00:17:35 · Raghu Raghuram, Josh Gruenstein, Martin Casado
[00:17:35] S1: roughly Like, you're not counting the Fanucs and the old robots. [00:17:37] S0: The Fanuc, right. But that's Nobody deployed any unitaries in The United States into any... They would have shown up in those numbers, but they were probably zero. And so, the supply chain that exists for robots is both too small, and as you called out, wrong. Right? Like, the robots that Fanuc and ABB are building, they're mostly not building in United States, but but even when they are building them in United States, they're building these objects that are designed for systems integrators, that are designed for fast repetitive motions. They are not cut from the set of trade offs that you would want to co design with frontier models. And so we're kind of starting from scratch on the hardware side. So Tutor, in order to deploy robots at scale, has actually been forced to design and manufacture our own hardware. For us today, like, we're not building actuators. Right? So we're not building cameras. There's a whole layer of stuff that we're sourcing from OEMs where they're manufacturing at a much larger scale. But the actual robot itself of, you know, the thing that drives around and has the arm on it and can do all the tasks, we actually are building at scale in Watertown, Massachusetts. [00:18:43] S3: Can you talk about the morphology of the robot? Is that what... Is that called morphology? Anatomy? [00:18:47] S0: You you can use whatever robot What [00:18:49] S3: do they look like? [00:18:50] S1: What do [00:18:51] S0: they look like? We make two. So one robot we make
00:18:51 · Josh Gruenstein, Raghu Raghuram
[00:18:51] S0: they look like? We make two. So one robot we make [00:18:55] S1: Look at his website, Martin. Yeah. Go ahead. Yeah. Send it.
00:18:57 · Josh Gruenstein
[00:18:57] S0: So Cassie. Cassie is kind of a brute. Right? Cassie is designed to do heavy duty work. It has a single arm and a lot of suction cups, and it's powered by foundation models in like the 200 to 400,000,000 parameter range. And came out of this world that Tutor was started out of in 2021 of what can foundation models do for robots. They can predict affordances, grasps that you can go then execute. So it's this co design of the hardware that you can manufacture at scale, what your models can actually do, and actually a big market need where in The United States, anything in the physical economy has to be transported on a pallet or in a cardboard box. So there ends up being an enormous amount of physical human handwork of transporting pallets cases by hand. And so Cassie is kind of the result of that co design, and we manufacture it at a very large scale, we deploy it to a big diversity of businesses across manufacturing logistics. Our second robot is called Sunny. And Sunny is kind of an industrial semi humanoid. Right? It's as if you said you were looking at a unitary, and you were like, I need this robot to run for three to ten years in a factory at human rates and reliability. And so you end up with a slightly different set of design decisions. Sunny is wheeled, not legged, because most indoor industrial settings have polished ground floors. It has a much higher payload capacity and can move much faster, and has industrial collaborative safety standards that enable it to operate around humans. And so we have a 100 Sunnies operating in Boston in our data factory, collecting data for internal use and advancing our research agenda. And then we also now have a growing fleet of Sunnies out in the real world doing more dexterous bimanual manipulation.
00:20:44 · Raghu Raghuram, Josh Gruenstein, Martin Casado
[00:20:44] S1: And do you see... How broad do you see this product line of different robot form factors? Can you capture Yeah. A big chunk of the useful market with three of them, or you need 30 of them? [00:20:57] S0: Depends how you define the useful market. Like, where do you wanna go? If you wanna just live inside of manufacturing logistics, Sunny and Cassie today can probably do 80% to 90% of the work. Right? These are designed for those cuts. What... Maybe just describe what that work is. Yes. Because... Yeah. I'm not sure [00:21:15] S3: if you probably understood. [00:21:16] S0: Yeah. So most people have this mental picture of what sort of the industrial base or manufacturing logistics look in The United States, which comes from the TV show How It's Made. I don't know if either of you have [00:21:26] S3: seen this. Of course. Of course. Yeah.
00:21:26 · Martin Casado, Josh Gruenstein
[00:21:26] S3: seen this. Of course. Of course. Yeah. [00:21:28] S0: And you see these, like, Rube Goldbergian machines of levers, and it's like, yeah, you don't see any humans in those pictures. It's somebody built a machine that is the factory. And that does exist. And if it exists, they probably filmed it and put it on how it's made. Right? Because that's the top point 01% of American manufacturing logistics. And so what's below that? And you walk into these million square foot facilities, and you see a bunch of people standing around on conveyor belts or folding tables doing things by hand. And it's kind of shocking for anybody who doesn't come from this industry and community. And so you look at a robot like Cassie, and it's like, you know, a huge amount of work, which is back breaking work that's really hard to hire for. There's a three month turnover where your average age of the worker doing that work is 55 years old and about to retire, and it's like, okay, we could use a Cassie to do that back breaking work. And similarly, Sunny is like, basically, anything you ever bought that came in a box, a human had to put that in a box, which is a crazy revelation for most people. Anything that requires any degree of assembly, right? Even iPhones, you would assume it's a robot. Putting that packaging together, no, it's a person, even at the highest level of scale. [00:22:41] S3: Then then to his question, which is so, like, you have, like, the single arm with the sucker, you've got the two armed humanoid. [00:22:47] S0: Yeah. What can't they do?
00:22:47 · Josh Gruenstein, Martin Casado, Raghu Raghuram
[00:22:47] S0: Yeah. What can't they do? [00:22:49] S3: Yeah. What can't they do, and where do you go from there? [00:22:50] S0: Yeah. So they can't go outside, and outside is really, really interesting. [00:22:53] S3: Oh, is that just, like, a locomotion issue? [00:22:55] S0: It's not locomotion. It's the hardware. Right? These robots have wheels, and they have a little bit of traction. They have these articulating hind legs, but they can't drive over gravel. Right? There's huge opportunities of robots in construction, robots reclaiming materials from landfills. Need robots with legs, for that. So I think that'll eventually be part of our pantheon of embodiments. And then similarly, robots in the home, you probably don't want a Cassie or Sunny in your home just as well. It's a little bit Yeah. Too industrial of a [00:23:30] S1: They look scary. [00:23:31] S0: Yeah. [00:23:31] S1: Yeah. Let's talk about the customer adoption side. How's how's that been? Obviously, not strictly from a... I don't have people, so I'll take whatever I can get. Yeah. To... Once they have it in their assembly line or whatever it is, how does adoption go in terms of their mindset?