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Chris Anderson: Don’t Confuse Valuation With Tech Adaptation · Masters in Business

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Speaker 1: Masters in Business is brought to you by the American
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Speaker 1: American Arbitration Association, the global leader in alternative dispute resolution
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Speaker 1: for over ninety years. Learn more at a d R
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Speaker 1: dot org. This is Masters in Business with Barry Ridholts
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Speaker 1: on Bloomberg Radio. This week on the podcast, I have
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Speaker 1: a special guest. His name is Chris Anderson. He is
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Speaker 1: the founder of three D Robotics. He was formerly editor
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Speaker 1: in chief of Wired magazine, and he is the author
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Speaker 1: of the book The Long Tail. Chris Anderson has been
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Speaker 1: at the forefront of technology for a good couple of decades.
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Speaker 1: He saw pretty much where the industry has been going,
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Speaker 1: long before the bulk of the public has figured it out.
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Speaker 1: He has tremendous insight into why certain things are as
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Speaker 1: valuable as they are and why certain products, industries, sectors, software, gadgets, etcetera.
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Speaker 1: Are capable of achieving mass acceptance. I find him to
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Speaker 1: be consistently insightful and forward looking, and I don't know
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Speaker 1: anybody else who's quite had his vantage point throughout the nineties,
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Speaker 1: two thousands and beyond. He really has seen a lot
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Speaker 1: of things coming before anybody else did. Three three D Robotics,
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Speaker 1: as an example, is a started out as a d
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Speaker 1: I Y drone company and they just got so of
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Speaker 1: warm with orders that they pivoted to being a drone
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Speaker 1: manufacturer and now they're a drone software creator. Really really
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Speaker 1: fascinating stuff. If you are at all interested in technology, drones, software,
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Speaker 1: this is sort of conversation that you're going to really enjoy. So,
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Speaker 1: with no further ado, my interview with Chris Anderson. My
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Speaker 1: special guest today is someone I've known for a long
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Speaker 1: time and have been a big fan of his work
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Speaker 1: for all these many years. His name is Chris Anderson.
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Speaker 1: He is the former editor in chief at Wired magazine,
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Speaker 1: worked as a journalist and editor at the Economist for
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Speaker 1: seven years. He is the author of several books, including
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Speaker 1: the New York Times bestseller The Long Tail. Presently, he
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Speaker 1: is CEO and founder of three D Robotics, which is
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Speaker 1: a UH drone and software company, The Long Tale. You
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Speaker 1: probably are familiar with it from either the original Wired
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Speaker 1: article or the book itself. The book won the Lobe
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Speaker 1: Award for the Best Business Book of the Year in
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Speaker 1: two thousand and seven. He has been named to all
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Speaker 1: man or of lists, one of Time magazines one hundred
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Speaker 1: most Influential People, Tech forty, the most influential minds in technology,
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Speaker 1: foreign policies, global thinkers. Chris Anderson, welcome to Bloomberg Radio,
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Speaker 1: and let me add thank you for having us here
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Speaker 1: in the Three D Robotics headquarters. There is just great
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Speaker 1: to have you on our coast. It's it's a pleasure
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Speaker 1: out here to be out here. And I travel all
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Speaker 1: over and don't frequently say I could I could live
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Speaker 1: in this climate. And this is one of those places where, yeah,
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Speaker 1: I could live here if I had to adapt. It's
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Speaker 1: worth noting. You're in Berkeley, which is the nicest part
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Speaker 1: of the pay area, is it? Do you say so? Yeah?
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Speaker 1: It's a little cooler here than down in normally what's
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Speaker 1: cooler than Palaul? A bit warmer than the city. Okay,
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Speaker 1: there you go. Um, so let's let's jump right into it.
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Speaker 1: You have a really unusual background. You studied quantum mechanics
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Speaker 1: and science journalism. Some people do science and some people
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Speaker 1: do journalism. Not a lot of people do both. How
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Speaker 1: did you find your way to marry those two fields.
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Speaker 1: I didn't actually study either of them properly. I might
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Speaker 1: my degrees in computational physics, okay, but it just so
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Speaker 1: happened that in writing up my my resume, I happened
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Speaker 1: to take have taken a class in science journalism, which
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Speaker 1: at the time seemed the only link I had to journalism,
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Speaker 1: so I stuck it on my on my resume. But
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Speaker 1: but no, my degrees in computation. So your whole career
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Speaker 1: is a sharade? Is that what you're it is? It
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Speaker 1: is no you know in it's in it's big dimensions.
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Speaker 1: It doesn't make a lot of sense. I went from
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Speaker 1: from physics, um, to ultimately end up working for a
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Speaker 1: fashion company. Um, it's conde NaSTA. But fashion advertising is
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Speaker 1: the main revenue. Okay, But they're a little more than
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Speaker 1: a fashion there. There are a lot more fine publication indeed, indeed,
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Speaker 1: and it's not fair to conde NaSTA call it. But
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Speaker 1: but when you're in the you know, the elevators of
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Speaker 1: when the time was four times square and it's supermodels
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Speaker 1: up and down, you ask yourself, how did I get here?
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Speaker 1: It is? It does require some explaining, to say the least,
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Speaker 1: so computational physics. I don't want to jump too far ahead.
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Speaker 1: The idea of how drones operate and managed to both
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Speaker 1: fly within three dimensional space as well as do analytics
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Speaker 1: of what's around them. That seems to be like, oh,
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Speaker 1: computational physics to drones. But the middle so years are
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Speaker 1: a little aberrational. So let's start with with the economists.
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Speaker 1: You were there for seven years a writer and editor,
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Speaker 1: is that right? Yeah? I ran Faius bureaus, but it
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Speaker 1: was mostly writing, as the case for most people. The economist,
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Speaker 1: I mean the the You're absolutely right, there's a straight
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Speaker 1: line from from physics to to drones and measuring the
5:37
Speaker 1: world and analyzing an etcetera. The wiggly in between bits
5:41
Speaker 1: which consists of a about thirty years UM had to do. Um.
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Speaker 1: It's kind of interesting paths. So physics in the late
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Speaker 1: eighties e early nineties, which is when I was there, UM,
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Speaker 1: we were all inspired by the way to physicists of
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Speaker 1: the twentieth century, the you know, the fiem etcetera. UM,
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Speaker 1: and that really was that the noble science. Unfortunately, UM,
6:05
Speaker 1: the quest of physics was to get closer and closer
6:07
Speaker 1: to the Big Bang, to understand the origins of the universe,
6:10
Speaker 1: and closer to the Big Bang means higher energies, which
6:12
Speaker 1: means bigger particle accelerators, which means more money. And eventually
6:16
Speaker 1: we just scaled out of government budgets and so there
6:18
Speaker 1: were no more particle accelerators in the US that we're
6:21
Speaker 1: going to be built, and so and so you had
6:23
Speaker 1: two choices. You could either like wait in line for
6:26
Speaker 1: you know, the LHC and CERN in Switzerland, wait in
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Speaker 1: line for like twenty years and maybe your experiment would
6:31
Speaker 1: be would be a success, maybe wouldn't. Or you could
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Speaker 1: take the skills that you learned in physics and apply
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Speaker 1: them elsewhere. So the skills were when you think about
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Speaker 1: the internet was invented in the physics world to connect labs.
6:43
Speaker 1: The web was invented at CERN, a physics laboratory, and
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Speaker 1: the first big data was physics data supercomputers using accelerator data,
6:52
Speaker 1: and so you really only had some Most people sort
6:54
Speaker 1: of said, well, what do I got here? I got
6:56
Speaker 1: I got you know, statistical skills, I can crunch big data.
6:59
Speaker 1: I'll go to Wall Street be a quant That was
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Speaker 1: the natural one. A lot of people went went and
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Speaker 1: did that for the money? Go for for the money.
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Speaker 1: Some of us said, well, Okay, yeah, we can do that.
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Speaker 1: But there's also this Internet thing, which seems kind of interesting.
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Speaker 1: The time, it was really just a network to connect
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Speaker 1: scientific laboratories. Well, the original Dark Book concept was, hey,
7:16
Speaker 1: we have to have the capacity to send launch instructions
7:20
Speaker 1: in the event that we're hit first. Well sure, but
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Speaker 1: I mean at the time this was a little bit
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Speaker 1: past then. The true the Internet was largely to connect
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Speaker 1: supercomputer centers for things like climate modeling. You know, this
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Speaker 1: is the part where Al Gore you know, invented it,
7:33
Speaker 1: um which you know, he actually had a lot He
7:34
Speaker 1: didn't invent it, but he had a lot to do
7:36
Speaker 1: with them with encouraging its growth during that era. Um. So,
7:40
Speaker 1: so those of us, you know, who were sitting here
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Speaker 1: and say, well, I don't want to go to Wall Street,
7:43
Speaker 1: but I do have some some Internet skills. What's the
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Speaker 1: internet good for? Along comes this magazine in called Wired
7:50
Speaker 1: with like fuluorescent ink and saying, hey, this Internet thing
7:53
Speaker 1: is going to be big one day. One day. It's
7:55
Speaker 1: not just you know, a tool to connect labs. It's
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Speaker 1: gonna be cultural revolution at cetera. And so I decided
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Speaker 1: to make my career the Internet, and the first step
8:04
Speaker 1: you know, there was I went. I was working for
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Speaker 1: scientific journals as an editor, and then the Economist asked
8:09
Speaker 1: me to take over their technology beat and I said sure,
8:12
Speaker 1: but I'd like to cover the Internet. And they're like why,
8:14
Speaker 1: I don't know, whatever, whatever, you say, what do you need?
8:16
Speaker 1: And I like I needed internet connection? This is this
8:21
Speaker 1: was ninety three. Yeah, and and at what point did
8:26
Speaker 1: you end up leaving so the economists you weren't necessarily
8:30
Speaker 1: covering covering economics and business. I was, I was originally
8:33
Speaker 1: and then I went to China to to run the
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Speaker 1: bureau there and China from just before the handover of
8:41
Speaker 1: Hong Kong Um. I guess that was ninety seven two
8:44
Speaker 1: after wto in two thousand and one. Fascinating time to
8:47
Speaker 1: be in China, got to serve to see China emerge.
8:50
Speaker 1: And there was in New York where you and I
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Speaker 1: spent time together and them was recruited from there too
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Speaker 1: by Condyn asked to run Wired. Um so the only
8:57
Speaker 1: publication I would leave the economists. You were in the
8:59
Speaker 1: econom New York Bureau, and that's what led to Conde
9:03
Speaker 1: Nast and Wired. So you take over Wired, which was
9:06
Speaker 1: it was always a good magazine, but it was kind
9:08
Speaker 1: of a hodgepodge for a while. Well it was, it
9:12
Speaker 1: was you know, it basically created this sort of esthetic
9:17
Speaker 1: and philosophical foundations of the Internet is going to be big.
9:20
Speaker 1: It's like the biggest things since electricity. That was kind
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Speaker 1: of the wired concept. UM. I took over in two
9:25
Speaker 1: thousand and one. So this is after the stock after
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Speaker 1: the dot com bust, and six weeks before September eleventh, UM,
9:32
Speaker 1: excellent time. Well, so you know, at that point everyone
9:36
Speaker 1: was dismissing the Internet as as as a fraud or
9:39
Speaker 1: at least or at least wildly over high. But that's
9:42
Speaker 1: what I mean by excellent time. You come in with
9:44
Speaker 1: very low expectations. People aren't torturing you to why don't
9:48
Speaker 1: he we have any results this quarter? Precisely so, so
9:51
Speaker 1: I was betting that the Internet was real and that
9:54
Speaker 1: the dot com bust was about Wall Street, not about
9:57
Speaker 1: Silicon Valley. UM. And And as you say, when you
9:59
Speaker 1: when buy at the bottom, you get three wonderful things. Um.
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Speaker 1: First of all, your failures are discard cloaked by the marketplaces.
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Speaker 1: It's just everybody's can't succeed in that in that in
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Speaker 1: that environment, Secondly, a lot of talent had come to
10:13
Speaker 1: Silicon Valley during the boom and they were available, so
10:17
Speaker 1: I was able to hire really good people on the
10:18
Speaker 1: cheap on the cheap um, well, they were available. And Thirdly,
10:24
Speaker 1: my year on years, I had a exactly the next
10:28
Speaker 1: year I was just going to blow through my n
10:30
Speaker 1: So before we move too forward past two thousand and one,
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Speaker 1: having lived through the nineties and all the enthusiasm and
10:38
Speaker 1: all the excitement and then the collapse, how did that
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Speaker 1: color your view of technology and the Internet or did it?
10:46
Speaker 1: It was? It was I think I was my um,
10:50
Speaker 1: my faith and technology was completely unshaken. Um. You know,
10:54
Speaker 1: as a physicist, you basically think in terms of like,
10:56
Speaker 1: you know, what's like fundamental in the world, and there's
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Speaker 1: something about the Internet that just struck me as fundamental.
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Speaker 1: It struck me as in the same category as democracy
11:06
Speaker 1: and evolution. It's kind of one of these one of
11:09
Speaker 1: these truisms. And as a matter of fact, when I
11:12
Speaker 1: was at the Economists my first they had these things
11:13
Speaker 1: called surveys, which are these big sixteen page special features.
11:17
Speaker 1: It's the only time you get to use your name
11:18
Speaker 1: as an author, and which is by the way, is
11:21
Speaker 1: unique in the world of journalism, pretty much unique exactly.
11:25
Speaker 1: I mean, where there's no byline, you write an article
11:27
Speaker 1: and it's by the economy. The notion of the collective voice. Yeah.
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Speaker 1: Um so, my my first survey on the Internet was
11:34
Speaker 1: entitled the Accidental super Highway. Um, and the notion of
11:38
Speaker 1: things happening, you know, by accident, suggests that really they're
11:43
Speaker 1: happening by nature. There's that that that you know, this
11:46
Speaker 1: this emerged it was an emergent organic universe exactly. And
11:50
Speaker 1: the fact that it was an emergent rather than synthetic,
11:53
Speaker 1: meant that it was more real. Huh. That that that's
11:56
Speaker 1: quite fascinating. The the thing I thought you were heading towards,
12:00
Speaker 1: and I think I'm mangling this is it met Metcalf's
12:03
Speaker 1: law that does the each node multiplies the value. That
12:08
Speaker 1: quickly became obvious that every time you add another user
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Speaker 1: to the Internet the value increased. Explanab absolutely. So that's
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Speaker 1: the value element. But the governance structure, the fact that
12:18
Speaker 1: it was not centrally controlled. I mean, there's some trivial
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Speaker 1: central control, but that's that's that's that's a very lowest level.
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Speaker 1: But the terms of the content itself, the fact that
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Speaker 1: it was the fact that it is, you know, truly
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Speaker 1: democratic ameritocratic system. Um. That is, that's actually the more
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Speaker 1: important rule um. And that's why we've worked so hard
12:40
Speaker 1: to protect the openness of the Internet is because the
12:43
Speaker 1: emergent properties come from that openness. So one of the
12:46
Speaker 1: questions I wanted to ask you, you kind of answered already,
12:49
Speaker 1: So I want to expand on it. You've been quite
12:54
Speaker 1: a student at forecasting let's call it near trends, extrapolating
12:59
Speaker 1: from just very nascent things not well formed. Well, at
13:04
Speaker 1: this point, I think we all can agree mobile is
13:06
Speaker 1: going to be big one thing. But on the other hand,
13:09
Speaker 1: you were looking at things that were the trend wasn't clear,
13:13
Speaker 1: It wasn't let's just extrapolate this in infinity. You identified
13:18
Speaker 1: seedlings and said this is gonna be significant. Is it
13:22
Speaker 1: simply the organic nature of it that court your eye?
13:25
Speaker 1: Or how did you How are you able to say, oh,
13:28
Speaker 1: there's huge potential. You know, you're just you know the
13:31
Speaker 1: people who, especially after the crash, people said, you know,
13:35
Speaker 1: it's too good to be true, this is just overhyped.
13:38
Speaker 1: What made you turn around and say, no, this is
13:40
Speaker 1: substantial forget the finance part of it. The technology part
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Speaker 1: of it is real. Yeah, I mean things like the
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Speaker 1: long tail or or drones, which I would do right now.
13:50
Speaker 1: So basically it's there's two elements. One of them is
13:52
Speaker 1: that it's just exciting. You know, it's just shiny and
13:55
Speaker 1: exciting and you know, my heart sings and all that
13:58
Speaker 1: kind of stuff. But that's that's necessary, but not suf issued.
