WEBVTT 00:00:03.000 --> 00:00:06.330 Matt Abrahams: The best communication is architected for understanding. 00:00:06.510 --> 00:00:09.780 My name is Matt Abrahams, and I teach strategic communication at 00:00:09.780 --> 00:00:11.580 Stanford Graduate School of Business. 00:00:11.880 --> 00:00:15.000 Welcome to Think Fast Talk Smart, the podcast. 00:00:15.600 --> 00:00:18.480 Today I am really excited to speak with Astro Teller. 00:00:18.900 --> 00:00:22.350 Astro is a computer scientist, entrepreneur, and inventor. 00:00:22.680 --> 00:00:27.180 He serves as Captain of Moonshots at X, Alphabet's Moonshot Factory, 00:00:27.450 --> 00:00:31.050 where he oversees audacious, high impact technology projects. 00:00:31.380 --> 00:00:35.070 He has written two novels, and the nonfiction book, Sacred Cows: The 00:00:35.070 --> 00:00:38.310 Truth About Divorce and Marriage that he co-wrote with his wife. 00:00:38.820 --> 00:00:42.269 He's also a new podcaster, hosting the really fun and 00:00:42.269 --> 00:00:44.880 insightful The Moonshot Podcast. 00:00:44.880 --> 00:00:45.210 Welcome Astro. 00:00:46.545 --> 00:00:48.644 I am super excited to be chatting with you. 00:00:48.644 --> 00:00:50.595 I've been excited ever since we arranged this. 00:00:50.595 --> 00:00:51.464 Thank you for being here. 00:00:51.525 --> 00:00:52.335 Astro Teller: Thanks for having me. 00:00:52.364 --> 00:00:52.845 Matt Abrahams: Excellent. 00:00:52.875 --> 00:00:53.595 Shall we get started? 00:00:53.595 --> 00:00:54.254 Astro Teller: Yeah, let's do it. 00:00:54.525 --> 00:00:57.045 Matt Abrahams: To begin, I'd love for you to define for our audience 00:00:57.045 --> 00:00:58.995 what you mean by a moonshot. 00:00:59.265 --> 00:00:59.745 Astro Teller: Sure. 00:00:59.835 --> 00:01:04.815 So we think of this as the blueprint for moonshots, and in order for us to have 00:01:04.815 --> 00:01:08.384 something that counts as a moonshot, it has to have three components. 00:01:08.715 --> 00:01:11.865 One, there has to be a huge problem with the world that you 00:01:11.865 --> 00:01:12.900 can name and you wanna solve. 00:01:13.619 --> 00:01:18.720 Number two, there has to be some kind of radical proposed solution that, however 00:01:18.720 --> 00:01:20.970 unlikely it is, you could make that thing. 00:01:21.119 --> 00:01:24.059 This is like a science fiction sounding product or service. 00:01:24.330 --> 00:01:27.630 We could agree ahead of time if you could make it, it would resolve 00:01:27.630 --> 00:01:28.979 that huge problem with the world. 00:01:29.490 --> 00:01:33.149 And then three, there has to be some kind of breakthrough technology that 00:01:33.149 --> 00:01:37.899 gives us at least a glimmer of a hope that we could make that science fiction 00:01:37.899 --> 00:01:40.960 sounding product or service that would solve that huge problem with the world. 00:01:41.470 --> 00:01:44.470 Once you have those three things, we're not done. 00:01:44.649 --> 00:01:49.899 That means you have a moonshot story hypothesis, you have a testable 00:01:49.899 --> 00:01:55.935 hypothesis, and from there the question is how quickly can we verify that you're 00:01:55.935 --> 00:01:59.085 wrong so we can move on to the next idea? 00:01:59.415 --> 00:02:05.325 Because anything that fits those three criteria that I just named, exciting 00:02:05.325 --> 00:02:11.655 as they are, it is exactly because it is so unlikely to work that we have to 00:02:11.655 --> 00:02:17.685 be constantly pursuing the reality that each one of them is likely to be wrong. 00:02:18.225 --> 00:02:21.405 Matt Abrahams: So the goal is actually to come up with these audacious 00:02:21.674 --> 00:02:26.144 ideas and strivings and then to as quickly as possible negate them. 00:02:26.655 --> 00:02:30.435 Astro Teller: Yeah, of course, we want any particular moonshot we come up with 00:02:30.555 --> 00:02:35.625 to turn out to be a once in a generation opportunity for the world, but since most 00:02:35.625 --> 00:02:42.175 of them aren't, wanting to win, wanting to get it to be right, each time leads to 00:02:42.175 --> 00:02:49.195 sadness after sadness, and denial kicks in that slows up the efficiency of being the 00:02:49.195 --> 00:02:54.055 learning machine that we would aspire to be, verifying which of the many that we've 00:02:54.055 --> 00:02:56.725 started is in fact worth doubling down on. 00:02:57.220 --> 00:02:59.679 Matt Abrahams: You said several things there I wanted to dive deeper into. 00:02:59.679 --> 00:03:04.269 So you see this as learning, and it's a learning machine, as you 00:03:04.269 --> 00:03:08.350 said, which leads me to wonder, is there a particular type of mindset 00:03:08.350 --> 00:03:12.130 that you try to bring about in your organization that looks at it this way? 00:03:12.130 --> 00:03:14.109 Because many people don't think of projects this way. 00:03:14.109 --> 00:03:16.510 They start a project, they want it to be successful, not let's start 00:03:16.510 --> 00:03:19.149 a project and figure out all the reasons why it won't be successful. 