← Leap Academy with Ilana Golan
Leap Academy with Ilana Golan
Google X's Astro Teller: Why the Biggest Breakthroughs Start with Failure | EP167
01:00:35
Loading summary
Transcript68 lines
- [00:00]
A
Radical innovation almost always doesn't work. Anyone who pretends differently is telling you a just so story after the fact.
- [00:07]
B
Dr. Astro Teller is the co founder and captain of Moonshots, the CEO of Google X and Alphabet's Moonshot factory. He leads the creation of breakthroughs technologies, innovation like Waymo. We gonna geek this out a little bit.
- [00:23]
A
The breakthrough technology that gives us a sense of that there's at least a glimmer of hope. In the early days we were having Googlers who use them for their commute. We said hands right by the steering wheel. We're going to have cameras in the cars looking at you. We saw people getting into the back seats, doing their makeup. One of them fell asleep. It was never our job to make and sell a car. Our job is to make the world's best driver.
- [00:47]
B
This was fascinating. I could probably talk to you for Dr. Astro Teller is the co founder and captain of Moonshots, the CEO of Google X and Alphabet's Moonshot factory where he leads the creation of breakthroughs technologies innovation like Waymo, the self driving cars which by the way we're the biggest fans, just FYI, Google brain wing which is redefining how bold ideas become real world impact. I mean so cool. And but before that he was also like he's a serial entrepreneur, he's a scientist, he's a former Stanford professor. As Astro has built, exited multiple companies, holds numerous patents, he's recognized as one of the leading voices in innovation and future thinking overall like it's just incredible that we get to hear him on the show. Thank you Astro for coming here.
- [01:41]
A
Alana, thank you for having me. I've really been looking forward to this conversation.
- [01:45]
B
It's going to be really fun and for everybody here listening, this is going to be a fascinating conversation about how first of all he got into Google X but also how they created not only real self driving cars finally, but also we'll talk about drones and AI and the future and so much more. And also remember, once a week we choose a question from our YouTube channel in a Leap academy with Zilan Golan. And I answer it here live at the end of the conversation today I actually want to invite Astro to answer this with me because the question from Greg was what do you think is around the corner that we are not aware of? And I love that question. So Astro, let's do this together.
- [02:28]
A
Let's do it.
- [02:29]
B
Okay, but first I'm gonna have to take you back in time a little bit because with all your extensive career and all the things that you achieved and all the things. Can you like give us a really quick recap? How do we even get into Google? Like why does Sergey come to Astro and says come to Google? Like what, what happens there?
- [02:46]
A
I'll give you a few different kind of vectors in. So one of the ways to think about it is that Google is known for giving people the opportunity to work on 20% time things. And they actually inside of Google now, Alphabet for a long time have talked about 70% like is like the work, 20% is the adjacent work. And then there's 10% which is the like really much farther out there kind of stuff. And they had a position open for quite a while called the director of other, which was meant to be like taking care of that 10%. And they interviewed me and I think several other people and didn't fill the role. But Larry and Sergey had been thinking about for a long time before Alphabet was created, the fact that there's like a physics to businesses and as they get larger they get more complicated. It's nobody's fault, it's just the physics of businesses. And they wanted to make sure that what they imagined as Alphabet even before it had that name would be able to keep stretching itself outside its comfort zone. And so X, the Moonshot factory was set up 16 years ago with that as our mission. Don't solve Google's current problems. Google's good at solving Google's current problems. Go find big new problems in the world that we could be really proud of solving and then hopefully find some world changing solution to those problems. So that's been our mission for a long time, is to help Alphabet, even before it had the name, get more surface area with the world and to create a series of businesses which we call Moonshots that were particularly audacious both in the way if they succeeded, they could help the world and, and in the sort of quality of the business created.
- [04:42]
B
Right. And maybe define Moonshot for the people listening.
- [04:46]
A
Awesome. So at least what we call a Moonshot is it has to have three components. The first one is there has to be a huge problem with the world that you can name and you want to solve. Otherwise it's a bit of an academic exercise. Then tell me a story. Tell us a story about some science fiction sounding product or service. Don't worry yet about whether you can make it, whether it's likely, how even you would make it. But what's that product or service that we could pre agree if you could make it, it would resolve that huge problem with the world. And then what's the breakthrough technology that gives us a sense that there's at least a glimmer of hope in the early days that we could actually make that science fiction sounding product or service so that we could resolve that huge problem with the world. And if we have that, we're not done. That's a moonshot story hypothesis. That's like opening up the starting gates. And from there, great, that's a testable hypothesis. Let's go get some evidence that teaches us either that things are a little bit more exciting than we thought or a little bit less exciting. And if they're less exciting, cool, we'll stop it. And if they're more exciting, great, we'll double down on it. And that is the sort of basic internal function of, of X. Back to your question about sort of how I got into this position. X and Waymo were kind of created, came into being at about the same time and at least partly X came into being as a place to house this thing that ultimately became Waymo. And as part of that getting formed, the founders of Alphabet asked a man named Sebastian Thrun to set up X. And then asked him if he wanted a co founder and he came and asked me if I would do that with him. So very practically that's how I ended up. For about two years I was his first mate. You know, we co founded it, but I reported to him and then he ended up leaving X after about two years to set up Udacity on the outside. And at that point I became the captain of Moonshots instead of the first mate.