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Speaker 1: Um what sufficient is that also has to align with
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Speaker 1: my world view of what what works, this sort of
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Speaker 1: notion of openness or emergence or or you know the
14:09
Speaker 1: fact that it benefits and democratization. Um. So when you
14:12
Speaker 1: so like my first book, The long Tail, I mean
14:16
Speaker 1: the an article as well. I mean the way that
14:18
Speaker 1: happened was not It wasn't an idea. Um. What happened
14:22
Speaker 1: is that I'm sitting here, you know, it's it's two
14:24
Speaker 1: thousand two. Um, I'm I'm a physicist in Silicon Value, right,
14:30
Speaker 1: I'm now running a magazine. I'm not really trained as
14:33
Speaker 1: a journalist. I'm not, you know, I was. I had
14:35
Speaker 1: a staff of brilliant narrative storytellers, but I was just
14:38
Speaker 1: kind of a nerd, you know, with number cruncher indeed indeed,
14:42
Speaker 1: so I need some numbers to crunch. And I was
14:45
Speaker 1: I was thinking, you know, I was like, Okay, look,
14:47
Speaker 1: I believe that this is the you know, the seeds
14:49
Speaker 1: of the century being formed in the Googles and Amazons
14:52
Speaker 1: and ebays around me. And I'll bet that in those
14:55
Speaker 1: servers is the data that can illustrate what the century
14:59
Speaker 1: it looks like. Let's just ask them for the data.
15:02
Speaker 1: And has anybody previously asked them, Hey, we'd like to
15:05
Speaker 1: see you know? And well, no, I mean because typically
15:08
Speaker 1: the academics weren't looking at that, because that was considered
15:11
Speaker 1: sort of cultural and trivial. Um. The companies themselves were
15:15
Speaker 1: just starting to bring up the data scientists and the
15:17
Speaker 1: commist was quite early, and UM and and journalists just
15:21
Speaker 1: typically weren't weren't quantitative exactly. So there was a brief
15:25
Speaker 1: window if you, if you asked nicely and you know, science,
15:27
Speaker 1: some n D s et cetera, that you could actually
15:29
Speaker 1: get that data. And so I I got the dat
15:32
Speaker 1: different places, like it was a rhapsody I think was
15:34
Speaker 1: my music services original one, but I also got sort
15:37
Speaker 1: of scrubbed data from from eBay and elsewhere. I just
15:41
Speaker 1: started analyzing, and the long tailed popped right out of
15:44
Speaker 1: it. It It was clearly obviously there was a kind of
15:45
Speaker 1: a power law distribution, and that the size of the tail,
15:50
Speaker 1: you know, depending on how you split it, was about
15:51
Speaker 1: the size of the head, which suggested that there was
15:53
Speaker 1: a market and a submerged marketplace out there beyond beyond.
15:59
Speaker 1: And what's interesting that about a year later after I
16:02
Speaker 1: started got all this data, then you may be remember
16:05
Speaker 1: this M A O L. You know, then people started
16:07
Speaker 1: academics started saying, hey, you know, there's some interesting data here,
16:09
Speaker 1: let's ask for it. A O. L. Released a bunch
16:12
Speaker 1: of data and anonymized it, but didn't anonymize it well enough.
16:15
Speaker 1: It got de anonymized, um you know, privacy issues, and
16:20
Speaker 1: then became impossible to get dat again. So it was
16:22
Speaker 1: like a window of about two years where you could
16:24
Speaker 1: have done the long tale, and I just happened to
16:25
Speaker 1: be there. Then I was a subscriber. I still have
16:28
Speaker 1: a subscribe to Wired for it's like a decade plus now.
16:32
Speaker 1: And and the thing that always stood out to me
16:35
Speaker 1: about Wired was the marriage of great content with the
16:41
Speaker 1: technology slant with fantastic design ethics. The the visual impact
16:48
Speaker 1: of the magazine felt like the Internet and a print
16:54
Speaker 1: magazine had a baby. It was. It was so visual
16:57
Speaker 1: in ways that other magazines weren't. Was the thinking beyond that,
17:01
Speaker 1: So I can take no credit for that whatsoever. Is
17:03
Speaker 1: that that was the vision of the original founding team
17:07
Speaker 1: A Lewis Rosetto, Jane Metcalfe and John Plunkett, who was
17:10
Speaker 1: the original designer and their inspiration at the time, the
17:13
Speaker 1: dear friends right now. As a matter of fact, every
17:14
Speaker 1: time there's a new editor, Nick Thompson from the New
17:16
Speaker 1: Yorkers now the In and we all had dinner together,
17:19
Speaker 1: we always kind of, you know, infuse the new editor
17:21
Speaker 1: with the creation myth and all that. But the idea.
17:24
Speaker 1: You know, if you if you ask them with the story, um,
17:27
Speaker 1: they'll say, well, you know, we were this was the
17:29
Speaker 1: emergence of computers and and so print ink has got
17:33
Speaker 1: reflective properties, but screens have a missive properties. So pixels
17:38
Speaker 1: emit light, and so you know, we wanted to we
17:41
Speaker 1: want to use an aesthetic that seemed emittive, emissive. It
17:44
Speaker 1: like like it glowed, and a lot of the page,
17:46
Speaker 1: a lot of the neon colors and other things. Very much.
17:49
Speaker 1: We were like a screen amidden absolutely. Um So I
17:52
Speaker 1: think that I think they'll forgive me for for saying
17:55
Speaker 1: that this is a little bit of a kind of
17:56
Speaker 1: a of a of a post facto expo nation. I
18:00
Speaker 1: think what really happened at the time is there was
18:02
Speaker 1: a new printing process, Like I again any about this.
18:05
Speaker 1: It was a five color printing process, and it was
18:09
Speaker 1: very expensive, and some printing plants that invested in these
18:12
Speaker 1: new kind of five color processes were looking for some
18:15
Speaker 1: examples to show them off. And it just basically that
18:18
Speaker 1: like a fancy ink and like fluorescent became available affordably,
18:22
Speaker 1: and so they took advantage of it. And it makes
18:24
Speaker 1: perfect sense. And the magazine always popped. You turned the
18:26
Speaker 1: pages and it really it really was alive. So you
18:30
Speaker 1: take over wired with the air coming out of the bubble.
18:33
Speaker 1: It was mid collapse, um. And it would get worse
18:36
Speaker 1: and and got worse. How hard was it to stay
18:38
Speaker 1: positive as things just went down the tubes? Um? For
18:42
Speaker 1: me it was it was super easy. Um So. Um.
18:47
Speaker 1: I would say that if you and I, you know,
18:50
Speaker 1: I think you're gonna be talking to Mark andresen As
18:52
Speaker 1: as well, you know, those of us who were there
18:54
Speaker 1: then never never doubted that the Internet was real. We
18:58
Speaker 1: understood the distinction between the this this stock market valuations
19:02
Speaker 1: and the underlying technology was the West Coast view. Oh,
19:05
Speaker 1: the guys in New York, really they really messed us up.
19:08
Speaker 1: You know, they took valuations too high. No surprise, Choris
19:12
Speaker 1: crashed into the sea. I was actually in China during
19:14
Speaker 1: the bubble, uh to the dot com bubble, So I
19:16
Speaker 1: can't really say what they with the collective view was,
19:19
Speaker 1: but I do think that, you know, the underlying belief
19:22
Speaker 1: there was something fundamental going on here with the networks,
19:25
Speaker 1: um was was never doubted. Now this is of course,
19:27
Speaker 1: you know, you know how the Internet works, like there's
19:29
Speaker 1: the layers, right, There's like the hardware layer with the
19:31
Speaker 1: fiber opter cables, and then there's like you know, then
19:34
Speaker 1: the software layers and content layers. A lot of the
19:36
Speaker 1: valuations were at the higher level of the content, and
19:39
Speaker 1: the notion was the content was ephemeral, would come and go.
19:41
Speaker 1: But the underlying notion of connecting the world was was
19:44
Speaker 1: really important. Um And so you know, the the I
19:47
Speaker 1: think when I got there, the consensus was that Wall
19:52
Speaker 1: Street had financed an extraordinary infrastructure build out which made
19:56
Speaker 1: fiber capacity super cheap and this was the best thing
19:59
Speaker 1: ever for restarting. That's suddenly the cost of enter the barriers,
20:03
Speaker 1: the cost of entry was very low, thank you, thank
20:05
Speaker 1: you Wall Street, and that we would just now, you know,
20:08
Speaker 1: build for the next two years without you know, the
20:11
Speaker 1: financial microscope and see where it goes. Dan Gross wrote
20:14
Speaker 1: a book called pop While Bubbles are better than people
20:18
Speaker 1: realizing and the example use whether it's railroads or telegrams
20:22
Speaker 1: or in this case dark fiber, Global crossing and Metromedia
20:26
Speaker 1: fiber and go down the list. They laid miles and
20:29
Speaker 1: miles of dark fiber at thousands of dollars per whatever
20:32
Speaker 1: it was, and it sells for pennies on the dollar.
20:35
Speaker 1: The theory is, but for this collapsing, you don't end
20:39
Speaker 1: up with YouTube and Facebook and all these other band
20:42
Speaker 1: with intensive intensive things. Yeah, now, Dan, Dan, Dan super
20:46
Speaker 1: smart And then the book's great um And I think
20:48
Speaker 1: when you look back now at that decade, it's almost
20:51
Speaker 1: impossible to see the bust when you look at the
20:53
Speaker 1: underlying adoption curves and data curves, etcetera. It's weird. I mean,
20:57
Speaker 1: you can obviously see it on the nineties or in
20:59
Speaker 1: the if you look back today, if you look back
21:01
Speaker 1: at internet adoption trends, you almost can't see the dip
21:05
Speaker 1: right because the end customers continued to be added at
21:09
Speaker 1: a tremendous rate because there was something real there. People
21:12
Speaker 1: wanted what we were making in the fact that was
21:13
Speaker 1: cheaper and accelerated the often. So let's let's talk about Wired.
21:17
Speaker 1: When you take over Wired, it's kind of uh we
21:20
Speaker 1: I said a Hodgepodge. I think at one point they
21:23
Speaker 1: didn't even own their own domain. So if you wanted
21:26
Speaker 1: to do internet stuff, how did that come about? Again?
21:30
Speaker 1: Before my time? But but yeah, so, um so Wired
21:34
Speaker 1: was you know, sort of the before the dot com bubble.
21:36
Speaker 1: There was there were previous bubbles, and Wired was the
21:41
Speaker 1: hottest thing around in the you know, in the late nineties.
21:44
Speaker 1: UM basically created a lot of online media. So like Apache,
21:48
Speaker 1: the web server's use was actually created um, you know
21:50
Speaker 1: in the Wired offices. The first at the first banner
21:54
Speaker 1: ad was on Wired. You know, a lot of the
21:56
Speaker 1: things we take for granted today we're actually being pioneered
21:58
Speaker 1: in the laboratories that were Wired. UM and they filed
22:01
Speaker 1: to go public UM and Wired as a standalone stand
22:05
Speaker 1: company again I'm gonna say nineties seven ish, maybe ninety eight, um,
22:13
Speaker 1: and didn't work. Filed again, didn't work. Had taken out
22:18
Speaker 1: some finance and debt on anticipation that they would go
22:21
Speaker 1: public and ended up having to kind of fire sale
22:24
Speaker 1: some of the bits and and the the magazine. The
22:26
Speaker 1: print bit went to Conde Nast and the digital bit
22:28
Speaker 1: went to Licos, which was which then got bought by
22:32
Speaker 1: some Korean media company. Anyway, it was. It was. It
22:36
Speaker 1: was like one of those like you know, the children
22:38
Speaker 1: got adopted by different families kind of deal, and you
22:40
Speaker 1: helped bring them both under the same I didn't the
22:43
Speaker 1: call credit goes to contact. It was clearly indeed to
22:45
Speaker 1: be done, and just you know, years went by and
22:47
Speaker 1: evaluations kind of stabilized, and kind of appropriately I bought it,
22:51
Speaker 1: brought it back, so you really, you really turned the
22:56
Speaker 1: entire magazine around and turned it into this award winning affair.
23:01
Speaker 1: I I actually, um, it was very much award winning
23:05
Speaker 1: before I got there. Um, I just Magazine in the Decade,
23:07
Speaker 1: not Editor of the Year. Those are pretty substantial awards
23:11
Speaker 1: in the industry. I think what we did is we
23:14
Speaker 1: believed in the underlying story. The reason I left the Economist,
23:16
Speaker 1: which is the best gig ever. By the way, was
23:19
Speaker 1: that Wired had changed my life? Um that I'm as
23:21
Speaker 1: as as a as a physicist sitting there nerding away
23:24
Speaker 1: on these networks, you know, not believing there were any
23:27
Speaker 1: more than than than physics. Wired it opened my eyes
23:30
Speaker 1: to the potential technology to change the world. I know
23:33
Speaker 1: it's a very kind of cliche to say that, but
23:35
Speaker 1: that's what it did. And um, And so when I
23:38
Speaker 1: had the opportunity to run Wired, I said, well, this
23:40
Speaker 1: is the biggest story of my lifetime. Um. The ability
23:43
Speaker 1: to be there in the middle Silicon Valley and tell
23:45
Speaker 1: this story is um. You know that that that story
23:48
Speaker 1: is not done. Um. And all I did is just
23:50
Speaker 1: kept the faith. So you're running the magazine, you're the
23:54
Speaker 1: editor in chief, you're overseeing publication, and you're writing both
23:58
Speaker 1: articles and books. How do you juggle any one of
24:03
Speaker 1: those things or a full time job? How do you
24:05
Speaker 1: juggle all of that at once? Um? Yeah? And you,
24:09
Speaker 1: by the way, you're married and have five kids. And
24:11
Speaker 1: you am married and have five kids and a lot
24:13
Speaker 1: of hobbies because they ended up starting starting a drone
24:15
Speaker 1: company maker dad, and then you had a lot of
24:20
Speaker 1: bulls in the airs. I did, Um, well, I mean
24:22
Speaker 1: I think I was, you know, I mean obviously I
24:25
Speaker 1: had a good staff, and you know that my general
24:27
Speaker 1: philosophy on on on, you know, leading teams is to
24:31
Speaker 1: kind of point them in a direction, set some some
24:33
Speaker 1: you know, some guidelines of what success looks, measurable targets
24:36
Speaker 1: and let them, let them, let them do their job.
24:40
Speaker 1: You know. One of the things that Wired as a
24:42
Speaker 1: as a as a bully pulpit, I guess for the
24:44
Speaker 1: technology stories, one of the things that you know that
24:46
Speaker 1: the editors can do is to be a public persona um,
24:50
Speaker 1: and to do their own writing. And you know, because
24:53
Speaker 1: I mean, unlike most media, which is which is an
24:55
Speaker 1: American media, which is required to be impartial and just
24:57
Speaker 1: passionate and not point take a point of view, the
25:00
Speaker 1: Commist and Wired shared one thing, which is that they
25:02
Speaker 1: do have a point of view. They have a worldview.
25:03
Speaker 1: The economists one famously is British liberalism, which is free
25:07
Speaker 1: markets and free people. Um. Wired basically took the same approach,
25:10
Speaker 1: but then had this evangelism for technology. So the notion
25:13
Speaker 1: of being evangelical that being a preacher um, which meant
25:16
Speaker 1: also being a doer U was kind of core to
25:18
Speaker 1: the to the Wired credo and so, um, the reason
25:21
Speaker 1: I did all these side things and you know, did
25:23
Speaker 1: the research that led to the long tail and and
25:25
Speaker 1: free and and makers was that that was the hands on,
25:28
Speaker 1: that was the doing. I mean, that's what Silicon Valley
25:30
Speaker 1: is all about. It's about it's about doers um And
25:32
Speaker 1: I just didn't feel like I could tell the story
25:34
Speaker 1: if I wasn't doing it. That's quite fascinating. You mentioned, uh,
25:38
Speaker 1: the free and the freemium model that was pretty prescient
25:44
Speaker 1: when you when you put that out. What do you
25:46
Speaker 1: think of the freemium model today? Is it's still working? Um?
