1 00:00:15,316 --> 00:00:26,076 Speaker 1: Pushkin. I'm Jacob Goldstein and this is What's Your Problem, 2 00:00:26,316 --> 00:00:29,436 Speaker 1: the show where we talk to entrepreneurs and engineers about 3 00:00:29,476 --> 00:00:31,876 Speaker 1: the future they're going to build once they solve a 4 00:00:31,916 --> 00:00:36,276 Speaker 1: few problems. My guest today is Keenan Wirobek. He's the 5 00:00:36,356 --> 00:00:39,596 Speaker 1: co founder of the drone delivery company zip Line, and 6 00:00:39,676 --> 00:00:42,876 Speaker 1: he has a message for the world. The drones are coming. 7 00:00:43,996 --> 00:00:46,436 Speaker 1: There's going to be more planes and flying cars flying 8 00:00:46,476 --> 00:00:48,156 Speaker 1: the airspace in twenty years by a factor of one 9 00:00:48,236 --> 00:00:50,076 Speaker 1: hundred than there are aircraft flying in the air today, 10 00:00:50,836 --> 00:00:55,036 Speaker 1: flying taxis, aerial pizza delivery. It could all be coming. 11 00:00:55,396 --> 00:00:59,236 Speaker 1: In fact, Keenan's company, zip Line is already doing hundreds 12 00:00:59,236 --> 00:01:03,316 Speaker 1: of drone deliveries a day every day in Rwanda and Ghana. 13 00:01:03,396 --> 00:01:06,116 Speaker 1: But the company has come up against a really interesting, 14 00:01:06,196 --> 00:01:09,676 Speaker 1: kind of surprising problem as it tries to expand the US. 15 00:01:10,236 --> 00:01:13,636 Speaker 1: It's not really a technological problem. It's more a problem 16 00:01:13,676 --> 00:01:16,836 Speaker 1: about the way America thinks about airspace, about the way 17 00:01:16,876 --> 00:01:20,556 Speaker 1: we regulate the sky itself, and this problem it goes 18 00:01:20,596 --> 00:01:22,956 Speaker 1: back to the early days of flight, but it also 19 00:01:23,076 --> 00:01:27,396 Speaker 1: has a huge impact on the present right now. Keenan's 20 00:01:27,436 --> 00:01:30,116 Speaker 1: a robotics engineer by training, and by the time he 21 00:01:30,156 --> 00:01:33,236 Speaker 1: co founded zip Line back in twenty fourteen, he'd already 22 00:01:33,276 --> 00:01:36,236 Speaker 1: worked on a few successful projects. So he was at 23 00:01:36,236 --> 00:01:38,676 Speaker 1: this moment when he could really think hard about what 24 00:01:38,756 --> 00:01:41,836 Speaker 1: his next big thing should be. And he told me 25 00:01:41,996 --> 00:01:44,956 Speaker 1: he went around looking for a problem to solve, kept 26 00:01:44,956 --> 00:01:47,596 Speaker 1: coming up with ideas, but when he went and asked 27 00:01:47,676 --> 00:01:50,436 Speaker 1: experts in the real world, is this a problem, they'd 28 00:01:50,436 --> 00:01:54,036 Speaker 1: be like, actually, no, that is not really a problem 29 00:01:54,076 --> 00:01:57,596 Speaker 1: for us. Finally, his wife pointed him in a new direction. 30 00:01:59,076 --> 00:02:02,036 Speaker 1: My wife's an epidemiologist, and she was telling me to 31 00:02:02,116 --> 00:02:05,756 Speaker 1: see these stories about health campaigns, you know, vaccine campaigns, 32 00:02:06,036 --> 00:02:08,316 Speaker 1: they just get stuck on logistics, and so of course 33 00:02:08,316 --> 00:02:10,716 Speaker 1: the wheels are turning. It's like, okay, maybe drones and 34 00:02:10,876 --> 00:02:12,956 Speaker 1: that actually that that seems like maybe there's a there's 35 00:02:12,956 --> 00:02:14,956 Speaker 1: a real problem to solve here that people are going 36 00:02:14,996 --> 00:02:17,796 Speaker 1: to really care about. Um. But at the same time, 37 00:02:17,796 --> 00:02:19,756 Speaker 1: I will learn you I'm a very skeptical person, so 38 00:02:19,796 --> 00:02:21,676 Speaker 1: it's like, Okay, I'm gonna dig into this, We're gonna 39 00:02:21,676 --> 00:02:23,316 Speaker 1: go learn about this, and I'm just sure there's gonna 40 00:02:23,316 --> 00:02:25,476 Speaker 1: be a thousand reasons why you know, they're never gonna work. 41 00:02:25,796 --> 00:02:28,236 Speaker 1: We can't ever solve this problem. Uh, And so we 42 00:02:28,236 --> 00:02:30,796 Speaker 1: spend a bunch of time and intential America, where my 43 00:02:30,836 --> 00:02:34,796 Speaker 1: wife is from. In Africa, we visited this one medical 44 00:02:34,836 --> 00:02:38,956 Speaker 1: supply warehouse in Tanzania, and outside the warehouse as far 45 00:02:38,956 --> 00:02:42,196 Speaker 1: as you could see, you know, football fields of palette stacked, 46 00:02:42,316 --> 00:02:45,276 Speaker 1: you know, two stories high in places. We're just outside 47 00:02:45,276 --> 00:02:47,596 Speaker 1: this warehouse. We're like, what's why do you have all 48 00:02:47,596 --> 00:02:50,556 Speaker 1: these medical supplies you know, vaccines, pharmaceuticals, other things. Why 49 00:02:50,556 --> 00:02:52,516 Speaker 1: are they outside? And you know, one of the people 50 00:02:52,516 --> 00:02:54,356 Speaker 1: in the delegation sort of quietly because they were kind 51 00:02:54,356 --> 00:02:57,276 Speaker 1: of embarrassed about it, they're like, yeah, that's all expired medicine. 52 00:02:57,396 --> 00:02:59,356 Speaker 1: That was one of those like moments where it clicked 53 00:02:59,356 --> 00:03:02,756 Speaker 1: of like, Okay, supply is actually not the big problem. 