- [06:51]
B
Oh, I love this story. And for those who don't know Sebastian, he actually, and correct me if I'm wrong, Astro, but he is kind of the godfather of the online open online courses. And you know, I think this is completely disrupting, you know, education. And we're going to talk about Masterclass in a second. But I mean, it's kind of like it created a huge impact on its own. Okay, so you're, you're somehow they're coming to you, but take me there for a second, Astro, because how do you know if you're set up for success if you just work on something very futuristic? How do you know if it's going to be successful? How do you even measure that? What does it look like?
- [07:29]
A
Well, spoiler alert. Radical innovation almost always doesn't work. Anyone who pretends differently is telling you a just so story after the fact. That's just survivor bias. You cannot do radical innovation without being mostly Wrong.
- [07:45]
B
Right.
- [07:46]
A
So the main thing that happened while I was interviewing with Alphabet is I kept asking what is your tolerance for stopping things? Because that is the rate limiting step of innovation. If you don't have tolerance for that, I can't succeed here. And essentially everybody said we want to be great at that, but we aren't yet great at that. And I believe them. They at least wanted to be. And so my only sort of ask or test before I joined Alphabet to help co found what is now the Moonshot factory was operational and cultural separation. Not because Google is anything other than great. Google's a really amazing company. But we needed to be and work differently in order to produce something that would be different. And I was convinced that in order to be able to create an environment where it was rational locally to actually kill your own projects, to be in this sort of much more rapid sort of discovery, intellectual honesty process, we needed to have a subtly but profoundly different culture. And that couldn't happen without the cultural and operational separation which Alphabet Google gave to me in Sebastian, which is why I joined.
- [09:05]
B
Right. And that's incredible. Google was always known for its innovation, like you said, the 10% future, work on the future, et cetera. But I think it's something very, very different knowing that you're going to need to kill your own projects. And I think there's something that, like, how do you motivate a team, Astro? Like how do you create a team that the morale is like, hey, let's. This is so cool. We just, like, we were really passionate about this and now we're gonna kill it. Like how, how do you not break the team?
- [09:37]
A
I'm gonna play a game with you where we're gonna pretend that you're coming to join X. Don't worry, I'm not actually stealing you. But, but for this conversation, imagine that you're considering coming to X and you're asking me that question, central thing that you should care about. And I had better be able to answer, yeah, on the surface all we're asking for is intellectual honesty, nothing more. So like, surely we can agree that if the thing that you're working on is not actually the best way for X and Alphabet to spend its money trying to help the world, it's not gonna. God came and told us that that was the truth. Like we could agree we should stop doing that thing. We both want to be intellectually honest. The trick is the way the world actually functions. Even though you want to be intellectually honest, that you would step away even with some sadness from something you had worked hard on. If that was no longer a really promising thing, the world has taught you not to do that. That is a career limiting move everywhere else. So the real question you're asking me is not whether I'm serious about that. It's what are you doing at X? What are the hundreds of things you're doing at X so that it's not a career limiting move to say, hey, the teleporter I've been working on really hard for two years, it's not working great. I'm not sure we're going to get there. I can't prove it won't work, but I think we should stop this. So there's all these questions like, if I do that, can I still get promoted? If I'm like a really great Xer, can I get a bonus at the end of the year? How will I be treated by my co workers at our all hands? If I stand up and I say I've killed my project, if everybody boos, not only will I never do that again, but nobody's going to do it again. If you get a standing ovation for killing your own project and for demonstrating your intellectual honesty, then you'll say, oh, maybe that's okay to do that here. And then other people who are sitting in the stands will think, oh, maybe I can be intellectually honest. Which is why we work so hard to make sure that when people kill their project, we give them a standing ovation. And it's like, no one of those things can undo it. You have been taught since you were five. We have all been taught since we were five years old to play the short game, to get an A plus on the test, to not say you don't know the answer. All of these things, which are actually exactly the opposite behaviors from what would actually drive radical innovation. But that's, that's adaptive, sadly, perhaps in our world. And so X has worked really hard to create a microcosm where those reinforcements don't exist, where there's a different set of reinforcements towards the habits that are more healthy for innovation.
- [12:22]
B
This is so fascinating because as you were speaking, I started my career in the Air force as an F16 flight instructor. And one of the big things that we would do there is be very harsh with ourselves. We would need to stand in front of everybody and say, basically all the mistakes that we've done and what are the lessons? Every single time. And it's like there's a humbling thing around. Like, I don't, I like this Feels like I'm naked right now, but it's like, this is what you need to do in order to learn really, really fast. And so I love that you shared this, but. But I will ask, like, we are, you know, we always train to kind of minimize risk. And now you're asking people to train them how to 10x the growth, right? You. You can't do this. If you think 1%. You. You have to think 10%.
- [13:06]
A
Or can I get on a tiny soapbox about risk for a second?
- [13:11]
B
Yes, please.
- [13:12]
A
You're absolutely right. The whole world is obsessed with getting risk as close to zero as possible, which is rational. If the size of the prize doesn't really matter, and you'll be punished if you don't get a success. That's why the whole world is so busy doing small, nearly meaningless and incremental steps most of the time, because they feel like they can't afford as individuals and as subgroups to not succeed. And once you have to get the risk to zero, you basically have thrown away almost all the upside you can get. So let's play a game. Choice A. Choice B. Choice A, you can give a million dollars of value to your business this year, guaranteed. Or choice B, you can give a billion dollars of value to your business this year, but it's not guaranteed. It' chance and 100. So choice A, million guaranteed. Choice B, billion one. Chance and 100. Which are you going to choose?