00:03:19.239 --> 00:03:20.524 Can you talk a little bit about that mindset? 00:03:21.180 --> 00:03:21.480 Astro Teller: Sure. 00:03:21.480 --> 00:03:22.980 Lemme give you one or two examples. 00:03:23.250 --> 00:03:27.180 I mean, the first is, if you were working at X, I would say, can we 00:03:27.180 --> 00:03:30.210 pre agree, before you've come up with something and then fallen in love with 00:03:30.210 --> 00:03:34.320 it, that if it's a one in a hundred chance of working, it has a ninety-nine 00:03:34.320 --> 00:03:35.790 percent chance of not working. 00:03:36.000 --> 00:03:41.130 Which means that if you tie your sense of self-worth to getting a 00:03:41.130 --> 00:03:43.380 yes, you're just lying to yourself. 00:03:43.800 --> 00:03:46.740 You think that you are the one percent and you're always gonna win. 00:03:46.740 --> 00:03:50.040 But this can't be Lake Wobegon, where we're all above average. 00:03:50.130 --> 00:03:54.185 So that's one way to help put some intellectual guardrails 00:03:54.185 --> 00:03:55.625 around what we're about to go do. 00:03:55.955 --> 00:03:57.275 Here's another way of doing it. 00:03:57.815 --> 00:04:01.145 Think of the last really hard thing that you and a team did. 00:04:01.295 --> 00:04:03.335 I'd ask each of your listeners to think about that. 00:04:03.875 --> 00:04:09.185 Now, imagine you lose all of the hardware, all of the software, anything except 00:04:09.185 --> 00:04:11.165 what's in your and your team's heads. 00:04:11.435 --> 00:04:14.735 How long, once you've succeeded, would it take for you to go 00:04:14.735 --> 00:04:16.565 back and rebuild the solution? 00:04:16.885 --> 00:04:18.745 Having already verified what it is. 00:04:19.075 --> 00:04:23.155 Most people say somewhere between five and twenty percent of the time that it took. 00:04:23.365 --> 00:04:27.165 And for moonshots, it's much closer to five percent than twenty percent. 00:04:27.354 --> 00:04:29.094 Let's call it ten percent on average. 00:04:29.484 --> 00:04:32.005 What are we gonna call that other ninety percent of the work? 00:04:32.245 --> 00:04:33.025 It's learning. 00:04:33.385 --> 00:04:38.245 Most of the work isn't the making of stuff, it's the learning what to make. 00:04:38.784 --> 00:04:42.565 And the more you are shooting over the horizon, which is what a moonshot is, 00:04:42.865 --> 00:04:49.275 the more of the journey is exploration, not the settling that happens afterwards. 00:04:49.664 --> 00:04:54.344 So if you agree conceptually, intellectually that we're on a 00:04:54.344 --> 00:05:00.555 learning journey, then scary as it is to be wrong, we need to focus on 00:05:00.555 --> 00:05:01.965 the moments where we learn something. 00:05:02.205 --> 00:05:03.555 And when do you learn something? 00:05:03.825 --> 00:05:06.914 You learn something when you have a model about the world, and then 00:05:06.914 --> 00:05:09.615 in some way you get some data that tells you you are wrong. 00:05:09.974 --> 00:05:11.414 You learn nothing when you're right. 00:05:11.474 --> 00:05:13.544 At best, you deepen grooves in your brain. 00:05:13.875 --> 00:05:17.295 If you are wrong, whatever else we wanna call it, that feels bad. 00:05:17.295 --> 00:05:18.615 That's a failure of a kind. 00:05:18.885 --> 00:05:23.895 If you hate failure, you will emotionally avoid that moment, which means 00:05:23.895 --> 00:05:25.585 you're emotionally avoiding learning. 00:05:25.855 --> 00:05:28.965 If we just agreed we're gonna spend ninety plus percent of our time 00:05:29.145 --> 00:05:34.920 learning, then we need to destigmatize failure so we can have our learning 00:05:34.920 --> 00:05:36.630 loops be as tight as possible. 00:05:36.780 --> 00:05:40.320 Matt Abrahams: So a moonshot mindset is really about seeing learning as the goal. 00:05:40.409 --> 00:05:44.880 How do you inculcate and support that, and how do you produce 00:05:44.940 --> 00:05:48.690 anything if, for many companies, productivity is what's the goal? 00:05:48.690 --> 00:05:53.760 So how do you produce the amazing things that you've done and help people see 00:05:53.760 --> 00:05:55.650 learning as the goal, not productivity. 