25:51
Speaker 1: And and how has it negatively impacted other industries like
25:55
Speaker 1: like print journalism? Yeah, I know exactly. Um So, I mean,
25:58
Speaker 1: just to be clear, I've written three books that I'll
25:59
Speaker 1: basic the same book, so the long tail hold on
26:03
Speaker 1: a second. So, so the long tail, that's a very
26:07
Speaker 1: specific book that an eBay or an Amazon or any
26:11
Speaker 1: online built, any online retailer. Netflix has the ability to
26:17
Speaker 1: have essentially an infinite warehouse versus a brick and mortar
26:21
Speaker 1: seers which is circling the drain, cannot have every or
26:25
Speaker 1: Barnes and Noble. For that matter, they can have every
26:28
Speaker 1: single book available in the store. That's a very different
26:32
Speaker 1: article argument. Then all right, give this stuff away for free,
26:38
Speaker 1: and some percentage of those users will pay you a
26:42
Speaker 1: small fee for a higher level of whatever it is. Um,
26:47
Speaker 1: you've articulated the thesis of those very well. Um, but
26:50
Speaker 1: let me suggest that the more connected than you they
26:52
Speaker 1: may suggest. Okay, So if infinite shelf space creates infinite choice,
26:58
Speaker 1: and therefore we can measure people's actual inter actual likes
27:02
Speaker 1: and dislikes in a world of infinite choice, and how
27:04
Speaker 1: do you get infinite shelf space. Well, the only way
27:06
Speaker 1: you can get infinite shelf space is the cost of
27:08
Speaker 1: shelf space, the marginal cost to zero or certainly as
27:11
Speaker 1: close to zero, close to zero. So what are the
27:15
Speaker 1: economics of zero cost markets? You know, these are markets
27:20
Speaker 1: where where essentially free is a is an attainable price.
27:24
Speaker 1: What are the economics are free Well, there weren't any. Um.
27:26
Speaker 1: You know, economics by definition is monetary economics, non monetary economics,
27:31
Speaker 1: or something else, psychology, sociology, sociology exactly. So, but what
27:35
Speaker 1: if you applied economic principles to try to create an
27:37
Speaker 1: economic framework for free to treat it the same way
27:40
Speaker 1: you would treat monetary markets. UM, then you could explain
27:43
Speaker 1: not only not only you know how things could be free,
27:46
Speaker 1: but how maybe you would use free as the way
27:49
Speaker 1: as a form marketing, that you would basically give things
27:52
Speaker 1: away for free and that and that unlike traditional market
27:54
Speaker 1: where you can give out you know, you can get
27:56
Speaker 1: free tastes of brownies, but not many, but a finite
27:58
Speaker 1: amount of a fixed cost to free exactly so. And
28:02
Speaker 1: so in worlds where you have non zero marginal costs,
28:04
Speaker 1: you can give away one percent and you must sell
28:06
Speaker 1: ninety nine. Where you have near the marginal costs, you
28:09
Speaker 1: can give away to sell one. And just that notion
28:13
Speaker 1: that there was an underlying economic model behind the long
28:15
Speaker 1: tail that drove the long tail led me to two free. Um.
28:19
Speaker 1: The so freemium, you're correct, is is the is the
28:23
Speaker 1: is the business model around it. And when I wrote it,
28:26
Speaker 1: freemium was you're kind of starting to be known in
28:29
Speaker 1: kind of business to business software, etcetera. UM. It was
28:32
Speaker 1: just before the app store on you know and mobile um,
28:36
Speaker 1: and you could start to see the beginnings of it
28:38
Speaker 1: was mostly in web games that you were seeing freemium
28:40
Speaker 1: as a as a model. But this is an example
28:43
Speaker 1: of you identifying something when it was just germinating and saying, oh,
28:47
Speaker 1: this is gonna be big one day. It was a
28:50
Speaker 1: you know, most people have one of those in their
28:52
Speaker 1: lifetime if they're lucky. Here it is not long after
28:55
Speaker 1: the long tail, and here's the next big thing, and
28:57
Speaker 1: you were dead right about it. I mean, I I
29:02
Speaker 1: have to admit that I didn't do anything. I mean,
29:05
Speaker 1: this was it was happening around me, and there was
29:07
Speaker 1: a bazillion great entrepreneurs. Fred Wilson from Union Square Eventure
29:10
Speaker 1: I think was that it was the person who deserves
29:12
Speaker 1: the most credit for popularizing freemium, but all I did.
29:15
Speaker 1: Did he he gave it the name, or did he
29:17
Speaker 1: just popularize one of his entrepreneurs I think coined the term,
29:21
Speaker 1: but freemium freemium, which is the combination of free in
29:25
Speaker 1: premium um. So you give all this away for free.
29:28
Speaker 1: And if you want to exactly and you can actually
29:31
Speaker 1: measure the metrics, here's here's our user research. Here's how
29:34
Speaker 1: many Here's how many people open it, Here's how many
29:37
Speaker 1: people engage, log in, sign up, and here's how many
29:40
Speaker 1: of those convert to the paying model in app purchases
29:42
Speaker 1: being the perfect example. So so today freemium is the
29:45
Speaker 1: canonical business model of online of web mobile apps, which
29:49
Speaker 1: is to say, most apps are free, especially games, etcetera.
29:51
Speaker 1: And there's all these in app purchases that encourage some
29:54
Speaker 1: people to to to pay upgrade you get secret levels
29:58
Speaker 1: or more weapons or whatever it. So again, I didn't
30:01
Speaker 1: you know, I didn't coin anything. I didn't I didn't
30:03
Speaker 1: invent anything. What I saw, though, is that there was
30:07
Speaker 1: a smart people were starting to act in a certain way,
30:10
Speaker 1: and I just created a framework for it. All right,
30:12
Speaker 1: So let's go from longtail to two free, two makers,
30:17
Speaker 1: which again I'm gonna argue as a totally different same
30:20
Speaker 1: book book, the long tailed physical goods. So you have
30:25
Speaker 1: the ability to put so when I was a kid,
30:27
Speaker 1: and we're not that far apart in age I was
30:29
Speaker 1: a kid, you could have these little scientific what was
30:32
Speaker 1: it called the company that put up Yeah, you you
30:35
Speaker 1: would either get a chemistry set or there were a
30:37
Speaker 1: variety of electronics set. I remember the electronics set, right,
30:41
Speaker 1: and you could put together. You can combine these things
30:43
Speaker 1: in different ways. Oh look, I could make a little
30:47
Speaker 1: home radio kit. Just by combining these different things. You
30:49
Speaker 1: didn't go much beyond that, right you point out that, hey,
30:53
Speaker 1: the cost of these things, including little electric engine little
30:57
Speaker 1: electric engines that you could order from China for next
31:00
Speaker 1: to nothing, here's what you could do today, and it's
31:04
Speaker 1: nothing like it was back then. So the fundamental difference
31:07
Speaker 1: there was not just the cost of the goods, because
31:10
Speaker 1: that they were already pretty cheap. It's just that when
31:12
Speaker 1: you and I were tinkering in our in our in
31:13
Speaker 1: our bedrooms or workshops or basements, etcetera, were essentially re
31:16
Speaker 1: all doing the same things while doing the same kids,
31:18
Speaker 1: but weren't kind of weren't doing anything new innovating. We
31:21
Speaker 1: weren't building on other people's work because we didn't have
31:23
Speaker 1: an internet back then. So we had a we had
31:26
Speaker 1: a book, and we followed the instructions of the book
31:28
Speaker 1: and we but yeah, that was it. We weren't doing
31:30
Speaker 1: anything innovative. Um. The virtue. So what was new about
31:34
Speaker 1: the maker movement? In two thousand and seven was the
31:36
Speaker 1: key year in the maker movement? Um? A bunch of
31:39
Speaker 1: things happened that year. Um, you know, first of all, um,
31:42
Speaker 1: and on all those things were standing on the shoulders
31:45
Speaker 1: of the web and oh and communities and open source, etcetera.
31:48
Speaker 1: But you had things like our duino, which was an
31:50
Speaker 1: open source computing board that allowed you to to to
31:54
Speaker 1: use your coding skills but actually move things in the
31:56
Speaker 1: physical world. There was the three D printing that allowed
31:58
Speaker 1: you to fabricate things you couldn't do on your own.
32:00
Speaker 1: There was you started to see these and the sensors
32:04
Speaker 1: with thinks in like a wee control or in my
32:06
Speaker 1: case it was Lego mind Storms that you allowed to
32:08
Speaker 1: measure the real world with the extraordinary little chips that
32:10
Speaker 1: could measure things. Um, there was Maker Make magazine, there
32:15
Speaker 1: was the Maker Fair and behind it all. That was
32:18
Speaker 1: the year the iPhone was released. And it wasn't clear
32:21
Speaker 1: initially that the iPhone had a connection to this. But
32:25
Speaker 1: when we said why is it that, you know? So
32:27
Speaker 1: I started with my kids. Um, we made a drone
32:30
Speaker 1: on the dining room table out of Lego parts, you know,
32:33
Speaker 1: fully autonomous, GPS guided, you know. And this is like
32:36
Speaker 1: you know a few years earlier that was like military industrial,
32:39
Speaker 1: classified export control stuff. And we did leg we did
32:42
Speaker 1: with Legos. You know, Lego mind Storms is pretty cool. Um.
32:46
Speaker 1: Only later did I say, how is it possible that
32:48
Speaker 1: we were able to do this? I mean, I can
32:50
Speaker 1: see you've got a you've got a fitbit of something
32:52
Speaker 1: on your on your arm, I've got a pebble. They're
32:55
Speaker 1: terribly inaccurate. Um. They make me feel good because I
32:57
Speaker 1: do twenty thou steps. Apparently every day I see, Well,
33:00
Speaker 1: there's a little green led that's just flashing like crazy
33:02
Speaker 1: and it's because my h it tries to measure my
33:05
Speaker 1: heart rate and it's unable to keep up. Okay, maybe
33:08
Speaker 1: not the best example, but the technology and this is astonishing.
33:12
Speaker 1: Go back in time and this so what I was
33:13
Speaker 1: I was sitting there in two thousand said, with my
33:15
Speaker 1: kids and Lego mind storms. Um, a guy named James
33:18
Speaker 1: Park had just gotten a wee controller. UM, and we
33:22
Speaker 1: you know the video showing the controller and he's like,
33:23
Speaker 1: what is this? What isn't this stick that? Let's that
33:25
Speaker 1: cursor in the three dimensional opens us a little chip
33:30
Speaker 1: in there and he says, awesome, what what else would
33:32
Speaker 1: that chip be good for? And he comes up with
33:33
Speaker 1: fitbit UM with with his colleagues. So, um, so what
33:37
Speaker 1: happened is that a series of core technologies, UM, what's
33:42
Speaker 1: called mem sensors. These these sensors on a chip, um
33:46
Speaker 1: micro electro mechanical sensors and this like a sensors so
33:52
Speaker 1: they can sense motion, direction, gravity, exact else. Um, these
33:56
Speaker 1: you know, these incredibly fast, low power processors, the arm UM,
33:59
Speaker 1: why I FI cameras, GPS, lithium battery technologies. All this
34:05
Speaker 1: stuff was coming out of the iPhone and other smartphones.
34:08
Speaker 1: And because you have these extraordinary kind of you know
34:11
Speaker 1: the amount of R and D and economies of scale production,
34:13
Speaker 1: those components were now available to adjacent industries. And you
34:17
Speaker 1: know that very inexpensive, very inexpensive, and I call this
34:20
Speaker 1: the peace dividend of the smartphone. Course. Um, what happened
34:24
Speaker 1: is that you take you take these extraordinary technologies, these chips,
34:27
Speaker 1: they are now available really you know, expensively. Then you
34:30
Speaker 1: have the uh these desktop fabrication tools like three D
34:35
Speaker 1: printers and seen C machines and laser cutters, et cetera.
34:38
Speaker 1: And then you have open source communities. You combine them
34:41
Speaker 1: and now you've got the germs of an industrial revolution.
34:44
Speaker 1: And that's and that's and this this kind of this
34:46
Speaker 1: ability for regular people to do to take take like
34:49
Speaker 1: the long tail of physical things rather than just digital things.
34:53
Speaker 1: Is what drove the maker movement and the kickstarter phenomenon
34:57
Speaker 1: what we're experiencing today. So yeah, so so um so
34:59
Speaker 1: I started by just sort of like, you know, just
35:01
Speaker 1: just a weekends throwing together kids, and you know the
35:03
Speaker 1: problem is that they sold out immediately and the kids
35:06
Speaker 1: just wouldn't do it again. So I'm like, I got
35:08
Speaker 1: better things to do than stuff pizza boxes. So I
35:10
Speaker 1: found a guy on the internet named Jordi MNOs who
35:12
Speaker 1: seemed really smart, and I sent him a check for
35:14
Speaker 1: five hundred bucks and he's just started doing it instead.
35:17
Speaker 1: And then it gets kept sending me pictures and he's like, yeah,
35:20
Speaker 1: I've expanded the space. I haven't met him, right, have
35:22
Speaker 1: expanded the space and hired some people, and by two
35:25
Speaker 1: thousand and twelve he's in Mexico. Is that wrong? I
35:29
Speaker 1: didn't know at the time. It turns out that he was,
35:32
Speaker 1: you know, when I met him, he was a nineteen
35:33
Speaker 1: year old in Tijuana, scraduate from high school. Um. But
35:36
Speaker 1: by you know, by the time I actually went it
35:38
Speaker 1: was like he keeps sending these pictures of bigger and
35:40
Speaker 1: bigger drone factories. By the time I met him, I mean,
35:42
Speaker 1: we're probably doing five million a year. UM. By the time,
35:46
Speaker 1: by the you know, by around two thousand and twelve,
35:48
Speaker 1: I think we were making more drones per month than
35:51
Speaker 1: all of America's aerospace companies combined out of a Tijuana
35:55
Speaker 1: drone factory, which by the way is a greating him
35:57
Speaker 1: for a band. Do you want a drone factory? That's
35:59
Speaker 1: absolutely and UM and so you know, so so by
36:02
Speaker 1: the time I actually made it like not a hobby
36:04
Speaker 1: but like my job and took venture capital, et cetera,
36:07
Speaker 1: is already pretty de rist and so yeah, we at
36:09
Speaker 1: this point we were making physical drones. UM. And you know,
36:13
Speaker 1: but we started UM. I'll just finish with one last
36:15
Speaker 1: story about this. UM in around two thousand and nine
36:18
Speaker 1: or ten or twelve or something like that. UM, there's
36:20
Speaker 1: the the aerospace industry has an annual conference is called
36:23
Speaker 1: a u VS a u v s I, and it
36:27
Speaker 1: has has Autonomous Vehicles Systems internationals like that. Anyway, it's
36:30
Speaker 1: like you know, the Boeings and the Lockets and they
36:33
Speaker 1: have predator drones that it's happening actually this week I
36:37
Speaker 1: think in Las Vegas is the only one anyway, UM,
36:40
Speaker 1: one of the more you know, innovative. Guys on the
36:42
Speaker 1: board invited me to speak to like, you know, the
36:45
Speaker 1: military industrial complex, and I gave I spoke and I
36:50
Speaker 1: held up this little board that we were making called
36:52
Speaker 1: arch Pilot, was based on our duino, and it cost
36:55
Speaker 1: and I said, uh, yeah, so we can do you
36:58
Speaker 1: know this point, drones cost ten million dollars end up
37:00
Speaker 1: and I come out with this board this night five
37:02
Speaker 1: and say, if you take this board and you stick
37:04
Speaker 1: it in like a toy airplane, you basically got the
37:06
Speaker 1: same thing you guys do, just for ten million dollars.
37:09
Speaker 1: And they just couldn't figure I mean, they couldn't decide
37:11
Speaker 1: whether I was you know, whether it was crazy or
37:14
Speaker 1: dangerous or both. But they knew that it wasn't that
37:17
Speaker 1: it was a joke. You know, they knew that I
37:19
Speaker 1: was not to be taken seriously. And you know the
37:22
Speaker 1: Gandhi phrase. They answers to ignore you, that I laugh
37:24
Speaker 1: at you, then they fight you, then you then you've
37:26
Speaker 1: won today. You know that board and others like that.
37:30
Speaker 1: There are other people were doing the same thing at
37:31
Speaker 1: the same time. I'm there now a million drones sold
37:34
Speaker 1: per year. You can now there's never been a technology
37:37
Speaker 1: I can think of that went from military industrial complex
37:40
Speaker 1: to the toy shelves of Walmart faster than drones. And
37:44
Speaker 1: when we started, people said you can't use the word
37:45
Speaker 1: drone because it sounds like a weapon. Now they tell
37:48
Speaker 1: us we can't use the word drone because it sounds
37:49
Speaker 1: like a toy. So so the question, all right, so
37:52
Speaker 1: I have to ask the question I asked when I
37:55
Speaker 1: saw that big black drone out outside of your reception areas.
38:02
Speaker 1: All right, so where's the hunter killer adaptation? How do
38:04
Speaker 1: I add something too? If I need to take care
38:09
Speaker 1: of business? What's the adaptation to It's got elements of
38:14
Speaker 1: Skynet to it. How often do you get that idiotic question?
38:18
Speaker 1: Because some of these things, look, it's not that idiotic.
38:21
Speaker 1: I mean isis is using drones very much like ours?
