00:24:56 · Bernt Øivind Børnich, Ty Morse
[00:24:56] S1: Well, you know, remember, like, most of, like, the the LLMs are mainly, like, trained on, I don't know, like, Discord forums, Reddit. Right. Like, worse forums than that. Like, it's, like, all over place. Humanity. All over the place. Right? So, like, it's like... It is like the dark side of humanity. And then you take that, and you know there's this, like, great meme, right, where you have, like, the big gatula monster, and then someone, like, slaps a smiley on it and says, like, now it's ready. And that's kinda like what a modern model is. Right? You have this, like, beast, and then you're just like, no. No. You're gonna behave well. And I think there's better ways to do that long term as you get more data. Right now, everyone is extremely data constrained. So are so are we. Right? But as you get this incredible tool to learn about how to operate in our world. Maybe you can be more selective on your data. I don't know. But maybe just encourage everyone to, like, be be kind to our robots, and your robots will be kind to you. But there is a balance here because the willingness to kinda, like, break rules and explore is a large part of how we learn. Right? It's how you get new ideas and creativity. And maybe that's one of the reasons you don't see that much creativity in models today. You don't really kinda encourage and expose that kind of behavior. [00:26:08] S0: How do you expose more of it? Like, if you were to try to drive the robots to do creative things, how how do you, like, seed that?
00:26:08 · Ty Morse, Bernt Øivind Børnich
[00:26:08] S0: How do you expose more of it? Like, if you were to try to drive the robots to do creative things, how how do you, like, seed that? [00:26:17] S1: I think play is just incredibly important. And I dream of a future where, like, robots kinda, like, curious and playful. And if they don't have anything else to do, they'll go and figure out how something works. I don't know. Go shuffle your feet in the sand and figure out how the dynamics of sand works. I don't know. It gets... Of course, it's pure speculation. But I think the ability to kinda, like, verify your hypothesis because you literally have the real world here grounding things, hopefully, will give you some more ability to explore because you can actually figure out whether or not your hypothesis result in what you thought it would. [00:26:55] S0: When we were on the drive over here, I was watching this kid just randomly. We were stopped at a stoplight, and this kid was just feeling around and, like, touching the world. Mhmm. I think it was, like, some handrail, and they were touching it, they're just feeling it around. And then it just occurred to me, there's all the tasks that you want your robot to do in your home. Maybe you want it to do the laundry, make you coffee, all this stuff. But then probably most of the time, if you're at work for eight hours, this thing is just there sitting idle. But you could potentially, like, have it collecting data by taking actions and just literally like a child experiencing the world, you know, experiencing the home, doing things.
00:27:33 · Bernt Øivind Børnich
[00:27:33] S1: And I I think also, like, we haven't talked about this yet, but, you know, there's the concept of the NEO platform where we open this up to developers and everyone to, like, build on it, which I think is gonna be incredibly important because it's such a big problem, and I don't think we can solve it alone. We really need to enable as many people as possible to do the development and, like, partake in the journey. And these robots will get exposed to very different environments and very different data. And I think that's also very important because you want, like, as far the distribution as possible. If you think about the home, I think you're partially right. But I think also, actually, as these systems become generally very capable, our standard will just go up. Alright? So, like, everything is gonna be, like, perfectly full. All of your clothes will be ironed. Like, even you... Even your sheets will be ironed, and they will be, like, perfect on your bed. And, like, all the glasses will be online in the cabinet. And, like, there will be no dust anywhere. And, like, can create a lot of work if you want to. Like, if if if there's, like, no... If there's no cost to the labor, you can come up with a lot of things that are, like, marginally useful, but I'm gonna do it anyway because, like, why not? So I'm not I'm not sure there will be that much idle time. We'll see. We'll see.
00:28:50 · Ty Morse, Bernt Øivind Børnich
[00:28:50] S0: You know, when you were talking about perfectly arranging the glasses, it was... I was thinking, like, most humans, like, my laundry is not perfectly folded. So if you emulated me... Like, it's it's it's folded, but it doesn't... Like, you see creases, you know? Yeah. If most people's environments are imperfect and the way that humans actually operate in the real world is just constantly imperfections, how do you collect, like, the best real world perfection data? [00:29:17] S1: I don't think you do. I think you just learn how the world works. And and, like, we learned that, like, there will be wrinkles in your T shirt if you do like you do. And sometimes you will have the, like, random example where, like, it's actually straight. Right? And and and both of them are equally important because how you... You learn how to get from one... Transition from one stage to another. And it more becomes, like, how do you ensure, like, that you have the intelligence emerge over this so that if I say, actually, I want my laundry to be, like, perfectly straight, then the robot understands how to do that. It's a pretty good path there. It's it's a pretty well explored problem, especially self driving is a good example of this. Like, most drivers are terrible drivers. [00:30:06] S0: For driving, it's a very it's a very thing. You you want the robot to do exactly, you know, perfect job every time.
00:30:06 · Ty Morse, Bernt Øivind Børnich
[00:30:06] S0: For driving, it's a very it's a very thing. You you want the robot to do exactly, you know, perfect job every time. [00:30:13] S1: Yeah. But, like, if you just clone human behavior in traffic, you're not gonna get that. No. Not at all. So you can't actually just do that. Right? You you learn from all the data about how people drive. It's very useful data. You learn what happens if you do something. You don't learn how to drive. You learn the consequence of driving. Right? Then when you have that understanding of how to operate a car and how traffic works and how typically, like, all the cars move and, like, how pedestrians, like, might move and, like, predicting all these things. Now you can learn how to operate in a manner that is desirable given that someone tells you what's the desired behavior. But I don't think models necessarily should explicitly learn through cloning human behavior. That's that's kinda like a very... That... That's how we used to do things, like, years ago, but, like, that... That's not how you do these things anymore. You learn how the world works, and then you can essentially search in that space for, like, whatever optimal solution that you would want to your problem. If you had to
00:30:13 · Bernt Øivind Børnich, Ty Morse
[00:30:13] S1: Yeah. But, like, if you just clone human behavior in traffic, you're not gonna get that. No. Not at all. So you can't actually just do that. Right? You you learn from all the data about how people drive. It's very useful data. You learn what happens if you do something. You don't learn how to drive. You learn the consequence of driving. Right? Then when you have that understanding of how to operate a car and how traffic works and how typically, like, all the cars move and, like, how pedestrians, like, might move and, like, predicting all these things. Now you can learn how to operate in a manner that is desirable given that someone tells you what's the desired behavior. But I don't think models necessarily should explicitly learn through cloning human behavior. That's that's kinda like a very... That... That's how we used to do things, like, years ago, but, like, that... That's not how you do these things anymore. You learn how the world works, and then you can essentially search in that space for, like, whatever optimal solution that you would want to your problem. If you had to [00:31:14] S0: think forward a few years, and you guys are not developing all the, like, models or whatever for your robots, and there's kind of, like, this almost mod store. Mhmm. Where people can create things and create, like, new actions or tasks that a robot can do. And then someone can just, like, download it onto their NEO, and suddenly, a new skill is unlocked.