 00:29:38,316
Speaker 3: So like if you think about like a toddler putting

555
00:29:38,356 --> 00:29:41,796
Speaker 3: blocks into the little toy, they'll be like triangle goes

556
00:29:41,796 --> 00:29:48,796
Speaker 3: in triangle, circle goes in circle. The plane is like car, tree, house, road, huh.

557
00:29:49,796 --> 00:29:53,356
Speaker 2: Like computer vision, like basic computer visions, computer vision stuff.

558
00:29:53,756 --> 00:29:57,236
Speaker 2: So that one is interesting in that I feel like

559
00:29:57,276 --> 00:30:01,076
Speaker 2: when you started that wasn't nearly as good.

560
00:30:01,156 --> 00:30:03,156
Speaker 3: Right, Yeah, you can do We could do a lot

561
00:30:03,236 --> 00:30:05,116
Speaker 3: more now than then we could at the beginning of

562
00:30:05,156 --> 00:30:09,716
Speaker 3: the program. And like you know, we we can run

563
00:30:09,836 --> 00:30:13,236
Speaker 3: like live classification on like you know, cell phone like

564
00:30:13,276 --> 00:30:13,996
Speaker 3: avion X.

565
00:30:14,316 --> 00:30:16,996
Speaker 2: Yeah, I mean, does does it also do that to

566
00:30:17,036 --> 00:30:19,436
Speaker 2: say like, oh, don't lower the box. There's the dog

567
00:30:19,516 --> 00:30:20,236
Speaker 2: running around the.

568
00:30:20,276 --> 00:30:22,996
Speaker 3: Yard yep, yep, so'll it'll do that. And it'll do

569
00:30:24,436 --> 00:30:29,316
Speaker 3: basically what's what's called delivery zone nudging, so like a

570
00:30:29,356 --> 00:30:32,036
Speaker 3: spot is picked sort of before the plane gets there

571
00:30:32,076 --> 00:30:34,876
Speaker 3: where to lower the box. If the plane is coming down,

572
00:30:34,956 --> 00:30:37,156
Speaker 3: it says, well, where you told me to lower the box.

573
00:30:37,196 --> 00:30:39,996
Speaker 3: There's a car or the tree branch is bigger than

574
00:30:40,316 --> 00:30:43,316
Speaker 3: what you said it was. It can, within a bounded

575
00:30:43,316 --> 00:30:46,316
Speaker 3: set of decisions sort of move it a certain distance

576
00:30:47,116 --> 00:30:49,156
Speaker 3: to drop off the box and then it will tell

577
00:30:49,276 --> 00:30:52,036
Speaker 3: us like, hey, I had a move where the delivery

578
00:30:52,076 --> 00:30:52,556
Speaker 3: zone was.

579
00:30:53,076 --> 00:30:56,036
Speaker 2: How often how often does a delivery fail? Like does

580
00:30:56,036 --> 00:30:57,356
Speaker 2: it get there and it's like, no, this isn't going

581
00:30:57,436 --> 00:30:59,596
Speaker 2: to work. I got to get out here pretty infrequently.

582
00:31:00,036 --> 00:31:05,076
Speaker 2: I mean, like one, it's in the hundreds or thousands. Okay,

583
00:31:05,756 --> 00:31:09,996
Speaker 2: So so big picture, if things go well for drone delivery,

584
00:31:10,036 --> 00:31:11,836
Speaker 2: what will the world look like in say five or

585
00:31:11,836 --> 00:31:12,596
Speaker 2: ten years.

586
00:31:12,956 --> 00:31:16,116
Speaker 3: Yeah. I think at the core of it, if if

587
00:31:16,116 --> 00:31:19,996
Speaker 3: this experiment works right, like if if drne delivery takes off,

588
00:31:19,836 --> 00:31:23,116
Speaker 3: it will be the like primary means that people get

589
00:31:23,316 --> 00:31:25,676
Speaker 3: small goods delivered, So I think that it will be

590
00:31:26,036 --> 00:31:29,876
Speaker 3: it'll be everyday occurrence for the same folks that order

591
00:31:30,076 --> 00:31:32,956
Speaker 3: food every day today. Most of that will be coming

592
00:31:33,196 --> 00:31:37,276
Speaker 3: with airplanes. Because think it just just makes more sense.