00:05:56.055 --> 00:05:59.325 Astro Teller: It's very hard to prevent people from chasing progress. 00:05:59.805 --> 00:06:03.224 Even at X, there's a decent amount of it, even though I'm constantly 00:06:03.224 --> 00:06:06.585 going around trying to stamp it out and redirect people towards learning. 00:06:06.795 --> 00:06:13.215 So it's not hard for the end result of a lot of learning to turn into 00:06:13.215 --> 00:06:16.305 something very valuable that looks ultimately like great progress. 00:06:17.070 --> 00:06:22.380 During the journey, the thing that is hardest to fight is you feel, 00:06:22.440 --> 00:06:25.470 especially, once you've done some learning and you've found something 00:06:25.470 --> 00:06:30.600 that works, it's so hard for you as an X'er not to feel like I found it. 00:06:30.750 --> 00:06:31.470 I'm right. 00:06:31.590 --> 00:06:33.990 Now, just let me build it and then I'll give it to the world 00:06:33.990 --> 00:06:34.345 and we're gonna be great. 00:06:35.130 --> 00:06:38.760 And I just have to say, we, the leadership at X, have to say over and over again, 00:06:39.300 --> 00:06:43.230 I know it feels like you found it and you know more about the teleporter, if 00:06:43.230 --> 00:06:44.880 that's what you're working on, than I do. 00:06:45.000 --> 00:06:48.720 But I'm telling you from induction, having watched this hundreds of 00:06:48.720 --> 00:06:51.210 times, now you are not correct yet. 00:06:51.420 --> 00:06:52.770 You have a lot to learn. 00:06:52.770 --> 00:06:55.260 And what you think is the answer isn't the answer. 00:06:55.465 --> 00:06:58.945 It's not that I don't want you to be right, it's just my experience tells 00:06:58.945 --> 00:07:02.455 me you have a lot more to learn, so I need you to stay in learning mode. 00:07:02.665 --> 00:07:06.025 Keep your humility and your curiosity really high for 00:07:06.025 --> 00:07:07.765 another two or three years. 00:07:08.155 --> 00:07:10.915 It's helping people to do that that's really hard. 00:07:11.575 --> 00:07:13.284 Matt Abrahams: I find it really interesting that humility and 00:07:13.284 --> 00:07:17.185 curiosity are what keep the flames going for learning. 00:07:17.700 --> 00:07:20.849 How do you capture the learning across the different teams? 00:07:21.179 --> 00:07:24.929 We had Amy Edmondson on, and she talks a lot about the right kind of failure, 00:07:25.020 --> 00:07:28.260 and learning from the failure, and the processes you can put in place. 00:07:28.500 --> 00:07:30.780 What are some of the best practices you've implemented? 00:07:30.780 --> 00:07:34.229 So if somebody learns something, that learning is cascaded so others 00:07:34.229 --> 00:07:35.520 can benefit from that learning. 00:07:35.914 --> 00:07:37.234 Astro Teller: There's a bunch of different ways. 00:07:37.354 --> 00:07:40.864 The truth is, some of it is just institutional knowledge, and that's 00:07:40.864 --> 00:07:45.364 sort of a background radiation that's very real at X. There are lots of things 00:07:45.364 --> 00:07:49.864 that we capture, we actually have a document called headwinds and tailwinds 00:07:50.164 --> 00:07:52.715 to remind us of some of these learnings. 00:07:53.104 --> 00:07:56.255 These kinds of things tend to be tailwinds in our experience. 00:07:56.255 --> 00:07:58.534 These kinds of things tend to be headwinds. 00:07:58.685 --> 00:08:02.405 That doesn't mean you can't ignore one of them if you want 00:08:02.405 --> 00:08:03.905 to or if you think it's worth it. 00:08:04.115 --> 00:08:06.935 But these are good reminders from the past that we've learned. 00:08:07.085 --> 00:08:11.159 We have maybe twenty percent of the people who work at X 00:08:11.219 --> 00:08:13.050 aren't on one of the projects. 00:08:13.200 --> 00:08:14.789 They're in these central teams. 00:08:14.969 --> 00:08:19.830 So this is like finance, legal, public policy, some business development, a 00:08:19.830 --> 00:08:21.900 lot of sort of hardware prototyping. 00:08:22.229 --> 00:08:25.380 And what happens is they go over here and they help the teleporter 00:08:25.650 --> 00:08:29.370 team, and then they go over here and they help the time machine team. 00:08:29.755 --> 00:08:35.635 And so they act as a kind of vector transplanting interesting ideas and 00:08:35.635 --> 00:08:37.645 learnings from one team to another. 