Travis Kalanick Is Back | Building the Future of Industrial AI

26:51If it does, you do to the kitchen what Uber did to the car. And you go, okay, that's kind of a big deal. But then you say, what do you need to do to get there? Okay, well, you need to do e-commerce for online food delivery, which means I need warehouses like Amazon style, except they're not just for logistics. It's not just picking, packing, sorting, and then putting in a car. You also have to have manufacturing there too. Manufacturing, also known as a restaurant. People don't think of that, but you go to the labor statistics, Bureau of Labor Statistics, restaurants are manufacturers, okay? So you have to have manufacturing and logistics infrastructure in the same place.

27:33That's real estate. Then you actually have to have automated production. That's the manufacturing. So robotic, food robots, essentially, food robotics. And then you need to have robotic hurriers. and you do those three things and then all of a sudden you are getting super high quality meals, everything you could ever imagine. We call it the internet food court. And it gets to you at the price of going to the grocery store. So you go, okay, nice. That's a nice story. Then you go, well, in 20 years, will robotics, I start with a really easy question. In 20 years, will people be cooking food regularly?

28:20And there will be a suite of robotics that basically will make higher quality meals.

28:30Like, it will be doing a better job than any of us could do. And I think most people, especially those in the robotics space, will be like, of course. It's obvious that that's going to happen. And you're like, in 20 years, are we going to have, I call them autonomous burritos, like boxes on wheels that hold food at temperature that come to your house? Yes. Everybody will say, yes, absolutely. We see Waymo's cruising around already. We just need a much cheaper version of that. So 20 years is like the easy one. Then you go, well, what about 10? What about seven? What about five? And so that's when you're bending reality.

29:07You're bending it towards now. so everybody would agree that this is going to happen and now it's about when and who and then you say lfg now sometimes you're a little bit early and i would say on the we were a bit early on cloud kitchens but but you build those bricks all those things i talked about we have hundreds of facilities in 30 countries many hundreds of facilities in 30 countries Restaurants, because the online delivery market keeps growing, the restaurants are doing better and better. So success is happening, right? Well, restaurant world has high churn. Your churn starts coming down because volume's going up.

29:53We have applications that guarantee volume into these restaurants so that we can have successful tenants, which means I'm a successful real estate guy from a business model perspective. The robotics start to work. you know we're getting a manufacturing line for our robots up this in Q4 so like the pieces start to come together you're like production is now 50 % cheaper once we get the couriers the robotic couriers you go from$12 a drop for each meal to 50 cents a dollar of distribution cost per meal and now you're taking now you're taking okay$6 out in labor you're taking, let's call it$10 or$11 out on the courier, on the real estate because you're going to get higher volume because you're driving the prices down.

30:46You probably save a few bucks, let's call it two or three bucks on occupancy per meal. And all of a sudden you've got like a eight or$10 meal that's delivered to you all in. Plus you don't have to recruit drivers, and get shoplifted. That's true. That's right. You can't shoplift a robotic courier. Yeah. Yes. We need to stop using this term. It's so wrong.

31:15Erik Torenberg:100 facilities in 30 countries, thousands of employees, over an eight-year period, and you're in stealth. Yeah, dude. Yeah, that's just super hard mode. Yeah. And the thing is, look, coming out of 17, things were, it was 150 articles a day of negative, negativity. And so I wanted to be able to build without bringing that negativity into the system. And I wanted the team to be able to build without worrying about what the New York Times was writing tomorrow. Yeah. Simple as that. And it was the right thing to do. Now we had to do hard mode is we had to recruit cold. And it was always from a recruiter who has a stealth thing in LinkedIn and on their signature.

32:04And you had to go get customers with like stealth in LinkedIn. Like, and you're thousands of people big. This is hard mode. And it was interesting. We didn't know how long it was going to go. And you have to trust that no one's going to leak. you know what happens is here's the cool part about stealth if you go that long and I don't recommend this for anybody it's a very special case you don't really but eventually there's this break in your narrative like there was a story arc and it was going going going and then it's discontinuous it stops and there's this whoops sorry about that guys there's this long period of time now where nothing is filling in.

32:52And what happens then is the media doesn't want to cover a story because it's so hard to discuss a thing that has a gap a few years before it. So it's too hard to do the story and it's too hard to cover it. So you get to this place where it becomes self-fulfilling, where it's easier to be stealth over time because even if somebody tries to leak, nobody even knows what to do with it. They're just like, I don't even understand. And by the way, we did crazy stuff. So people know it as Cloud Kitchens in the US, but it's Casinos Equeltas in Latin America. And we have different names. That means like magical kitchens, essentially.

33:37We have like Kitchen Valley in Korea. We have Flash Kitchen and three other names in China. We have, I mean, Food Stars in London. like go it goes you know yeah you know i think it's uh kitchen park in middle east we were going to go with yalla kitchens like you know it's like a bunch of things like this so it was very hard to connect the dots yeah you're extra still yeah anyways and so at some point an even bigger vision

34:06Erik Torenberg:for this company emerges to digitize the physical world where you know we're category creating the you're creating a category the term industrial ai yeah talk about when this bigger vision starts to culminate. So look, the vision for digitizing the physical world for me started at Uber. Okay. And treating atoms like bits started at Uber. You were, it was sci-fi at one point, I promise. You would touch glass and a car would come to you. Yeah. And you had satellite view, you're watching this car come to you. That was crazy. Now it's just like, whatever. Okay. But But it was crazy at the time. Everybody's first Uber experience was a magical moment.