54 00:03:02,996 --> 00:03:06,876 Speaker 1: There's actually something much more practical around around how to run, 55 00:03:06,996 --> 00:03:08,556 Speaker 1: you know, how to get this supply from you know, 56 00:03:08,596 --> 00:03:11,836 Speaker 1: point a these warehouses to these doctors. That was one 57 00:03:11,876 --> 00:03:13,996 Speaker 1: of the experiences that kind of just like the bit 58 00:03:14,036 --> 00:03:16,476 Speaker 1: flipped in my head from like this is probably not 59 00:03:16,516 --> 00:03:19,196 Speaker 1: a problem we can solve to like, holy shit, we 60 00:03:19,276 --> 00:03:21,716 Speaker 1: have to solve this problem. And it just became really 61 00:03:21,716 --> 00:03:24,596 Speaker 1: clear you could leap frog over all these factors by 62 00:03:24,716 --> 00:03:27,036 Speaker 1: doing this with drones in an on demand way. So 63 00:03:27,076 --> 00:03:30,996 Speaker 1: this is the rare instance where a robot can solve 64 00:03:31,036 --> 00:03:33,436 Speaker 1: a big important problem in the world that the people 65 00:03:33,836 --> 00:03:36,436 Speaker 1: dealing with the problem actually agree is a big important 66 00:03:36,476 --> 00:03:39,636 Speaker 1: problem exactly. And I'd say that that people agreeing it's 67 00:03:39,676 --> 00:03:42,716 Speaker 1: important problem was another big part of my concern. Right, 68 00:03:42,876 --> 00:03:45,116 Speaker 1: Like in Silicon Valley, we like to use the word 69 00:03:45,156 --> 00:03:47,676 Speaker 1: disruption as a good word. Right, you walk into a 70 00:03:47,756 --> 00:03:51,236 Speaker 1: health system, a national health system of a country and say, 71 00:03:51,436 --> 00:03:55,636 Speaker 1: let's disrupt this, Like nobody is exciting. Yeah, everybody's like, 72 00:03:55,796 --> 00:03:58,556 Speaker 1: here's the door. We're busy. You're like, go' disrupt somebody else, 73 00:03:58,556 --> 00:03:59,956 Speaker 1: Like we have a job to do. I was very 74 00:03:59,996 --> 00:04:01,916 Speaker 1: worried that there just wasn't going to be an appetite 75 00:04:01,916 --> 00:04:05,956 Speaker 1: for change in these health systems. But really the opposite happened, 76 00:04:06,036 --> 00:04:08,356 Speaker 1: where we got started getting to know these health systems 77 00:04:08,356 --> 00:04:10,516 Speaker 1: and the ministers of health in these countries. And I 78 00:04:10,556 --> 00:04:13,476 Speaker 1: still remember the first interaction with the Minister of health 79 00:04:13,516 --> 00:04:15,756 Speaker 1: in Rwanda. She said, Okay, you've got two weeks. You know, 80 00:04:15,836 --> 00:04:18,636 Speaker 1: we've got all the data, like you've been modeling how 81 00:04:18,676 --> 00:04:20,636 Speaker 1: a drone system, like this could work in a health system. 82 00:04:20,876 --> 00:04:23,276 Speaker 1: Put together the case, what's the health impact, what's the 83 00:04:23,316 --> 00:04:25,676 Speaker 1: economic impact, and then we'll go from there, and that 84 00:04:25,716 --> 00:04:28,516 Speaker 1: was just like amazing. The rest is of course history. 85 00:04:28,556 --> 00:04:30,676 Speaker 1: The case was really compelling on the health side and 86 00:04:30,756 --> 00:04:35,356 Speaker 1: the economic side, and they became our first customer. And specifically, 87 00:04:35,396 --> 00:04:38,476 Speaker 1: what is the ask, what is the job? The job 88 00:04:38,516 --> 00:04:42,396 Speaker 1: from Rwanda is deliver blood on demand. The obvious answer 89 00:04:42,396 --> 00:04:44,396 Speaker 1: in the early days like, okay, cool, which drone are 90 00:04:44,396 --> 00:04:45,796 Speaker 1: we going to buy? So went out to all the 91 00:04:45,876 --> 00:04:47,756 Speaker 1: drone companies they could make a drone that could do 92 00:04:47,796 --> 00:04:51,596 Speaker 1: what we wanted. And this was an incredibly frustrating journey 93 00:04:51,636 --> 00:04:54,636 Speaker 1: because the best quote I got for a drone was 94 00:04:54,796 --> 00:04:57,916 Speaker 1: two hundred thousand dollars per drone with a two hundred 95 00:04:57,916 --> 00:05:00,356 Speaker 1: flight warranty if I didn't fly it in the rain. 96 00:05:02,676 --> 00:05:04,516 Speaker 1: And it was like and obviously the economics of that 97 00:05:04,556 --> 00:05:06,516 Speaker 1: are just like don't work at all. And you know, 98 00:05:06,556 --> 00:05:08,916 Speaker 1: the customers want delivery all the time when it's waning 99 00:05:08,956 --> 00:05:11,436 Speaker 1: or this was all really clear and it just became 100 00:05:11,956 --> 00:05:14,876 Speaker 1: this is one of those wake up call moments of like, oh, 101 00:05:14,956 --> 00:05:17,916 Speaker 1: you gotta do this yourself. Um, and getting this first 102 00:05:18,036 --> 00:05:20,236 Speaker 1: product service off the ground for this customer is going 103 00:05:20,276 --> 00:05:22,316 Speaker 1: to be a much bigger lift than than you thought. 104 00:05:22,996 --> 00:05:25,196 Speaker 1: So you realize you're going to have to build your 105 00:05:25,196 --> 00:05:27,836 Speaker 1: own drones from scratch. And one of the things that's 106 00:05:27,876 --> 00:05:30,076 Speaker 1: interesting to me about this part of the story is 107 00:05:30,076 --> 00:05:33,276 Speaker 1: is it right you wind up basically using iPhone parts. 