00:08:37.765 --> 00:08:42.085 So even if those teams don't talk to each other very much, because they share 00:08:42.085 --> 00:08:46.575 these central teams, the central teams can move good ideas back and forth. 00:08:46.905 --> 00:08:49.065 Matt Abrahams: So you actually have a structural element where there are people 00:08:49.065 --> 00:08:52.935 spoke and hub and the those folks in the hub bring those learnings across. 00:08:52.935 --> 00:08:55.995 I find that really helpful for other people to think about in their 00:08:55.995 --> 00:08:57.735 organizations, how they might do that. 00:08:57.945 --> 00:09:01.785 Astro Teller: Yeah, it is hub and spoke from a help perspective, but 00:09:01.785 --> 00:09:06.025 it is not, as the concept of the visualization of hub and spoke might 00:09:06.025 --> 00:09:09.325 imply, a highly top down process. 00:09:09.595 --> 00:09:12.775 Discovery is mostly a bottoms up process. 00:09:12.775 --> 00:09:17.365 It's very hard to dictate, so you have to create some structure and 00:09:17.365 --> 00:09:21.655 guardrails, but then let people be pretty free range within those 00:09:21.715 --> 00:09:25.255 guardrails, or they won't ultimately find things that are unexpected. 00:09:25.845 --> 00:09:29.505 Matt Abrahams: So you have to have just enough boundary setting to keep 00:09:29.505 --> 00:09:32.715 things moving forward, but not so much that people can't be creative. 00:09:32.745 --> 00:09:33.855 And we've seen that a lot. 00:09:33.855 --> 00:09:36.765 We've talked a lot about improvisation and how that mindset helps. 00:09:36.765 --> 00:09:40.635 And in improv, they have some rules and that's what allows for that creativity. 00:09:40.845 --> 00:09:41.055 Astro Teller: Right. 00:09:41.055 --> 00:09:42.194 Let me give you an example. 00:09:42.555 --> 00:09:45.375 Obviously we have to have a performance management system. 00:09:45.375 --> 00:09:46.455 It'd be weird if we didn't. 00:09:46.635 --> 00:09:51.255 The temptation across the whole world, so including at the Moonshot Factory, is 00:09:51.255 --> 00:09:56.295 to have our performance management system be one that rewards people for outcomes. 00:09:56.835 --> 00:09:57.915 You rang the bell. 00:09:58.005 --> 00:10:01.395 You got the million dollars or the big deal you signed. 00:10:01.575 --> 00:10:02.235 Good for you. 00:10:02.235 --> 00:10:04.055 Bonus promotion, whatever that is. 00:10:04.425 --> 00:10:06.959 That is the death of radical innovation. 00:10:07.140 --> 00:10:11.219 Because if I'm asking you to do things that have a one in a hundred chance of 00:10:11.219 --> 00:10:17.130 success, and then you get rewarded on the basis of a yes of a success, you'll very 00:10:17.130 --> 00:10:22.469 quickly learn to pretend you're doing radical innovation, but find ways to get 00:10:22.469 --> 00:10:26.939 the safety of like, okay, maybe it's not as radical, maybe it's not as innovative, 00:10:27.240 --> 00:10:30.360 but I'll dress it up so it looks like that, and I'm pretty sure I can make 00:10:30.360 --> 00:10:32.400 this work even if it's not that exciting. 00:10:32.790 --> 00:10:36.660 And so I'm gonna focus on this thing because I know I'm only gonna 00:10:36.660 --> 00:10:38.310 get rewarded when I get a yes. 00:10:38.580 --> 00:10:40.050 All humans will do that. 00:10:40.260 --> 00:10:45.690 And so the performance management system we have directs people back towards 00:10:45.690 --> 00:10:48.570 the habits, not towards the outcomes. 00:10:48.690 --> 00:10:55.860 What are the kinds of things like humility and curiosity that tend to have wild 00:10:55.860 --> 00:10:58.950 success as a long-term side effect? 00:10:59.520 --> 00:11:03.990 And then you have to trust, and this is a big scary trust fall, that those outcomes 00:11:03.990 --> 00:11:06.330 will happen when you focus on the habits. 00:11:06.660 --> 00:11:08.490 Matt Abrahams: And you have good evidence that will happen. 00:11:08.640 --> 00:11:12.210 It's harder from a management point of view to measure those kind of things 00:11:12.210 --> 00:11:14.010 versus did you ring the bell or not? 00:11:14.010 --> 00:11:18.425 That's a very binary, easy thing to do, so you have to have more flexibility and 00:11:18.425 --> 00:11:20.675 openness as managers, I guess as well. 00:11:20.765 --> 00:11:25.355 Astro Teller: Yeah, and this is a struggle to this day at X. It is so much harder to 00:11:25.355 --> 00:11:31.055 train managers to hold people accountable to habits rather than to outcomes that 00:11:31.055 --> 00:11:35.555 they routinely will try to find ways to hack the systems so that they can reward 00:11:35.555 --> 00:11:39.099 people for outcomes, or they'll gripe about their performance management system. 