34:47So digitizing the physical world was the thing. And this idea of what I would call an atoms-based computer was something I sort of was working on in terms of her framework at the end of Uber, which is CPU manipulates bits, storage stores bits, network moves bits from point A to point B. Okay, well, CPU manipulates bits, what manipulates atoms? that's manufacturing. Storage stores bits what stores atoms that's real estate. Network moves bits from point A to point B what moves atoms well that's transport logistics and those now are your three core computing resources in an atoms-based computer and you know what everything you learn in your computer science curriculum everything you learn in engineering it plays in Adam's world.

35:36Same frameworks. All the data structures. All the algorithms. It works exactly the same. And I can... Grabbing algorithms. Oh, totally. Totally. In fact, we use TCP... OSPF. We use TCP sawtooth to basically manage how much demand to send to certain kitchens based on capacity and reliability, as an example. But like we look at when I go and I'm messing around, like when I'm pitching this to a tech person who wants to understand, that 10 ,000 square foot facility, I call a 10 ,000 square foot semiconductor. And it's a 30 core processor, 30 kitchens. They're computing atoms, not bits. The corridors where the food moves, that's a network bus.

36:23The processing center is like an L1 cache or something similar. You've taken this analogy very far. The cold storage where you have ice cream and juice, okay? That's pre-computed items that sit on the edge. Those are your Akamai servers. The courier who comes and picks up the food and goes on the road and brings the meal to you, that's a TCP packet. This shit goes forever. That's excellent. Okay, so the vision started at Uber. So the point is that atoms-based computation is a thing. And honestly, it's always been a thing. and the idea that, oh, okay, Uber was network for the physical world, digitized transportation, and by the way, almost done.

37:10Why almost done? Because it's almost fully software, right? Waymos are cruising. It's almost fully software. But what about CPU for the physical world and storage for the physical world? basically digitize manufacturing and digitize real estate. There's just so much to do there. It's crazy. And so there's a huge amount of innovation there, not just with what Adams is doing, but like there's going to be lots of stuff even beyond what we're doing. It's a portfolio strategy, really, if you're investing. It's very interesting because you kind of got to the conclusion that we've now all learned from AI, which is you can model just about anything with computation.

37:55And you basically were ahead of that in modeling this physical world, even metaphorically with computation, and now kind of manifesting that. It's, you know, probably entirely with AI on top of your computation model. It's funny because the framework started near the end of my Uber time, really when we were getting deep. We were going into deep learning and heavy-duty ML. And I was, you know, we would go after some of the best AI. we had an AI lab that was probably one of the best in the world as well. And I was always pitching that the physical world is more interesting for this stuff than the digital one.

38:35And, you know, look, I'm selling my book. Like, that's what we do, right? But you have way many more variables, axes of stochastic distribution. Yeah, much harder problem. Which then means you're not going to solve it with an algorithm. You're going to solve it by empirically understanding how it works. Yeah. Right. So let's fast forward to how the bigger vision for Adams comes together

39:08Erik Torenberg:in terms of the combination of the companies. I keep stopping you. And then I want to get to the partnership because it also ties together. Yeah, it's all good. So, okay. you've got to have your manufacturing logistics hub that's the real estate you've got to have your automated production and you've got to have your autonomous burritos the minute about a year ago i started looking into autonomous burritos and i went to china and checked out all of the autonomy guys i was here in the u.s talking to a lot of the autonomy guys word got out they're like Travis is looking at autonomy again people started going what's going on yeah yeah and you know folks like you know folks like uber other partners across different categories were like we're interested like for one reason or another because it's like you could even be doing you but you could be like supply chain guy on food.

40:12You're also saying, I need to have, for business continuity and just like peace of mind, I need to have another alternative for how these freight, how these trucks, heavy transport, are gonna move. And I need an alternative, and I'd love to have a partner as an example, this kind of stuff. And so, okay. So partnered with a couple folks, actually created a new company to do it because funding autonomy through a sort of core food company, it just wasn't going to work at first. And the reason why is because it's like these are just different profiles. It's a real estate company. This is like heavy-duty software, big money going after it.

40:59It's like a computer company trying to build a network company off of the side. You got to buy a networking company. So we just got, and these partners wanted a pure play. And so we created that sort of near the end of last year. But what happened is it's like you got to get, okay, well, now I need to get my team together. I need to get my guys from way back when, 2016, when we were, 2017, when we were running hardcore at autonomy. We need to get that going because if you're going to be in the specialized robotics game, you have to have autonomy for yourself. You have to. Your robots are moving and acting in the physical world and you cannot depend on only one company that has an existence proof now.

41:47Of course, Tesla is going to get there, you know, sometime soon or maybe some amount of time. We don't know exactly. You got to, you can't be dependent in that way. And so, okay, get your team together. Eric Meioffer, who ran ATG, is already running my food robotics division. That's Uber's advanced technology group, is working for us. And then Anthony Lewandowski, who is one of my top leads on autonomy back at Uber, was running Pronto, which was an autonomous mining company. Let's call it off-road autonomy. me, but in a workflow or category where it's like much more than just like this thing needs to move.

42:31It's like, how does it move? What is the context for which it's moving? It's like a very specialized thing. I was the biggest investor in Pronto. I'm like, let's go. So, uh, acquired Pronto and now I'm in the mining business, but it's not like I didn't know about it. I was the biggest investor in it to begin with for a good reason. It's one of the most beautiful and interesting autonomy categories or use cases. And on our mining business, our mission statement is more productive minds to power Earth's industries. We can go to a gold mine CEO right now and say, would you like to get 20 % more gold per year?