- [14:15]
B
I will choose B.
- [14:16]
A
You're going to choose B because B has 10 times the expected utility of choice A. It has an expected utility of 10 million. Choice A has an expected utility of 1 million. That is a rational thing to do. What you have just done is by moving from thinking about risk by itself, you've moved to thinking about reward divided by risk at X. I think everybody has internalized the idea. If you're working on something and you could find something that has twice the risk but four times the upside, you should probably stop what you're currently doing and work on that other thing instead, because it has twice the expected utility. And so moving people away from risk minimization to reward risk ratio maximization is one of the essences of innovation.
- [15:11]
B
So let me take you there for a second because it sounds good on paper, but I bet there's some sleepless nights involved in this, like, shiny world. Like, is there moments where you're like, oh, God, like, I don't know if this is going to work. Like, I don't know what successes I can look like? If you could take Yourself back in time. Like, can you share, like a moment where it's like, geez, like, I don't know, like, maybe we are too early in our, you know, to this kind of innovation, like, share a little bit? Because it sounds amazing, but I'm sure emotionally there's a bigger roller coaster here.
- [15:45]
A
There absolutely is. So the tension is, on the one hand, you don't want to excuse, make your way sort of to the horizon, where you're working on something that really is sort of a zombie, but you keep it alive because you're like, just one more try, Just one more try. You never know. So that would be bad. That's the opposite of what I'm describing. On the other hand, as you're pointing out our most successful things, things like Waymo, things like Wing. More recently, you know, our moonshot for the electric grid called Tapestry, which is now profoundly important around the world for grid operators. Like, I can't tell you the number of times we almost stopped it because we just, we couldn't figure out whether there was a there, there, which way we should go. Like, what are we really doing here? Do we have something that's important enough to continue to take this kind of risk and to spend significant money on this? And so it's an art as much as a science. That's just part of the reality, is that there isn't a right answer. Every one of these things is a bit of a snowflake because you're always going. You're like an explorer. You're going to a place that no one's ever been before. So you don't get a map, and so there isn't a checklist that teaches you. You keep going until this point and then you stop, no matter what. It's a judgment call. And getting a group of people to agree is almost impossible. But there are lots of tricks, intellectual architectures that you can put around people that help them think through this in various ways.
- [17:20]
B
So give us some tools. And by the way, I'll give you a little plug because you actually talked about the grid innovation on your podcast. So I was listening to it and, and it sounds fascinating and. But I, I do want to, to maybe give some of these tools, but maybe we can also run to an example of Waymo, which, you know, started, I don't know, what was it, 15 years ago, right. Or whatever that adds up to be. Right. And there is. So I would love for you to also take us a little bit back to kind of look at what, what does that look like? Because I think it's so easy to look at the cars now driving, and they're so cool. And, you know, I've. I've been one of your biggest sponsors. You know, I love it since we have it in Arizona and now in San Francisco, et cetera. But the truth is, you know, there were probably years of, like, is this going to make it to the market? Right. So. So can you take us back in time with me maybe?
- [18:14]
A
Sure. Let me. I'll give you two examples exactly as you just mentioned, for your listeners, if they would like to just search for Moonshot Factory Moonshot podcast. Our second season just came out a few days ago. I think they'll really enjoy this. These are these very unfiltered deep dives into the stories you and I are about to, like, take some little pinches of. But if people want to hear more, I think they will really enjoy the podcast. So let me give you two stories, one from Wing and one from Waymo, since those are two that I think your listeners will be familiar with. In the case of Waymo, we spent the first five years thinking we were going to make cars that drove themselves and sell them to people. That was kind of what cars were. And so we were just going to make better cars. That was our conception. And so we had them after about five years on the freeway. We were having Googlers who didn't work at Axe take them and use them for their commute. And we said, okay, but you have to promise, promise, promise, you're gonna keep your hands right by the steering wheel. We're gonna have cameras in the cars looking at you. No messing around. The cars are really good. But this is like public safety. So you have to keep your hands really close to the steering wheel all the time. You're good. And these Googlers. Oh, absolutely. And these Googlers are great human beings. They're way above the average, I think, for, like, diligence for human beings in general as drivers. And within days, we saw people getting into the backseat, eating their lunch, doing their makeup. One of them fell asleep, and we had to stop the project because we had been assuming that humans can be backups for technology that's not quite ready. And when the safety is this serious, that just doesn't work. Now, we could have stopped the project. Like, that was a big red flag relative to what we assumed our job was, what the business was. Now we didn't. We had some serious conversations, but in the end, we said, oh, it was never our job to make and sell a car. That was A misdescription of the mission, A real mission is to transform mobility. Like an elevator. You should just get in, say where you want to go and it just takes you there. That's what these vehicles that we're working on should be. And we worked on that for another five years and came to a new conclusion that was much more business related than safety related, which was we still have it wrong that mobility needs to be transformed. But that's not our job. Our job is to make the world's best driver. That's our job. And there's a lot of ecosystem partners that can help us with the other parts. But what we should be great at is making the world's best driver. And so there was like real evolution of the thinking of what Waymo wanted to be when it grew up. And the first of those big evolution points was this crisis moment where we realized that our whole conception of like what would make it safe, that the humans would be the backup, was a terrible assumption and we had to abandon that.