108 00:05:33,556 --> 00:05:36,276 Speaker 1: So the sensors, many of the sensors that make the 109 00:05:36,356 --> 00:05:38,876 Speaker 1: drone fly, Um, you know, these are the same sensors 110 00:05:38,916 --> 00:05:41,636 Speaker 1: that are in your phone. Uh, And that the tech 111 00:05:41,796 --> 00:05:44,076 Speaker 1: like whether or not you know what orientation your phone 112 00:05:44,116 --> 00:05:46,516 Speaker 1: is started for your video is like, so your phone 113 00:05:46,556 --> 00:05:48,876 Speaker 1: knows the videos should be sideways, are playing those which 114 00:05:48,916 --> 00:05:50,476 Speaker 1: way is up? And how to fly without you know, 115 00:05:50,476 --> 00:05:52,716 Speaker 1: falling out of the sky. And it's truly the same 116 00:05:52,716 --> 00:05:56,516 Speaker 1: basically the same sensors. Oh yeah, made by the same companies. 117 00:05:56,716 --> 00:06:00,036 Speaker 1: Like yeah, what if there are others? Can you just 118 00:06:00,076 --> 00:06:02,436 Speaker 1: like rattle off like, oh, sure, what sensors that are 119 00:06:02,436 --> 00:06:05,716 Speaker 1: in my iPhone more or less are in your drones? Yeah? 120 00:06:05,756 --> 00:06:09,076 Speaker 1: So GPS, Uh, the cell modems that are in your 121 00:06:09,516 --> 00:06:12,156 Speaker 1: we have in our drones. Even the basically the processors 122 00:06:12,196 --> 00:06:14,596 Speaker 1: that are in your phone, we use very similar technology 123 00:06:14,636 --> 00:06:16,996 Speaker 1: processing cheap more or less similar exactly. That they're so 124 00:06:17,076 --> 00:06:21,116 Speaker 1: power efficient and they're so capable. It's amazing to me. 125 00:06:21,236 --> 00:06:24,076 Speaker 1: I guess in part because you know, I've gotten used 126 00:06:24,076 --> 00:06:29,916 Speaker 1: to thinking about giant businesses like I don't know, Uber 127 00:06:30,516 --> 00:06:34,436 Speaker 1: or Instagram that like, okay, I guess that those you 128 00:06:34,476 --> 00:06:37,276 Speaker 1: couldn't have without the iPhone, right, that is intuitive to me. 129 00:06:37,836 --> 00:06:40,196 Speaker 1: But the idea that, like, you know, a company sending 130 00:06:40,276 --> 00:06:43,956 Speaker 1: drones across sub Saharan Africa to deliver blood, that that 131 00:06:44,116 --> 00:06:47,316 Speaker 1: is also built on the iPhone is wild. Like you 132 00:06:47,396 --> 00:06:50,356 Speaker 1: needed the cell phone the smartphone revolution. You needed the 133 00:06:50,356 --> 00:06:53,156 Speaker 1: iPhone to have come along and made all these components 134 00:06:53,636 --> 00:06:57,676 Speaker 1: super cheap, super reliable, super smart exactly. So I want 135 00:06:57,716 --> 00:07:00,036 Speaker 1: to try. I want to just talk through in some detail, 136 00:07:00,076 --> 00:07:02,636 Speaker 1: how like one on what do you call it delivery? 137 00:07:02,636 --> 00:07:06,036 Speaker 1: I guess how one delivery works. So some doctor or 138 00:07:06,156 --> 00:07:11,996 Speaker 1: nurse needs something in their hospital. What happens? Yeah, so 139 00:07:12,076 --> 00:07:14,756 Speaker 1: a doctor or nurse needs something, they place their order 140 00:07:14,876 --> 00:07:16,476 Speaker 1: right And by the way, we're really flexible there. They 141 00:07:16,476 --> 00:07:18,876 Speaker 1: can use an app, they can use their phone, they 142 00:07:18,876 --> 00:07:20,996 Speaker 1: can use WhatsApp, they can pick up the phone and 143 00:07:21,036 --> 00:07:24,116 Speaker 1: call us, whatever's easy for them. So our team they're 144 00:07:24,236 --> 00:07:25,556 Speaker 1: they're gonna get the unit of blood out of the 145 00:07:25,636 --> 00:07:28,156 Speaker 1: freezer or fridge. They're gonna get the unit off the shelf, 146 00:07:28,796 --> 00:07:31,116 Speaker 1: they're gonna pack it up, put it into one of 147 00:07:31,156 --> 00:07:34,596 Speaker 1: the drones. The drone gets put into a launcher. And 148 00:07:34,756 --> 00:07:37,356 Speaker 1: I'm gonna pause you there because we have a video 149 00:07:37,676 --> 00:07:39,756 Speaker 1: and I know we're like watching videos on a podcast 150 00:07:39,836 --> 00:07:42,236 Speaker 1: is a questionable move, but let's try it, because like 151 00:07:42,276 --> 00:07:44,996 Speaker 1: I do want to see it. Right, it's a it's yeah, 152 00:07:45,036 --> 00:07:48,076 Speaker 1: it's cool. So you ready, I'm gonna you push play too, Okay, ready, 153 00:07:48,516 --> 00:07:52,076 Speaker 1: go all right? Okay, So, so somebody is loading it 154 00:07:52,396 --> 00:07:54,676 Speaker 1: looks like a plane, a plane about the size of 155 00:07:54,716 --> 00:07:59,196 Speaker 1: a person, onto some kind of a launcher right onto 156 00:07:59,276 --> 00:08:03,796 Speaker 1: like a ramp exactly. Well, there's propellers. The propellers are spinning, 157 00:08:04,836 --> 00:08:08,636 Speaker 1: I like your narration. And then there's a guy. What's 158 00:08:08,636 --> 00:08:10,796 Speaker 1: the guy there doing? Oh, it just launched. He just 159 00:08:10,876 --> 00:08:14,076 Speaker 1: launched it. Yeah, wingspans about ten feet so