593
00:31:38,116 --> 00:31:39,316
Speaker 3: Uh huh.

594
00:31:39,356 --> 00:31:42,156
Speaker 2: What's the version of the future where it doesn't work? Like,

595
00:31:42,196 --> 00:31:43,756
Speaker 2: what are the reasons it might not work?

596
00:31:45,276 --> 00:31:48,436
Speaker 3: I think some of it is if people can actually

597
00:31:48,476 --> 00:31:51,716
Speaker 3: get past the what ifs, like you know, do people

598
00:31:51,836 --> 00:31:56,476
Speaker 3: order frequently enough? Is it a good experience for the partners?

599
00:31:56,476 --> 00:31:59,076
Speaker 3: Like are you integrating well enough into their workflow? Where

600
00:31:59,436 --> 00:32:02,196
Speaker 3: Joon delivery is an asset, not a burden to their

601
00:32:02,276 --> 00:32:05,316
Speaker 3: sort of the day in the life of their associates.

602
00:32:06,556 --> 00:32:08,916
Speaker 3: Are all the companies in the space still around right?

603
00:32:08,956 --> 00:32:11,436
Speaker 3: Like this is like these are really long timelines in

604
00:32:11,516 --> 00:32:13,076
Speaker 3: a challenging funding environment.

605
00:32:14,396 --> 00:32:18,676
Speaker 2: So like, you know, it's really expensive to get to

606
00:32:18,716 --> 00:32:21,116
Speaker 2: a point where the business makes sense to get to scale.

607
00:32:21,956 --> 00:32:27,036
Speaker 3: And then I think I worry sometimes that that folks

608
00:32:27,116 --> 00:32:31,076
Speaker 3: will sty'll sort of chase the long tail of the

609
00:32:31,116 --> 00:32:35,276
Speaker 3: sort of use case. So you know, drones don't have

610
00:32:35,356 --> 00:32:40,436
Speaker 3: to deliver everything, right, and so I worry about sort

611
00:32:40,436 --> 00:32:42,836
Speaker 3: of a lack of focus of like okay, like you know,

612
00:32:42,956 --> 00:32:44,796
Speaker 3: here's a place where drones make a ton of sense

613
00:32:44,796 --> 00:32:48,836
Speaker 3: to deliver stuff. Let's be really successful there rather than like, oh,

614
00:32:48,916 --> 00:32:52,436
Speaker 3: they might be able to deliver you know, the case

615
00:32:52,436 --> 00:32:54,596
Speaker 3: of bowling balls, Like yeah, they might be able to,

616
00:32:54,716 --> 00:32:56,756
Speaker 3: but advan is a much better use case for that.

617
00:32:59,476 --> 00:33:09,756
Speaker 1: We'll be back in a minute with the lightning round.

618
00:33:11,196 --> 00:33:13,396
Speaker 2: So I just want to do a lightning round. I

619
00:33:13,396 --> 00:33:17,436
Speaker 2: appreciate your time. I want to talk about I want

620
00:33:17,436 --> 00:33:21,276
Speaker 2: to talk about your Instagram, Like it's it's stuff like

621
00:33:21,516 --> 00:33:23,916
Speaker 2: I'm looking and like here's like it's a lot of

622
00:33:23,956 --> 00:33:30,396
Speaker 2: Star Wars, like planes like X wing Fighter, and there's

623
00:33:30,436 --> 00:33:32,996
Speaker 2: the X wing Fighter and it's it's actually flying right

624
00:33:33,036 --> 00:33:35,516
Speaker 2: you click on it. And there's the like winged win

625
00:33:35,636 --> 00:33:39,316
Speaker 2: a Bago from space Balls. There's the flying toaster, which

626
00:33:39,356 --> 00:33:41,636
Speaker 2: is like a cut from the it's like the ninety

627
00:33:41,716 --> 00:33:44,556
Speaker 2: screen saver, right, and like so you take these things

628
00:33:44,596 --> 00:33:45,836
Speaker 2: and you actually make.

629
00:33:45,756 --> 00:33:50,356
Speaker 3: Them fly by. So not surprisingly, I'm a bit of

630
00:33:50,396 --> 00:33:55,356
Speaker 3: a nerd, like I like star Wars and sci fi things.