- [21:23]
B
So it all starts, correct me if I'm wrong, Astro, but it all starts with a fundamental mission, if you will. There's millions of people that die every year from car accidents. This doesn't make any sense. Robots can do better. And basically it all starts with that. And then the question is, which one is the best vehicle to create that in? Am I reading this correctly or no?
- [21:46]
A
I mean, I certainly agree that the huge problem with the world is well described as more than a million people a year die from car accidents that were caused by human error. There's also more than a trillion dollars a year wasted with people sitting in traffic unnecessarily scraping up their cars, a whole bunch of other stuff. Human lives are more important than the trillion dollars, but you know, you can solve them both at the same time. So that's a good thing. The radical proposed, the science fiction sounding product or service is a car that drives itself. You said the vehicle. Obviously the vehicles are evolving also. But I would argue that it's a complex mix of the vehicles, the sensors, the compute, the algorithms, the data. There's a lot of different parts that go into making the world's safest driver. But you know, over 16 years we've gone from that sounds crazy to it's in 10 cities. And you know, lots of people get in waymos every day and have a ride, which is kind of mind blowing for the first 30 seconds. And by the end people are just like on their phones back to doom scrolling and not even noticing that there's nobody in the front seat. Can I give you a different kind of example with Wing?
- [22:58]
B
Sure.
- [23:00]
A
So, because we were talking about intellectual architecture that sort of helps people past these crisis moments.
- [23:06]
B
Yeah. And by the way, for those who don't know what Wing is, is basically drones that deliver packages. Right. Like, am I basically Wing?
- [23:15]
A
Wing has been on a mission for about 13 years now to solve the last mile problem. If you could just have anything that fits in a bread box, like up here, anywhere you are, anything that could fit in that bread box in like a couple minutes for like a dollar, that's like nearly a teleporter. It would fundamentally change how we think. Not just about things like food delivery, but I have a hammer in my garage. The person next door to me has a hammer in their garage. Like, we could probably share one hammer across like 10,000 of us, but we don't have a way for the hammer to move around. Right. Libraries are like, basically useless at this point, but if you could actually have the book come to fly to you, like Harry Potter, owl post and then fly home again, all of a sudden those books are not stranded assets anymore. There's just so much about the world this would change. So as we were coming to launch, this was now about 10 years ago. I sat down the whole Wing team and I said, it is not today. It is three months from now. And our launch has been an unmitigated disaster. We feel physically sick. It went so bad, we can't even look each other in the eyes when we walk by each other in the hallway. And you know, you know why it went so bad. This is a test. You have two minutes. There's paper in front of each of you. Write down why it went so bad. And by moving people from a pride and the launch fever that can kick in to that 16 year old, you want to get an A on the test kind of thing and prove how smart you are. Everyone started frantically writing down all the things that were wrong with Wing. And this was about a month before the launch. And once they had written for two minutes, I said, great, let's organize everything you wrote down, then sort the list, start fixing things. And we had a great launch. That is one of a hundred tricks that X has to help people work through. Some people might call a softer version of that a pre mortem. That was a sort of very intense pre mortem.
- [25:25]
B
I love that. That was so powerful because I could feel it in my bones. And I think you talk about a concept that I really love. What's the Monke, can you share that a little bit? Because I think it's so profound. Because we many times look at the same thing, but we fix the wrong problem or we address something that is not the riskiest assumption. Can you talk to us a little bit about it?
- [25:48]
A
Sure. So in the early days of X, I kept saying incorrectly, assuming that it would land well with people, we should always work on the riskiest part of the problem first. And like, in my mind, that sounded like duh. But everyone at X clearly was like, not sure what Astro's saying. That doesn't sound right. So I think I was having no effect on people, at least on that subject for several years. And then I was at a Wall Street Journal live conference on stage. Someone was interviewing me and I said, like, obviously, you should work on the riskiest part of the problem first. And the woman who was interviewing me said, that doesn't sound right. Can you explain that? Like, unpack that somehow? And I was just in a moment of being hyperbolic, I said, look, let's pretend we were working on a project and our mission was to get a monkey to stand on the top of a 10 foot pedestal and recite Shakespeare. Which should we do first? Should we build the pedestal first or should we spend our time training the monkey first? In that really extreme example, we know that if we built the pedestal first and we're like, hey, boss, look, I'm half done. In some really lame sense, you're half done. But in a much more meaningful sense, you have burned down 0% of the risk. You have utterly wasted your company's money. The only thing that matters is, can you train the monkey? Because if you can't, thank God you didn't spend time building the pedestal. And if you can, we can get a pedestal afterwards to like, get under the monkey. But now, like, that's an extreme example, but in much more subtle ways. The world is awash with people who are building pedestals not because they're stupid and not because they're nefarious. It's because their companies reward pedestals. They're just thinking, like, I want to feed my family. I want my career to go well. If I work on the monkey, it's probably not going to work. I kind of have a sense that, like, this monkey's probably not going to recite Shakespeare. I don't know what I'm going to do next, but I know if I build the pedestal, then I can like, hey, boss, I'm half done and I'll get a bonus. I'll get A promotion. And, you know, I can leave the monkey problem for like whoever comes after me or just hope that like the monkey thing doesn't come up till after I quit, moved on to another job. Like, it sounds ridiculous, but actually this is most of corporate America and this is another one of these intellectual tricks is finding a way to really viscerally connect people to the important habits. We're trying to be like the card counters of innovation. And so helping people, like learn the little tricks and not just learn them intellectually, but really get them into their hearts and their guts as well so that they can internalize it till it becomes like muscle memory is what it takes to not just culture isn't what you put on the poster. Culture is what people actually do. Right. And so that's like why most of the work that we do here is trying to connect people to these ideas in sort of visceral ways that last and that tend to get reinforced by our environment.