picture. Yeah, 160 00:08:14,076 --> 00:08:17,156 Speaker 1: it's like a big RC plane. Okay, a big remote 161 00:08:17,156 --> 00:08:20,036 Speaker 1: control plane. And by the way, I mean, it's not 162 00:08:20,116 --> 00:08:22,316 Speaker 1: in fact remote controlled, right, Like what does it is? 163 00:08:22,316 --> 00:08:24,756 Speaker 1: It actually just flying on its own? Yeah, so it 164 00:08:25,076 --> 00:08:27,636 Speaker 1: is flying it's flying automatically all the way out to 165 00:08:27,636 --> 00:08:31,156 Speaker 1: the delivery site. Does that mean there are people whose 166 00:08:31,236 --> 00:08:33,436 Speaker 1: job is to sit somewhere at the warehouse fan in 167 00:08:33,516 --> 00:08:37,116 Speaker 1: office and like look at what a camera from to 168 00:08:37,276 --> 00:08:39,156 Speaker 1: basically do air traffic control, to look at what all 169 00:08:39,156 --> 00:08:41,516 Speaker 1: the drones are doing and make sure that exactly So 170 00:08:41,556 --> 00:08:44,076 Speaker 1: we call our drones zips, and we call those people 171 00:08:44,196 --> 00:08:47,236 Speaker 1: ZIP controllers. Their job is very similar to air traffic control. 172 00:08:47,316 --> 00:08:49,876 Speaker 1: And do they generally have to do anything or do 173 00:08:49,956 --> 00:08:52,636 Speaker 1: the drones take care of themselves? The drones take care 174 00:08:52,676 --> 00:08:55,836 Speaker 1: of themselves. Okay, so here, let's keep watching. So now 175 00:08:56,476 --> 00:08:59,356 Speaker 1: now that drone is going to make the drop. First 176 00:08:59,396 --> 00:09:00,876 Speaker 1: of all, you have to picture a package. So picture 177 00:09:01,156 --> 00:09:05,516 Speaker 1: a cake box, right size package with a paper parachute 178 00:09:05,516 --> 00:09:07,636 Speaker 1: on it that's in the belly of this drone. And 179 00:09:07,716 --> 00:09:11,196 Speaker 1: so the drone flies over the delivery site and when 180 00:09:11,196 --> 00:09:13,476 Speaker 1: it drops it, that paper parachute will inflate and the 181 00:09:13,516 --> 00:09:16,396 Speaker 1: package drifts to the ground a little bit like a cartoon, 182 00:09:16,516 --> 00:09:19,516 Speaker 1: is how I That's how I'm watching it right now. Yeah, 183 00:09:19,516 --> 00:09:23,196 Speaker 1: it worked, It worked. It looks kind of fast, it's 184 00:09:23,196 --> 00:09:25,316 Speaker 1: coming down kind of fast. Yeah, yeah, it's it does 185 00:09:25,356 --> 00:09:27,396 Speaker 1: come down fast. It's a This is the fun of 186 00:09:27,396 --> 00:09:29,956 Speaker 1: the engineering challenge here. If you come down really slowly, 187 00:09:31,036 --> 00:09:35,556 Speaker 1: that accuracy that basically goes gets worse because the wind 188 00:09:35,556 --> 00:09:38,636 Speaker 1: can blow it to the side. More basic, exactly exactly 189 00:09:38,756 --> 00:09:40,556 Speaker 1: if it hit you on the head, it looks like 190 00:09:40,596 --> 00:09:43,076 Speaker 1: it would hurt. I have been a test subject of 191 00:09:43,116 --> 00:09:45,996 Speaker 1: this intentionally to make sure someone who has to do 192 00:09:46,036 --> 00:09:47,436 Speaker 1: it under it. So it hit you on the head. 193 00:09:47,516 --> 00:09:49,556 Speaker 1: Is that what you're telling me? You know what's happening. 194 00:09:49,796 --> 00:09:52,676 Speaker 1: I live to tell the tale. So okay, I'm more seriously, 195 00:09:52,876 --> 00:09:55,276 Speaker 1: has anybody ever gotten hurt by one of your drones? No, 196 00:09:55,276 --> 00:09:57,036 Speaker 1: No one's gotten hurt by one of our drones. But 197 00:09:57,076 --> 00:09:59,316 Speaker 1: there's a lot of engineering work that goes into really 198 00:09:59,356 --> 00:10:01,956 Speaker 1: minimizing the chances that you can get hurt by a drone. Okay, 199 00:10:02,116 --> 00:10:04,556 Speaker 1: tell me about the end of the flight. It doesn't 200 00:10:04,676 --> 00:10:06,676 Speaker 1: land in the way one would think of a little 201 00:10:06,716 --> 00:10:09,676 Speaker 1: plane landing. It doesn't land it. Yeah, So there's like 202 00:10:09,716 --> 00:10:12,676 Speaker 1: two arms sticking into the air. There's two poles sticking 203 00:10:12,676 --> 00:10:14,676 Speaker 1: into the air, and those poles are on motors. Okay, 204 00:10:14,676 --> 00:10:16,636 Speaker 1: so they move up and down, but basically you know 205 00:10:16,636 --> 00:10:20,676 Speaker 1: they're on motors. Between those two poles. Is a string, okay, 206 00:10:20,996 --> 00:10:23,716 Speaker 1: really small string okay. And basically what's happening is our 207 00:10:23,836 --> 00:10:27,036 Speaker 1: drone flies between these two poles and at the last second, 208 00:10:27,076 --> 00:10:29,436 Speaker 1: look the last fraction of a second. Yeah, if everything 209 00:10:29,476 --> 00:10:32,156 Speaker 1: looks good, those poles, the motors on those poles will 210 00:10:32,156 --> 00:10:35,276 Speaker 1: snap those polls up, so the line flings into the 211 00:10:35,316 --> 00:10:39,356 Speaker 1: tailhook of the plane, capturing the plane and that's how 212 00:10:39,356 --> 00:10:45,556 Speaker 1: it lands. That is amazing in a minute, the truly 213 00:10:45,596 --> 00:10:48,356 Speaker 1: surprising reason that it's harder to build a drone business 214 00:10:48,436 --> 00:10:56,076 Speaker 1: in the United States than in Rwanda. Now, let's get 215 00:10:56,116 --> 00:10:59,876 Speaker 1: back to what's your problem. Zipline expanded from Rwanda to 216 00:10:59,916 --> 00:11:02,276 Speaker 1: Ghana a few years ago and now delivers lots of 217 00:11:02,316 --> 00:11:06,316 Speaker 1: medical supplies across both countries. It's like a normal routine 218 00:11:06,356 --> 00:11:09,236 Speaker 1: thing there, hundreds of flights a day every day. But 219 00:11:09,236 --> 00:11:12,316 Speaker 1: the company is just starting to expand into the United States. 