631
00:33:56,436 --> 00:34:02,396
Speaker 3: I always have, and I reached a point where sort

632
00:34:02,436 --> 00:34:05,476
Speaker 3: of both the intersection of technologies and my skill at

633
00:34:05,476 --> 00:34:08,476
Speaker 3: designing airplanes were such that I could make the toys

634
00:34:08,516 --> 00:34:10,876
Speaker 3: that I had as a can work as like real things.

635
00:34:11,156 --> 00:34:13,716
Speaker 2: Right, So you take the like plastic X wing fighter

636
00:34:13,796 --> 00:34:16,796
Speaker 2: that I had in my room, and like I made

637
00:34:16,796 --> 00:34:18,756
Speaker 2: it fly by like throwing it in my hand and

638
00:34:18,956 --> 00:34:21,876
Speaker 2: making the sounds right, and you actually make it fly.

639
00:34:22,036 --> 00:34:24,916
Speaker 3: Yeah, no, it's it's It's also like how I sort

640
00:34:24,956 --> 00:34:30,356
Speaker 3: of continuously sharpened my skills as an engineer. So like

641
00:34:30,516 --> 00:34:33,396
Speaker 3: often they're like really hard airplane design problems of like

642
00:34:33,916 --> 00:34:35,756
Speaker 3: what are the aerodynamics of an X wing?

643
00:34:35,996 --> 00:34:38,356
Speaker 2: So let me ask you on that note, let me

644
00:34:38,396 --> 00:34:41,396
Speaker 2: ask you, like is there a specific thing you learned

645
00:34:41,596 --> 00:34:45,676
Speaker 2: in building these models that you brought to your work

646
00:34:45,716 --> 00:34:46,116
Speaker 2: at Wing.

647
00:34:47,276 --> 00:34:50,756
Speaker 3: I think I've brought a similar philosophy, which is like,

648
00:34:52,516 --> 00:34:54,756
Speaker 3: how do you how do you get to a complex

649
00:34:54,796 --> 00:34:59,156
Speaker 3: result without a complex solution? Where it's like, okay, how

650
00:34:59,156 --> 00:35:01,156
Speaker 3: do I how do I get that same joy? How

651
00:35:01,156 --> 00:35:05,196
Speaker 3: do I get to that same result with a simpler answer? So, uh,

652
00:35:05,716 --> 00:35:07,916
Speaker 3: that's I think that that's that's how I approach my

653
00:35:07,996 --> 00:35:09,116
Speaker 3: professional life as well.

654
00:35:09,836 --> 00:35:11,956
Speaker 2: You got a white whale. Is there something you want

655
00:35:12,036 --> 00:35:14,236
Speaker 2: to build that flies that you haven't been able to do?

656
00:35:14,436 --> 00:35:17,116
Speaker 3: I have always wanted to do a tie interceptor. This

657
00:35:17,236 --> 00:35:19,556
Speaker 3: is always my favorite star warship. But there's like not

658
00:35:19,716 --> 00:35:22,076
Speaker 3: much in the way of wing on that.

659
00:35:22,436 --> 00:35:23,156
Speaker 2: Who flew that?

660
00:35:23,396 --> 00:35:23,716
Speaker 3: Was that?

661
00:35:23,756 --> 00:35:29,596
Speaker 2: The the good guys? Okay, right, so it's like what

662
00:35:29,636 --> 00:35:32,956
Speaker 2: the storm Troopers flew? Sort of a variation on that.

663
00:35:33,276 --> 00:35:35,116
Speaker 2: You built one of those that goes in the water

664
00:35:35,716 --> 00:35:36,716
Speaker 2: some some version of that.

665
00:35:36,836 --> 00:35:37,396
Speaker 3: Yeah. I saw that.

666
00:35:37,436 --> 00:35:38,716
Speaker 2: I was like, does that fly? And then I saw

667
00:35:38,716 --> 00:35:39,196
Speaker 2: that it was in the.

668
00:35:39,876 --> 00:35:42,396
Speaker 3: Like every probably every four years, I get in the

669
00:35:42,476 --> 00:35:45,356
Speaker 3: submarines and I'll like build some submarine stuff and then

670
00:35:45,356 --> 00:35:46,796
Speaker 3: I'll put it on the shelf.

