Physical AI that Moves the World — Qasar Younis & Peter Ludwig, Applied Intuition

**Alessio** (0:04)
Hey, everyone, welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.

**Swyx** (0:10)
And today we're very honored to have the founders of Applied Intuition, Qasar and Peter, welcome.

**Qasar Younis** (0:17)
You guys really know how to turn it on to podcast mode. That was, you guys are real pros at this. They were just joking around right before this, and then they flipped it pretty quick.

**Alessio** (0:29)
Yeah, it's good to have you guys. Maybe you just want to introduce yourself so people know the voice on the mic. Oh, sure.

**Peter Ludwig** (0:34)
Yeah, I'm Peter Ludwig. I'm the co-founder and CTO of Applied Intuition.

**Qasar Younis** (0:37)
And my name is Qasar Younis. I am the CEO and co-founder with Peter.

**Alessio** (0:42)
Nice. Can you guys give the high level of a view of what Applied Intuition is? And I was reading through some of the Congress files when you went out there, Peter, and 18 of the top 20 global non-Chinese automakers, you two guys, you have customers in agriculture, defense, construction. I think most people have heard of Applied Intuition, tied to YC when it was first started, and then you were kind of in stealth for a long time. So maybe just give people the high level of a view of what it is today, and then we'll dive into the different pieces.

**Peter Ludwig** (1:10)
Yeah. So Applied Intuition, our mission is to build physical AI for a safer, more prosperous world. And so we work on physical AI for all different types of moving systems, everything from cars to trucks to construction and mining equipment, to defense technologies, and we're a true technology company. So we build and sell the technology, and we sell it to the companies that make the machines, we sell it to the government, really anyone that wants to buy technology to make machines smart.

**Qasar Younis** (1:37)
Yeah. And I think in the broader AI landscape, a lot of the focus, rightfully so, in the last three years has been on large language models, and so everything fits in a screen. You know, like whether it's code complete products or things like that.
And what's different about us is we're deploying intelligence on to a lot of things that don't have screens. You know, they're physical machines. There are sometimes screens within the cabin, or for example, of a car or a truck or something like that. But most of the value we provide is putting intelligence that is in safety critical environments. So those two words are really important because learned systems can make mistakes if you're asking for like, you know, some, you know, something like, tell me about these podcast hosts that I'm about to go meet. But you can't do that. Obviously, when you're, you know, we run like, as an example, we run driverless trucks in Japan right now. Like, as we speak, we can't have errors. Those are L4 trucks. Yeah.

**Alessio** (2:39)
Yeah. Was that always the mission? I remember initially, I think people put you and Scale AI very similarly for some things being kind of like on the data infrastructure side of things. What was the evolution of the company?

**Peter Ludwig** (2:51)
Well, from the very beginning, we always wanted to really be a technology company that helped generally push forward the industrial sector. And so we started off working in autonomy. Our very first customers were robotaxi companies.
And we started off doing a lot of work in simulation and data infrastructure. And then over the years, we've expanded our portfolios. Now we have over 30 products. And it's a pretty broad technology play within the landscape of physical AI.

**Qasar Younis** (3:18)
Yeah, I think the scale reason is because we're all YC universe companies.
But it was a very, very different company. Scale is more of a services company, data labeling company fundamentally. We started and still are do a lot of tooling. So you think developer tooling is now in vogue again, thanks to the AI boom. But honestly, 10 years ago, it was out of vogue. Doing a tooling company in 2016, 2017 was not the thing to do because, I don't know if you remember, the VCs generally, their views was the toolings are just workflows, and workflows ultimately are not really interesting.
And we're going to come full circle of that. But when we started the company, it's kind of like in the periphery of what the company wants to be. It was like, from our earliest days, we want to deploy software on physical machines, like on cars and on trucks and things like that. Now obviously we didn't know that the transformer boom was going to happen. We didn't know that autonomy systems would become end to end. Those things we didn't know. And why that's important, when the time is in the end, it is just, now you can, those models can be generalized to multiple form factors.