43:16We don't get no. Right? Now he says, prove it. He says, prove it. And we're like, let's go. But that's what's happened is so separately, Pronto is working on mining for eight years on their own. Seven, eight years on their own. Go ahead. Also a great target for autonomy because, you know, maybe the worst job for humans there is. It's the mining jobs, right? And we have, so our mining customers, because we're operating in a bunch of mines around the world, our mining customers have existential safety problems. Or let's call it safety issues, safety concerns. Yeah. Like where bad things can happen on any given day.

44:01And you've got real people that are putting their lives on the line when they're at these mines. and so when you automate certain parts of mining, you dramatically improve safety. And you, I mean, in a real way. That's like when you look at the work that's being done and how it's being done, it's a little bit heart-wrenching when you are exposed to it and you see how mines work. It's not the mind's fault. It's just the nature of the work. and um there's a massive safety upside that goes along with the productivity upside which is really special um yeah so so what happened is is that pronto just now is coming past human productivity so it's like you do it's like any enterprise software company yeah you do some cool pilots with big companies you got stuff you're like dude i've got like corner case i've got like eight seats at this 10 ,000 person company.

45:01And you're like, okay, maybe. And then all of a sudden, it's better. And in the autonomy world, it's about it's better than human productivity. That means your mines and the quarries. And it's like, exactly. Go time. That's when you hit the gas. So we're going to see super exponential. We're seeing it. We're in the middle of it right now. Super exponential growth on the mining side, which is super special. These guys ran a very lean startup for a long time. And now I'm going to their customers who are begging us to move faster and get more out there. We have to manufacture kits. Sorry, we have to do supply chain and manufacture kits.

45:41We have to install these kits on these machines that are in the middle of the Amazon or on the border of Saudi and Iraq or like in these crazy wild places and do it fast. And then do the change management at every one of these mines. So they're like, it's time to go, let's go. And they're pushing us. And so how we talk to them is like, look, we were a lean startup and we're going to muscular. And that's how I talk to the team too, because you don't want it to get fat. It's like lean muscle. But we need some protein shakes and creatine and things like that. And it's about process, professionalizing a lot of this stuff, but it's in some ways the growth there is almost deterministic as long as you do the professional things to like get all that stuff in mind.

46:33But what it means is that existing minds are going to be producing more and they're going to be able to go much further in getting more and new minds are going to emerge that were not viable before. And what that means for AI, what that means for progress here and everywhere

46:54Erik Torenberg:super big deal yeah yeah and so to to continue i'll get to the partnership conversation at what point does this become sort of are you thinking from the beginning this is a conglomerate or at what point does this become all wrapped up in the in the atoms well so this i mean the the fundraise was part of it so what happened is is we started the fundraise and you know ben remembers this because I gave him a preview at first in Vegas, actually. And I'm like, I was like the guy with a trench coat that's got like 20 watches. I'm like, which watch do you want? I got all kinds of watches. And he's like, I just want the whole freaking trench coat.

47:33You know, the idea being, I don't want to invest in mining or transport or food. I want the things that you're doing and let's be partners for all the things you do and so that's that was the impetus for um bringing the companies together creation and the funding itself yeah the creation of atoms and the funding itself uh being at what we would call top co level yeah right and so now it's just one entity i mean there's sub entities there all over the place but But it's one equity structure, which is great for the employees and great for me because managing – honestly, I don't know how Elon does it or did it slash does it.

48:24It's pretty wild. And I'm really glad I don't have that headache, to be honest. Yeah, yeah. It's very complicated alignment. but you know it's kind of an interesting point because it's very obvious when we talked about it here the way it should work and I think the narrative of how these things get built is mistold constantly by the industry, by the press which is, you know, if you hear about how did Facebook come about how did Google come about how did Tesla come Oh, they had this idea, and the idea was to do this. But that's not really what happened. A lot of motherfuckers had that idea. You know, there's a lot of those ideas out there.

49:13And, like, if you look at Tesla, there was a very famous documentary called Who Killed the Electric Car that came out before Tesla. And if you were an entrepreneur watching that, what you would see is big oil, big auto, big government. We're never going to let that happen. They would kill you. But then the reality is, oh, Elon Musk, that motherfucker's hard to kill, right? Like, so he by himself kind of decarbonized American auto industry, which is, you know, really unbelievable in retrospect. But then it gets told, right, like if you listen to the politicians now, they're like, oh, he didn't build Tesla.

49:53He just like struck a gold mine and is just pulling the gold out. Like all those people built it. But why didn't all those people build another Tesla? Like there's only one because there's only one non-fungible, very rare person in that equation who could do that. And that's why there's only one SpaceX. And that's why, you know, that's why meta is meta and friendster is friendster and all that kind of thing. That's a good one. I haven't heard that one for a long time. Yeah. It's good. And so to build, you know, to build a company, you know, a great company, it's always a great entrepreneur. And so when we looked at it, we're like, there's a very few entrepreneurs, you know, in the history of the Valley that built something like Uber.

50:43And that Uber, basically, it survived and is still a very valuable company without them, which almost, you know, like that never happens without the founder. I mean, it usually turns to crap very fast. And so that was what we, like, yes, the idea is great. The ambition is amazing. it's going to be amazing for the world if he pulls it off but like we want to invest in the guy who could pull it off and that's kind of what drove the whole thing and there's a fun thing I realized this at Uber too is that I think maybe Bezos was the guy to sort of really go there which is the only constraint to your imagination is management capacity because like look at all the things that Amazon started doing.