00:11:39.735 --> 00:11:44.475 I get it, and that's an example where we're trying to create some guardrails. 00:11:44.745 --> 00:11:49.005 Let them use some creativity within those guardrails, but also make sure 00:11:49.245 --> 00:11:52.965 that they're pointed in this case towards the habits rather than the outcomes. 00:11:53.325 --> 00:11:55.815 Matt Abrahams: I really like this idea of rewarding people 00:11:55.815 --> 00:11:57.345 for habits, not for outcomes. 00:11:57.645 --> 00:11:58.755 I want to take a step back. 00:11:58.755 --> 00:12:01.605 We haven't actually heard from you an example or two of 00:12:01.605 --> 00:12:02.835 what you guys have created. 00:12:02.835 --> 00:12:05.805 Can you share one moonshot that was successful so we can have 00:12:05.805 --> 00:12:07.855 an appreciation of the different types of things you work on? 00:12:08.400 --> 00:12:10.410 Astro Teller: Let me give a few examples. 00:12:10.710 --> 00:12:16.064 Google Brain, which is one of the places that caused the explosion of 00:12:16.064 --> 00:12:20.204 industrialized machine learning that is now the sort of hot topic in the world, 00:12:20.535 --> 00:12:22.425 that came from X. That's an example. 00:12:22.785 --> 00:12:24.944 Uh, the self-driving cars now called Waymo. 00:12:24.944 --> 00:12:30.405 Those came from X. Uh, Wing, the drones for package delivery, which are actually 00:12:30.584 --> 00:12:36.224 doing almost as well as Waymo and people haven't caught on that it's going to 00:12:36.224 --> 00:12:40.635 be as big a deal, that came from X. And I will give some more examples, 00:12:40.635 --> 00:12:42.255 but let me use Waymo as an example. 00:12:42.555 --> 00:12:44.840 So this is now fifteen years ago. 00:12:45.260 --> 00:12:46.490 Huge problem with the world. 00:12:47.030 --> 00:12:50.900 More than a million people a year die in car accidents in the 00:12:50.900 --> 00:12:52.700 world because of human error. 00:12:52.790 --> 00:12:57.200 More than a trillion dollars is wasted between sitting in traffic 00:12:57.350 --> 00:13:00.710 and all of the costs of the accidents, even leaving death aside. 00:13:01.040 --> 00:13:05.540 Between a million lives and a trillion dollars, that's a problem worth fixing. 00:13:05.810 --> 00:13:07.310 Radical proposed solution. 00:13:07.670 --> 00:13:12.750 What if, just like we got to the place with elevators where we 00:13:12.750 --> 00:13:16.109 realized you didn't have to have a human driving the elevator. 00:13:16.260 --> 00:13:18.870 You could just trust the elevator to drive itself. 00:13:19.319 --> 00:13:26.219 We could get behind the idea that if they could drive themselves, we could get to 00:13:26.219 --> 00:13:31.064 the place where these metal boxes, like an elevator, take the passengers where 00:13:31.064 --> 00:13:35.025 they need to go, and you just push a button and say, here's where I want to go. 00:13:35.234 --> 00:13:37.755 And it takes you there much safer. 00:13:37.994 --> 00:13:41.895 And there's all kinds of benefits, including, maybe particularly, the lives 00:13:41.895 --> 00:13:48.015 that are being saved because those metal boxes can now take themselves there much, 00:13:48.015 --> 00:13:49.935 much safer than a human driving the car. 00:13:50.715 --> 00:13:52.694 So that's the radical proposed solution. 00:13:53.025 --> 00:13:59.415 And then there was a set of, at the time, new technologies, how to coordinate lidar, 00:13:59.505 --> 00:14:03.990 radar, and cameras around a vehicle. 00:14:04.260 --> 00:14:08.699 There had been some evidence, before we started on what is now called 00:14:08.699 --> 00:14:11.610 Waymo, from the DARPA Grand Challenges. 00:14:11.910 --> 00:14:17.939 The first of which in 2006 was one by Stanford here. 00:14:18.180 --> 00:14:19.709 That car was called stanley. 00:14:20.045 --> 00:14:22.595 Matt Abrahams: And DARPA, just so people understand, is something that the US 00:14:22.595 --> 00:14:26.765 Federal Government, it's a funding source for creative ideas that can 00:14:26.765 --> 00:14:28.444 be used for defense and other things. 00:14:28.444 --> 00:14:28.985 Astro Teller: Exactly. 00:14:28.985 --> 00:14:31.805 And so there was this worldwide, or at least countrywide, grand 00:14:31.805 --> 00:14:35.015 challenge that was announced about cars that could drive themselves. 