220 00:11:12,596 --> 00:11:14,716 Speaker 1: So far, ziplanes work in this country is limited to 221 00:11:14,756 --> 00:11:17,876 Speaker 1: a few pilot projects. They're delivering medical supplies for a 222 00:11:17,916 --> 00:11:21,036 Speaker 1: hospital system in North Carolina. They're also flying stuff like 223 00:11:21,116 --> 00:11:24,596 Speaker 1: bandages and over the counter medicine to Walmart customers in 224 00:11:24,676 --> 00:11:28,196 Speaker 1: rural Arkansas. And in their work in the United States, 225 00:11:28,436 --> 00:11:32,396 Speaker 1: Zipline is facing one particularly hard problem. A lot of 226 00:11:32,396 --> 00:11:36,676 Speaker 1: the challenge comes down to the regulatory environment. In the US, 227 00:11:36,836 --> 00:11:39,436 Speaker 1: our airspace is very old fashioned. We have a philosophy 228 00:11:39,476 --> 00:11:41,116 Speaker 1: here in the US and the airspace where we kind 229 00:11:41,116 --> 00:11:45,676 Speaker 1: of grandfather everything in so not absolutely everything, but mostly everything. 230 00:11:45,716 --> 00:11:47,276 Speaker 1: A lot of things you could do in the forties 231 00:11:47,356 --> 00:11:49,356 Speaker 1: you can still do in the airspace today, and that 232 00:11:49,396 --> 00:11:51,876 Speaker 1: makes things very complicated. Most other countries, basically the way 233 00:11:51,916 --> 00:11:54,076 Speaker 1: they talk about it is, say we have modernized our airspace. 234 00:11:54,116 --> 00:11:57,116 Speaker 1: We've required things like transponders so all planes can tell 235 00:11:57,356 --> 00:11:59,356 Speaker 1: by radio where all the other planes are. We don't 236 00:11:59,356 --> 00:12:01,156 Speaker 1: require that here in So you're telling me there's some 237 00:12:01,236 --> 00:12:03,876 Speaker 1: device that you can put in a plane that allows 238 00:12:03,916 --> 00:12:06,436 Speaker 1: all other planes to know that plane is there, and 239 00:12:06,436 --> 00:12:07,956 Speaker 1: in the US you don't have to have that in 240 00:12:07,996 --> 00:12:10,756 Speaker 1: your plane. That is correct and as crazy as it sounds. 241 00:12:10,876 --> 00:12:14,956 Speaker 1: And so in terms of like regulating airspace, like Ghana 242 00:12:14,996 --> 00:12:17,596 Speaker 1: and Rwanda are doing sort of sensible modern things that 243 00:12:17,636 --> 00:12:20,996 Speaker 1: the US is not doing. That's exactly right, and that 244 00:12:21,036 --> 00:12:24,796 Speaker 1: makes their airspace essentially much simpler to integrate drones into 245 00:12:25,476 --> 00:12:28,436 Speaker 1: versus here in the US. Tell me what other problems 246 00:12:28,436 --> 00:12:30,676 Speaker 1: are you trying to solve what's a technical one that's 247 00:12:30,716 --> 00:12:34,236 Speaker 1: interesting when we're working on that that's extraordinarily hard, which is, 248 00:12:34,796 --> 00:12:37,716 Speaker 1: this comes down to operating in airspaces like the United States, 249 00:12:37,716 --> 00:12:41,196 Speaker 1: where you have planes flying around that don't have you know, 250 00:12:41,236 --> 00:12:43,436 Speaker 1: a radio transponder that tells you where they are, and 251 00:12:43,476 --> 00:12:46,076 Speaker 1: so you have to have sensing on the drone that 252 00:12:46,236 --> 00:12:50,076 Speaker 1: directly senses where these other aircraft are hard to avoid. Okay, 253 00:12:50,436 --> 00:12:52,036 Speaker 1: and this is something that's very hard to do for 254 00:12:52,076 --> 00:12:55,796 Speaker 1: a bunch of reasons. We tried radar and radar that 255 00:12:55,836 --> 00:12:58,356 Speaker 1: can see in all directions. It just you literally need 256 00:12:58,436 --> 00:13:01,676 Speaker 1: hundreds of pounds of radar equipment to see far enough 257 00:13:01,676 --> 00:13:04,876 Speaker 1: in all directions, which of course there drones don't weigh 258 00:13:04,916 --> 00:13:08,076 Speaker 1: hundreds of pounds to begin with. And camera is the 259 00:13:08,116 --> 00:13:10,476 Speaker 1: same problem. So many cameras with so many lenses and 260 00:13:10,516 --> 00:13:13,116 Speaker 1: so many you know, pixels if you will see that, 261 00:13:13,356 --> 00:13:15,116 Speaker 1: you know, that speck in the air, and of course 262 00:13:15,156 --> 00:13:17,316 Speaker 1: cameras they just don't work when it's cloudy, which is 263 00:13:17,956 --> 00:13:19,636 Speaker 1: you know, a big deal. So basically you've had to 264 00:13:19,636 --> 00:13:22,476 Speaker 1: do a sensor technology development from the ground up for this, 265 00:13:22,556 --> 00:13:26,076 Speaker 1: and it's it's something that's been really challenging and really 266 00:13:26,276 --> 00:13:29,116 Speaker 1: really exciting because if we can solve this problem, it'll 267 00:13:29,236 --> 00:13:32,436 Speaker 1: enable scaled operations for drones, you know, around the world. 