51:32They were earlier than everybody else starting to do lots of things, right? And so I'm like – By the way, another good one. How many motherfuckers had the idea for an online bookstore or online retail or online any of that? There we go. And how many Amazons? Yeah, totally. You know, and by the way, Jeff, like everybody who knows Jeff, everybody who's heard him talk, you're like, oh, he's very special. That's a special CEO right there. and that's our business is to invest in that kind of very very special individual and they're super rare and so I think in many ways Bezos may have been I always want to say the OG on something but then you find out a hundred years earlier somebody else did that but of our time where it's like how did AWS happen?

52:23It literally had nothing to do with a bookstore really Nothing. I mean, there's some fun stories they tell, but it's like, this is just a whole new thing. Yeah, by the way, it wasn't like the shit that was running Amazon. Yeah, no, totally. That's my point. Yeah, yeah. So once you get the foothold, the beachhead, whatever, and it's working, you can start going, you go Uber rides, then it's Uber Eats. Then it's Uber autonomy. Then it was Uber freight. then it's like Uber AI Labs. Like you can start letting your imagination with constraints start to do really interesting things. And so where you start matters.

53:09Yeah. You're right. And it has to be like you need knowledge. Yeah. Right. Like the thing that Amazon did have on AWS is they had knowledge of what it meant to run these things at scale because they were the first to get there or one of the first, like, five to get to that kind of scale. And so they had that knowledge. Totally different business, totally different, but they had the knowledge about what the product should be. And because he's a customer of these things, right, at Uber, he all of a sudden, he knows what the network is. He knows how to do that. And although it's a totally different business, that knowledge is transferable if you can scale and execute and expand management.

53:48And sometimes you go to, sometimes those, look, Like, adjacent categories are way easier than whole new off-the-rails categories. Yes. And there's also, I mean, the amazing thing about AWS is it's one of the few expansions where, like, nobody would think, well, what I want to buy from Amazon is like a compute cloud. Like, nobody was thinking that at the time. Yeah, no. You know, like, there's always, oh, I should sell them more stuff they want to buy from me. But that's a whole other thing. but you know if you're if you have that level of jeff skill which like in terms of organizational design cultural continuity that guy is pique bezos hard to beat very good yeah so where you start matters don't let him living his best life yeah he gets a lot of bad pr well i was wondering

54:45Erik Torenberg:you javis you could have had a version of living your best life where you're just like hey this is would I do, you know, or was it like, I'm gonna keep doing it forever? Or was it like, hey, I chased the promised land. I got really far, but I could have got so much further. I'm going to get there next. What was the sort of motivation to just get right back in the, it's just, I love being in the arena fighting it. And it's not, you know. By the way, he's one of the very rare, rare guys who made as much money as he did and wanted to keep playing. I mean. And start over, basically. Not totally, but almost completely, right?

55:21So, the, yeah, you got to really want, because also remember, I did it stealth. Yeah. So, what it means, here's the thing about stealth is that. Stealth and starting at the bottom, right? Nothing. Doing it by hand, right? Like, not. Like, I walked in, I acquired this company. I'm the executive chairman. I acquired Cloud Kitchens. It partnered with a buddy of mine, Diego, right? and there were like six people in the company that i acquired okay so it's so funny because you gotta think the last all hands i did had 20 000 people yeah the next all hands i did and this is the only company i was in had six and i stood in front just like the same and i'm like let's go guys let's do this charts you know like here what's happening you know let's roll let's do it.

56:11And these guys who, like, I just walked in, they're like, what the fuck just happened? They went to work that morning at a six-person startup. And an hour later, the founder of Uber is now the CEO. Yeah. Yeah. That is wild. And by the way, like, we've seen it so many times where somebody gets to the penthouse and they're like, oh, I want to do a new thing. But they don't want to go all the way down to the ground floor. and start at the bottom fucking putting the building together. Okay, now you're in a fucking shotgun house. They want to jump all the way to the – which never works. You can't start at the top.

56:52And the bottom thing also is about there's a humility thing to it. Yeah. And there's like – there's an anti-fame thing to it. And what I mean by that is imagine – you start from the bottom. You also do it stealth. It means you plus everybody in your company gets fulfillment from the work they do every day, not because they're going to get famous, but because they enjoy the people they're working with and what they're doing day in, day out. By the way, if you can pull it off, that's a very significant cultural advantage because… And as soon as the company feels like it's doing something for the outside status, it's a dangerous.

57:37Yeah. It's a volatile fucking situation. That's right. You start making decisions based on external validation versus internal correctness. Yeah. You lose true north. Yeah. And that's part of the upside of stealth and part of what I was doing. Because remember, I wanted to build without worrying about what the New York Times was saying. So it starts with internal correctness versus external validation.

58:04Once a company starts doing that, it's hard to – like you already see this with the big labs. People keep going, oh, why did the big labs smack themselves in the face? Well, it's because they need that external validation for their employees because their employees are addicted to it. I want to be a good guy. I want to be a good AI researcher, so go ahead and tell them that we're going to take all the jobs. It's like, really? You want to say that? You don't even know if it's true, but you want to say that. Well, why are you doing that? Well, it's that external validation is so important to them.

58:37And it's so important not just to the people running it, but to all the people in the company. And so they almost have to do it. even though they if you want it if that's what you think then work on like those problems work on like oh you don't want it to reward hack well why don't you try and solve that as opposed to go running your mouth because you care about the external validation more than the actual thing and that's the yeah it's very easy to slip into that like many companies slip into that and it's and here's the same once it gets out of the bag it's very hard to put that. There's a human nature aspect to being proud of what you do, wanting your mom to be proud of what you do and your community at large.