00:14:35.194 --> 00:14:40.115 And while even in the second time it was run, there were three groups 00:14:40.115 --> 00:14:43.655 that completed the hundred and fifty miles, they were out in a desert. 00:14:43.655 --> 00:14:48.005 It was one one thousandth the difficulty of what Waymo currently has to do, 00:14:48.485 --> 00:14:51.555 but it was enough evidence that maybe it just, maybe it was time. 00:14:52.290 --> 00:14:55.620 Matt Abrahams: I love that example and many people listening perhaps 00:14:55.620 --> 00:14:59.130 have not seen a Waymo or been in one, I have, and where I live is 00:14:59.130 --> 00:15:00.660 where a lot of them were tested. 00:15:01.080 --> 00:15:02.250 So I'm a little more used to it. 00:15:02.550 --> 00:15:05.760 It is freaky to be in the back of a car that has no driver, but 00:15:05.760 --> 00:15:07.950 it is absolutely cool as well. 00:15:08.250 --> 00:15:11.580 I want to come to something that you just did. 00:15:11.700 --> 00:15:15.330 You just told us, not just about Waymo, but you told us a story. 00:15:15.840 --> 00:15:19.950 How important is storytelling in defining and realizing moonshots? 00:15:20.339 --> 00:15:22.775 Astro Teller: I think storytelling is phenomenally important. 00:15:23.535 --> 00:15:27.824 But I watch people at the Moonshot Factory get a little bit confused about this. 00:15:28.035 --> 00:15:32.265 At least when I say storytelling, I don't primarily mean marketing 00:15:32.415 --> 00:15:34.064 or just getting someone excited. 00:15:34.395 --> 00:15:39.795 I mean, if you worked at X and you're proposing that we start a moonshot for 00:15:39.795 --> 00:15:44.805 teleportation, let's say, I need from you an architecture of understanding. 00:15:45.645 --> 00:15:47.594 Where are we trying to go? 00:15:47.954 --> 00:15:51.645 What makes us think we might be able to get from where we are to there? 00:15:52.005 --> 00:15:54.314 And how should we interpret things along the way? 00:15:54.314 --> 00:15:57.675 What's that set of lily pads that you can envision? 00:15:58.095 --> 00:15:58.905 You'll be wrong. 00:15:58.935 --> 00:16:03.555 I'm fine with the fact that you're wrong, but if you can't paint that picture 00:16:03.645 --> 00:16:08.865 so that we have a hypothesis to test, it's very hard to get behind the idea 00:16:09.225 --> 00:16:13.395 that the upside of getting there will be worth the risks if you can't even 00:16:13.395 --> 00:16:18.555 paint an idealized picture of how we would get there in a controlled way, 00:16:18.555 --> 00:16:22.125 where the costs aren't out of control, where nobody gets hurt, et cetera. 00:16:22.530 --> 00:16:26.070 Matt Abrahams: The idea of an architecture of understanding is what a story provides. 00:16:26.070 --> 00:16:29.340 And the outcome of the story for you that's important is a hypothesis that 00:16:29.340 --> 00:16:34.170 can be tested, and that's a really unique way, I think, of looking at storytelling. 00:16:34.590 --> 00:16:38.310 So you've added podcast host to your list of titles and accomplishments. 00:16:38.490 --> 00:16:42.510 What do you think about the hosting gig and what motivated you to start the show? 00:16:42.510 --> 00:16:43.740 I listen and I love it. 00:16:43.740 --> 00:16:44.550 I've learned a lot. 00:16:44.550 --> 00:16:47.340 It's really cool for me to be in person with you after having 00:16:47.340 --> 00:16:48.840 listened to you in my headset. 00:16:49.080 --> 00:16:49.890 What brought it about? 00:16:50.300 --> 00:16:52.850 Astro Teller: First, if people are interested, they can just look up 00:16:52.850 --> 00:16:56.070 Moonshot Factory, Moonshot Podcast. 00:16:56.070 --> 00:16:59.780 We were turning fifteen years old and at least one of the things was, you 00:16:59.780 --> 00:17:02.930 know, we're trying to get a little bit less secret and we wanted to 00:17:02.930 --> 00:17:08.120 start exposing some of how we work and what we've done, what we've learned. 00:17:08.570 --> 00:17:13.580 Partly because we want to empower other people to take their own moonshots and 00:17:13.580 --> 00:17:17.870 giving them that learning opportunity, hopefully gives them a boost. 00:17:18.204 --> 00:17:24.024 Rather than me, just blah, blahing about moonshot taking, what we've done is we've 00:17:24.085 --> 00:17:28.764 sliced it up into about fifty minute episodes, ten of them in the first season, 00:17:29.065 --> 00:17:33.885 where we've given people who've come through The Moonshot Factory a chance to 00:17:33.885 --> 00:17:36.135 tell their stories, what they've learned. 