268 00:13:33,196 --> 00:13:36,796 Speaker 1: So how do you solve it? Are you getting closer? 269 00:13:36,836 --> 00:13:39,356 Speaker 1: We're getting a lot closer. And this is I have 270 00:13:39,396 --> 00:13:41,236 Speaker 1: to tease here because the actual thing I can't talk 271 00:13:41,236 --> 00:13:44,196 Speaker 1: about quite. It's a secret because of like intellectual property, 272 00:13:44,236 --> 00:13:46,356 Speaker 1: because you're going to try and plent it, literally because 273 00:13:46,396 --> 00:13:48,876 Speaker 1: of intellectual property, because we're gonna because we're trying to 274 00:13:48,876 --> 00:13:51,036 Speaker 1: patent it. So let me ask a question. If you 275 00:13:51,076 --> 00:13:53,156 Speaker 1: haven't solved this problem yet, how are you able to 276 00:13:53,196 --> 00:13:55,796 Speaker 1: fly in the US? Yeah? So in the US, and 277 00:13:55,876 --> 00:13:58,036 Speaker 1: this is true of all drone operators in the US. 278 00:13:58,196 --> 00:14:01,516 Speaker 1: Even even everybody who flies drones in the US is 279 00:14:01,556 --> 00:14:05,636 Speaker 1: doing exactly this thing I'm gonna describe, which is not sophisticated. 280 00:14:05,716 --> 00:14:09,756 Speaker 1: There are people along those routes looking at the sky. Wow. 281 00:14:09,836 --> 00:14:12,556 Speaker 1: So wherever your drones flood, you have people who are 282 00:14:12,596 --> 00:14:14,796 Speaker 1: your employees. They are getting paid by the hour to 283 00:14:14,956 --> 00:14:18,636 Speaker 1: look at the sky and what text or something if 284 00:14:18,636 --> 00:14:20,716 Speaker 1: they push a button, if they see exactly they have 285 00:14:20,716 --> 00:14:23,196 Speaker 1: a special app that they can communicate with our controller. 286 00:14:23,196 --> 00:14:25,196 Speaker 1: If they see something and then there's a whole protocol 287 00:14:25,196 --> 00:14:27,916 Speaker 1: around what do And just to be clear, you don't 288 00:14:27,916 --> 00:14:30,036 Speaker 1: have to do this in Rwanda or in Ghana because 289 00:14:30,076 --> 00:14:33,036 Speaker 1: all of the planes flying there have transponders, so the 290 00:14:33,116 --> 00:14:36,476 Speaker 1: drones automatically know when there's another plane. Yeah, and you know, 291 00:14:36,476 --> 00:14:39,476 Speaker 1: we feed our data there into basically their literal air 292 00:14:39,476 --> 00:14:42,036 Speaker 1: traffic control, so they have a view of their whole airspace, 293 00:14:42,076 --> 00:14:45,116 Speaker 1: including all the aircraft with people and all of our drives. 294 00:14:45,196 --> 00:14:47,156 Speaker 1: So wild to me that we don't have that. Maybe 295 00:14:47,156 --> 00:14:49,836 Speaker 1: I'm super naive, I guess obviously I am super naive 296 00:14:51,356 --> 00:14:54,516 Speaker 1: to be surprised by that. Like is there any broader 297 00:14:54,636 --> 00:14:57,676 Speaker 1: lesson from that, Like, is there anything I can conclude 298 00:14:57,676 --> 00:15:00,556 Speaker 1: about the way the United States works, the way regulation 299 00:15:00,596 --> 00:15:02,356 Speaker 1: works here? I don't know. I mean it is some 300 00:15:02,436 --> 00:15:05,076 Speaker 1: of it is a philosophical thing, right like here we 301 00:15:05,356 --> 00:15:09,836 Speaker 1: sort of we sort of romanticize and cherish like sort 302 00:15:09,876 --> 00:15:12,636 Speaker 1: of the old ways of flying, and so we cowboys 303 00:15:12,796 --> 00:15:16,396 Speaker 1: cowboys in the sky and their little cessna or whatever exactly. 304 00:15:16,596 --> 00:15:18,116 Speaker 1: They are pilots I've met who have told me to 305 00:15:18,156 --> 00:15:19,996 Speaker 1: my face, I'm never going to put a transponder because 306 00:15:20,036 --> 00:15:21,556 Speaker 1: that means people know where I am, and some of 307 00:15:21,556 --> 00:15:24,036 Speaker 1: it is also just uh, you know, I think this 308 00:15:24,076 --> 00:15:25,356 Speaker 1: is one of the things I think a lot about 309 00:15:25,356 --> 00:15:27,436 Speaker 1: with this country, right, where As we kind of mature, 310 00:15:27,716 --> 00:15:29,476 Speaker 1: if you will, as a country, right, A lot of 311 00:15:29,476 --> 00:15:32,636 Speaker 1: these countries like Rwanda and Ghana, these are literally young countries. 312 00:15:33,836 --> 00:15:36,996 Speaker 1: Their whole mindset is around growth and becoming, you know, 313 00:15:37,276 --> 00:15:39,636 Speaker 1: and becoming the economic power they want to be in 314 00:15:39,636 --> 00:15:41,916 Speaker 1: the future and things like that, and they're very willing 315 00:15:41,956 --> 00:15:44,876 Speaker 1: to sort of make decisions that are very future focused. 