38:24
Speaker 1: Hopefully not ours, but very much like ours today. Um,
38:27
Speaker 1: they did exactly what you described. They bought typically they'll
38:30
Speaker 1: buy um uh drones from China. Um. They stick a
38:34
Speaker 1: little a little hook on the bottom, and then they
38:37
Speaker 1: drop bombs off of the drones. So there was another
38:41
Speaker 1: drone I was looking at uh last weekend in the
38:44
Speaker 1: Apple store. That it's very light, it's very small. The
38:50
Speaker 1: um rotors are engaged in a sort of hovered drone. Yeah,
38:55
Speaker 1: and it has his facial recognition software built in, so
38:59
Speaker 1: when you lock it on somebody, it just tracks them.
39:02
Speaker 1: And I'm like, oh, that's how you assassinate people. You
39:05
Speaker 1: just need some some minor thing. So it's not that
39:11
Speaker 1: far from skynet. Yeah, I can be pretty you know,
39:13
Speaker 1: whatever the science fiction catastrophe you imagine. You know, there
39:16
Speaker 1: may be catastrophe, but it won't be that. Oh, I
39:18
Speaker 1: don't think it's a broad catastrophe. I think it's just
39:21
Speaker 1: an efficient way to remove certain people who are problematic.
39:24
Speaker 1: Well how far away is that that? So that Tuesday,
39:28
Speaker 1: that particular one. So that's not going to happen for
39:30
Speaker 1: a number of reasons. First of all, if you'd actually
39:32
Speaker 1: take an hour of the box and turn it on,
39:34
Speaker 1: you would have heard that it's really noisy, and you're
39:36
Speaker 1: not gonna let this like buzzing. You know many laws,
39:39
Speaker 1: by the time you hear it, it's too that's their tagline.
39:42
Speaker 1: By the time you hear us coming, it's too late.
39:44
Speaker 1: Would that that were true? You heard drums this morning?
39:47
Speaker 1: There there there their noise. You're not gonna stealth, you know, now,
39:50
Speaker 1: at least not. What the hellico, how far away are
39:52
Speaker 1: we from stealthier rotors or is that just physics and
39:55
Speaker 1: that's never going to change. Well, you know we work
39:57
Speaker 1: hard on that. You know, we don't make the drums anymore.
39:59
Speaker 1: We just do this off where but you know, um,
40:01
Speaker 1: you know, up against so we can absolutely do more
40:03
Speaker 1: with you know, there are different propeller designs and you know,
40:06
Speaker 1: vibrations and resonant frequencies and on speeds and all this
40:08
Speaker 1: kind of stuff, but but by large you up against physics.
40:10
Speaker 1: Now that's not to say that an airplane, you know,
40:13
Speaker 1: the ones with wings can't just glide their way silently.
40:16
Speaker 1: But it's not gonna hover, So you get hover and
40:18
Speaker 1: noise or you get non hovers, so either stealthy or
40:21
Speaker 1: or very mobile. So you mentioned earlier the you realize
40:25
Speaker 1: this is a real business. You um said, let's let's
40:28
Speaker 1: most of this is the risk. Let's go to the
40:30
Speaker 1: venture capital route. What was that process? You had VC
40:34
Speaker 1: money from Qualcom, from Richard Venture, Richard Branson from True Ventures.
40:39
Speaker 1: What is the process like going to a VC and saying, hey,
40:43
Speaker 1: we have this idea for a new company, what we're
40:44
Speaker 1: gonna build and sell this new technology. Well at this
40:49
Speaker 1: point it wasn't a new company. Remember we bootstrapped it
40:52
Speaker 1: to you know, to to something like five million of revenues,
40:54
Speaker 1: and you know, it was make money and and so
40:57
Speaker 1: that's quite unusual to do risk something that that much.
41:01
Speaker 1: Um So, taking it to to venture capitals, I mean,
41:04
Speaker 1: it's very early. And at this point we were roughly
41:06
Speaker 1: basically technology. We're sort of saying, you know, we have autopilots,
41:09
Speaker 1: which are these boxes the brains for the planes instead
41:12
Speaker 1: we have autopilots. You know, we have some kits. Um
41:15
Speaker 1: it was by no means the shelves of Walmart yet,
41:19
Speaker 1: and we actually um articulated the the the ultimate goal
41:23
Speaker 1: not being selling consumer electronic devices and Walmart, but rather
41:26
Speaker 1: putting sensors in the sky. The intention was always to
41:29
Speaker 1: use drones as a tool, um to extend the Internet
41:32
Speaker 1: into physical space. And so you know, part of extending
41:35
Speaker 1: the Internet into physical spaces to gather it's a sense
41:38
Speaker 1: the space and the cameras, etcetera. The other is to
41:41
Speaker 1: extend the intelligence of the Internet out so the devices
41:44
Speaker 1: can basically harness the collective whatever, the big data in
41:47
Speaker 1: neural networks whatever. Um So, the idea was, Okay, we're
41:50
Speaker 1: gonna put sensors in in in in the sky. It's
41:53
Speaker 1: gonna compliment ground sensors, it's going to complement satellites. If
41:57
Speaker 1: you look up, this guy is empty. It's just the
42:00
Speaker 1: just thing. I mean, it's very hard to find a
42:01
Speaker 1: market as empty as the sky. But that's there's a
42:04
Speaker 1: lot of sky out there in this room for plenty
42:07
Speaker 1: of drones, and it doesn't look like you're really taking
42:10
Speaker 1: up a lot of space exactly. And the drones are
42:12
Speaker 1: smart in the same way, the same way. You know.
42:13
Speaker 1: The analogy I would use is on wireless. You know,
42:16
Speaker 1: there was a time when the f c c S
42:18
Speaker 1: job was to give give wireless carries monopoly ownership of
42:22
Speaker 1: certain way of certain spectrum. You know, you know, this
42:24
Speaker 1: frequency is yours and that frequency of somebody else's, and
42:27
Speaker 1: we have to kind of, you know, block off the
42:29
Speaker 1: bits so they don't interfere and ruin you know, grandma's
42:31
Speaker 1: television reception or whatever. It wasn't those then along came WiFi,
42:36
Speaker 1: which says, hey, you know what if we have like
42:38
Speaker 1: low power and the ability to kind of listen before
42:40
Speaker 1: you talk, and you know, digital radios etcetera. Maybe you
42:43
Speaker 1: could just give us a sandbox, a little sort of
42:45
Speaker 1: you know, spectrum, just let us know play, no licenses,
42:49
Speaker 1: no ham radio, just you know, no no monopolies, just
42:52
Speaker 1: let us play. And that's a sense to you what
42:54
Speaker 1: we achieved. Um, with drones, we sort of we said, hey,
42:58
Speaker 1: you know, give us a sandbox, and sandbox is going
43:00
Speaker 1: to be visual line of site under four hundred feet,
43:04
Speaker 1: don't fly over people, private land and things like that.
43:06
Speaker 1: And and recreated originally was recreational used, not commercial use.
43:11
Speaker 1: And all those things were were legal, you know, call
43:14
Speaker 1: them loopholes or call them. You know, it was a
43:17
Speaker 1: carve out, it was. It wasn't. I think it was
43:20
Speaker 1: a carve out actually for radio control hobbyists rather than
43:22
Speaker 1: for drones. That happened in the seventies. But we used
43:25
Speaker 1: that carve out to to basically stick a million drones
43:28
Speaker 1: in the air. And then we're like, okay, now they're here,
43:30
Speaker 1: they're good. Now what are they good for? And this
43:33
Speaker 1: became the commercial use. And originally I thought it was
43:35
Speaker 1: gonna be agriculture. I thought we were going to be
43:37
Speaker 1: you know, um, and they are currently used pretty robustly,
43:40
Speaker 1: and they are, but not as agriculture, real estate. I
43:44
Speaker 1: can't tell you how many homes I've seen that standard
43:48
Speaker 1: drone and over. Oh isn't that lovely? Look at it?
43:52
Speaker 1: I mean, that's become stand So Hollywood, of course is
43:54
Speaker 1: that was was was one. So you guys were involved
43:57
Speaker 1: with Fast and Furious, if I've seen some of your
44:00
Speaker 1: toys actually, and we were involved in the Benghazi film.
44:04
Speaker 1: But the Fast and Furious is that we have these sprints,
44:07
Speaker 1: um and you know, so sprints are are our development
44:11
Speaker 1: milestones are all named after Fast and Furious films. Uh,
44:15
Speaker 1: you know, Fast and Furious exactly. And it just turns
44:17
Speaker 1: out there making the films about as quickly as we
44:19
Speaker 1: can develop. So so you know, I think this is
44:21
Speaker 1: the towards the end of them at this point, this
44:24
Speaker 1: last one. You think the number eight is going to
44:25
Speaker 1: be the I'm hoping, well, we'll have to come up
44:28
Speaker 1: with another theme for our sprints. So so what have
44:31
Speaker 1: you done much in with Hollywood? Have you done much
44:34
Speaker 1: on that side? So so we we did a tiny
44:36
Speaker 1: bit in Hollywood. But actually there's a you know our
44:39
Speaker 1: you know, back when we were making drones, our biggest
44:40
Speaker 1: competitive with a Chinese company called d g I, which
44:42
Speaker 1: was extraordinary, perhaps the best company I've I've ever seen anywhere,
44:46
Speaker 1: not just in China. And um, they really focused on
44:50
Speaker 1: the on the cameras, the stabilization, et cetera. And today
44:54
Speaker 1: Ji makes the Parrot. No no, but the Parrot is
44:57
Speaker 1: a fringe company makes the Fantom, the Phantom of and
45:00
Speaker 1: you know it's something called the magick. I remember when
45:02
Speaker 1: the Phantom first came out, it was like two thousand
45:04
Speaker 1: dollars and it was twelve dollars and it was seven.
45:07
Speaker 1: The prices just plummeted in that is that China subsidizing
45:11
Speaker 1: this or these guys really ringing out economies of scale
45:15
Speaker 1: like that? It's that good. Yeah, so, um, you know
45:18
Speaker 1: I lived in China. I knew, you know when I
45:20
Speaker 1: lived in China for those those years of the Economist,
45:22
Speaker 1: everyone said, oh, don't worry about China. They can't do x.
45:25
Speaker 1: X was like innovate or design or software global or
45:29
Speaker 1: global brands or anything like that. It's a very subtle
45:33
Speaker 1: racism built into that, which is a repeat of what
45:37
Speaker 1: I recall hearing about Japan right Japan early on was
45:42
Speaker 1: oh they only make junk and they're good in imitating.
45:45
Speaker 1: They can't innovate anything, and then suddenly, wow, this is
45:49
Speaker 1: really first class products. And if you remember when Hyundai
45:52
Speaker 1: first came out, they were kind of junkie cars, and
45:55
Speaker 1: now suddenly they were the only company that comes out
45:58
Speaker 1: of the financial crisis increasing market share. I think with
46:01
Speaker 1: them so that, oh, those guys can't do anything. That's
46:05
Speaker 1: a very dangerous assumption for anyone to ever make. So so,
46:09
Speaker 1: you know, everything I learned about China before going there,
46:12
Speaker 1: I think turned out to be wrong. Everyone said, oh
46:15
Speaker 1: you know, um, you know, the political system is unsustainable,
46:18
Speaker 1: their economic growth is unsustainable. It's Quoe unquote. Centrifugal forces
46:22
Speaker 1: would sort of splinter. They you know, they can't innovate,
46:25
Speaker 1: They only copy and and I And it was it
46:28
Speaker 1: was around two thousand eight or two thousand nine where
46:30
Speaker 1: I spent most of my time in Guandong province around Shenzhen,
46:34
Speaker 1: and I spent uh. I spent a night in Huawei,
46:38
Speaker 1: which is the telecoms company at the time they were
46:40
Speaker 1: being accused stealing from the Cisco stuff. It was way
46:46
Speaker 1: before iPhone. I just said, this is nineties, um and uh,
46:51
Speaker 1: and so I spent a night. You know, the engineers
46:53
Speaker 1: are working all night and sleeping on phutons, and I
46:55
Speaker 1: was like, these guys are awesome. They're serious. They're basically
47:00
Speaker 1: and you know they're basically. Yes, they're making iPhones today,
47:02
Speaker 1: but they're taking notes. And um, the company we ended
47:06
Speaker 1: up competing with d G I started around actually a
47:08
Speaker 1: little bit before US. Um but um, you know, the
47:11
Speaker 1: so called in China can't do X. We haven't found
47:14
Speaker 1: an X. So they they innovated. They raised ten billion
47:19
Speaker 1: dollars billions of dollars of of venture capital, ten billion
47:25
Speaker 1: dollar valuation. They went global initially, they actually targeted outside
47:28
Speaker 1: of China before China. Their design exquisite, their marketing is fantastic.
47:33
Speaker 1: Um you know, uh there and then the production efficiencies
47:37
Speaker 1: because they were insins and they vertically integrated, so they're
47:40
Speaker 1: doing everything. You know, they're you know, they weren't. They
47:42
Speaker 1: weren't like they weren't just like buying off the shell
47:44
Speaker 1: stuff like we were. They were making fundamental physics, you know, um, designed, etcetera.
47:51
Speaker 1: So so you know, watching them, you know it's uh,
47:54
Speaker 1: you know, I knew that these twenty one century Chinese
47:58
Speaker 1: companies were coming. I knew that they were going to
47:59
Speaker 1: be good. Um, but just watching the price decline that
48:02
Speaker 1: came with that price decline in nine months, I think
48:07
Speaker 1: there's a you know, we were as the quality went
48:09
Speaker 1: up exactly and I don't think they were dumping. I
48:13
Speaker 1: think they're just that good. So we were one of
48:15
Speaker 1: the first Silicon Valley companies to encounter twenty one century
48:18
Speaker 1: native Chinese company, and um, we won't be the last.
48:23
Speaker 1: So let's talk about the pivot. You originally were designing
48:26
Speaker 1: and manufacturing drones and doing all the software that went
48:29
Speaker 1: into it. The concept is, hey, we we don't even
48:32
Speaker 1: want to try and compete with this behemoth on manufacturing,
48:36
Speaker 1: but the software sort of an Apple model of hey,
48:40
Speaker 1: we'll let these guys build the hardware. We're gonna build
48:44
Speaker 1: the brains of it because that's where our expertise is.
48:46
Speaker 1: How how did that pivot come about and how is
48:49
Speaker 1: that going? So we originally we did it all. Um,
48:52
Speaker 1: we did the hardware, we did the software, which is
48:54
Speaker 1: like the operating system for the drone, and we also
48:56
Speaker 1: did the apps that it ran with it. Um we
48:58
Speaker 1: ended up breaking into three parts. The hardware part we
49:01
Speaker 1: just spun off and don't do that at all anymore.
49:03
Speaker 1: And we now know support whatever hardware's out there. So
49:07
Speaker 1: if I want to go out and buy a three
49:09
Speaker 1: dr drone, are they still available for sale? They they
49:12
Speaker 1: they are. UM, it's called site scanned. It's our it's
49:15
Speaker 1: our commercial one. It's actually it's actually it is. It
49:18
Speaker 1: is a drone that we did make. But the the
49:21
Speaker 1: solo or the it's it's it's it's a derivative. The solo,
49:23
Speaker 1: it's got a fancy Sony cameras, fancy GPS, etcetera nice
49:27
Speaker 1: skimble attached to it as well, exactly. But but soon enough, UM,
49:31
Speaker 1: if you want a different kind of drone, will support
49:32
Speaker 1: that as well. So we're trying to be hardware agnostic
49:34
Speaker 1: right now. We think that this particular integration with the
49:37
Speaker 1: Sony cameras, you know, the best camera, and that's the
49:39
Speaker 1: way to go. But I think that over time we're
49:40
Speaker 1: going to be more flexible and if people want, you know,
49:43
Speaker 1: a different drone, that's that'll be fine. I think that's
49:45
Speaker 1: I'm almost all American drone companies have done the same thing.
49:48
Speaker 1: Everyone stopped making their own hardware. Most people are supporting
49:51
Speaker 1: d g I at this point. Um. Then there was
49:53
Speaker 1: the operating system part um and that was mostly open
49:57
Speaker 1: source thanks to the way we started, and so we
50:00
Speaker 1: spun that off and that's not part of the Linux Foundation.
50:02
Speaker 1: Is it's called drone code and so on the chairman
50:04
Speaker 1: of that as well. That's interesting. So that's open source,
50:07
Speaker 1: available to anyone who wants to anybody or improve it
50:10
Speaker 1: exactly exactly. That's drone code, um. And then there's the apps,
50:14
Speaker 1: and the apps is where we focus. This is using
50:16
Speaker 1: the drone data. So it's less about the drone, more
50:18
Speaker 1: about the data, using the drone data to do something useful.