00:17:36.135 --> 00:17:38.625 So you get to hear in the first person what it was like 00:17:38.625 --> 00:17:40.395 to be taking those moonshots. 00:17:40.665 --> 00:17:43.815 And these are some people who are now luminaries in their 00:17:43.815 --> 00:17:48.405 field, Sebastian Thrun, or Andrew Ng, or Jeff Dean, and others. 00:17:48.675 --> 00:17:50.865 And how did we get to something like Google Brain? 00:17:50.865 --> 00:17:54.585 How did we get to something like Waymo, the self-driving cars? 00:17:55.065 --> 00:17:59.730 And when you hear from them the mistakes they made or those initial things that 00:17:59.730 --> 00:18:04.440 gave them the faith to start, that, that seed crystal that they thought 00:18:04.440 --> 00:18:09.240 was worth building on, I hope it then helps other people, not only understand 00:18:09.270 --> 00:18:13.260 us and the moonshots we take, but inspire them to go do some of their own. 00:18:13.560 --> 00:18:16.470 Matt Abrahams: It's very inspirational and it's really cool to hear in 00:18:16.470 --> 00:18:18.090 their own words what they've done. 00:18:18.480 --> 00:18:19.920 And there are learnings that come. 00:18:19.920 --> 00:18:23.370 I have listened and thought differently about ways I team with 00:18:23.370 --> 00:18:26.820 people and the ways that I think about the decisions I need to make. 00:18:27.420 --> 00:18:30.330 So I'm excited that you're doing it and I'm excited to listen to season two. 00:18:31.590 --> 00:18:34.170 Before we end, I ask all my guests three questions. 00:18:34.170 --> 00:18:36.660 One I create just for you, and then the other two are similar. 00:18:36.660 --> 00:18:37.230 Are you up for that? 00:18:37.320 --> 00:18:37.710 Astro Teller: Sure. 00:18:38.160 --> 00:18:40.110 Matt Abrahams: I'd be very curious, what's a current moonshot you're 00:18:40.110 --> 00:18:42.030 working on that has you really excited? 00:18:42.480 --> 00:18:44.129 Astro Teller: We started this about eight years ago. 00:18:44.129 --> 00:18:46.379 This is very typical of the moonshots we take. 00:18:46.590 --> 00:18:50.160 They seem crazy when we start them, and then at least occasionally, much 00:18:50.165 --> 00:18:53.580 later, they turn out to be in the right place at the right time, is 00:18:53.580 --> 00:18:55.950 a moonshot for the electric grid. 00:18:56.220 --> 00:19:00.580 It turns out that everyone would like to make software that helps the 00:19:00.580 --> 00:19:02.560 electric grid get better, including us. 00:19:02.740 --> 00:19:04.030 And you can't. 00:19:04.300 --> 00:19:11.190 You can't until somebody has a circuit diagram for the grid itself. 00:19:11.610 --> 00:19:16.320 If you don't have a digital twin for the grid where every wire is, where every 00:19:16.320 --> 00:19:21.120 inverter is, where every transformer is, no software on top of that will help 00:19:21.120 --> 00:19:26.100 you manage what you have or plan for the future or optimize it in real time. 00:19:26.520 --> 00:19:32.835 And so what our team, Tapestry, did over the last seven years was build out 00:19:33.075 --> 00:19:38.655 the tools for taking in a wide variety of data, including the very noisy and 00:19:38.655 --> 00:19:42.315 imperfect data that grid operators have about their own grid, 'cause they 00:19:42.315 --> 00:19:44.325 don't have a map of their own grid. 00:19:44.595 --> 00:19:50.145 And then using lots of different sources, street view cars, drone data, satellite 00:19:50.145 --> 00:19:56.525 data, lots of different inputs, we can then use induction and deduction to do 00:19:56.525 --> 00:20:02.885 the detective work and back out the exact grid that a particular grid operator has. 00:20:03.155 --> 00:20:07.445 And then we can help them manage the grid they have, plan for 00:20:07.445 --> 00:20:10.535 the future of their grid, and optimize their grid in real time. 00:20:11.105 --> 00:20:13.835 Matt Abrahams: So it's as if you've decoded the genome for the grid and 00:20:13.835 --> 00:20:15.095 now we can do some work with it. 00:20:15.215 --> 00:20:18.395 That sounds very useful and hopefully very beneficial. 00:20:19.025 --> 00:20:22.175 Question number two, who is a communicator that you admire and why? 00:20:22.830 --> 00:20:27.030 Astro Teller: I enjoy giving public talks, and so oration has 00:20:27.030 --> 00:20:28.650 always been very interesting to me. 00:20:28.890 --> 00:20:34.470 And I have watched a wide variety of public speakers, not because I'm going 00:20:34.470 --> 00:20:40.200 to be any one of them, but to understand how each of their patters functions. 