- [28:48]
B
Ah, I love that. And I'm just like, there's like a bunch of things coming my way because I think one of the things that we notice in Leap Academy or any, you know, one of these education companies, it's not so much about the content, everybody runs to create the content, but the hardest thing is to create client experience that says, I'm stuck, I need to reinvent myself, I have no clue what I'm going next. And they choose the academy and actually get results. So it's like, I love that. A monkey example, because a lot of time people are working on the wrong things because that's not what's gonna help shape everything. I think one of my.
- [29:22]
A
Sorry, can I. Can I tell you another inside jokes that's recently.
- [29:26]
B
Yeah, go for it.
- [29:27]
A
This is very X. Like a number of years ago, people decided that they did. They thought our swag wasn't fun enough. So some group of Xers, I still don't really know who they are, started an Etsy store which I think is now on bonfire, called Schweggy McSwaggerton, where you could get this, like, schwag that's made by Xers but not like, approved by X. And at some point there was a joke here that the really hard thing. I think you will particularly appreciate this. The. The monkey. The hardest part of the problem is actually us. It's an inside game. It's working on managing our own psychology. And so to reference, like, the monkey is us, the monkey is inside us. There's now one of these things where like this monkey kind of clawing its way out of the T shirt that people wear around the office to remind us not only should we be working on the monkey, but the biggest monkey of all is managing our own psychology.
- [30:23]
B
But. But. So I want to tap into that because I think mindset is especially in a moonshot is going to be insanely important, right? And it's going to be this relentless. I'm not a failure. The fact that I didn't find this out yet, it's okay because it's just going to take more time and it's going to take more trials and more errors and more experiments and. Oh, how do you dial this kind of a mindset, Moonshot mindset, if you will.
- [30:51]
A
I'm going to. I'll give you an example or two, but no one thing will do it. You cannot just tell people this is the right answer. Go be like that. You have to constantly, in all of these little ways, reinforce it. You know, there's a flag behind me that says keeping Alphabet weird with a flying pig. I'm literally happen to be wearing the tarot card of the fool. I don't believe tarot cards are magical, but I'm just really in. In all these different ways I want to. I'm somewhat known for wearing rollerblades around the office to remind people that we need to be in the beginner's mindset. That in a way, that's the answer. But I actually just a minute ago mentioned card counting. So card counting is a process, you know, under the right circumstances. If you watch at on you're playing blackjack and cards come across the table and then are retired, and that starts to slowly change the statistics. Imagine if all of the aces came out. The first four cards dealt were aces. Maybe a little odd, but it could happen. That would change the odds of how you should play the game afterwards. If all of the kings came out next, that would change the odds even faster. Right? So people can actually get an edge over the casino in playing blackjack if they do two things. They're very careful about watching what cards have come by, and then they deeply understand the statistics and how the statistics change depending on which cards have already gone across the table. Now imagine I was go. You were gonna. You claimed you could card count and I was gonna go to Vegas with you and I was giving you my money. If you please don't. Me too.
- [32:41]
B
Kidding.
- [32:41]
A
Me too. I'm not particularly good at card counting. But if I gave you money because you claimed you could card count and then you just like went wild and you're just like randomly doing stuff and you happen to win. I would say shame on you. And I wouldn't give you any more money. Even though you had won, you had taken my money and grown it. Because what I really care about is, do you have a process that works? And I want you to feel pride about that. Now imagine you go to Vegas with some of my money. I stand over your shoulder and you are perfect at counting the cards, figuring out the statistics and how they're changing, and you play every hand perfectly relative to the statistics and you just get unlucky and you lose some of my money. I would say, great job, take more of my money. I will play that game all day long. The reason I take you and your listeners through that is that's what innovation should be like. If you care about efficiency. Side note, innovation is really easy. If you don't care about efficiency, you just find a lot of smart people, you throw a lot of money at them, and you'll get some innovation. It's just not efficient. But if you want it to be efficient, you have to get people to abandon tying their pride to the outcome and tie their pride instead to. To a set of habits which tend to result in radical innovation efficiently. Now. Easy to say, Very hard to do. So then you have to find hundreds of different ways to send them signals that you actually mean that you want that and reward them when they do behave that way.
- [34:13]
B
Oh, this is so good. Oh, my God. This is. This is incredible. I love that you. It's like, it's more the habits and the formula, if you will, and then when you can create that, it's incredible. Yeah.
- [34:25]
A
If people want to hear more about some of this, our podcast is a deep dive into these stories, the creators, these people who've gone through X. I think it's really wonderful. But we also have this masterclass certificate course if people want to dig in more to the sort of operations, some of these habits and how to tie them together. I think the masterclass on breakthrough innovation that we did would be a good way for your listeners to have that experience.
- [34:55]
B
Yeah. And Masquelas is incredible. And by the way, we're, like I said, talking to the founder David Rudyar today. So that's going to be super fun. But let me just ask you one more thing, because you guys also had Google Brain, which had a substantial impact on AI as we know it today. And if I'm not mistaken, there was an article in New York Times, I think it was something like 2012, that says that I think it was like 16,000 computers needed to be, you know, to be there to identify a cat or something there. Right. So how did we get from there to here? Can you walk us through a little bit of speaking of the formula, like, what was it?