50:21
Speaker 1: In our case, we've partnered with Autodesk, who's the dominant
50:24
Speaker 1: company in the design. Yeah, it's auto cad. It's construction
50:29
Speaker 1: and engineering and architecture and things like that, and they,
50:33
Speaker 1: you know, their initiative has been to sort of say, well,
50:35
Speaker 1: you know, in construction, you start everything digital on screen cad,
50:39
Speaker 1: and then the moment you dig a spade of dirt,
50:41
Speaker 1: it's it's it's now analog and you can't measure it,
50:43
Speaker 1: you can't use the same tools. So what you need
50:45
Speaker 1: to do is redigitize the world as you're building it.
50:48
Speaker 1: And that's called reality capture. And where the capture and
50:51
Speaker 1: the reality capture that's interesting. I've been watching somebody putting
50:55
Speaker 1: up it's got to be for the past I want
50:57
Speaker 1: to say, two years, every month or every two months,
51:02
Speaker 1: the drone flyover of the Apple campus. And I've watched
51:05
Speaker 1: this come together. It's it's it certainly is time compressed.
51:09
Speaker 1: It feels like cheef. They've been working on that a
51:12
Speaker 1: long time. It seems like it's only a year or so.
51:14
Speaker 1: I've been watching this, but it's astonishing at the clarity
51:19
Speaker 1: and focus and amount of details that you can see
51:23
Speaker 1: for what is essentially private property. Yeah, we're gonna go in.
51:26
Speaker 1: And what sort of issues do you have when you're
51:29
Speaker 1: trying to get that granular on a construction site? And
51:33
Speaker 1: are there problems with people sending drones? So the first
51:37
Speaker 1: question is really the first question is really how granular
51:42
Speaker 1: can you get on a construction site and identifying how
51:45
Speaker 1: big is this whole, how deep is this foundation? How
51:47
Speaker 1: much sand is this here? And then I'll save the
51:50
Speaker 1: question about people doing flyovers for later. Yeah, and the
51:53
Speaker 1: answer to the first is two centimeters per pixel. Two centimeters.
51:58
Speaker 1: Basically we can see a quarter Okay, Um, that's pretty detail.
52:01
Speaker 1: It's pretty detailed. Um, So what you describe as photographs
52:04
Speaker 1: maybe video. That's actually not what the construction industry you're
52:08
Speaker 1: talking about. Actually the measurements of everything contained there, the processes,
52:13
Speaker 1: and you probably saw it this morning on a on
52:15
Speaker 1: a roof. The processes. You you take out an iPad.
52:18
Speaker 1: There's a drone just sitting there. You turn on the drone,
52:22
Speaker 1: pruss the button, take out your iPad. Um you you
52:25
Speaker 1: either either, but you're doing the same scan every day,
52:27
Speaker 1: which cakes you just swipe or you just drag a
52:30
Speaker 1: box around the thing you want to scan and then
52:32
Speaker 1: you swipe. The drone then takes off. It flies like
52:35
Speaker 1: a law and mower pattern or cross hatch pattern. It
52:37
Speaker 1: takes photographs of exactly the right time. So this photographs
52:40
Speaker 1: can be stitched together into a three D model or
52:43
Speaker 1: two D model, and then that is then you superimpose
52:47
Speaker 1: the CAD file, which you know the underlying design over
52:50
Speaker 1: this this model, and you can compare AD as designed
52:53
Speaker 1: with as built. So so this is a little bit
52:55
Speaker 1: of augmented reality. Yeah, you're essentially putting a it's almost
53:00
Speaker 1: like a wire map on top of the world and
53:03
Speaker 1: comparing it to what was supposed to be built precisely.
53:06
Speaker 1: And because it's all so precise. If something's off, it's
53:09
Speaker 1: actually off. So if you if a post is off,
53:12
Speaker 1: or trenches off or or you know, or one of
53:15
Speaker 1: the cables for the you know, for the it's called
53:18
Speaker 1: post tension in cables, which is a big thing in construction.
53:21
Speaker 1: You can actually see it's called a clash. And when
53:24
Speaker 1: you see that, the the that the physical you know,
53:26
Speaker 1: the physical site is often the design. There's only it's
53:29
Speaker 1: only two possibilities. Either it was an intentional change for
53:33
Speaker 1: good reason um and which case you need to reflect
53:35
Speaker 1: that change back into the model so that everyone understands
53:38
Speaker 1: and things have changed. Or it was an accident, in
53:40
Speaker 1: which case you need to catch it and fix it.
53:41
Speaker 1: And it sounds like it's vastly less expensive to catch
53:44
Speaker 1: it early than to catch it after the building is built.
53:47
Speaker 1: In Hey, why are we tilting in San Francisco. There's
53:51
Speaker 1: that famous building that's off. You guys would have caught
53:54
Speaker 1: that earlier, whatever was. I don't know if we would
53:56
Speaker 1: have cat got that one. But the construction industries the
53:59
Speaker 1: second largest day the stry in the world after after food,
54:02
Speaker 1: eight trillion dollar industry, and unlike agriculture, which is hedged
54:05
Speaker 1: against all sorts of inefficiencies, constructions not it's got eight
54:10
Speaker 1: average cost overruns, so it's like it's like a five
54:15
Speaker 1: trillion dollar industry that overran the self to eight trillion
54:17
Speaker 1: dollars UM. And those cost overruns are typically due to
54:21
Speaker 1: to just stuff happened right, mistakes, delays, it's a complicated
54:26
Speaker 1: supply chain. Any kind of delay turns into cost um
54:29
Speaker 1: So this is a huge efficiency created a huge cost savings.
54:33
Speaker 1: Is the expectation. Eventually every major contractor is using some
54:37
Speaker 1: form of drones to help build their don't you know
54:41
Speaker 1: it's it's UM. So there's lots of ways to to
54:43
Speaker 1: do reality capture. You can do it I'm on the
54:46
Speaker 1: ground with laser scanning. You can do it on the
54:48
Speaker 1: ground with cameras. There's inside the building and outside the building.
54:51
Speaker 1: So what drones scanning is best force is commercial construction UM.
54:56
Speaker 1: Typically some of the larger sites often not like in
55:00
Speaker 1: in the city center because you have fa regulations about
55:03
Speaker 1: where you can fly and where you can't fly. So
55:05
Speaker 1: it's kind of commercial sites um lucky think as skyscrapers
55:08
Speaker 1: in big, big complexes to be the outside of a
55:11
Speaker 1: city center. But still that you're talking about maybe a
55:13
Speaker 1: third of construction falls into that category. And then the
55:16
Speaker 1: most important time to do it is at the beginning,
55:18
Speaker 1: when you've got the site, you're digging the holes and
55:21
Speaker 1: the foundations, etcetera. That characterizing it because remember the drones
55:25
Speaker 1: just scanning the outside of the building. So you scan
55:27
Speaker 1: the site you scanned with foundations, and then you scan
55:29
Speaker 1: each layer as they build it up. So given this
55:31
Speaker 1: NEPHU with that leaning tower of San Francisco, how unlikely
55:37
Speaker 1: is it that eventually ciney planters are gonna say, hey,
55:39
Speaker 1: if we want to avoid this, we have to allow
55:42
Speaker 1: some sort of external scanning. It's being required right now.
55:45
Speaker 1: It's part of a So Japan has just required drone
55:48
Speaker 1: scanning for in major cities. Yeah, well it's for government infrastructure.
55:53
Speaker 1: They do a lot of roads and bridges and highways
55:56
Speaker 1: and things like that. Um. This is part of a
55:59
Speaker 1: trend called building information modeling BIM and building information modeling
56:03
Speaker 1: basically the notion of digitizing sites so you can manage.
56:06
Speaker 1: You know, you can only manage what you can measure,
56:08
Speaker 1: and governments are now requiring BIM, which is to say, hey,
56:12
Speaker 1: you know, we need you to measure these sites because
56:14
Speaker 1: these costs, over runs are being paid for by somebody,
56:16
Speaker 1: and it's either the ultimately it's the consumer, the end user.
56:20
Speaker 1: Who's who's going to subsidize that, unless it's a government project,
56:24
Speaker 1: in which case it's a tax pay it's a reasonable request.
56:26
Speaker 1: Measure what you're doing so that we can manage it better.
56:29
Speaker 1: You know, either we're gonna avoid the errors, or if
56:31
Speaker 1: it happens, we know why it happened, who caused it?
56:34
Speaker 1: Paper trail. I mean, so many construction projects and in
56:36
Speaker 1: lawsuits and you have this like this question, like how
56:39
Speaker 1: did that happen? We were discussing earlier about the low
56:44
Speaker 1: cost of all these chip sets and and individual chips
56:48
Speaker 1: that allowed you to do really incredible things at a
56:51
Speaker 1: very low cost. What made you realize that, hey, these
56:55
Speaker 1: drone things, this is more than just a cool little toy. Um.
57:01
Speaker 1: First of all, I didn't initially realize that. Okay, So,
57:04
Speaker 1: I mean my path was really simple. I've got five kids,
57:07
Speaker 1: and my wife and I are are former scientists. We
57:09
Speaker 1: try to get our kids sided about science and technology,
57:11
Speaker 1: and we fail and fail and fail again. Um, And
57:14
Speaker 1: so every weekend, i'm you know, I'm I'm trying to
57:17
Speaker 1: think of something that will engage them keeping busy, well,
57:20
Speaker 1: I mean keep them busy. I mean video games will
57:22
Speaker 1: keep them busy, but I want to keep their minds
57:23
Speaker 1: busy as well. So, UM, one weekend, an editor wired,
57:28
Speaker 1: you know, and I we get these like products in
57:30
Speaker 1: for review, and this lego mind storms and xt robotics
57:35
Speaker 1: kit comes in, and this like radio control airplane comes in.
57:37
Speaker 1: I'm like, okay, one of these two things is going
57:38
Speaker 1: to work. Um, either the robot building robot will be
57:42
Speaker 1: cool or at least flowing a plane will be cool.
57:44
Speaker 1: And um, you know, the kids roll their eyes and
57:47
Speaker 1: another one of Dad's things. Um, so we we build
57:49
Speaker 1: a robot, and um, it was not cool. It was
57:52
Speaker 1: not I thought it was cool. Um, but you know
57:55
Speaker 1: it's basically spent all morning building and I leg up
57:57
Speaker 1: pieces and it rolls very slowly. I guess it doesn't
57:59
Speaker 1: all if I only a wave. Its arms basically just
58:02
Speaker 1: had two wheels and it rolled towards a towards the
58:04
Speaker 1: wall and then kind of backed away. And they're like,
58:05
Speaker 1: come on, we've seen transformers away the lasers. Um. And
58:08
Speaker 1: then you know, the next then then on the next
58:11
Speaker 1: day we flew the airplane, which is to say I
58:13
Speaker 1: flew directly into a tree and then right that sucked. Um,
58:16
Speaker 1: so I My thought process consisted of the following, Um,
58:20
Speaker 1: you know one those rotten kids to that actually wasn't
58:24
Speaker 1: very cool. Three what would have been cooler? Ha? What
58:28
Speaker 1: if the robot could fly the plane? What if we
58:30
Speaker 1: had a flying robot? That'd be cool? What's a flying robot?
58:33
Speaker 1: Just came home googled flying robot. If you google flying robot,
58:37
Speaker 1: you will find the first result is drone And you're like, oh, ha,
58:41
Speaker 1: I guess the drone is a flying robot. Wait what's
58:43
Speaker 1: the drone? Google drone? Oh, a drone is like an
58:46
Speaker 1: airplane with an autopilot. It's like a plane with the brain.
58:49
Speaker 1: Oh yeah, I guess that makes sense. Wait, what's an autopilot?
58:52
Speaker 1: Google autopilot. An autopilot is like sensors and and and
58:57
Speaker 1: software that you know, kind of measure you know, the
59:00
Speaker 1: orientation on the plane and flight. It's like, oh, wait,
59:02
Speaker 1: sensors and software. Isn't that what's in the Lego mind
59:05
Speaker 1: storms box. Let's just do that. And so they're on
59:08
Speaker 1: the dining room table. We put together a Lego autopilot
59:11
Speaker 1: and we stuck it in the RC plane which I
59:13
Speaker 1: had retreat from the tree and took it back to
59:16
Speaker 1: the field, and you know, it worked just well enough
59:20
Speaker 1: and kind of flew autonomously, just just just long enough
59:23
Speaker 1: for me to say, holy cow, what have we just
59:26
Speaker 1: done here? The kids are like, yeah, as we said,
59:28
Speaker 1: that sucked dad, um, you know, and I'm like, wait,
59:31
Speaker 1: so there's Kittie Hawk watching the Invention of drones and
59:35
Speaker 1: they're like, yeah, what else you got? Yeah? Because he
59:37
Speaker 1: flew flights sixty? Come on, you know, where's where's my
59:41
Speaker 1: jet back? Um? Um? I had that T shirt? Where's
59:44
Speaker 1: my flying car? So? Um? Uh? So I you know,
59:49
Speaker 1: I the hairs went up on the back of my neck.
59:51
Speaker 1: I was like, I don't know what just happened there,
59:53
Speaker 1: but I need to find out. And so I create
59:55
Speaker 1: a website called d I y Drones, which was basically
59:58
Speaker 1: a place for me to ask them questions in public.
1:00:00
Speaker 1: And when you ask dumb questions in public, two wonderful
1:00:02
Speaker 1: things happened. Number One, people answer your dumb questions, and second,
1:00:06
Speaker 1: it liberates other people to ask their own dumb questions.
1:00:08
Speaker 1: And it was just that moment. Its two thousand and seven.
1:00:10
Speaker 1: It's the moment where all these disciplines were coming together.
1:00:13
Speaker 1: There were software, people on hardware, people on airplane people, etcetera.
1:00:17
Speaker 1: And over the course of a couple of years they
1:00:19
Speaker 1: based at the community basically created the most advanced drones.
1:00:24
Speaker 1: You know that you well, certainly most advanced drones you
1:00:26
Speaker 1: could buy, and possibly most of advanced drones in the world,
1:00:29
Speaker 1: at least the technology. And it was our jobs to
1:00:31
Speaker 1: create a company to turn them into a product. So
1:00:33
Speaker 1: so originally you were selling kits. You could get these engines,
1:00:37
Speaker 1: you could get these motors, these battery packs. Here, put
1:00:41
Speaker 1: this to your together yourself and have have some fun.
1:00:44
Speaker 1: When did that? First of all, how long did that
1:00:46
Speaker 1: go on? And how did that come about? And then
1:00:49
Speaker 1: when did that transfer to let's build drones and sales
1:00:53
Speaker 1: to the public. So it was a hobby from two
1:00:55
Speaker 1: thousand seven to thirteen oh so full six years of
1:00:58
Speaker 1: just me, just new LNG. Wait now when I say hobby,
1:01:01
Speaker 1: um uh, you know it started with me and my
1:01:04
Speaker 1: kids putting together robot blimp kids in the pizza boxes.
1:01:09
Speaker 1: Um did they ever get excited about the idea of drones?
1:01:12
Speaker 1: That never? Never, And you have some crazy cool stuff here,
1:01:16
Speaker 1: even this stuff they're like, who cares? Yeah, no, I know,
1:01:20
Speaker 1: you know you got any more kids? I brought one
1:01:24
Speaker 1: and he's walking around, eyes bugging out of his head, going,
1:01:27
Speaker 1: oh my god, look at all this stuff. But he's
1:01:29
Speaker 1: in his thirties, so this is he's the right age.
1:01:33
Speaker 1: I think they're spoiled that. Let's talk about Silicon Valley
1:01:38
Speaker 1: and the so called bubble and unicorn. So I always
1:01:42
Speaker 1: hate when people pull out the most extreme example of
1:01:46
Speaker 1: something and try and paint everybody with that brush. Is
1:01:50
Speaker 1: there a bubble and Silicon Valley today? I'm I'm the
1:01:55
Speaker 1: worst person to ask, um, So actually know it to
1:02:00
Speaker 1: evaluations really just it's it's not how we keep Doesn't
1:02:05
Speaker 1: it affect the ability to either fine talent higher source
1:02:10
Speaker 1: things that when things get crazy, it's like, hey, we
1:02:13
Speaker 1: can't hire anybody's engineers are asking for four hundred thousand
1:02:16
Speaker 1: as a base seller. Doesn't the when things get really
1:02:19
Speaker 1: out of hand doesn't affect everything? It must? I mean,
1:02:22
Speaker 1: I'm sure you're right, um. I mean the engineers that
1:02:26
Speaker 1: I've worked with in the past are motivated primarily by
1:02:29
Speaker 1: the work. They want to do the most exciting work
1:02:33
Speaker 1: of their career. I mean, there was a while when
1:02:35
Speaker 1: our recruiting technique consisted of the words flying robot, do
1:02:39
Speaker 1: I sign? Yeah? Exactly. Um, I mean, I'm sure that
1:02:44
Speaker 1: at some level the ability to you know, have upside
1:02:47
Speaker 1: in your in your stock options or sorary. I mean,
1:02:50
Speaker 1: of course that's a that's a thing, but it should
1:02:52
Speaker 1: be a second order um thing. I mean, the reason
1:02:55
Speaker 1: that you know, the Tesla's and ubers are able to
1:03:00
Speaker 1: there is a special case, let's say, the Teslas of
1:03:01
Speaker 1: the world where apples are able to hire so well
1:03:04
Speaker 1: is because you're going to do really exciting, meaningful work.
