00:22:47 · Bernt Øivind Børnich, Ty Morse
And it's gonna be very interesting to see see how that evolves. I think it's gonna be quite beautiful to have, like, this companion throughout your life that kinda, like, is always on your side, remembers everything that's happened, and is always there for you. And I think I think we could all need that. [00:23:03] S0: I think there's very few products that most people would describe as delightful to have in their lives. And I I I think this is gonna be one of them where when people think of the experience of interacting with humanoid robots and NEOs, it's gonna feel like delight. Like, things just are happening. You didn't really tell it to do something. Just, like, magically did some task that you weren't expecting, and you have this little surprise and joy. How do you think about designing something that is just going to be, like, a delightful product?
00:23:32 · Bernt Øivind Børnich, Ty Morse
[00:23:32] S1: I think, ultimately, it's all in the data. Right? So it becomes a data problem of how do you kinda, like, create the desired behaviors through how you tune your data. I think there's still a lot of uns unsolved research there. Just like a lot of work to do. I don't have the solution. Like, everyone else, we're working on it. But I think it's something that will really, really, really greatly improve the enjoyability of using the models. And it... It's been a lot of discussion lately. Right? When you look at the best LLMs now, they're kinda becoming worse personality wise because you have to be so careful to make sure they don't do anything wrong. And we're clearly gonna have the same problem here. Like, we want to make sure these robots are caretakers of humanity and, like, they help us. And finding the balance there, I think, is gonna be be very hard. So, yeah, that's that's something we're gonna work a lot on. And I do hope that through kinda exposing the robot the right kinda, like, behaviors that we would like to see in other people. This is emergent behaviors. [00:24:46] S0: It actually just occurred to me. If you have a robot in a home environment, it doesn't... Not all homes are actually happy. Right. And there might be learned behaviors that are not good.
00:24:46 · Ty Morse, Bernt Øivind Børnich
[00:24:46] S0: It actually just occurred to me. If you have a robot in a home environment, it doesn't... Not all homes are actually happy. Right. And there might be learned behaviors that are not good. [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.
00:24:56 · 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.