316 00:15:45,596 --> 00:15:47,556 Speaker 1: And I think more and more I see, you know, 317 00:15:47,636 --> 00:15:49,756 Speaker 1: as a as a society right at the balance between 318 00:15:49,796 --> 00:15:52,116 Speaker 1: clinging to the past and and focusing on the future 319 00:15:52,436 --> 00:15:53,996 Speaker 1: and how do you do both in the right way? 320 00:15:54,076 --> 00:15:56,436 Speaker 1: So we so we actually you know, stay who we 321 00:15:56,476 --> 00:15:58,316 Speaker 1: want to be and become who we need to be. 322 00:15:58,796 --> 00:16:00,636 Speaker 1: And that's a that's a tricky thing to do. And 323 00:16:00,476 --> 00:16:02,316 Speaker 1: I see when I sit in a room of the 324 00:16:02,316 --> 00:16:05,116 Speaker 1: fa leadership and they're literally debating this kind of thing, 325 00:16:05,436 --> 00:16:08,716 Speaker 1: like in these kind of terms, the FAA has more 326 00:16:08,756 --> 00:16:11,796 Speaker 1: old as regulations that makes it harder for you to 327 00:16:11,836 --> 00:16:15,076 Speaker 1: do what you do. You're working closely with the FAA, 328 00:16:15,116 --> 00:16:18,756 Speaker 1: and like like where does that sort of land like, 329 00:16:19,356 --> 00:16:21,676 Speaker 1: is there some I know there's no endpoint, but if 330 00:16:21,676 --> 00:16:24,476 Speaker 1: there's some big like step that's going to happen where 331 00:16:24,516 --> 00:16:28,036 Speaker 1: they're going to say, Okay, you can delivered hospitals all 332 00:16:28,076 --> 00:16:30,236 Speaker 1: over the country and like what problems do you have 333 00:16:30,276 --> 00:16:33,556 Speaker 1: to solve for that to happen. Yeah, So the journey 334 00:16:33,596 --> 00:16:37,396 Speaker 1: with the FA, Yeah, it's incremental rights. It's all about 335 00:16:37,436 --> 00:16:39,396 Speaker 1: taking the right next step that leads you to the 336 00:16:39,396 --> 00:16:41,756 Speaker 1: next step that leads you to the next step, both 337 00:16:41,876 --> 00:16:44,716 Speaker 1: for them to get comfortable, for them to learn, for 338 00:16:44,796 --> 00:16:46,556 Speaker 1: us to get to know each other. Literally, there's a 339 00:16:46,596 --> 00:16:48,196 Speaker 1: lot of trust that has to be built between a 340 00:16:48,236 --> 00:16:51,036 Speaker 1: company like Zipline doing something very new and a regulator 341 00:16:51,076 --> 00:16:53,476 Speaker 1: like the FA who you know, to their credit, right, 342 00:16:53,596 --> 00:16:57,276 Speaker 1: the advent of autonomy in the airspace is like the 343 00:16:57,276 --> 00:17:01,516 Speaker 1: biggest change to the airspace literally since flight began. Yeah, right, 344 00:17:01,516 --> 00:17:03,116 Speaker 1: and I mean that in every sense of the word. Right. 345 00:17:03,196 --> 00:17:05,636 Speaker 1: There's going to be more planes and flying cars flying 346 00:17:05,636 --> 00:17:07,276 Speaker 1: in the airspace in twenty years by a factor of 347 00:17:07,276 --> 00:17:09,036 Speaker 1: one hundred than there are aircraft flying the air to 348 00:17:09,596 --> 00:17:12,876 Speaker 1: It's that big of a change. And you know, to 349 00:17:12,956 --> 00:17:15,036 Speaker 1: their credit, like they can't you know, they can't be 350 00:17:15,076 --> 00:17:16,636 Speaker 1: reckless here, this is going to be hard to do, 351 00:17:17,036 --> 00:17:20,956 Speaker 1: and do it safely in a minute, The Lightning Round, 352 00:17:21,116 --> 00:17:25,116 Speaker 1: including Keenan's tips for solving hard problems and the biggest 353 00:17:25,156 --> 00:17:34,036 Speaker 1: misconception most people have about drones. Okay, let's get back 354 00:17:34,036 --> 00:17:36,436 Speaker 1: to the show. We're gonna close with the Lightning Round. 355 00:17:36,676 --> 00:17:40,836 Speaker 1: Are you ready? I'm ready. What is one piece of 356 00:17:40,876 --> 00:17:43,276 Speaker 1: advice you'd give to somebody who is trying to solve 357 00:17:43,276 --> 00:17:47,076 Speaker 1: a hard problem. If it's a hard business or customer problem, 358 00:17:47,356 --> 00:17:50,676 Speaker 1: start with real human customers before you do anything else. 359 00:17:51,036 --> 00:17:54,716 Speaker 1: If it's a technology problem, focus on the hardest part 360 00:17:54,716 --> 00:17:57,436 Speaker 1: of the technology problem, ignore all the rest, and then 361 00:17:57,476 --> 00:17:58,676 Speaker 1: go on to the next hardest and then go on 362 00:17:58,676 --> 00:18:01,516 Speaker 1: the next hardest. What's your favorite app on your phone? 363 00:18:02,036 --> 00:18:05,116 Speaker 1: My favorite app on my phone. I'm sure I have 364 00:18:05,156 --> 00:18:08,196 Speaker 1: such a positive relationship with my phone. Actually, you know, 365 00:18:08,356 --> 00:18:11,676 Speaker 1: recently I I got Nebula. I really like Nebula. I 366 00:18:11,956 --> 00:18:14,956 Speaker 1: don't know Nebula. What is it? It's basically a bunch 367 00:18:14,956 --> 00:18:18,116 Speaker 1: of the more wonkier YouTubers got together and made an 368 00:18:18,196 --> 00:18:21,756 Speaker 1: ad free YouTube for to cheat sidestuff to YouTube algorithm, 369 00:18:21,796 --> 00:18:24,636 Speaker 1: and they just make some great content. Oh great, Yeah, 370 00:18:24,916 --> 00:18:28,036 Speaker 1: that's a good tip. What's the biggest misconception people have 371 00:18:28,116 --> 00:18:33,036 Speaker 1: about drones? Biggest misconception people