1:03:08
Speaker 1: On the way up here, we passed the Tesla factory
1:03:11
Speaker 1: and it's enormous, and it's just like, wait, what was
1:03:14
Speaker 1: there before? This was? Oh, that was just a field. No,
1:03:18
Speaker 1: it was actually no, it's a it's a great story.
1:03:20
Speaker 1: Is a really good this American Life episode. It was
1:03:22
Speaker 1: a new me. Um, the GM Toyota, I think, um
1:03:26
Speaker 1: the future of of car manufacturing. Well, it turned out
1:03:30
Speaker 1: to turn out there that's the future of it could
1:03:32
Speaker 1: be the future of cars. People don't give give enough
1:03:35
Speaker 1: credit for that particular one. He was able to buy
1:03:38
Speaker 1: that factory. It's a mile long, right, he was able
1:03:40
Speaker 1: to buy that factory for um, you know, for pennies
1:03:43
Speaker 1: on the dollar before there was any real case, and
1:03:46
Speaker 1: originally tested was like a tiny corner like one factory
1:03:49
Speaker 1: at the end. By the end, by the time he's done,
1:03:52
Speaker 1: he'll be using it, all of it and more. And
1:03:53
Speaker 1: then brought all that equipment as well for again pennies
1:03:56
Speaker 1: on the dollar. That that was so the original slow
1:04:00
Speaker 1: was buying the Lotus, taking the engine out and filling
1:04:03
Speaker 1: the floor of the car with batteries essentially, And this
1:04:07
Speaker 1: is where they're actually making the cars, and it's it's
1:04:09
Speaker 1: astonishing to drive by. It's gleaming and amazingly amazingly huge.
1:04:14
Speaker 1: And then you know, keep going, you know you'll get
1:04:16
Speaker 1: to the solar City bit and battery factory, Gigga factory.
1:04:20
Speaker 1: You keep driving south and you'll get to SpaceX. So
1:04:23
Speaker 1: there's some cool stuff happening after here. And by the way,
1:04:25
Speaker 1: you don't have to drive because he's digging a tunnel
1:04:27
Speaker 1: between the two the hyper loop. Is that really gonna
1:04:29
Speaker 1: I'm not think that the tunnel hyper different thing. Really, Yeah,
1:04:32
Speaker 1: I can't keep it's not actually taking a tunnel between
1:04:35
Speaker 1: the two. But would it would be fun if he
1:04:37
Speaker 1: if he was Um, so you don't really think about
1:04:41
Speaker 1: valuation or bubbles. What motivates people who are attracted to
1:04:49
Speaker 1: this part of the part of the world. What what
1:04:52
Speaker 1: is the driving factor? There are vast riches here, but
1:04:55
Speaker 1: there's some really cool stuff here. What what's the dominant
1:05:00
Speaker 1: meme out here? Well, you know, I did, I mean,
1:05:02
Speaker 1: I don't dominant meme is is saying a lot. I mean,
1:05:06
Speaker 1: I think in general, and it sounds like a cliche.
1:05:09
Speaker 1: You know, the idea that this goes right back to
1:05:11
Speaker 1: the foundings of Wired, The idea that can technology that
1:05:13
Speaker 1: can change the world continues to resonate. Um. You know,
1:05:17
Speaker 1: Elon Musk is kind of everybody's hero. But you know,
1:05:19
Speaker 1: Jeff Bezos and you know Larry and Saragei from from
1:05:22
Speaker 1: Google are all in the same category. They are tackling
1:05:25
Speaker 1: the big problems. This is the environment, food, life off
1:05:29
Speaker 1: the planet, the future of transportation of energy. I mean,
1:05:32
Speaker 1: this is like, you know, say nothing of biotech and
1:05:34
Speaker 1: medicine and all that. Um, people feel like they're doing
1:05:37
Speaker 1: meaningful work. It certainly makes makes a lot of sense.
1:05:41
Speaker 1: Let's talk about all these private companies that have chosen
1:05:45
Speaker 1: not to go public. What do you again, I look
1:05:48
Speaker 1: at you as somebody who is a astute observer of
1:05:52
Speaker 1: the technology seen around you. So even if you don't
1:05:57
Speaker 1: necessarily care about valuation, what do you make of these companies?
1:06:01
Speaker 1: Go down the list of unicorns that have these huge
1:06:03
Speaker 1: valuations and just seem to show no interest in I
1:06:06
Speaker 1: p owing. What's the exit for the vcs and and
1:06:10
Speaker 1: what is the reluctance to cash out or raise more capital.
1:06:15
Speaker 1: I guess for someone like Uber they don't need more capital. Well,
1:06:18
Speaker 1: the reluctance to go public is obvious, which is there's
1:06:21
Speaker 1: that it's a hassle to be a publicly traded company. Yeah,
1:06:23
Speaker 1: but it's how you, as an individual get liquid. It's
1:06:28
Speaker 1: how your backers. Well as an individual, there's lots of
1:06:31
Speaker 1: ways to go to get liquid. You know, a Travis
1:06:33
Speaker 1: you know, there's there's plenty of secondary markets for that.
1:06:37
Speaker 1: It is for your employees, it's a little it's a
1:06:39
Speaker 1: little tougher, and you know, there's been a lot of
1:06:41
Speaker 1: me you will you'll probably you know, maybe you can
1:06:43
Speaker 1: advise me on this. It's been all this talk of like,
1:06:46
Speaker 1: you know, secondary markets that liquid, secondary markets that could
1:06:49
Speaker 1: allow people, employees, et cetera, to get liquid Um, they've
1:06:53
Speaker 1: always they've never really come to fition. Course. Well, part
1:06:57
Speaker 1: of the reason is when you're you go public, you
1:07:00
Speaker 1: go through the SEC process, You go through this and
1:07:02
Speaker 1: there's a very standard set of ways of you're locked
1:07:06
Speaker 1: up for this period of time, and now if you
1:07:08
Speaker 1: want to sell some or all of your stock, here's
1:07:10
Speaker 1: the methodology. The various secondary markets simply aren't big and
1:07:15
Speaker 1: deep and liquid enough to do that for every company
1:07:18
Speaker 1: that wants to go public or doesn't want to go.
1:07:21
Speaker 1: But that's right, and then you you also end up
1:07:23
Speaker 1: with the venture capital backers and the original founders who
1:07:27
Speaker 1: either put up money or sweat equity or both. It's
1:07:31
Speaker 1: hard to see how they capitalize on the success without
1:07:35
Speaker 1: going So is this I look at this as a
1:07:38
Speaker 1: little bit of a Koy dance and Uber will eventually
1:07:41
Speaker 1: go public, as will Lift as well all the other
1:07:44
Speaker 1: unicorns or am I you know old school? Well I
1:07:47
Speaker 1: wouldn't see the whole thing through the lens of unicorns.
1:07:49
Speaker 1: I mean, obviously, have a multibillion dollar valuation, you know,
1:07:52
Speaker 1: there aren't a lot of ways to get liquid. But
1:07:54
Speaker 1: if you have a lower valuation hundreds of millions or
1:07:56
Speaker 1: something like that, then m and a is a perfectly
1:07:59
Speaker 1: reasonable short to do it. And so I would I
1:08:01
Speaker 1: would say that you know, the the you know there
1:08:05
Speaker 1: are when you look at our investors in particular combinations
1:08:08
Speaker 1: strategics like at a desk and qualcom and then venture capitalists,
1:08:11
Speaker 1: they're all looking at creating big value down the line.
1:08:15
Speaker 1: Either it's you know, like you're looking at construction and
1:08:17
Speaker 1: we have the opportunity to be part of the you know,
1:08:20
Speaker 1: transformation of the second biggest industry in the world. Um.
1:08:23
Speaker 1: You know, if we get this right, there will be
1:08:25
Speaker 1: any number of companies that would want to buy us.
1:08:28
Speaker 1: We may not choose not to sell um. But but
1:08:31
Speaker 1: the notion of when you're creating value, you have you
1:08:33
Speaker 1: open up optionality. That's the thing. Now, you don't want
1:08:36
Speaker 1: to create your valuation so high that you that there's
1:08:39
Speaker 1: you could have created a lot of value, but there's
1:08:40
Speaker 1: only like you know, three people, three countries, three companies
1:08:43
Speaker 1: in the world that could buy you, and they won't
1:08:44
Speaker 1: because then you have to go public. UM. So it's
1:08:47
Speaker 1: it's a it's a delicate balancing act. But if you
1:08:49
Speaker 1: created value and if you get taken the time to
1:08:51
Speaker 1: sort of take a tackle a big, big industry. How
1:08:55
Speaker 1: far are we from flying robots really being uh an
1:08:59
Speaker 1: everyday part of life, ordinary life. You mentioned Bezos. There
1:09:03
Speaker 1: was a lot of buzz when he talked about using
1:09:05
Speaker 1: drones as as delivery vehicles. How serious is that? Are
1:09:09
Speaker 1: we eventually going to order something from Amazon and a
1:09:12
Speaker 1: drone is going to drop it at our house? Well,
1:09:14
Speaker 1: you know, so Bezos has the delivery. But there's also
1:09:17
Speaker 1: Uber and others are talking about air taxis. Um, you
1:09:20
Speaker 1: know we're talking about you know, drones on every construction
1:09:23
Speaker 1: side or every farm, et cetera. Um, you know, of
1:09:26
Speaker 1: all of those, I think actually sing drones as a
1:09:29
Speaker 1: conventional part of you know, construction or agriculture is probably
1:09:33
Speaker 1: the nearest. My grandfather, UM was the inventor of the
1:09:37
Speaker 1: automatic sprinkler system, and um he was my inspiration the
1:09:42
Speaker 1: automatic sprinkler system meaning if I have if I have
1:09:46
Speaker 1: timer really yeah, So he was a He was a
1:09:49
Speaker 1: Swiss engineer in Los Angeles working to bring the talkies.
1:09:53
Speaker 1: So you come from a long line of makers. In
1:09:55
Speaker 1: other words, one um, two generations back. That's pretty pretty
1:10:00
Speaker 1: good ancestry for exactly. It was certainly mind spirence. I
1:10:04
Speaker 1: spent my summers as it was kind of a rotten kid,
1:10:06
Speaker 1: and so I was sent to spend my summers with
1:10:08
Speaker 1: my grandfather and we just spent the summer silently working
1:10:12
Speaker 1: in the in the workshop. But what I love about
1:10:14
Speaker 1: the sprinkler, sprinkler is my inspiration for drones. You may
1:10:17
Speaker 1: not think so. I mean, I could see the connection.
1:10:18
Speaker 1: But a sprinkler is a robot. You know, sprinkler is
1:10:21
Speaker 1: connected to the internet, has got sensors. It's you know,
1:10:23
Speaker 1: it comes up mechanically, does its own thing, goes back.
1:10:26
Speaker 1: And well, I love about is how boring it is.
1:10:28
Speaker 1: You just put your sprinklers and you live in New York,
1:10:30
Speaker 1: so he probably no, I live in the burbs, have
1:10:32
Speaker 1: underground sprinklers. Absolutely, you're sticking war zones the rain sensors
1:10:36
Speaker 1: so it doesn't go on in its raining. It's an
1:10:38
Speaker 1: interesting little technology. It just kind of works, right, Yeah, yeah, yeah,
1:10:42
Speaker 1: to take it for granted, So I would that's that
1:10:44
Speaker 1: is the sign of success. So if someday drones are
1:10:47
Speaker 1: as boring as sprinklers, which is to say, there's a box,
1:10:51
Speaker 1: there's a box on the farm, there's a box on
1:10:52
Speaker 1: the construction site, whatever, And every morning it's like eight
1:10:56
Speaker 1: thirty a m. The box opens. The it's not a
1:10:59
Speaker 1: sprinkle coming out as a drone coming out. It surveys this,
1:11:02
Speaker 1: but it goes hone, charges itself and waits for the
1:11:05
Speaker 1: next morning. And this whole thing is completely automated. And
1:11:08
Speaker 1: you and and we I would love to be covered
1:11:10
Speaker 1: in mud. I'd like that stickers like Union stickers on it,
1:11:13
Speaker 1: something like that, you know, just absolutely conventional construction equipment.
1:11:18
Speaker 1: And no one cares about it because all they care
1:11:19
Speaker 1: about the data. What they know is that every morning
1:11:22
Speaker 1: they have a you know, an up to date, super
1:11:25
Speaker 1: high resolution three D two D model of the site
1:11:29
Speaker 1: they digitized. The site was just automatically digitized in the
1:11:32
Speaker 1: cloud every day. Now, that is not something that's decades
1:11:37
Speaker 1: or years off in the future. It's months or weeks away.
1:11:40
Speaker 1: We could do it today today. The only thing stopping
1:11:44
Speaker 1: us is that um f A A regulations currently require
1:11:48
Speaker 1: a pilot in command. Now the pilot that this is
1:11:52
Speaker 1: the p I C. The pilot command doesn't have to
1:11:53
Speaker 1: be a pilot doesn't actually have to be in command,
1:11:55
Speaker 1: but there has to be human present. And when I
1:11:57
Speaker 1: meant when I said that, the way it works that
1:11:59
Speaker 1: you open up your iPad and just swipe. That's swiping
1:12:02
Speaker 1: acts acquired by regulation. So it can't be so it
1:12:07
Speaker 1: can't quite be like a roomba. Not that I have
1:12:10
Speaker 1: a room, but but the way I understand it is
1:12:13
Speaker 1: it knows where it's to home, dock is and how
1:12:15
Speaker 1: to charge. It goes and does its thing and then
1:12:17
Speaker 1: it returns and it does it regularly, like the irrigation system.
1:12:20
Speaker 1: So the regulatory reason you need a human to to
1:12:24
Speaker 1: push a button. Yeah, so so our our our drones
1:12:26
Speaker 1: are fully autonomous. They do all that stuff all on
1:12:28
Speaker 1: their own. The only including coming back to a charging
1:12:32
Speaker 1: doc it can be it's a pad, and we don't
1:12:34
Speaker 1: happen to use the pad because because since we have
1:12:37
Speaker 1: a human there, we might as well to use them
1:12:39
Speaker 1: to change the batter. Um. But but yeah, such a
1:12:41
Speaker 1: thing exists. You can buy charging charging docks or pads
1:12:44
Speaker 1: and things like that. Um, but no the so, so
1:12:47
Speaker 1: what we're talking about is autonomy, the notion of taking
1:12:49
Speaker 1: the human out of the loop. And it's simply a
1:12:51
Speaker 1: regulatory thing. So we work with the FAA to figure
1:12:54
Speaker 1: out what what would it take to allow them, So
1:12:57
Speaker 1: like right now has to be one person, one human,
1:13:00
Speaker 1: one drone. What about one human drones? What about one
1:13:05
Speaker 1: human global fleet of drones monitored remotely. Turns out that
1:13:09
Speaker 1: that actually, you know, you can sit there on the
1:13:11
Speaker 1: ground and you know you're in command, but you're not.
1:13:13
Speaker 1: You're you're not you're checking your email, you're not looking drones.
1:13:17
Speaker 1: The drones got much better perceptual powers than you have.
1:13:20
Speaker 1: You're there, it's over there. It has cameras all over
1:13:23
Speaker 1: the place. That's sensors. It's got you know, radar and
1:13:26
Speaker 1: sonar and light are and all this kind of stuff.
1:13:29
Speaker 1: How about just let the drone, you know, stay, it
1:13:33
Speaker 1: turns away and if it's got an issue, it can
1:13:35
Speaker 1: alert you and tell you to pay attention to make sense.
1:13:38
Speaker 1: But in the meantime, why don't you do what you're
1:13:40
Speaker 1: best at, which is answering whatever it was exactly. So
1:13:43
Speaker 1: that's the process we're going through with the f A
1:13:46
Speaker 1: to figure out what what sort of evidence they need
1:13:48
Speaker 1: to allow that kind of autonomy. And that's my assumption
1:13:51
Speaker 1: is that's not all that far off in the field.
