The Exchanges

Q What was going on in Carnegie Mellon when you were there? What kind of robotics work?

A So what's interesting is that at that point, um, nobody could imagine how aggressively we would get pushed to commercialization. At that point it was, uh, you know, the Robotics Institute existed since I think the early nineties was the only university that really invested in that, that degree. It was a lot of work funded by NASA, by DARPA, um, Uh, caterpillar and deer were actually starting to fund a little bit of kind of more, uh, kind of industrial applications, but it was a lot of, like, applied research for autonomous driving, so navigating on-road, off-road, um, starting to develop the beginnings of perception systems, path planning systems, being able to ship this onto large-scale mobile robots, and actually try to drive intelligently, and a lot of the, um, people around that time ended up being the seeds, uh, that then propagated to all the, Grand Challenge, Urban Challenge, and then Waymo, Aurora, Uber, ATG. It was this really fascinating pocket of talent, actually.

AI assessment note: “a lot of, like, applied research for autonomous driving, so navigating on-road, off-road”

Q guy at that younger guy at that time. So I'd like say, I'll test it and see how, like if I can get it to like break quickly, like if no one else is around, I wasn't trying to cause any damage. I'm sure you've seen much worse than me, but you're curious as a driver, like how will this react? And was it 10 years ago? When was it?

A Yeah, so it's 2019, uh, summer through, um, uh, spring of 2024, so about five years. Uh, and it was like a really cool phase because it went from that, like, kind of really aggressive R&D point to where that launch in San Francisco was the beginning of this incredible hockey stick that, uh, uh, is like actually the beginnings Of like, real scaled commercialization for autonomous driving, and, ah, and there's a couple things that were amazing about it, where one, there was a real aggressive transformation of the technology stack to kind of embrace these very machine learning, kind of new age of machine learning and kind of data-driven approaches, ah, ah, particularly on the behavioral side, where you're learning from large-scale data instead of engineering a system with heuristics and search and so forth.

AI assessment note: “Yeah, so it's 2019, uh, summer through, um, uh, spring of 2024”

Q Yep. That makes sense. Well, let's, let's shift. So you guys, a lot of the top talent in the world, obviously crushed these problems at Waymo. It's it's everyone's seeing what it's starting to do now. It's amazing. And you decided to move into Construction, and starting, starting with excavators for the real world. Like, like, so how do you make that shift? Why, why'd you found bedrock?

A Yeah, so we, so part of it was really, um, appreciating how incredible those scalability capabilities we just talked about were, um, where you start with a beachhead, in Waymo's case was San Francisco, and now you have this fly where you're adding new capabilities, new geographies, new platforms, and setting aside the complexity of the public road driving domain, the generalization actually, like, really, really works well. Um, Um, we saw an opportunity to apply that to a space that never had that type of, uh, approach, uh, in it, which, which is, uh, automation of specialized heavy machinery, and construction was a especially exciting, uh, place to start where you have, um, large numbers of machine types. They're all in these slow moving, semi-controlled environments. Uh, you have astronomical amounts of, of work that needs to be done. You have an industry that, um, fundamentally has these Astronomical tailwinds where, um, manufacturing has to be, like, built at massive scale. Uh, you have, um, you know, on-shoring of manufacturing, re-industrialization. Infrastructure is going through a refresh cycle where you have to re-repave giant amounts of roads. You have housing shortages. You have energy. So you have these huge demands. At the same time, labor is going the opposite direction where, um, you're seeing the average age go above 50, Um, the, uh, uh, up to 40% of, of constru…

AI assessment note: “we saw an opportunity to apply that to a space that never had that type”

Q jobs. I believe it's going to bring prices down. I believe it's going to help our crumbling infrastructure. Uh, so I mean, this is, to me, it's obviously good, but a lot of people aren't going to understand that. People are not very good systems thinkers. They assume you're just drawing jobs. Like, how do you think about it? How do you explain this to people about why it's good?

A So this is not a zero sum game. Uh, there's an astronomical demand for projects for, uh, just given all the trends we're seeing, the data centers that need to be built, the housing that's too expensive, the roads that are in a refresh cycle. Uh, there's just not enough people to do this work, and it's actually getting a lot worse, like a lot worse. Uh, and this is the number, like, number one problem that we're hearing in the industry from almost everybody we talked to, and every single GC we talked to has more jobs that they could take on that they just, like, physically can't, and so when that happens, market forces come into play. You have prices that skyrocket. You have projects that just simply don't get done. The things that absolutely have to happen get done, but get, get done for a much higher cost. That cost gets burdened by companies, by consumers, by governments, which in the end goes to taxpayers, uh, and all of this Kind of perpetuates, um, and, uh, and we've heard of literally multi-billion dollar projects that got approved and funded, but don't get off the ground because they don't pencil out, meaning you just cannot do them profitably. And so when you think of something like the heavy machinery work that happens up front in the project, um, that might be, uh, it's actually a very painful, expensive, and unpredictable phase of it, but what it does is it can chang…

AI assessment note: “So this is not a zero sum game. Uh, there's an astronomical demand”

Q And you know, for me, I, I, you know, I tend to think we are on the cusp of not only an advanced manufacturing revolution that brings back a huge amount of activity to us, but also robotics revolution that's coming. I think is what you're doing related closely to robotics. It's a form of robotics in a way, isn't it?

A It's definitely a form of robotics where we're automating physical behavior, right? In action. Um, it's just a physical manifestation of the AI wave that's kind of happening, um, all over where, um, we've all seen it on the, you know, chat bot side, LM side with, uh, chat GPT and everything else. Um, uh, obviously we're seeing it in transportation with Waymo. It is absolutely inevitable that that starts to hit manufacturing, construction, and these other industries. Um, and in a lot of ways, it's actually, I'm, to me, it's even more exciting because, uh, like, Like, 80, 85% of our GDP is physical industries. It's the physical world. And so there's only so much you can do with, like, more intelligent data movement. But, uh, at the end of the day, we have to build things. We have to harvest things. We have to produce things. And, um, it's a real economy. I mean, we love our digital side too, but like, yeah, it's the, it's the, the, there's, there's something both like beautiful about the, you know, just gigantic potential of all this and the physicality of it, but there's just a practicality that, What transforms the economy? A big portion of it is building. It's the building things, manufacturing things.

AI assessment note: “It's definitely a form of robotics where we're automating physical behavior, right?”

Q And did, did coming from the Soviet Union to America give you an appreciation for, for business and freedom and building things at all?

A Yeah. It's, it's interesting that not, not even to the, probably like talking to my parents, the things that they went through, Uh, it's hard to even imagine. I try to, uh, grasp it, but they've been trying to leave for about 15 years before they were finally able to, uh, and were really deeply involved in even, kind of, helping organize the first, kind of, batch of immigrants that were able to leave, uh, legally in a deal between the Reagan administration and Gorbachev administration, and, and then we immigrated, and it was, um, uh, you know, it was like a very, you, you leave everything and, uh, start from scratch, and I actually, it was kind of interesting because, like, last year I hit the age that my dad was when he, Left, uh, the country barely spoke like a tiny bit of English, zero assets left. Every asset he had had a six year old me and my sister was one month old and it was like a fresh start. And so it kind of hit me hard. I'm trying to imagine what that would feel like. And it's really hard to put yourself in those shoes just to totally start over.

AI assessment note: “Yeah. It's, it's interesting that not, not even to the, probably like talking”