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?
00:23:50 · Josh Gruenstein
[00:23:50] S0: Yeah. It's an interesting challenge because almost everybody we're selling a robot to has never purchased a robot before. And that kinda comes out of these stats. If The United States is only deploying 38,000 robots a year, if nine out of 10 US factories and warehouses don't have any robots, then almost all of the market is greenfield. And these people understand what this old guard of automation looks like, and they assume a robot doesn't work for them. And so the way we break through that actually isn't by talking about AI, or models, or tutors, or anything like that. We called them up and we're saying, hey, have you ever considered a robot for $16 an hour? And they haven't. That's a new proposition for them. So you can book a meeting, and then you can kind of explain to them this thing that we're doing, and get people interested and involved. And by creating that business model where there is that true incentive alignment between us as the robot vendor and the customer, we're able to run distribution of robots at velocities that, you know, are many orders of magnitude faster than traditional industrial automation industry. We have an average time from that first call to a robot signing contract of forty to sixty days. We have an average time from that signed contract to robots actually in the customer site of about forty days doing work. We stand up robots in production within a day, often within the first couple hours that a robot is on-site. So we're able to move very, very, very quickly because not only is the robot this generally intelligent, generally capable machine that we're not customizing, we're just shipping directly from the factory to the customer, but we're not putting any sort of economic risk on the customer. So we're able to get them on board.
00:25:28 · Raghu Raghuram, Josh Gruenstein, Martin Casado
[00:25:28] S1: And once they deploy it, how do their attitudes about labor versus machines change? [00:25:35] S0: The operations community is really, really fantastic because they see a thing work, it's like, it works. Right? That's it. Right? It's like, yeah, I can see obviously it does the job. I know all the places where this job needs to be done. Let's go put it in all those places. So, we've been able to scale up very, very quickly, both with small businesses and to some of the largest companies in the supply chain from one robot in one site to a dozen plus robots across many sites. [00:26:05] S3: It is interesting though, because a lot of gen AI was like, there's a social element where people get very attached to their models, and it's hard to swap models, and so, listen, you probably have more experience deploying robots than most people alive at this point. Like, are you saying the same thing? Like, they viewed like equipment, or are they starting to be viewed like beings and coworkers? [00:26:27] S0: Yeah. So I saw a very funny tweet, which was, a robot is a robot unless it works, in which case it's a machine. Gotta figure out the attributes. [00:26:37] S3: Is it a Zip Meal? I guess it It's it's pretty real. Is what it is? Like, they just view it as like a piece of equipment once it works?
00:26:37 · Martin Casado, Josh Gruenstein, Raghu Raghuram
[00:26:37] S3: Is it a Zip Meal? I guess it It's it's pretty real. Is what it is? Like, they just view it as like a piece of equipment once it works? [00:26:42] S0: Certainly, at, like, the factory manager level, yes. I think there's still the layer of, interestingly in robotics, your buyer is not your user. Right? Your buyer is the COO or the general manager, and the user is a factory worker, right, who's working with the robot all day long. And there, you actually do need to cultivate the relationship between those workers and the robots because you know, we don't fully automate 100% a factory. We automate some jobs in a factory or warehouse. Do you [00:27:08] S3: have a philosophy on how you even approach this? You try to make them look more like coworkers or less like coworkers? Do you make them talk? How do you view this philosophically? [00:27:17] S0: Yeah. Very, very luckily, there is a whole school of academic research called HRI, human robot interaction. [00:27:23] S3: No idea. [00:27:24] S1: There you go. [00:27:25] S0: Yeah. Lot of people have spent a lot of time thinking about this, including a bunch of people from my academic background, And there are a whole bunch of tricks. So one trick is every robot has a name, and so that lets us actually build relationships with the robots. [00:27:41] S3: Who names [00:27:41] S0: it? Mostly our manufacturing technicians. [00:27:44] S3: Okay, you name it, not the... It's not like a dog is when you get a new dog, can rename it?