59:22Yeah. So there is a human nature piece, which I was malnourishing by being stealth. Yeah. But it forced a emotional intelligence that's very powerful now that we're moving out of stealth. Yeah. And it will be interesting to see how the coming years go. Yeah, that's a... Going to be a very interesting cultural case study, see what the company is like over time.

59:47Erik Torenberg:Yeah. Yeah. Yeah. So we've talked about, you know, what books were to Amazon, you know, food is to Adams in the sense of it. It's where you start and where you start matters. So why was it important that you started at food in terms of what's generalizable? What's like, yeah, same word. So here's the thing, right? So what Cloud Kitchens was, was all about the way I saw it. And this is what I brought to the party, but it was like, this is digitized manufacturing and digitized real estate. It was called, I called it when I came, people know it as cloud kitchens because that's what we'd sell restaurant customers on.

1:00:22But the name of the company was City Storage Systems. Ah, okay, storage for the physical world. This is digitized real estate. Yeah. This is a food computer with a basis in real estate. Storage. Okay. That needs a network. Yeah. So this was the name of the company from the beginning. or once I came in, okay? It was purposely boring because I was going stealth. You imagine selling something called city storage systems? Like people are like, what is that? They'll forget literally 20 minutes after you talk to them. They're like, city, CSS. They're like thinking HTML. They're like, they're confused.

1:01:01They don't know what's going on. So for me, the framework was already there. I already thought about this as digitized manufacturing in real estate about an atoms-based computer, about a food computer. And that's why I was excited. The idea captured me because of that. And so it wasn't like, why'd you start with food? It was like, I saw something different than even maybe the original team that was working on it saw it, but I saw where it was going and in the way that I just described. And that's what the romance was about. And yes, there are lots of digitized manufacturing problems out there.

1:01:50Yeah. Like mining. Like mining, like a whole bunch of other things. But this is just captured me at the right time. You know, I was sitting at the bar and somebody came up and we had a great conversation, you know, went to Cabo the next weekend and then just put a ring on it. Like, let's go. It's serendipity, man. Yeah. It's a real thing. So, and that's okay because the thing is, if you believe that you can, like, find something, make it work, just grind it out, make it work, will it into working, your imagination can keep going. So for me, it's not as much about where you start. It's about making sure you're passionate about where you start.

1:02:36And then where you go, you have no idea. And this is very much, I go back to the Bezos style, which is like your imagination will just keep coming up with new cool ideas. And so it's not about where you start. It's about why you start and how you build a culture that allows you to keep going into new places over time and lets your imagination, when it's right, flourish. Yeah. That's what I was. It's not an idea. It's an idea maze. And the more you learn about the idea and all the things, and you don't know any, like the thing that is so hard to understand coming from the outside is you know so little when you start.

1:03:16Like when he's, I mean, he didn't even tell me. He started, he didn't know fucking 1 % of the fucking problems he was going to run into with Cloud Kitchens. Yeah, for sure. Because you've got to really get into it. By the way, what tech guy knows anything about real estate? Yeah. 0.0. Yeah, so it's all, the whole thing is a learning process. And then it's the best entrepreneurs can take those learnings and then multiply the applications. And that's, you know, it's just a very, very rare thing. Like, look, the fact that Elon has taken SpaceX to Starlink to data centers in space, it's just like nobody would start there.

1:04:01Or think about this. Yeah. The first roadster Yeah. is now Optimus. Yeah. Okay? Yes. Talk about Yes. Yes. letting the imagination flourish is a beautiful thing. Yeah, understanding what the core, core principles are. Yeah. And applying them.

1:04:21Erik Torenberg:So, with that said, paint us more, paint us a picture about the future of Adams or more about the, or maybe you say some of the guiding principles that will dictate which industries you enter next or how you think about where you go. Yeah, look, I tell people I'm very focused right now because it's only food, mining, and transport. There's so many things I haven't done yet. I'm so constrained right now. But it goes back to that thing I was saying before is you've got to find that beachhead, make it flourish build management capacity to solve 98 % of the problems that are going on and then you have the room to go do a new thing and really what it is you know I've been accused of using the marathon analogy too much and I'm going to live up to that which is you know at some point you might be doing a business and it just starts working i i started seeing that on rides at uber where it was like

1:05:29i had my leads in different geos and i'd call them up because we would jam on hard ideas and crank and all this we didn't have much to talk about yeah because it was it just worked yeah you know and they're like travis we got this i don't know why you're calling me right now you know so actually this brings up one of the things that he did best at uber um having had to deal with these guys was, like, if you look at most companies, most of the, really the big tech companies that emerged in the 2000s and 2010s, the management team were kind of professional middle managers, et cetera. He had so many guys who you would have gone, no, that's a founder.

1:06:15You know, that's a founder over there. That's a founder over there. That's an actual entrepreneur. And it's amazing that he's not building his own company because he's, like, working for Travis. But that enabled them, like, to get to a multitude of ideas, you need, like, a team like that. And there's just not that many people who can build that kind of – it's just a very hard to attract and maintain that level of capability. Because those guys, unless you're building something absolutely spectacular, they're not going to be in. And even if you are, you're dealing with – you've got to be able to manage that.

1:06:54Well, what happens is the management of it becomes an empowerment puzzle. Yeah. Yeah. So – Yes. Okay. By the way, not unlike here. I know. So you've got – I've got – I'm running Uber, let's say. I have, I don't know, five continents going at any given time. You have an engineering team that's multiplexed across, a finance team that's multiplexed across, a product like there's a lot going on. And the only way it works is, okay, you have that entrepreneur there, but they have to, basically empowerment starts with alignment, which is, okay, what's the strategy? Are we aligned on it? that's the challenge, right?

