Digitized | Spotlight
00:14:49 · Amanda, Winnie
[00:14:49] S0: Yeah, definitely. So, Seesaw is focused on egocentric video and capturing this via iPhone. It's a subnet that was launched a month ago by Virtuals. And essentially, they've gotten like a ton of demand so far. I think almost 300,000 tasks have been submitted. And these are tasks like, you know, unload the dishwasher, fold laundry. So the response has been, really strong from the community. Who's submitting these tasks? So any anyone can download this iPhone app. So you just need an iPhone. So people around the world are some are submitting these tasks. [00:15:25] S1: And I guess, like, what is virtuals? I'm curious, like, their involvement in kind of helping launch a subnet. What is, like, kind of their thesis or their strategy there? I hadn't known they were doing this. That's very cool to hear. [00:15:37] S0: Yeah. So I think for... So FrodoBots Labs, which is essentially the development studio of BitRobot, started off as building the sidewalk robot game, which we call the subnet one EarthRover. And so so Michael and his team are creating a bunch of subnets and helping launch, other subnets within the ecosystem. But the idea here is like, we want to be bigger than just ourselves. Right? And so we want to attract ecosystem teams, either robotics startups and manufacturers, startups to also launch subnets. And so virtuals is one of those teams.
00:15:37 · Amanda, Winnie
[00:15:37] S0: Yeah. So I think for... So FrodoBots Labs, which is essentially the development studio of BitRobot, started off as building the sidewalk robot game, which we call the subnet one EarthRover. And so so Michael and his team are creating a bunch of subnets and helping launch, other subnets within the ecosystem. But the idea here is like, we want to be bigger than just ourselves. Right? And so we want to attract ecosystem teams, either robotics startups and manufacturers, startups to also launch subnets. And so virtuals is one of those teams. [00:16:15] S1: Love that. Cool. And I think for the past few years, I also read that you guys have been organizing this, Earth Rover challenge, which is a real world urban navigation competition with researchers from, like, Google DeepMind, Meta, and a lot of academia folks. Maybe tell us a little bit more about what that is, what led you to start this competition, and what have been some of the learnings and research and stuff to come out of it.
00:16:39 · Michael Cho
[00:16:39] S2: Yeah. That's... Yeah. Well... Yeah. So the the competition basically, fundamentally, we we take the top human gamers who play our game to take on AI models that are built by all these different labs. Know, this could be universities like UT Austin, National University of Singapore, Seoul National University, basically like labs that do this kind of research. So they built AI models that basically take on the same game as a human gamer. So if you think about it, it's basically humanity versus AI playing the same basically Pokemon GO game, something like that. And so like I mentioned earlier, the researchers are very interested in this platform because this is... We have basically one of the largest... Mean, far... Actually by far the largest dataset of its kind already, and many of the research team takes take advantage of that to build the models. And then more importantly, because these robots that we've built are really affordable, cheap, therefore a lot easier for them to actually start experimenting versus some of these other traditional robot like you know they're very fancy, way more capable than ours, it's just that they're damn expensive. Yeah it's so I'm really happy to see so now there are like academic papers that have been being written. Many of them have been published and more on the way, and so we are... I feel that we are really making a meaningful difference already through the data set and also through through this competition. By the way, like, the humans are way better than the AI in industry marketing. So so so the AI is still pretty shitty.
00:18:23 · Winnie, Michael Cho
[00:18:23] S1: We're not quite there yet. Our job is still backstage from AI. [00:18:28] S2: Yeah. I mean, the urban navigation... Business sidewalk driving is in many ways the same kind of like stack as a problem set as self driving on the road. It's just that way more resources and also way more data have been gathered on the road and so cyber robot in a way is way behind. So but hopefully, through what we've been doing, are getting a lot of these researchers to push further ahead. I think if you look at the universities and also some of our co organizers, many of them actually, like you mentioned, from researchers from DeepMind, Meta AI, and and universities. So I think for them to be involved with us, I mean, speaks volume about, like, this is very much needed in the research world, and and I think we we are already providing value even at this stage. Yeah. [00:19:23] S1: Yeah. No. I think you also run a podcast with... Where you kind of talk a lot about and interview some of these top researchers, correct, in robotics. What are some, like, exciting frontier things? I guess a lot of what you're doing is already quite frontier, but, like, what are some interesting research pathways or, you know, exciting things that you guys have been discussing lately that you can share?
00:19:23 · Winnie, Michael Cho
[00:19:23] S1: Yeah. No. I think you also run a podcast with... Where you kind of talk a lot about and interview some of these top researchers, correct, in robotics. What are some, like, exciting frontier things? I guess a lot of what you're doing is already quite frontier, but, like, what are some interesting research pathways or, you know, exciting things that you guys have been discussing lately that you can share? [00:19:46] S2: Yeah. I mean... So... Yeah. Me me and this guy, Chris Paxton, shout out to Chris. He... He's a real expert. He himself is a top researcher. So I I feel very privileged to do the podcast with him. I think both of us, I mean it's, I mean you can tell me I'm very geeky, read like research papers for years and people are going to sleep so I've been doing it for ages. [00:20:07] S1: I mean you spent COVID building robots so.
00:20:10 · Michael Cho
[00:20:10] S2: Yeah yeah yeah so that was my COVID. Yeah so yeah there are I think there are some clear trends I would say because like we do this like once or twice a week now there's just so many cool papers coming out But broadly speaking, like, I I can name a few big trends. Like, for... So for example, models that are trained using ecocentric videos. This is... I I I I kinda feel that the last maybe half a year, there was a big trend. There's a lot more papers coming out partially because of some of these, like, work that's done especially by Meta. They have this smart glasses called ARIA. So that has spun off a bunch of research. And to be honest, EcoCentric video had been looked at by the computervisioncom... Community for, like, ages, But I thought nothing really moved until quite recently, and now there's a huge amount of interest. So something has changed, I think, technology that that allows researchers to pick a lot... To do a lot more with ecocentric video. So I think that's one big one. Of course, all the humanoids, they are very, very... Like, advancing very, very quickly. You know, a year plus ago, they can barely walk. Now they are, like, kicking around, like, you know, doing crazy dance, and and and so, I think there are a lot of very cool papers coming that's specific to humanoid as well. Some of the other stuff also more fundamental research like I think reinforcement learning, it's traditionally doesn't really work for robotics. Know? So, like, for example, AlphaGo is is basically all RL, but but because you you can always, you know, like, we can... You can restart the game. It's all in simulation. Right? And so whereas in the robot in the real world if you do some rl like on policy rl online rl and then basically if robots fail you can't you can't respawn yeah so that's why it's never quite worked but I'm starting to see people pushing a boundary on what you can do and I think that's a very big piece of the puzzle as well that needs to be solved. It's not soft but a lot of cool works coming out. I just saw yesterday like something from physical intelligence using IRL to a great extent.