have about drones. I have 372 00:18:33,076 --> 00:18:35,636 Speaker 1: a good friend who's now worked at SpaceX and zip Line, 373 00:18:36,116 --> 00:18:38,596 Speaker 1: and he likes to joke that rockets are easier than 374 00:18:38,596 --> 00:18:41,276 Speaker 1: people think, and drones are harder than people think. Good. 375 00:18:41,476 --> 00:18:43,076 Speaker 1: A lot of people they look at the little you know, 376 00:18:43,116 --> 00:18:44,436 Speaker 1: they look at a drone that you play with as 377 00:18:44,436 --> 00:18:45,996 Speaker 1: a hobby, and they're like, what's the big deal. Let's 378 00:18:46,036 --> 00:18:48,116 Speaker 1: put a package on the bottom and deliver stuff. And 379 00:18:48,596 --> 00:18:50,036 Speaker 1: I'll be honest, I was a little guilty of that 380 00:18:50,076 --> 00:18:53,836 Speaker 1: too when I started zip Line two, two or three 381 00:18:53,876 --> 00:18:58,476 Speaker 1: more favorite trait and a co worker, Oh easy, someone 382 00:18:58,516 --> 00:19:01,476 Speaker 1: who has a lot of fun when ship gets hard. Yeah, 383 00:19:01,516 --> 00:19:03,396 Speaker 1: it's actually this actually the main thing I interview for. 384 00:19:03,436 --> 00:19:05,996 Speaker 1: It's sort of funny because they're so much fun because 385 00:19:05,996 --> 00:19:08,236 Speaker 1: startups so just like it's one hard thing to the next, right, 386 00:19:08,316 --> 00:19:10,396 Speaker 1: and and people who really are going to enjoy that, 387 00:19:10,476 --> 00:19:13,116 Speaker 1: And are you're gonna have fun with through that? You know? 388 00:19:13,356 --> 00:19:17,116 Speaker 1: People who love the problem? Yeah, exactly. Um, what would 389 00:19:17,116 --> 00:19:20,436 Speaker 1: you do if you couldn't do what you do? Oh goodness, 390 00:19:20,476 --> 00:19:23,676 Speaker 1: I've looked. Yeah, this this is this is interesting if 391 00:19:23,716 --> 00:19:27,436 Speaker 1: I carbon sequestration, how will you know when it's time 392 00:19:27,476 --> 00:19:30,836 Speaker 1: to retire that I have? I have no idea, you know. 393 00:19:30,916 --> 00:19:33,396 Speaker 1: I think the you know, zip Line today is the 394 00:19:33,396 --> 00:19:35,676 Speaker 1: biggest company I've ever worked at by a lot. How 395 00:19:35,716 --> 00:19:40,956 Speaker 1: big is it? Going on? Seven hundred folks? Yeah, um 396 00:19:41,316 --> 00:19:44,116 Speaker 1: and um yeah. You know, if you had asked me 397 00:19:44,156 --> 00:19:45,556 Speaker 1: eight years ago, if I'd still be here when were 398 00:19:45,556 --> 00:19:48,156 Speaker 1: seven hundred people, I would have been like, Nope, that 399 00:19:48,196 --> 00:19:51,556 Speaker 1: doesn't sound like me. So it's a painful growth for sure. 400 00:19:51,636 --> 00:19:53,716 Speaker 1: I work hard at it, and I have a lot 401 00:19:53,756 --> 00:19:55,956 Speaker 1: of awesome people around me who don't hesitate to give 402 00:19:55,956 --> 00:19:58,516 Speaker 1: me feedback, which is, you know, the only way to grow, right. So, 403 00:19:59,356 --> 00:20:01,476 Speaker 1: but at the same time, like it's hard to imagine 404 00:20:01,476 --> 00:20:08,076 Speaker 1: that I can keep up the zip Line forever. Keenan 405 00:20:08,156 --> 00:20:12,116 Speaker 1: Wyrobek is the founder of Ziplan. On the next few 406 00:20:12,116 --> 00:20:14,316 Speaker 1: episodes of What's Your Problem, I'll be talking to people 407 00:20:14,356 --> 00:20:18,076 Speaker 1: about artificial intelligence. What problems do we have to solve 408 00:20:18,156 --> 00:20:20,756 Speaker 1: to get to self driving cars and to chatpots that 409 00:20:20,796 --> 00:20:23,956 Speaker 1: we can actually chat with chatbot's good enough to teach 410 00:20:24,036 --> 00:20:28,916 Speaker 1: us a new language. Today's show was produced by Edith Russelo. 411 00:20:29,116 --> 00:20:31,916 Speaker 1: It was edited by Kate Parkinson Morgan and Robert Smith, 412 00:20:31,996 --> 00:20:34,796 Speaker 1: and it was engineered by Amanda kay Wong. Theme music 413 00:20:34,796 --> 00:20:37,636 Speaker 1: by Luis Garra. Our development team is Lee, Tom Mulad 414 00:20:37,676 --> 00:20:40,596 Speaker 1: and Justine Lang. A huge team of people makes What's 415 00:20:40,596 --> 00:20:43,916 Speaker 1: Your Problem possible. That team includes, but is not limited to, 416 00:20:44,556 --> 00:20:47,916 Speaker 1: Jacob Weisberg, Mia Lobell, Heather Fame, John Schnars, Kerrey Brodie, 417 00:20:47,916 --> 00:20:52,276 Speaker 1: Carli Mcglehory, Christina Sullivan, Jason Gambrell, Brand Hayes, Eric Sandler, 418 00:20:52,316 --> 00:20:55,916 Speaker 1: Maggie Taylor, Morgan Ratner, Nicolemrano, Mary Beth Smith, Royston Deserve, 419 00:20:55,996 --> 00:20:59,636 Speaker 1: Maya Kanig, Danielle Lakhan, Kazia Tan and David Clever. What's 420 00:20:59,636 --> 00:21:03,116 Speaker 1: Your Problem is a co production of Pushkin Industries and iHeartMedia. 421 00:21:03,396 --> 00:21:06,636 Speaker 1: To find more Pushkin podcast listen on the iHeartRadio app, 422 00:21:06,836 --> 00:21:10,756 Speaker 1: Apple Podcasts, or where I'm Jacob Goldstein and I'll be 423 00:21:10,876 --> 00:21:13,756 Speaker 1: back next week with another episode of What's Your Problem,