1:07:42Empowerment plus alignment. So, alignment on the front end, accountability on the back end. Yeah. And we would call this let builders build. Yeah. And so, but you... By the way, there's also, so you've got alignment, but alignment is multidimensional because it's alignment on, okay, what are the goals? What are the objectives? Also, what is the culture? Like, what is the behavior you guys are doing over there? because that's going to affect us over here and us over there and so forth. So, like, we can't dilute the culture because we gave you autonomy. We've got to have that. And that combination is, it's like a very high level of management skill.

1:08:25And that leader has to be good enough to do it. Yeah. And that leader then has to work with the CFO and the CFO's people, the product, the head of product, and the product guy's people, engineering and engineering people to make sure that it works because if i'm a single point of failure it ain't scaling on 24 time zones yeah there's no freaking way and i think that's the difference between what we did at uber versus we're seeing how a lot of other companies are expanding internationally they're buying things like i was like well i buy we can just freaking do this well city's a city let's go and then if you buy it guess what you brought another culture Yeah.

1:09:06Okay, and now you got another reputation. And then that reputation is going to seat back. And then, okay, now you don't have a culture. Because how are those motherfuckers getting away with that in Korea when we can't get away with that in the U.S.? Like all those things start to affect. And by the way, your product, your technology is a reflection of your culture. So then what happens is you just have the cultures reflected in the technology and in how even that technology is built, the product decisions that are made. And now you've got to fuse these products and technologies together, which is very hard.

1:09:38Two years later, maybe. Yeah, exactly. That's why I didn't buy Lyft. By the way, that was a very different culture. Yeah. I can attest. This was the reason I couldn't do it. Yeah. Yeah. Yeah, super interesting.

1:09:57Erik Torenberg:And so you're constrained now by three different industries. What is the key? Take him off script. What is the criteria that's going to determine if and when you go into another? Yeah, it's the beachhead thing. And it's the, I'll go back to the marathon analogy, is that if it's getting easy, you must make it hard again. But you've got to get it too easy. You've got to start, and it's a vibe. It's like a feeling where basically I'm constantly creating problems. I'm a problem creator. A problem creator might be like creating a problem might be like, hey, let's do Uber in China. That's creating a real freaking problem.

1:10:47And by the way, you don't have a full understanding of that problem when you create it. And why is that hard? because, well, if you create a problem, you have to solve it. So I have this like framework I call the meta problem, which is the derivative of your problem creation, dt, must be less than or equal to the derivative of your problem solving, dt. And if it's not, you have a real fucking problem. Yeah, well then... You're underwater. Yeah, then you're underwater. And then you can drown. And if you have multiples of those, you're really underwater. That's right. So when you create a problem, you're guessing at what your capacity is to solve problems.

1:11:35And you're guessing six months, 12, 18 months ahead with only a certain understanding of what the nature of the problem is. And when you get it really wrong, you're underwater. And then you must stop all problem creation so that you can get back above water. And then when you go from your neck and then you're like at your waist in terms of how underwater you are with your problem solving, when you're at your waist, you're like, oh, I could get to here. You create more problems. You let the problem creation spigot open. And by the way, when you talk about capacity, a lot of it in this case is he's talking about his personal capacity because he's got to be able, if he's creating a new large problem, he's got to be able to not pay attention in nearly the level of detail to the other parts of his business.

1:12:25Those have to be working. Because if he's solving problems over there and created a big new problem and that one gets in trouble, like then. And so it's not just like capacity of the team. It's also personal capacity. It's a little bit of both. It's a little bit of both. And so it's a real deep deal. I never felt like Rideshare was solved because what happened? Oh, it's time for autonomy. Yeah. Okay. All right. Let's go. By the way, you were right about that. Yeah. Yeah. Despite.

1:12:58Erik Torenberg:Yeah. I'm not going to even mention names. and so if you if you had still been running uber um you know in this other universe or some of the vision that you have here with atoms would that have been you know could you have gotten to mining with like it's a continuation the same vision yeah right so the digitizing the physical world the atoms-based computation that was already set yeah and so if the future of food is about

1:13:32infrastructure, automated production, automated logistics, that's the future of Uber Eats too. Now, it doesn't mean when you're an OEM and you make a food computer, it doesn't mean you have to make all the parts, right? Yeah. And so, but the future is the same. Yeah. And so, so that's my point, is that once you have that framework, why is the framework important? It's because it tells you what the future is gonna be. It's correct. And it's also compelling. Like it's interesting once you start seeing things. Like, by the way, I built with my team like 500 cloud kitchens facilities around the world.

1:14:23Like you could just look at it as like, why are you building kitchens? which of course I would, I sort of would go around all the time and tell people I'm just your local humble, I'm just your local humble kitchen builder, you know, just sort of messing around. But like when you're hiring, it's like, why does this matter? Yeah. Oh, that's right. It's a food computer. Yeah. But once, so it's a mix of, it's telling you where the future is going and it's pointing the way towards where the interesting things are and it's helping you describe this in a way to really top quality talent who now can see what you see and can get excited about it.

1:15:01Yeah. And there's another kind of interesting thing which we went through when we were understanding the business, which is unlike in a computer where you have storage and that storage kind of becomes obsolete over time, in the physical storage world, in real estate, If you have the computer optimizing the storage, the storage becomes more valuable. So you build the food computer, and the storage is essential to deliver the end service, particularly before there's OEMs and everybody knows there's a food computer available. But that food computer multiplies the value of the real estate. So it's weird.

