Sources with Alex Heath
00:44:16 · Ellis Hamburger, Tony Zhao
[00:44:16] S1: How can that be? [00:44:18] S0: Yeah. And this is actually kind of reflective of a a broader thing of, like, how we think about systems in robotics. So people tend to think about robotics as, like, singular things like the hands, now the data, and maybe the the legs and, something like that. But it's actually a lot more interconnected, than it look like. So for example, if, like, it could be true that, let's say, the bottleneck is the hand, and you can build a very, very dexterous hand. But the problem is, like, how can you get a lot of data for it? Like, what... If without the data, the whole thing doesn't work no matter how good the hand is. Right? So what we do is [00:44:55] S1: You can make a really nice fake video if you want. I feel like many have been accused of that in the last year.
00:44:55 · Ellis Hamburger, Tony Zhao
[00:44:55] S1: You can make a really nice fake video if you want. I feel like many have been accused of that in the last year. [00:45:03] S0: Yeah. I will not comment on that. Our videos But I I think it's actually more about, like, instead of building the most dexterous hand and call it a day and that's the optimization they want to do, we're like, hey. Can we build a hand that is so cape... Is capable, but we can also get a lot of data to unblock the AI part. So when we design the hand, it's actually not about like, hey, let's get the most amount of fingers out of it. Let's get five fingers. Let's get like 22, 27, whatever degree of freedoms and pack all the motors in. But can we design it like together with the glove? And the glove is something that people can wear and efficiently collect data. So I think when it comes to like for us in terms of the moat as a company, I actually think it's less about whatever data that we have because we're going to have so much more than that. But always approaching these problems with a global knowledge of, like, AI, of software, of hardware, and, like, the whole thing together, like controls. And that kind of always steers us to making decisions that is slightly different from the rest of the the field. And I think that will be the kind of the core competency that will continue to to own and that will continue to help us make bets that are somewhat unpopular in the beginning, but are post op obvious.
00:46:30 · Ellis Hamburger, Tony Zhao, Alex Heath
[00:46:30] S1: Yeah. I mean, what can you tell us about the other stuff we've seen in the space? I know there's been different demos that kinda have or haven't been real visualizations of robots capabilities. I mean, does that bother you when you see that stuff? Like, what type of stuff seems not real when you see it going viral on Twitter? [00:46:49] S0: The way I think about it right now is, like, videos are easy, but, like, uncut videos are slightly harder. But live demo is the boss, and real deployment is the final boss. Right? So if you look at videos, like, let it be from researchers or companies, it could be the one time that it works out of, like, a thousand tries. Right? The success rate could literally be 1%. But as long as we can cherry pick one video, it looks like things work all the time, which is, like, not really true. But if we move along the spectrum and we see, for example, at CES, there are companies that are doing live demos in front of, like, hundreds and thousands of people. And I think that's something that I respect a lot, because that is when you have the true confidence to, like, show it in front of people as opposed to, like, like hedging it and be like, hey. As long as we got a video out, we're all good here. [00:47:47] S1: Yeah. Did we miss you at CES? [00:47:49] S2: Yeah. Were you there? We saw ping pong. We saw Yeah. I was boxing. [00:47:54] S0: Yep. [00:47:54] S2: Yeah. It was cool. [00:47:55] S0: It was cool. [00:47:56] S1: Well, what what of that stuff is real and what isn't?
00:47:56 · Ellis Hamburger, Tony Zhao
[00:47:56] S1: Well, what what of that stuff is real and what isn't? [00:47:59] S0: I would say the ones that I saw that are at CES, namely, like, the... For example, in pound the boxing and some of the, like, I think, grasping objects from a shelf, I think they're all real. They're all driven by real AI. They're not like... There's nobody... Well, the boxing one has someone, like, kind of remote controlling it, but the controls of the... Like, the fact that the robot is not falling down is autonomous. And to my knowledge, the audio Thomas demos of the... Like, there's a folding windmill and, like, taking photos with the dextrous hand. Those are all, like, real and autonomous. [00:48:37] S1: Yeah. It can be tough to tell. Sometimes the outside looks shinier than than, you know, if you will, how well the inside works. I mean, if you look at one of the ones that we saw at CES, the unfortunately named LG CLOiD kinda has a cute face. I mean, is that the one that looks like most similar to Memo? I'm not sure exactly what it can do or how it works, but it looks polished. And I think as the average person, you're like, oh, it certainly looks like it works. But I mean, are you basically telling us that without the Glove data, some of these household chores just aren't possible yet for anybody else? [00:49:14] S0: I think for now, that totally seems to be the case. And I think I will have... It would change my mind if they... They're willing to live demo it, like, many, many times in front of the, like, the audience.
00:49:14 · Tony Zhao, Ellis Hamburger
[00:49:14] S0: I think for now, that totally seems to be the case. And I think I will have... It would change my mind if they... They're willing to live demo it, like, many, many times in front of the, like, the audience. [00:49:28] S1: Yeah. Speaking of, Memo is definitely a better name than CLOiD. Imagine welcoming guests to your house. Please come on in. Allow CLOiD to serve us some amused boosh. [00:49:39] S0: It sounds a little like a... I don't know, like a... Some evil things. [00:49:45] S1: I mean, the e... The... Some are some are, like, actively going for the evil vibes or the transformers vibes, optimists or this or that. And, like, optimists is gonna fall over and squash your cat. Like, Elon doesn't really seem to care about, you know, that stuff in the short term. But if you look at it, I mean, logically, the way that you design it shows you what its goal is. And when I look at some of the others, the goal is to look impressive. And, I mean, I assume you guys looked at the legs and you're like, oh, we don't need that unless we wanna be vain about it.
00:49:45 · Ellis Hamburger, Tony Zhao
[00:49:45] S1: I mean, the e... The... Some are some are, like, actively going for the evil vibes or the transformers vibes, optimists or this or that. And, like, optimists is gonna fall over and squash your cat. Like, Elon doesn't really seem to care about, you know, that stuff in the short term. But if you look at it, I mean, logically, the way that you design it shows you what its goal is. And when I look at some of the others, the goal is to look impressive. And, I mean, I assume you guys looked at the legs and you're like, oh, we don't need that unless we wanna be vain about it. [00:50:21] S0: Yeah. And I think a lot is about really the safety. And if we want, like, flashy demos, legs are are are great. They look like humans. But... And I I think also people wouldn't disagree on the fact that, like, if you look ten years into the future, like, the robot may all have legs. We'll all converge into that eventually. But I think the question is more about, like, do we... Can we earn the trust of real consumers or other customers with whatever the robot that we're building right now? And that will give us a ticket to build that ultimate robot that is, like, can do everything. Right? And I think just prioritizing safety in a... Almost like a passive way that, like, if you just unplug the robot's battery while he's doing something, it will not fall over, is going to be, like, helping us gain the trust so that people know that we consider those edge cases.