- [35:37]
A
So, I mean, by the way, if people are interested, there's a deep dive on our podcast on this. But I'll tell you the teaser bit. This came to be because there was a professor at Stanford, his name was Andrew Ng, who had had, in retrospect, maybe it seems like a really obvious discovery now, but at the time it broke artificial intelligence orthodoxy, people neural networks were considered almost dead as a field. Back in like 2009ish time, there were a few researchers who were figuring out things sort of like Andrew Ng was, but mostly was considered dead is like that. That is a dead end for the field of artificial intelligence. But he noticed that every time he made his neural networks bigger, they got a little bit better. And so he was just like, hey, I've got six points here. It looks like maybe we could just keep making them bigger and they would keep getting better. I wonder how much bigger we could make them. And maybe that's just the solution to artificial intelligence. The entire field of artificial intelligence didn't just say no. They got angry at him. And so he came to us and he said, hey, I have this observation. What do you think? And we said, come on in. So that was an exploration that turned out to be right. So he paired up with Jeff Dean, who came over from Google to be at Google X, and the two of them built up Google Brain. And it started, at least mainly around this observation. I wonder how much bigger we could make it. And at the time, making it hundreds of thousands of times bigger than had ever happened in a university was not something a university could even run as an experiment. But we had at Google at the time the processing power and the expertise to actually try to make what by today's standards is a tiny neural network. But by those day standards, in 2000, you know, 10, late 2010, when we started Google Brain, it sounded crazy big. And that's really how we got started, was the bigger we made it, the more it seemed to work. And there were lots of questions like, how do you distribute the training of this thing across lots of machines? Because if we had trained it on one machine, it just would have taken forever to train. Computers were a lot slower back then. So that's, that's kind of the, the little glimmer that started Google Brain.
- [38:04]
B
Incredible. And I want to tap a little bit into kind of like, future pace you a little bit. Like, what do you think is coming? I mean, it's moving at a pace that we don't know. Like, it's just mind blowing for those listening that are just like, what else is coming? And I think we also got a question like that on our YouTube channel. What do you think is coming? What do you think that gonna, like, surface in the coming years that we might not even start thinking about? What do you see?
- [38:35]
A
I mean, I'll describe to you some of the things that we're seeing and that we're pretty confident are going to turn out to be a really big deal in the world. But before I do, another little soapbox. Just because it bothers me that there's so many visionaries who tell you how the world's gonna be. Nobody knows.
- [38:54]
B
Nobody knows.
- [38:54]
A
That's the actual answer. You can explore into the world efficiently or not efficiently, but nobody just gets to, like, tell you, oh, I know how it is. There's like, a whole class of people who think they know the answer, but if you average it all together, you just get zero.
- [39:12]
B
Right?
- [39:12]
A
Because if they all said the same thing, it wouldn't be interesting. And, like, to ground this, I think about the following all the time. I went to a museum exhibit. This was in the late 90s at the Carnegie museum of art, and they were doing an exhibit on the history of aluminum in art and architecture and product design. Sorry, product design and architecture. And in the corner in this exhibit, there was a hat stand. And it was made of wood. And I was like, that's weird. Why did somebody leave a hat stand in this? And then I went up. There's a little plaque by it. And it turned out after there was an electrolysis process that all of a sudden made it so aluminum went from being more expensive than gold per ounce to being a lot cheaper than gold. And the first thing that people did was someone. One of the first things was made was a hat stand. And then they painted the hat stand to look like wood, because that's what a hat stand is. And the reason that that sticks in my mind is people hadn't yet imagined all of the aerospace benefits of aluminum. The idea that we were going to make beer cans and coke cans out of aluminum or make folding chairs, the lawn chairs from, like, the 70s that many of us still remember. Like, no one could conceive of those things. The thing I'm most confident about is that we don't know what the future is going to Bring that technology is going to surprise us in the most profound impacts of technology, of the technology we can see today, are things that we can't even imagine, maybe don't have words for. I guarantee you if you went back to the arpanet, the original beginning of the Internet, and tried to describe them, this podcast that we're having, or all of the other things calling a waymo through the Internet, it would have completely broken their brains. That was not what the Internet was for back when it was the arp. But let me give you two examples of futures that we're really excited about right now. So one is right now there's about a trillion dollars a year of embodied value that just goes to landfill because we don't know how to get it back. Not because it couldn't be recycled or reused, but because we don't know what we're looking at. Literally, if there's a potato chip bag that is going down some conveyor belt somewhere in the world, what's in that potato chip bag? You have no idea. If you have a camera, you can see it's a potato chip bag, but it's got like 50 different chemicals in it. And if it has half a percent of the wrong thing, it will not only turn your whole recycling batch into goop, it might well ruin your recycling machine. So off to landfill it goes. Trillion dollars. Between plastic e waste that probably doesn't even include like textiles, building materials, it's probably a lot more than a trillion dollars. What if there was some magical way to look down on a conveyor belt as stuff was rushing by at 15 miles an hour and be able to know every molecule that was in every one of the things zooming down the conveyor belt and be able to route it in just the right ways so you could get that embodied value back. Number one, like someone's going to make a trillion dollars. But two, you could get humanity back to being a lot more circular in our use of resources instead of like constantly burning dinosaur juice and digging up the world to get at the stuff that goes into the everyday objects in our lives. And so we've built that. It's called Matera. It's still somewhat early days, but it is very much working. We're really excited about it. I managed to get through that whole thing, by the