1:15:42Imagine a computer that multiplied the value of its storage. I guess it's a little like in AI. Like if you've got data, all of a sudden data has become valuable in a way that it wasn't really before. Well, or you think of it this way. We could go to a data center. That's real estate, right? How many tops are now happening at a data center today versus 20 years ago? Yeah, exactly. And how much value is coming out of those tops? Right. So the value of a data center in terms of what it provides society is going up over time dramatically. A lot. And there's a lot of happy data center owners right now because of it.

1:16:24No doubt. Yeah. My friend Rob Roy. Yeah. So that's Rob.

1:16:28Erik Torenberg:Yeah. We'll get him on soon. So speaking of, you know, painting this vision to talent and just talking about where the future is going, talk more about the emerging category that Adam sits within, you're calling industrial AI. Yeah. So, look, I did a vision letter when we launched Atoms that outlined sort of vision for like physical AI where we sit in it. And even went into like what a physical AI stack is. and it's really in some ways it was like it was philosophy about where the technology world in the the tech industry in the physical world where it's gonna go but what I didn't do was get to the brass tacks and sort of when you look at okay well there's software there's bits that are affecting how atoms, what happens to atoms, like how they're assembled, where they go, what function do they do in the physical world.

1:17:41We basically, we started, I'm all over the place right now. Cut, edit. But we wanted to create an easy way to understand what it means. And I said, okay, Adam's mission, physical automation to transform industries. You're like, okay. Okay, kind of gets me there. But what does that mean exactly? Well, it means we take entire industries that are ripe for automation and AI, and in doing so, that these are physical industries, and in doing so, just completely transforms them. In a sense, you've had one idea. Like Uber and Atoms. Atoms is the evolution of Uber, in a sense, in that you kind of said, okay, we're the Cisco of the physical world.

1:18:39and then you're like, well, what about the other parts of the physical world? And you built that. You extended that vision into the computer and now you're adding the parts. But the computer is around an industry. Yes. So we make computers for industries. Yeah. Those computers are... Right, that's an important kind of distinction. They're industry-specific computers. But generalized networks in some sense. Yes. So you go, okay, why are we doing transport? Well, because you've got to have wheelbase for robots. Okay, cool. But like actually what it means is every industry is moving things. There's some movement of things eventually.

1:19:22And you must have wheelbase as part of what they do if you want to automate full stack that industry as an example. But transport itself is an industry too. Yeah. But maybe a horizontal one versus a vertical. Right. Yeah.

1:19:38Erik Torenberg:Peter Thiel a decade ago famously sort of talked about how we've had so much progress in bits, but not in atoms. And because regulation or for whatever reason, it was just easier in bits. And yeah, here we are. And we're finally, yeah, getting to it in a real way. Well, and it's like I think the entrepreneurs that are coming up since the Uber time are not scared of regulation the way the bits. Yeah, well, that was a breakthrough in a large sense that you made. Yeah. Yeah. And so what it means is— Well, and then they've been trying to regulate bits lately. Yeah, totally. But these go together. Yeah.

1:20:13Because it's like once the bits start controlling atoms in the physical world, then the regulators are in the game big time. Yeah. And because that's generally how regulation works, it's about our physical world, and that's how it's been for thousands of years, really. Certainly hundreds. And so, yeah, once you get in the physical world, you're like, okay, regulatory is a thing. and you say, okay, when in the past have we seen something like this? And it's like, if you start studying the second industrial revolution, there's so many parallels between what the Carnegies, the Rockefellers, the Fricks, like you just go through the list.

1:20:56Fords. The Fords, what those guys had to deal with in that massive rapid change at that moment. Same, very similar political climate. Yeah. Very similar. That's right. The New Dealers were not that different than the current, in terms of their complete hatred of the industrialists. That's right. Okay. So, like, there's a guy, Frick, who I think was Carnegie's partner. and this is about steel and how to process steel and do it at scale i i believe this story is accurate uh let's just say mythology possibly true but i believe it's true he a anarchist broke into his office while he was working this is in like their eight like early 1900s or late 1800s an anarchist yeah broke into his office shot him in the neck wow he got it stitched up went back to work that day and like somebody's gonna look it up i i believe it's true yeah but somebody should should fact check but you get the vibe of what's going on and how those guys rolled and think about some of the entrepreneurs today that roll that way Not all of them do.

1:22:19The Bits guys don't necessarily roll this way. Elon rolls. But the Adams guys roll this way. Definitely. Right? And so, the second industrial revolution, and you look at the characters and what they had to deal with and the adversity they had to go through. By the way, they're also, none of these guys is Jesus. So, they had their flaws too. Yeah, yeah. I bet they were amazing. But there's a really. And they built the country, yeah. There's a very interesting parallel to what's happening slash about to happen now with like the coming industrial age. If we're selling our own book, we would call it the Adam's Age.

1:22:57Yeah, there's a book actually that's very interesting on the kind of building of the war machine by the industrialists, which won us World War II, no question. And the resistance that they got, it's called Freedom's Forge. and you know it was Scott Bill Newton who was like the complete badass who figured out like the mass production at Ford and then got in an argument with Henry Ford and went to Chevy or went to GM and like built Chevy and like all that kind of thing and then went to work for the government for a dollar to industrialize the nation and the way he got fought by the press and everybody like on the most basic thing Like he's like, well, if we tell him to shut down making cars, and cars, by the way, employ 20 % of America at the time.