1:13:53
Speaker 1: I mean, I think when you're talking about places like farms,
1:13:56
Speaker 1: which is private land away from people, I think that's
1:13:58
Speaker 1: going to be a lower density againstity. You're talking about
1:14:01
Speaker 1: going beyond visual minus site, which is particular phrase. So
1:14:04
Speaker 1: I think it's gonna be bits where it's accepted first.
1:14:06
Speaker 1: And when getting back to delivery, um, you know the Amazon,
1:14:10
Speaker 1: you know, original video delivering in your suburbs, that's that's
1:14:12
Speaker 1: hard dogs kids, telephone lines, treats. But delivering to a
1:14:17
Speaker 1: rural area that's quite expensive for the postal service to
1:14:20
Speaker 1: get to. That actually makes more sense. Do we have
1:14:22
Speaker 1: the battery life to send something fifty miles out into
1:14:25
Speaker 1: a farming back? It seems fixed wing? An airplane you
1:14:28
Speaker 1: know said about you know, consumer drones or consumer sized
1:14:32
Speaker 1: drones flo across the Atlantic. Oh really, yeah, you know,
1:14:35
Speaker 1: so you doesn't have to elect consumer side like three
1:14:37
Speaker 1: ft across. I get like an airplane that's like a
1:14:40
Speaker 1: three ft four ft wingspans that it doesn't have to
1:14:43
Speaker 1: be a battery, but you can't use a gas power. Um,
1:14:46
Speaker 1: so yeah, it's it's not a problem. So I want
1:14:48
Speaker 1: to talk about one of the Ted talks you did. Well,
1:14:51
Speaker 1: you talk about four key stages of viable technology, right price,
1:15:00
Speaker 1: market share, the displacement of existing technology, and finally becoming ubiquitous.
1:15:08
Speaker 1: Is that four stage process something that's pretty standard, or
1:15:11
Speaker 1: do I have them wrong? Chris Anderson? I get that
1:15:14
Speaker 1: a lot. So is the joke you're making is that
1:15:17
Speaker 1: the curator of of TED is also named Chris Anderson. Here,
1:15:21
Speaker 1: how big of a pain and necka is having someone
1:15:24
Speaker 1: else in tech one plus one equals three. We have
1:15:26
Speaker 1: we have a mutual non destruction pact. Okay, that's promised
1:15:30
Speaker 1: not to ruin the Chris Anderson brand. There you go
1:15:33
Speaker 1: befward each other each other's misdirected emails without you do
1:15:37
Speaker 1: you guys get each other. So let me a quick digression.
1:15:41
Speaker 1: My last name is spelled O L t Z. We
1:15:44
Speaker 1: have cousins who don't have the second T. So I
1:15:47
Speaker 1: have a cousin named Barry Ridholts r I T H
1:15:50
Speaker 1: O l Z. He has a kid, brother, Richard, as
1:15:53
Speaker 1: do I. So there's two Barry and Richie ridholts Is.
1:15:57
Speaker 1: At one point in time, we both had offices in
1:15:59
Speaker 1: three parts and we would get each other's male and
1:16:02
Speaker 1: it was pretty hilarious. Now I'm his nightmare because he
1:16:06
Speaker 1: has to deal with me in the media and he
1:16:09
Speaker 1: he's a lawyer at a mutual fund company. So is
1:16:13
Speaker 1: one of us is a little higher profile than the other,
1:16:16
Speaker 1: so he has the bigger headache. How does this work
1:16:19
Speaker 1: with you and Chris Anderson? Shank and he's a player too,
1:16:23
Speaker 1: let's sell. So so you're both spelled with a C though,
1:16:28
Speaker 1: it's so, do you really get each other's I think
1:16:33
Speaker 1: he's full on British? He lived there for a long time.
1:16:36
Speaker 1: You were born in London. So is this a genuine
1:16:41
Speaker 1: like does genuine confusion happen with this? Um? Yeah, no,
1:16:45
Speaker 1: I mean but in the best sort of way, which
1:16:47
Speaker 1: is like people give it, give us credit for each
1:16:49
Speaker 1: other's work. It's like, you know, Chris, you know you've
1:16:51
Speaker 1: done something. You've written these books Wired three, dr Andy
1:16:55
Speaker 1: run Ted, how do you do it? It's like, well,
1:16:58
Speaker 1: you know, I have a clothe that that's hilarious. So
1:17:02
Speaker 1: the four stages of tech, any viable technology, right price,
1:17:06
Speaker 1: market share, displacing established tech, and then eventually becoming ubiquitous.
1:17:12
Speaker 1: Is that the process that we always see with technology,
1:17:16
Speaker 1: or at least for the foreseeable future. Sure, Barry, I
1:17:20
Speaker 1: have to admit I can't even remember that talk. Really,
1:17:22
Speaker 1: I'm sure you've done it several of them. Yeah, I'm
1:17:24
Speaker 1: sure it was inspired. The only reason that talk is
1:17:27
Speaker 1: on YouTube. Is that my other talks were abject failures
1:17:31
Speaker 1: And it turns out not all talks get Get, Get,
1:17:34
Speaker 1: Get put on the website. Yeah, my other ones were
1:17:37
Speaker 1: tech demos, right and fresh and Burn, Fresh and Burn. Oh,
1:17:40
Speaker 1: that's that's hilarious. We have been speaking with Chris Anderson.
1:17:44
Speaker 1: He is the founder and CEO of three D Robotics,
1:17:47
Speaker 1: as well as the author of the long tail Makers
1:17:51
Speaker 1: and Free. If you enjoy this conversation, be sure and
1:17:55
Speaker 1: check out the podcast Actus Will we keep the tape
1:17:57
Speaker 1: rolling and continue chatting about all in digital technology. We
1:18:02
Speaker 1: love your comments, feedback and suggestions right to us at
1:18:06
Speaker 1: m IB podcast at Bloomberg dot net. Follow me on
1:18:10
Speaker 1: Twitter at Dhults. You can see my daily column at
1:18:12
Speaker 1: Bloomberg View dot com. I'm Barry Hults. You've been listening
1:18:16
Speaker 1: to Masters and Business on Bloomberg Radio. If you're having
1:18:32
Speaker 1: a business dispute, the process can be slow and drawn out,
1:18:35
Speaker 1: especially if you rely on litigation in the courts. You
1:18:38
Speaker 1: can wait for years before your case is resolved, and
1:18:41
Speaker 1: the longer your case proceeds, the more your case can cost.
1:18:45
Speaker 1: Not with the American Arbitration Association arbitration or mediation with
1:18:49
Speaker 1: the American Arbitration Association is faster. In fact, nearly fifty
1:18:54
Speaker 1: of our cases settled prior to hearings. A d r
1:18:57
Speaker 1: dot org resolve faster. Welcome to the podcast, everybody. This
1:19:05
Speaker 1: is really fascinating stuff. I'm having a great time here,
1:19:08
Speaker 1: and thank you for the drone I get to take
1:19:09
Speaker 1: home with Palati drones that were sending U And we
1:19:14
Speaker 1: didn't get to do a demo that we need. If
1:19:17
Speaker 1: I'll be late going into the city. If I don't,
1:19:20
Speaker 1: I don't have time. But if you want to hang around,
1:19:22
Speaker 1: the team will happily give you a demo. I have
1:19:23
Speaker 1: to be somewhere at twelve thirty, but I would love
1:19:26
Speaker 1: to and I we watched them take off and land
1:19:28
Speaker 1: before and it was just the return to home to land.
1:19:33
Speaker 1: It literally lands on the same square inch where it
1:19:36
Speaker 1: took off, right. It's amazing. So so let's get through
1:19:39
Speaker 1: some of these standard questions before you have to head
1:19:42
Speaker 1: into the city. The most interesting thing that people don't
1:19:46
Speaker 1: know about your background. Um failed out of college and
1:19:50
Speaker 1: played in punk rock bands for most of my failed
1:19:53
Speaker 1: Would you go to school? Well, I fail. I ultimately
1:19:57
Speaker 1: went to school to George Washington study that you see Berkeley,
1:20:00
Speaker 1: which is where we are here as well. Um, I
1:20:02
Speaker 1: failed out of school. I won't mention, um. But but
1:20:06
Speaker 1: the cool bit why is that? Why won't you mention it?
1:20:10
Speaker 1: Just because it's fair to the school? Okay it was
1:20:12
Speaker 1: it was on you, it wasn't on the yea. Um.
1:20:16
Speaker 1: But ultimately you got a college degree. Yeah. No, I
1:20:18
Speaker 1: went to I was I was as a playing punk
1:20:20
Speaker 1: rock bands. I was a bicycle messenger by day. And
1:20:23
Speaker 1: at age like twenty seven, Um, you know, finally get
1:20:27
Speaker 1: back to school and get a degree. Um. I was
1:20:30
Speaker 1: such a mess up that I decided to do the
1:20:33
Speaker 1: hardest thing possible just to convince people that I actually
1:20:35
Speaker 1: had a brain. So that's why I did physics. Um.
1:20:38
Speaker 1: But the cool bit is that one of the bands
1:20:40
Speaker 1: I played in was called R E. M. But not that,
1:20:44
Speaker 1: not that, And we had a we had a very
1:20:47
Speaker 1: funny we released our albums on the same week and
1:20:51
Speaker 1: it was this coincidental like, I mean, who knew who
1:20:54
Speaker 1: are em? Well they were like these hicks from the
1:20:56
Speaker 1: Sticks and we were like these the coolest band in Washington. See,
1:21:00
Speaker 1: I know it's a bit of a non secure um.
1:21:03
Speaker 1: And so our manager thought would be funny to have
1:21:04
Speaker 1: a battle of the R E M s where the
1:21:06
Speaker 1: winner got to rename the loser. And did that ever happen?
1:21:09
Speaker 1: It did? Indeed? Oh really? And what and what did
1:21:12
Speaker 1: they rename you? I'm gonna they renamed us a good
1:21:15
Speaker 1: assumption they need renamed us Ego Slavia. That's hilarious. Under
1:21:20
Speaker 1: which name we released our only album, Ego Slavia. Oh
1:21:24
Speaker 1: my god, that's that's hilarious. So let's talk about some
1:21:27
Speaker 1: of your early mentors, one of which I have to
1:21:30
Speaker 1: assume is your grandfather. After the story you subsolutely Fred
1:21:33
Speaker 1: Fred House or Swiss immigrant l A. You know, by
1:21:36
Speaker 1: day working on in the film industry, bring sound to
1:21:39
Speaker 1: you know, bring the talkies in, and by night I'm
1:21:41
Speaker 1: inventing the automatic sprinkler system, which, by the way, is
1:21:44
Speaker 1: exactly what a Swiss engineer in l A would do.
1:21:47
Speaker 1: L A is greening the desert. The Swiss engineer would
1:21:49
Speaker 1: put a clock on a sprinkler. Did he make a
1:21:51
Speaker 1: fortune in this or was it one of those things
1:21:53
Speaker 1: that the patent did? Fortune? Alright, hey, better than no fortune.
1:21:58
Speaker 1: That that's interesting? Who um who? Well? Any other mentors
1:22:01
Speaker 1: affected the way you think about either technology or writing. Um, well,
1:22:07
Speaker 1: you know Whired and it's and its founders had it
1:22:09
Speaker 1: had a huge influence on me. So you know Kevin
1:22:12
Speaker 1: Kelly in particular, Um, you know his book, well, Culturals
1:22:17
Speaker 1: is what he's you know, one of the things he's
1:22:19
Speaker 1: known for, but one of his original books, out of Control.
1:22:22
Speaker 1: So earlier in the conversation, we're talking about emergence and
1:22:24
Speaker 1: the notion of capitalism and democracy and the Internet being
1:22:28
Speaker 1: essentially emergent you know, um phenomena. Um, well, out of
1:22:32
Speaker 1: Control extends that to biological and more net kind of
1:22:35
Speaker 1: natural examples. I mean, the notion of emergent phenomena, the
1:22:39
Speaker 1: notion that there's some general principles physics or chemistry, whatever
1:22:43
Speaker 1: that just set these rules and then everything else all that,
1:22:45
Speaker 1: you know, life and civilization emerges from these principles. That's
1:22:50
Speaker 1: that was one of the most influential ideas of my
1:22:52
Speaker 1: of my formative years. Interesting, let's talk about who else
1:22:58
Speaker 1: influenced your approach to write, because you are a quite
1:23:02
Speaker 1: an accomplished writer, not just three books, you're a very
1:23:06
Speaker 1: influential writer. Who who shaped your approach to that aha
1:23:11
Speaker 1: moment and then turning it into Hey, this is an
1:23:15
Speaker 1: article in a magazine. Oh no, there's more here. Let's
1:23:17
Speaker 1: turn this into a book. So I don't think of mice.
1:23:19
Speaker 1: I mean, thank you for saying that. I m my
1:23:22
Speaker 1: parents were writers, and so I promised to do everything
1:23:25
Speaker 1: but that and I failed once again. We become, we
1:23:29
Speaker 1: become our parents. Is no way to avoid it and
1:23:32
Speaker 1: bite everything. Genetics actually is a thing. Um. So I
1:23:36
Speaker 1: I think of I mean, I I don't. I don't
1:23:40
Speaker 1: think of myself as a writer. I think of myself
1:23:42
Speaker 1: as as a you know, a guy who can sort
1:23:44
Speaker 1: of get capture ideas and get them out there. So
1:23:47
Speaker 1: as an editor, of course, you're not typically not writing.
1:23:49
Speaker 1: You're just packaging ideas. Companies package ideas, open source communities
1:23:53
Speaker 1: package ideas, and writing is one way to do it.
1:23:55
Speaker 1: I think the perhaps the most influential writer for me
1:23:57
Speaker 1: was that Nicholas Niggerponte and his um original book Being
1:24:01
Speaker 1: Digital UM, which very early days, but sweeping notions that
1:24:07
Speaker 1: digital was different, that it almost had kind of fundamental
1:24:10
Speaker 1: physical properties UM. And I think that was probably I mean,
1:24:13
Speaker 1: I haven't read it for years, but I can't I
1:24:15
Speaker 1: can't tell you whether it's well written or not. But
1:24:17
Speaker 1: it's very powerful ideas. So since you brought up books, Uh,
1:24:20
Speaker 1: probably the question we get asked more than any other
1:24:23
Speaker 1: is hey, what are your guest favorite books? So let's
1:24:26
Speaker 1: you mentioned being digital. What other books have you found
1:24:28
Speaker 1: to be important, influential, valuable to you? Fiction, nonfiction, technology,
1:24:35
Speaker 1: non tech, it doesn't matter. Yeah. Um, Well, recently I've
1:24:39
Speaker 1: been reading. UM. I had this rule for like thirty years.
1:24:42
Speaker 1: I would only read nonfiction. UM and the books the
1:24:46
Speaker 1: Keevin Colors of the World. I've recently I've been been
1:24:48
Speaker 1: reading fiction again, but only science fiction on the grounds
1:24:52
Speaker 1: that it's say, you know, I can I can almost
1:24:53
Speaker 1: testify it because there's you know, it's kind of a
1:24:55
Speaker 1: vision of the fay. Here's here's where tech is going.
1:24:58
Speaker 1: I mean the Three Body Problem him series. UM. Uh oh,
1:25:02
Speaker 1: now you're now you're asking um it's Chinese um author
1:25:06
Speaker 1: um and it's uh something Lee. We can look it
1:25:09
Speaker 1: up Body Problems, the Three Body Problems series. UM, it's
1:25:15
Speaker 1: it is the most exciting science fiction. UM. If you
1:25:18
Speaker 1: liked Yeah, So there's the first one, the Three Body Problem.
1:25:21
Speaker 1: The second one was The Dark Forest, and the third
1:25:23
Speaker 1: one his name is Escaping Me. But with those two
1:25:26
Speaker 1: I can yeah, and it's Quinly something. No, it's not Quinly.
1:25:30
Speaker 1: I can't remember the exactly. But what's cool is that
1:25:33
Speaker 1: the guy the author like by day he's a he's
1:25:37
Speaker 1: an engineer in a like power plant in the middle
1:25:40
Speaker 1: of China, and by night he writes the most exciting
1:25:43
Speaker 1: kind of mind expanding um science fiction about you know
1:25:48
Speaker 1: about you know, what would the university like if there were?
1:25:52
Speaker 1: If there were, you know, how how would we encounter life? Um?
1:25:55
Speaker 1: Why haven't we encountered life? Um? How would we communicate? Um? Away?