way, without saying artificial intelligence, obviously the way our system works, this thing that is looking down includes tools and techniques from machine learning. But it's so tiring when people are like wooga, wooga, wooga, AI. AI is not Benefit. Like the benefit in this case is, you know, what's in the thing. So you can recycle the thing. Let me tell you another story like that. Right now humanity makes six or seven trillion dollars a year in vats of various kinds. Most of it are chemical processes. Think of like Dow and dupont kind of stuff, oil refineries, those kinds of things. Humanity makes like 1% of that in fermenters. So I don't know, on the order of a few hundred billion dollars a year. And it could be so much more. Right now it's mostly there's alcohol, there's cheese, there's yogurt, there's some medicines, there's some cosmetics, but it's so expensive, especially if you're trying to get yeast or E. Coli or algae. These tiny little self replicating carbon negative machines that evolution has made for us that we can go ask them to make other things for us. In principle they can make jet fuel for us. They could make things that are like building materials. There's not really an obvious limit to what we could ask biology to make for us. And we can now reprogram biology. This is not X. Like the world has figured this out over the last two decades. So this is CRISPR finding a place on the DNA and then Cas9 being able to sort of snip into it and make a change on the DNA. But then what happens? You have a new yeast or bacteria or algae. You hope that your reprogramming of its DNA is going to cause it to burp out something else you want instead of alcohol, maybe a medicine, let's say. Are you right? Who knows? Like step two is put it in a petri dish and wait. That is so slow that the entire field of strain engineering and trying to make these things better so that humanity can move to biology being the main way that we manufacture the raw materials, at least in our lives, is completely bottlenecked around this issue of wait and see what happens. So X has spent the last eight and a half years building a simulator for small cell biology and how it acts in its medium. How much food is there? What's the ph, what's the pressure, what's the temperature? And then when you reprogram it, what is it actually going to do? How will it self replicate? How much of the stuff you actually want will it burp out? And so we're now this is working well enough, it's called Alife that we're now offering this to manufacturers around the world who make whether it's MSG or human milk sugar for baby formula, cosmetics material, and saying, you give us your current yeast or E. Coli or whatever and we'll tell you a reprogramming that's wildly better and all we want. You don't have to pay us almost anything up front, just give us 30% of the upside. Like, well, that's a pretty good deal because if you don't succeed, cool. And then we're routinely making these things two to ten times more efficient, which is then opening up whole new fields for them when those prices are coming down in those ways again. I got through that whole thing without saying artificial intelligence. But obviously this process is like a tight loop between wet labs for biology and artificial intelligence. So I've used these as examples. I hope your listeners can take away from this that the world feels topsy turvy right now. But wouldn't that be incredible if some of the very things that are making the world feel topsy turvy right now could also bring us these sort of supercharging elements that make our lives radically better?
- [47:26]
B
Yes, absolutely yes to that, Astro. But let me ask you two questions that I think are kind of like. I think that it will be great to kind of make sure that we touch them before we go. One question is, if somebody right now is listening, maybe they lost their job, maybe they're trying to contemplate another job or another business, or they're a little lost. They're scared of the future. They're trying to figure out what's next. What are some of the things that you think, first of all, I mean, the whole education, future work is changing really, you know, in a massive way. What do you think, what would be your tip to some of these people? Because again, they don't, they don't have the backup of like Google with millions, you know, on innovation, etc. But they do want to maybe create something big or they want to pursue a dream or test things out or start experimenting. What would you say to them? Ask.
- [48:20]
A
You know, I'd start with, it's important that we have compassion for everyone being on their own journey. And there are people who look like they've got it made, who actually have big challenges and people who look like they're really struggling or where we would really struggle in their circumstances, who actually are footloose and fancy free. So I just want to recognize like it's really easy to armchair quarterback somebody else's life. That said, I see most of the people who are even here at X and most of the other People I meet in the world are at 5 or 10% of their personal capacity. They're weighed down by mostly I think it's some version of fear. And that doesn't mean none of us have anything to fear. But letting fear control you and your choices is so destructive to our ability to get things that we want in our lives. Which is back to this issue I was describing of being able to manage your psychology to get into a neutral position from which you can be wise and make choices which might be complicated, might have some risk in them, but where you're not letting your fears sense of guilt, other things kind of like just grab your steering wheel and whip you around the the road. That's what I see most people spending most of their lives doing. And what I just described, like open heart surgery is easier to do than actually building a deep understanding of yourself and being able to manage your own psychology in a really great way. So I'm not saying it's easy, but that's the work that anyone who I'm coaching it is all about that because once you can manage your own psychology, everything else is kind of easy by comparison. And until you do, it doesn't matter whether you've got Alphabet's backing or not. It's pretty easy to screw things up.
- [50:20]
B
That's so good. Do you think there's something in your past asro, that maybe some people don't know, that it built you to who you are today?
- [50:28]
A
Probably most of your listeners don't know anything about me.
- [50:31]
B
I do.
- [50:31]
A
I'll give you an example. You could go digging if you want more, but I grew up in a family that was particularly focused on intellectual prowess. My father's father was Edward Teller, the father of the hydrogen bomb, helped build the Manhattan Project, started this sort of nuclear sub process for the United States with Admiral Rickover, and actually started the Star Wars Initiative, the space based defense system. And my mother's father won a Nobel Prize in Economics in 1983.