1:23:45If we tell him to shut down making cars to make tanks and other things, then we're going to have to give them some money. So like can we give them cost plus 7 %? And which, you know, like seem very reasonable like reading about it. They're going to profit on the war. da-da-da-da-da, like in Eleanor Roosevelt, like everybody was just out to kill this guy. And, you know, somehow, but that kind of resistance is like very similar to what we're seeing in data centers today and that kind of thing where I think the governor of New York just banned data centers in the state. There's a lot of parallels politically, which actually I would just call that resistance to change.

1:24:29Yeah. And nature. Very fast change. That's correct. so I you know I like you know I sort of think of it as like the most important truth-seeking is the seeking of valuable unknown truths but if you're good at finding valuable unknown truths you're creating change then you know things other people don't know which means you can do things that other people can't do and the better you are at it the faster the change comes and the matter and the faster the change comes the more nature will do what it does it's called resistance to change. Yes. And so, you have to figure out how to bring big-time progress to overwhelm resistance to change.

1:25:10And you also have to build trust as best as you can so that you have more advocates versus adversaries. And this is the dynamic. And one of the things I want to say, just on the industrial— Very hard to do, by the way. Very hard. Everybody loves progress. It's changed. They can't stand. Yeah, those two happen to go together. Dope. Yeah. So like, but on the industrial AI thing, it was like my whole vision note was physical AI and like this theoretical thing. It was very academic and theoretical. And I want to say, I want to get something that was practical brass tacks. Industrial AI is basically this stack of software, sensors, robotics, machinery that automates an industry.

1:25:55and we take it one industry at a time and it just became much more real and clear about what it is. You go physical AI, you're like, oh, so you're doing a humanoid. I'm like, no, no, no, we're like the non-humanoid guys. I don't have a problem with them, but that's not what we do. You're like, oh, do you do like some military thing? You're like, no, that's not my thing either. You know, it's like, so this felt very clean about what it is we're about and how we're going after it. By the way, you know, a really interesting point on this whole thing is one of the things that we completely forgot how to do.

1:26:23We were the best in the world by far. we taught the world how to do was manufacture. And now we've basically forgotten how to do it as a country other than like Elon. Like if you need somebody who knows how to manufacture, you literally have to get them from Elon. And we're going to have to relearn that. And actually the beginnings of that are literally data centers. That is a manufacturing problem to a large extent with the cooling and the power. And you've got to build your own power and all that kind of thing. and there's so much resistance to that from the exact people who were just harping and harping for years about all the manufacturing jobs are going away.

1:26:59Well, they're back, but we don't want them. And so like that's how tough this story is and this kind of narrative is. Thank God there's still enough places that are still welcoming data centers. Yeah. That it's not like, the federal system is a wonderful thing because it's like you have this competition of some kind. It's really interesting how that works out. Otherwise, we'd be Europe.

1:27:28Erik Torenberg:So, we were talking offline. You were saying when you started Uber, you worked with people who would choose to work with you. Now, you're in a different position. You have a bit more choice. You've been building in stealth. Now, this is your coming out story. Talk to us about what kind of team you're building here, how folks can help. Well, look, we just multiplied the number of industries we're going after by three. So that's a kind of a thing. And each of them is a multi-trillion dollar opportunity. And, you know, look, I had some awesome guys. Like, you know, this is kind of a funny thing to say, but when you make somebody hundreds of millions of dollars, it's hard to hire them again.

1:28:10I've never had great success hiring rich people. Yeah, so there you go. So, you know, but, you know, there's the crew. Like, Emil Michael's now undersecretary of defense, but he was my right hand on doing just epic deal-making and strategic moves. I need the next Emil Michael, if that makes sense. Like a head of CorpDev, BizDev that can build an inspired team, an inspiring team, as an example. we're we're we're in the market for a general counsel so we're looking for somebody who can ride shotgun and and and make sure that I'm you know so I like to go to the line we should be like a few inches off the line that's a good thing to do and then of course it's just the like I need I need a CEO of my mining business yeah like I I need to be build technical leadership across the board from autonomy, heavy duty robotics.

1:29:18And it's really like we have lots of folks coming in like all the time, but it's like those epic leaders that can inspire their team to just go above and beyond and do really like make magic. So we're all, no matter where you are as an entrepreneur, the talent game is the game. And again, when you multiply the industries by three, you're back in the flow. And because we were stealth for so long, we weren't in the flow. We were cold calling everybody. And I think it's one of the beautiful things about us being back out there is, okay, like we can now have like a place for people to understand who we are, what we're about.

1:30:03And I can start putting teams together that can be out there in a very public way and let people know the great work we're doing.

1:30:15Erik Torenberg:And if you're joining now, you're joining both with the benefit of having, you know, all the lessons you've learned and things you've proven out with Cloud Kitchens. And of course, Uber before that's almost two decades, but early enough such that there's the upside of, you know, enormous opportunity going forward. And the ability to do something like super meaningful. I mean, save kids from working in the mines, you know, basically making it so that everybody can have great food like, you know, instead of like eating. Super healthy food that gives people their time back. Yeah. While also saving money.

1:30:57Yeah. Yeah. Yeah, it's a hell of a mission. Yeah, so we're having a lot of fun. It's good times. It's a great place to wrap. All right, cool. Thank you. Awesome. Thanks, guys.

1:31:10Erik Torenberg:Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z and subscribe to our Substack at a16z.substack.com. Thanks again for listening, and I'll see you in the next episode. As a reminder, the content here is for informational purposes only, should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.

1:31:50Erik Torenberg:Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com forward slash disclosures.