Travis Kalanick, Founder of Uber & Atoms

**David Senra** (0:02)
I want to start with atoms.

**Travis Kalanick** (0:03)
Yeah.

**David Senra** (0:04)
You have this great line on the website that I actually love. It's this awesome sentence. It says, physical world autonomy requires AI for the physical world. This kind of intelligence requires computation we have invented, at an efficiency we can't yet fathom, with deep learning models to understand and act in the physical world that don't yet exist. Tell us what you're building.

**Travis Kalanick** (0:24)
Let's start the mission. It's easier that way. Physical automation to transform industries.
So you start there. You can sort of go, it's almost socratic, like, what does that mean? And sort of in the terms that people use today is physical AI and robotics to transform industry. And you go, okay, well, so what is it, a humanoid? And no, it's not.
I wouldn't call myself anti-humanoid. It's just what we're doing is not that. It's specialized robotics, that it's not like we make robotics and anybody can have some. It's more like robotics and AI that go after an industry, one industry at a time. And in the industries, we think it makes massive moves, big moves. And once we get our sea legs, we go to the next and the next. If you're doing it really well, I like to say that the only constraint on our imagination is management capacity.

**David Senra** (1:27)
What does that mean?

**Travis Kalanick** (1:28)
We're solving problems every day.
If I have to solve lots of small problems because I don't have a lot of management capacity under me, we're not going to do very much. I'm going to be constrained in what portion of my imagination can become possible, like real. But if you have lots of management capacity, lots of problem solving capacity, then those constraints unwind.

**David Senra** (1:53)
So how do you broaden and expand the management capacity you have?

**Travis Kalanick** (1:56)
Okay. So why don't we step back and talk a little bit about, like I have a lot of frameworks for this kind of stuff. One of them I call the meta problem.
Imagine if you have this equation, which is the derivative of problem solving, DT, must always be greater than or equal to the derivative of problem creation, DT. And if that's ever not true, you have a real problem.
I call that the meta problem. So what's happening is, is that if you are creating problems faster than you can solve them, then you're kind of F'd. But when you create problems, like in an Uber context would be like, let's go to China. That's creating a problem, right? Now the way I think about problems, I don't think about them in a negative way. I think about problems the way like a math professor would think about a problem. Is a math professor without interesting problems to solve as a sad math professor? Yeah. So it's like a good thing. So you want to create interesting things to solve. You want to create problems to solve. You have to predict well the nature of the problem and your ability and capacity to solve it. You create a problem today, you may not understand the nature of the problem solving you're going to have to do. You have to predict it. Those problems start coming ashore in like six months and like a real heavy way and maybe even longer.
So you have to be good at predicting what is the nature of that problem and say, okay, well, what is my management capacity to solve it? If that equation gets out of balance, then you have to stop problem creation while you get the solving going so that you're not drowning anymore, right?

**David Senra** (3:51)
Can you give us an example of what happened in China then?

**Travis Kalanick** (3:54)
I mean, China was like amazing, but very difficult and in some ways impossible to predict. Let's go to China, sounds like fun. It was a super awesome adventure because what happened was is I was like, sounds cool.
And I got, it was 2000, probably 2013 or early 13, Uber started in 2010 So it was still early crew.
And I got a crew of folks like super OG guys, and we stayed in an apartment in China for a week or two, a week and a half, two weeks, something like that, and met with everybody we could. It's actually when I first met Wan Xing at Meizhuang, actually, and he told me I was crazy. Don't do it. It's the worst idea ever.

**David Senra** (4:46)
What was your response when people tell you you're crazy, it's not gonna work?

**Travis Kalanick** (4:49)