671
00:35:51,916 --> 00:35:56,516
Speaker 2: So I feel like I'm I'm moving on from what

672
00:35:56,556 --> 00:36:01,796
Speaker 2: you built now. Just to be clear, the I feel

673
00:36:01,796 --> 00:36:07,356
Speaker 2: like the word drone is is not doing drones any favors, right,

674
00:36:07,396 --> 00:36:09,636
Speaker 2: I feel like it has a lot of negative notations.

675
00:36:09,636 --> 00:36:12,396
Speaker 2: There's like a militaristic connotation. There's the connotation of like

676
00:36:12,716 --> 00:36:16,156
Speaker 2: a worker who is unfeeling and doesn't do anything. Is

677
00:36:16,196 --> 00:36:18,156
Speaker 2: there a word that you think would be better?

678
00:36:19,356 --> 00:36:22,476
Speaker 3: I mean at this point, I think that that that

679
00:36:22,636 --> 00:36:25,836
Speaker 3: ship is long since sailed in his left board. I mean,

680
00:36:25,836 --> 00:36:28,036
Speaker 3: there was like a there's been a South Park episode

681
00:36:28,036 --> 00:36:31,636
Speaker 3: about it, Like I don't think that like like uh so,

682
00:36:32,316 --> 00:36:34,236
Speaker 3: I don't know. I think it's it's a word. I

683
00:36:34,236 --> 00:36:37,116
Speaker 3: don't think you should ever be afraid of of of

684
00:36:37,156 --> 00:36:40,916
Speaker 3: the word. And at the core of it, like I

685
00:36:40,916 --> 00:36:42,876
Speaker 3: don't know, I think of them all as airplanes, Like

686
00:36:43,036 --> 00:36:45,636
Speaker 3: they fly around with other airplanes, like they need to

687
00:36:45,676 --> 00:36:50,436
Speaker 3: do airplane stuff. And I think that like part of

688
00:36:50,476 --> 00:36:52,756
Speaker 3: the reason that the skepticism that that you brought up

689
00:36:52,756 --> 00:36:56,476
Speaker 3: earlier exists is the sort of the gap between the

690
00:36:56,516 --> 00:36:59,356
Speaker 3: sort of promise and the reality. And so you know,

691
00:36:59,636 --> 00:37:03,756
Speaker 3: the the sooner that we can get these services sort

692
00:37:03,796 --> 00:37:09,556
Speaker 3: of real and live and interacting with more people. I

693
00:37:09,636 --> 00:37:12,676
Speaker 3: think that people will just look at these as tools

694
00:37:12,716 --> 00:37:15,276
Speaker 3: that are flying around providing a service. And my I've

695
00:37:15,276 --> 00:37:17,556
Speaker 3: always I tell the team frequently, I like, I want

696
00:37:17,596 --> 00:37:20,156
Speaker 3: people to look at the plane and think of it

697
00:37:20,196 --> 00:37:22,596
Speaker 3: like a shopping cart, and it's just like it's a

698
00:37:22,636 --> 00:37:24,876
Speaker 3: thing that's very useful. People use them all the time,

699
00:37:25,236 --> 00:37:27,556
Speaker 3: but you don't really give it a second thought, and

700
00:37:28,076 --> 00:37:30,156
Speaker 3: it's just that it's an asset that you use.

701
00:37:32,756 --> 00:37:36,756
Speaker 2: Adam Woodworth is the CEO of Wing. Today's show was

702
00:37:36,756 --> 00:37:39,636
Speaker 2: produced by Gabriel Hunter Chang. It was edited by Lydia

703
00:37:39,676 --> 00:37:41,596
Speaker 2: Jean Kott and engineered.

704
00:37:41,076 --> 00:37:42,036
Speaker 3: By Sarah Bruguer.

705
00:37:42,916 --> 00:37:47,756
Speaker 2: Please email us we are at problem at pushkin dot fm.

706
00:37:48,196 --> 00:37:50,476
Speaker 2: Let us know would interview on the show, how to

707
00:37:50,476 --> 00:37:53,996
Speaker 2: make the show better, et cetera. I'm Jacob Boldstein and

708
00:37:54,036 --> 00:37:56,316
Speaker 2: we'll be back next week with another episode of What's

709
00:37:56,316 --> 00:38:03,596
Speaker 2: Your Problem