- [51:08]
B
So oh my God, that's a scary family to be in.
- [51:11]
A
When I was a kid that was the yardstick, was like how smart you were. And I love him dearly, but my brother's much smarter than me. And I had lost to my younger brother. I was probably seven and he was five by the time it was super clear I was the dumb one in the family. And that was really complicated for me. And you know, at the time it felt like an entirely bad thing. But I think I got really lucky in a funny way because I learned at a really young age that how smart you were wasn't actually, that wasn't how I was going to win, clearly. So from a very young age I got interested in what else I could do. You know, I remember being really attached to round seven or eight. Do you remember those Avis ads way back in the day? We try harder. There was, there was like a sense, I mean, it turns out effort is not a good way to try to win. So I'm not advocating that. But when I was a kid, there was a period where I thought, we try harder. That's like, I'm gonna be like Avis again. Don't do that. Work smarter, don't work harder. But I've learned a lot because I felt from an early age like I had to go figure out on my own new yardsticks to define my own self worth, figure out what I was really good at. And you know, I think sometimes we just take too much what society says, here's what you're good at as at face value. And I got to skip that part of the process. So I think that really helped me. Weirdly, huh.
- [52:48]
B
Do you know what built this level of confidence now that allows you to build like Google X to and these kind of innovations and continue to build yourself and know that, you know, I can do this. Like how. How did that become so strong then?
- [53:07]
A
I'm not completely sure, but let me give you another story to see if it helps. I was in college and I was still probably at the tail end of my we try harder phase. And a doctor sat down with me. I thought I was having an ulcer at the time. This was back when people thought ulcers were because of stress. They're not for people who still think that's true. And the doctor said, in retrospect, this is kind of irresponsible of him. But he said, you're going to die by the time you're 50 if you go on like this. Because I was just pushing myself too hard. And despite the fact that that was an irresponsible thing for him to say, I really hurt him. And I had a couple weeks where I thought really hard about it and I made a new deal with myself, which I think has stood me in really good stead ever since, which is I am not going to hold myself to the outcomes. I can't have the outcome that I'm holding myself to be set up where my grandfathers were. That's like, you know, a few hundred people in a century, like ring the bell like that. I can't hold myself to that standard. It was like literally driving me crazy. So I but I have to hold myself to some standard. So I said I'm going to hold myself not to the outcome standard but to the process standard. If I am a ferocious learner, that's what I'm going to be proud of. If at the end of every day I have been open to feedback, not just to hearing the feedback but to like taking it and try to get better at anything. If I stay really curious, I'm going to trust that I will, you know, there'll be luck involved. The outcomes will be what they are. I bet they're actually going to be pretty good. I just don't care about the outcomes anymore. I only care about whether I personally am a showed up today as a ferocious learner, as a really open, generous, kind hearted human who is like in receive mode and improve mode. If I do that, I win. That's just my new definition of winning. And I think there's, I don't know, I got lucky, but I think there's a lot of truth in living your life that way because I have complete control over whether I don't always do it perfectly, but at least I have control over it. I don't have anyone to blame but myself when I don't show up. That way there's no luck involved in that. I think that's really helped me to be confident and happy.
- [55:32]
B
That's incredible. I don't know if you notice how equivalent this is to the process of innovation that you're building. Right? Because it's like, it's actually pretty incredible to hear this because it's like, you know, it's those imperfect steps. I'm going to take them. I going to look only at like the formula and sure enough, at the end of the day, ta da. You're like, you know, running the whole moonshot CEO of Google X. I mean that's incredible to hear. Astro. This is such a fun story. Thank you for sharing. This is so cool.
- [56:06]
A
Yeah, I think it's worth saying both for people who are running something but also for people who are part of an organization. I appreciate the kind shout out and I obviously do my part here but this is not a top down organization. I am a supporter and a nurturer of the awesome people who work here. Like they have to do as you were talking about earlier, they have to do the hard yards at least as much as I do. And so I often end up the one on the podcast who talks about it. But this is not like the Astro show. And everyone's just implementing my vision. And I feel pretty strongly that that's actually the right way to do innovation. So I'm not rejecting your compliment, but I just. I think it's important that your listeners appreciate it's actually about all of them, which actually, again, is why we did the podcast. The podcast is not me saying, let me, you know, Astro splain to you how X works. It's actually me as the host asking questions and trying to pull out of these awesome human beings who've gone through the moonshot factory. What was your journey like? What were the hard parts? Where did the breakthroughs come from? Now that you're on the other side and you're winning, what does it feel like? Or if you killed your project, like, how did that feel like? What happened to you afterwards? I think those people and their journeys are actually more important than what the leader is doing.
- [57:32]
B
This is powerful, and I'll. I'll just kind of end with it because. Yes, I mean, we're listening both to the podcast and the master class. They're very, very different. And in Leap Academy, we always say it's not about what you make, but it's what you make possible. And I think it's really fascinating to see what you, Astro as a human, but also as Google X, what you guys are making possible in the world. So it's just really fascinating. Thank you for sharing this, Astro. This was fascinating. I can probably talk to you for hours.
- [57:59]
A
It was my pleasure that the time went super fast, and I really enjoyed it.
- [58:04]
B
Thank you so much.