1:26:00
Speaker 1: It's six in louid C I X I N L
1:26:03
Speaker 1: I U the three body problem, the dark forest, remembrance
1:26:08
Speaker 1: of Earth's past, and Death's end? Are those the three?
1:26:12
Speaker 1: Those are the three? But then on the list that
1:26:14
Speaker 1: sounds fascinating, Yeah, is this firm his paradox is that
1:26:17
Speaker 1: what he's describing or something more more forward than that,
1:26:23
Speaker 1: I it is. It is more so so one notion,
1:26:27
Speaker 1: I mean, the most interesting that I don't want to
1:26:29
Speaker 1: ruin the plot, but the dark forest, the middle one
1:26:32
Speaker 1: sort of explains the notion that if you encounter, if
1:26:35
Speaker 1: you know that there's another species out there, you assume
1:26:37
Speaker 1: that sooner or later they're going to kill you, and
1:26:40
Speaker 1: so it's really important that you that they not know
1:26:43
Speaker 1: you exist. And and he kind of walks to the logic,
1:26:46
Speaker 1: but you know, so we shouldn't be broadcasting television signals
1:26:49
Speaker 1: in space precisely. And so the reason that you know
1:26:52
Speaker 1: the case, there's the reason we haven't encountered other civilizations
1:26:55
Speaker 1: since as they're hiding because they know that it's a
1:26:58
Speaker 1: fascinating that's a fascinating On sept I like that any
1:27:01
Speaker 1: of the books you want to mention, Um, those you know,
1:27:06
Speaker 1: I I got, I mean there's m I hate to
1:27:09
Speaker 1: you know, keep using U Kevin Kelly examples. Um, those
1:27:13
Speaker 1: are the ones I'm reading right now. Um uh there's
1:27:18
Speaker 1: a new book. Well anyway that those are the ones
1:27:21
Speaker 1: I'm gonna I'm not a a highlight for now, okay. Um.
1:27:24
Speaker 1: We talked about changes in the technology industry. We talked
1:27:27
Speaker 1: about shifts and uh, let me briefly ask you about
1:27:31
Speaker 1: the digital shift in journalism and the problem that genuine
1:27:36
Speaker 1: media outlets are having competing with free and digital. How
1:27:40
Speaker 1: big of a problem is that for the idea of
1:27:43
Speaker 1: a free press in America when that business model is
1:27:46
Speaker 1: under attack from everywhere. So I'm always baffled by that,
1:27:51
Speaker 1: that question. I get it all the time. Um, there
1:27:53
Speaker 1: is no shortage of media. You know, it's the golden
1:27:56
Speaker 1: age of media. Now we call that media Facebook, or
1:27:59
Speaker 1: we call it you know, you know, the web, but
1:28:01
Speaker 1: we're called social media. But there's you know, um, you know,
1:28:04
Speaker 1: we now have access to global media. Um. You know,
1:28:07
Speaker 1: I get the ft every day there you go, and
1:28:09
Speaker 1: India digitally as as well. So it's very hard to
1:28:13
Speaker 1: believe there's any kind of suppression of of of of media. Um.
1:28:18
Speaker 1: For economic reasons. I mean, you know, basically, the cost
1:28:21
Speaker 1: of distributing, creating, distributing content is very low. Um. So
1:28:25
Speaker 1: when people talk about the free press, it's a very archaic,
1:28:28
Speaker 1: almost American notion of the fourth of state. I mean,
1:28:31
Speaker 1: no other country has this sort of maybe some other countries,
1:28:34
Speaker 1: but in general, this this notion that you know that
1:28:37
Speaker 1: you have these kind of you know, natural monopolies, big
1:28:40
Speaker 1: city newspapers who are necessary to counterbalance political forces. Very weird,
1:28:46
Speaker 1: very American, very twentieth century. Doesn't seem relevant today. Tell
1:28:52
Speaker 1: us about a time you failed and what you learned
1:28:54
Speaker 1: from the experience. Where where do I start? Um? Uh
1:28:59
Speaker 1: So you know, in our in our progression UM three
1:29:02
Speaker 1: dr from the technology to the consumer electronics to the
1:29:06
Speaker 1: tool using using drones as sensors. UM. Because of regulation,
1:29:11
Speaker 1: that regulation only allowed recreational use. So the only way
1:29:14
Speaker 1: you know, we couldn't do commercial use until last September
1:29:18
Speaker 1: of last year. And so in between, the only way
1:29:20
Speaker 1: you could really get drones out there was on the
1:29:22
Speaker 1: shelves of Walmart and UM. And so we raised a
1:29:25
Speaker 1: lot of money and we spun up you know, outsourced
1:29:28
Speaker 1: manufacturing and consumer electronics and you know, perhaps the most
1:29:31
Speaker 1: complex consumer electronics device you know ever at that time.
1:29:36
Speaker 1: And we decided to you know, to do the consumer products,
1:29:43
Speaker 1: you know, the thing right with distribution and marketing and
1:29:47
Speaker 1: distributing retail shelves and all that. UM. And we designed
1:29:51
Speaker 1: a good product and we um, you know, did everything right,
1:29:55
Speaker 1: UM and UM that's when the prices fell by by
1:29:58
Speaker 1: by sevent months and and we ended up we ended
1:30:03
Speaker 1: up with negative margins. Uh. And you know your units
1:30:09
Speaker 1: called dollars to build, yeah, exactly. We were so when
1:30:12
Speaker 1: we saw when we started, the going price for an
1:30:15
Speaker 1: advanced drone was about fiftie hundred even more. And so
1:30:18
Speaker 1: you know, our bill of materials was about half that,
1:30:20
Speaker 1: which is appropriate. UM. By the time a couple of
1:30:23
Speaker 1: months after we after we launched, the going price was
1:30:26
Speaker 1: below bill materials and and as of like about a
1:30:29
Speaker 1: year ago, was down to about three D. So well,
1:30:32
Speaker 1: these were not like not like bad technology, not toys.
1:30:35
Speaker 1: These are serious, serious things. So so what did you
1:30:38
Speaker 1: learn from that? What was the takeaway? I learned that.
1:30:41
Speaker 1: I mean my instinct right now is that that essentially
1:30:44
Speaker 1: was the universe telling me what should have been obvious,
1:30:47
Speaker 1: which is that Silicon Valley should focus on software. Um.
1:30:52
Speaker 1: China is extraordinarily good at hardware. The notion of advanced
1:30:55
Speaker 1: Silicon Valley cloud software running on Chinese hardware, which by
1:30:58
Speaker 1: the way, is your phone actually, UM, is the way
1:31:02
Speaker 1: we should go. And it's kind of like, don't fight it.
1:31:04
Speaker 1: It's you know, rather than build your own hardware, go
1:31:07
Speaker 1: find some brilliant company in China that's making the hardware
1:31:09
Speaker 1: and partner lets them have all the costs and produce
1:31:12
Speaker 1: it at half. And every time I talked to you know,
1:31:15
Speaker 1: a new company and Silicon valid it's doing hardware, they're like, yeah,
1:31:18
Speaker 1: we know that the hardware is commoditized, and we know
1:31:20
Speaker 1: the chance. But we think we have five or seven years.
1:31:21
Speaker 1: And it's like, yeah, I said that too, you got
1:31:23
Speaker 1: six months, you got six months. Um, what do you
1:31:26
Speaker 1: do to keep either mentally you're physically fit, and what
1:31:29
Speaker 1: do you do to relax outside of the office? Um?
1:31:33
Speaker 1: So physically fit, UM, I just play tennis. Um, but
1:31:36
Speaker 1: I have some of my dear friends and mentors or
1:31:39
Speaker 1: my tennis partners, and so tennis is not about the tennis.
1:31:42
Speaker 1: So not spending time with you know, with with with
1:31:44
Speaker 1: with with your friends, you wouldn't otherwise schedule. Um. Intellectually
1:31:47
Speaker 1: I have I still have tons of tons of hobbies.
1:31:50
Speaker 1: And ten years ago we did d I Y drones.
1:31:51
Speaker 1: Now we're doing d I Y robot cars and applying
1:31:54
Speaker 1: the same sort of grassroots bob you know, you know,
1:31:56
Speaker 1: sort of like what what what if you made an
1:31:58
Speaker 1: autonomous car for a hundred ours now wouldn't carry a
1:32:00
Speaker 1: person in the same way of drone doesn't carry a person,
1:32:03
Speaker 1: But it's the same. It's light, our computer vision, neural networks,
1:32:07
Speaker 1: you know, Google clouds. This is now down to the
1:32:10
Speaker 1: d I Y level, the various At one point in time,
1:32:13
Speaker 1: this was a um was it a dark book? Dar
1:32:18
Speaker 1: you know, the Darker Competition, the Grand Challenge, etcetera. So
1:32:20
Speaker 1: this weekend, for example, we're gonna be doing um, robot
1:32:23
Speaker 1: to robot, wheel to wheel Thomas car racing in a
1:32:27
Speaker 1: in a huge warehouse like semi abandoned warehouse in in Oakland, California.
1:32:31
Speaker 1: And then we're gonna do robot versus human um. And
1:32:34
Speaker 1: this is not These are not toys. I mean they
1:32:36
Speaker 1: look like toys because they're like in a one tense scale,
1:32:38
Speaker 1: But the exact same technology, isn't it Tesla or And
1:32:41
Speaker 1: they could scale right up if they scale right up,
1:32:43
Speaker 1: it's basically using the same Google Neural network stuff. But
1:32:47
Speaker 1: the cost of the hardware itself is about a hundred
1:32:49
Speaker 1: dollars undred fifty dollars. And um, we made it so
1:32:54
Speaker 1: it's fun. We made it so that students could do it,
1:32:58
Speaker 1: and um, you know it's dangerous for the cars, but
1:33:01
Speaker 1: not for humans. These are they're truly autonomous. You basically
1:33:05
Speaker 1: three to one go and this one, this one just
1:33:07
Speaker 1: outside this room, we're gonna have to take a look
1:33:09
Speaker 1: at that. Now I have to ask my final two questions. First,
1:33:13
Speaker 1: what sort of advice would you give to a millennial
1:33:16
Speaker 1: or someone just starting their career in either technology or journalism.
1:33:21
Speaker 1: So you know, I have kids who are who are
1:33:23
Speaker 1: just going to college or or soon will local or
1:33:27
Speaker 1: or elsewhere. No, they refused to go locally in the
1:33:29
Speaker 1: same way. Why did I Why did I knew that? No,
1:33:32
Speaker 1: that was the answer. I mean, we live in Berkeley,
1:33:34
Speaker 1: you know, you see, you see, Berkeley is like one
1:33:35
Speaker 1: of the best schoals in the world. But they just
1:33:36
Speaker 1: won't go to it. Um. I didn't get in either,
1:33:39
Speaker 1: but they didn't. They didn't apply. I didn't in fairness,
1:33:41
Speaker 1: they didn't apply. Um uh so um. You know, if
1:33:45
Speaker 1: you ask me what I was to study today, I'm
1:33:48
Speaker 1: gonna give you an answer which sounds boring, and then
1:33:50
Speaker 1: you have to find a sexier way to sell The
1:33:52
Speaker 1: answer is statistics. Probability and statistics are not boring at all,
1:33:56
Speaker 1: but it doesn't sound super compelling. So let's call it.
1:33:59
Speaker 1: Let's call it something a sex here like it's called
1:34:00
Speaker 1: data science. I'm gonna take it a step further. Probability
1:34:04
Speaker 1: and statistics is how you discern reality from falsity, truth
1:34:09
Speaker 1: from nonsense, and so sell it to my seventeen year
1:34:12
Speaker 1: old I can't tell you how often something comes along
1:34:16
Speaker 1: and you say, no, that's you're giving me a sample
1:34:20
Speaker 1: set of two Who cares it's it's not if you
1:34:23
Speaker 1: don't know that, you cannot identify reality. So my seventeen
1:34:26
Speaker 1: year old is like, he's trying to choose a major,
1:34:30
Speaker 1: and you, Barry uncle Barry as we'll call you, for
1:34:33
Speaker 1: the purpose of this argument, are going to convince my
1:34:35
Speaker 1: seventeen year old to major in what you just said,
1:34:40
Speaker 1: sell it in a way that doesn't sound like spinach. Well,
1:34:44
Speaker 1: what do you want to do with your life? What
1:34:46
Speaker 1: do you what are you interested in? How would you
1:34:48
Speaker 1: like to have a way to identify what's real and
1:34:51
Speaker 1: what's false in that? How would you like to be
1:34:53
Speaker 1: able to inject the truth serum into anything that takes
1:34:58
Speaker 1: place in meat space and some stuff that takes place
1:35:01
Speaker 1: in the virtual world and figure out if it's real
1:35:04
Speaker 1: or it's false. And what if they say it sounds
1:35:07
Speaker 1: hard and is it even a job? Anything that's worth
1:35:10
Speaker 1: doing is hard number one, And it's a job, but
1:35:13
Speaker 1: it's only a fabulous, paying, fascinating job. So if that's
1:35:17
Speaker 1: of interest, you know the ability to And by the way,
1:35:22
Speaker 1: this is a well established science. Many people have problems
1:35:26
Speaker 1: with it. But the ability to walk in and look
1:35:29
Speaker 1: at something and say, here's how we know their story
1:35:32
Speaker 1: is false based on this is an amazing, amazing thing.
1:35:37
Speaker 1: And I'm I'm astonished more people who don't recognize it
1:35:42
Speaker 1: for what it is. So so the I agree with
1:35:44
Speaker 1: everything you just said. Um, the way I ended up
1:35:46
Speaker 1: selling it was I said, well, okay, um, let's call it.
1:35:50
Speaker 1: Let's call its computer science, and it's called data science.
1:35:52
Speaker 1: The data science is basically computer science plus statistics of
1:35:55
Speaker 1: various sorts. Um. One of my one of my sons
1:35:58
Speaker 1: is at North Northwestern and and he did economics, econometrics,
1:36:03
Speaker 1: and computer science, which is another way. So and so
1:36:08
Speaker 1: when you put econometrics and computer science together, if if,
1:36:11
Speaker 1: if the employers want to see that as data science,
1:36:14
Speaker 1: data science, it is, and that's a very hot profession
1:36:16
Speaker 1: and get paid for that. Sure to say the least
1:36:18
Speaker 1: our final question before I make you late for your
1:36:21
Speaker 1: next appointment, what is it that you know about technology
1:36:25
Speaker 1: writing journalism today you wish you knew twenty five years ago.
1:36:30
Speaker 1: I mean, I've been pretty lucky in being in the
1:36:32
Speaker 1: right place at the right time throughout im I've sometimes
1:36:38
Speaker 1: been too early. Is as bad as being wrong, and
1:36:41
Speaker 1: I've certainly been too early on on some things. UM yeah,
1:36:47
Speaker 1: I uh, I think I might have. UM, so I
1:36:51
Speaker 1: could have moved to Silicon Valley sooner. Um, but in
1:36:55
Speaker 1: that if I'd done so, I would have missed China.
1:36:58
Speaker 1: I would have missed being in China. That's a cool
1:37:00
Speaker 1: into it and that was that was cooler. I guess
1:37:03
Speaker 1: I would have. UM. The only time I regret at
1:37:05
Speaker 1: the time I spent in Washington, d C, I was
1:37:07
Speaker 1: I was too long in Washington. I saw the world
1:37:09
Speaker 1: through kind of a political lens, and I wish I'd
1:37:12
Speaker 1: gotten out of there sooner. The you know, here's the
1:37:15
Speaker 1: Looking Valley, d C fields a long way away. Governments
1:37:19
Speaker 1: seem not terribly not as important, markets and even countries
1:37:24
Speaker 1: don't seem as important as as as as trade relationships.
1:37:28
Speaker 1: So I wish i'd traveled center. We have been speaking
1:37:31
Speaker 1: with Chris Anderson, CEO of three D Robotics, author of
1:37:36
Speaker 1: The Long Tail and Makers and Free. If you enjoy
1:37:40
Speaker 1: this conversation, be showing look up an inch or down
1:37:43
Speaker 1: an inch on either Apple, iTunes, SoundCloud, Bloomberg dot com,
1:37:47
Speaker 1: and you could see our other hundred and fifty or
1:37:49
Speaker 1: so such uh recordings. I would be remiss if I
1:37:53
Speaker 1: did not think Michael Battnick, who helped prepare these questions,
1:37:57
Speaker 1: Chris ven who has been my boyfriend today on this trip.
1:38:01
Speaker 1: And Chris, thank you so much for being so generous
1:38:03
Speaker 1: with your time. I know you have other things and
1:38:05
Speaker 1: better places to do and be. I'm Barry Retults. You're
1:38:09
Speaker 1: listening to Masters in Business on Bloomberg Radio. Masters in
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