00:20:40.500 --> 00:20:44.850 You know, Martin Luther King Jr., great speaker, his preacher style, there 00:20:44.850 --> 00:20:46.350 are things you can learn from that. 00:20:47.010 --> 00:20:53.310 James Baldwin, amazing speaker, not a preacher, somewhat professorial, but 00:20:53.310 --> 00:20:58.530 with a calm angriness because of the specifics of the life that he led. 00:20:59.040 --> 00:21:01.770 Barack Obama very professorial. 00:21:02.159 --> 00:21:06.270 My grandfather, Edward Teller, actually, was another great public 00:21:06.270 --> 00:21:09.780 speaker, and I learned a lot from watching each of these people. 00:21:10.290 --> 00:21:13.260 Matt Abrahams: Yeah, they each bring a really interesting approach that you can 00:21:13.260 --> 00:21:16.500 then synthesize, and by the way, your TED talk is one that everybody should 00:21:16.500 --> 00:21:20.129 listen to because you deliver it very well and it's very exciting to learn from. 00:21:20.490 --> 00:21:23.970 Final question, what are the first three ingredients that go into a 00:21:23.970 --> 00:21:26.100 successful communication recipe? 00:21:26.670 --> 00:21:30.630 Astro Teller: I personally don't love the start with a personal story. 00:21:30.900 --> 00:21:36.510 I would encourage people to get real, as in honest, get 00:21:36.510 --> 00:21:40.200 specific, and you can be human. 00:21:40.440 --> 00:21:48.010 So when we tell a story, like in our podcast, we use visuals from the field, 00:21:48.460 --> 00:21:50.530 from the actual people who were doing it. 00:21:50.830 --> 00:21:55.540 We explain what we were trying to do and how where we actually 00:21:55.540 --> 00:21:57.910 ended up wasn't that, getting real. 00:21:58.030 --> 00:22:03.430 We show people how we harvest value, even from being wrong, and can have 00:22:03.430 --> 00:22:05.260 fun in the process of learning. 00:22:05.590 --> 00:22:10.460 And when you get a cycle of those three things, while that doesn't feel like Mary 00:22:10.460 --> 00:22:16.220 Jane in Idaho start of the sort of New York Times article, it is deeply human. 00:22:16.220 --> 00:22:19.220 You can feel what it feels like for these people to go through it. 00:22:19.670 --> 00:22:21.740 It's exciting, it's meaningful. 00:22:21.740 --> 00:22:23.180 You can see yourself in it. 00:22:23.180 --> 00:22:25.250 It's memorable because of those things. 00:22:25.490 --> 00:22:26.750 So that's how we try to do it. 00:22:27.020 --> 00:22:30.620 Matt Abrahams: Be real, be specific, be human, and all of that allows 00:22:30.620 --> 00:22:31.820 you to connect through emotion. 00:22:32.429 --> 00:22:35.550 I appreciate that recipe, and I appreciate this conversation, Astro. 00:22:35.550 --> 00:22:36.629 This was fantastic. 00:22:36.629 --> 00:22:39.929 You've talked about architecting to understanding, and you certainly did 00:22:39.929 --> 00:22:43.800 that for us, and I hope all of us can build these habits and reward ourselves 00:22:43.800 --> 00:22:45.479 for these habits and not just outcomes. 00:22:45.479 --> 00:22:46.260 Thank you for your time. 00:22:46.469 --> 00:22:46.800 Astro Teller: Thank you. 00:22:46.800 --> 00:22:47.580 That was a lot of fun. 00:22:50.520 --> 00:22:52.469 Matt Abrahams: Thank you for joining us for another episode of 00:22:52.469 --> 00:22:54.659 Think Fast Talk Smart, the podcast. 00:22:54.959 --> 00:22:58.590 To learn more about creativity and innovation, please listen to episode 70 00:22:58.590 --> 00:23:01.154 and 20 with Jeremy Utley and Tina Seelig. 00:23:01.680 --> 00:23:06.750 This episode was produced by Katherine Reed, Ryan Campos, and me, Matt Abrahams. 00:23:07.080 --> 00:23:08.640 Our music is by Floyd Wonder. 00:23:08.760 --> 00:23:10.625 With special thanks to Podium Podcast Company. 00:23:11.415 --> 00:23:14.534 Please find us on YouTube and wherever you get your podcasts. 00:23:14.774 --> 00:23:16.875 Be sure to subscribe and rate us. 00:23:17.205 --> 00:23:20.324 Also follow us on LinkedIn, TikTok ,and Instagram. 00:23:20.774 --> 00:23:24.735 And check out fastersmarter.io for deep dive videos, English language 00:23:24.735 --> 00:23:26.865 learning content, and our newsletter. 00:23:27.314 --> 00:23:30.584 Please consider our premium offering for extended Deep Thinks episodes, 00:23:31.480 --> 00:23:36.875 AMAs, Ask Matt Anythings, and much more at fastersmarter.io/premium.