Sources with Alex Heath
00:38:17 · S5, Alex Heath
[00:38:17] S5: This episode is brought to you by Google Chrome. You think you know a browser, but Gemini in Chrome? That's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50 page restoration block or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses, setup required, compatibility, availability varies 18 plus. [00:38:47] S2: The neo launch was super interesting to me because, again, it was really good branding. The keynote was awesome. And then you realize it's like, oh, no. They wanna charge you, like, $20,000 to do data collection in your home with a teleoperated robot. I don't know if that's your strategy, Tony, with Sunday. Sorry if it is. That's, I think that's not gonna work at scale. I think, like, you can sucker a few early adopters into doing that, but, you have to have value and not, like, trick people into actually being the customer, right, in a way that they don't know that they're the customer. Like, you know, you can buy the robot, but you're actually feeding the data back to the company, and that's the reason they're doing it. You're actually giving them more value than they're giving you. Right? And you wanna... You don't wanna do that, I assume, with Sunday.
00:39:34 · Tony Zhao, Ellis Hamburger
[00:39:34] S0: Yeah. I I think for us is... Our opinion is it's not worth shipping a not autonomous robot. And the reality is, like, when people think about robots, robots should be autonomous. It should be, by definition, autonomous. Right? It's a robot. It's not like a human, like, wearing the the shirt of the robot. Right? So I think what... But the reality is, right, like, if we do not have data, like, the AI isn't there, and without the AI, it will not be autonomous. So we have almost this, like, chain egg problem there that without deployment, you cannot gather robot to autonomous enough to be useful. So we... We're actually, like, thinking about this problem since the early days of, like, how can we break this chicken egg problems? And what we end up with is the whole idea of using gloves to collect data. So, essentially, instead of, like, getting robot to your home and get someone else to, like, log in to your robot and collect data in your home, all we do is we build these gloves. I actually have one here. It's right here. [00:40:36] S1: It just gave us the finger. Thanks so much, Tony.
00:40:36 · Ellis Hamburger, Tony Zhao, Alex Heath
[00:40:36] S1: It just gave us the finger. Thanks so much, Tony. [00:40:40] S0: So it's... We have the hand actually here and the gloves. So the goal part here is that you actually don't have to use a whole robot to be generating data to train the robot. All you need is to wear these gloves and do the task, and we'll be able to, like, leverage that to train the robot. So what that allows us to do is we don't have to get data solely from our customers. Right now, we are actually having, like, more than 500 people in The US as contractors, and it's part of their work to be, like, just wearing the glove and do the chores, and we'll pay them for that. And that's how we train the robot without, like, needing to deploy it in the first place. [00:41:23] S2: How much are we paying for this? I mean, can you hook a hook a brother up? I mean, I'm an entrepreneur now. I need some side income. [00:41:29] S0: I think they're they're actually paid very well. In terms of wall clock time, every hour they spend, they get paid, like, $40 ish, which is very good. And the additional nice thing... I I think it's actually a very good job as in, like, you don't need to leave your home. You can just stay there, and you can do it anytime. You can do it for, like, ten minute in the morning, ten minute in the afternoon, and ten minute at night. Right? And we don't control for that. All we need is to get, like, this amount of well instructed, like, you know, clean data from your home, which brings us the diversity and the dexterity that's needed.
00:41:29 · Tony Zhao, Ellis Hamburger
[00:41:29] S0: I think they're they're actually paid very well. In terms of wall clock time, every hour they spend, they get paid, like, $40 ish, which is very good. And the additional nice thing... I I think it's actually a very good job as in, like, you don't need to leave your home. You can just stay there, and you can do it anytime. You can do it for, like, ten minute in the morning, ten minute in the afternoon, and ten minute at night. Right? And we don't control for that. All we need is to get, like, this amount of well instructed, like, you know, clean data from your home, which brings us the diversity and the dexterity that's needed. [00:42:06] S1: Is that like an ongoing project in terms of the training or do you feel like at some point it's gonna magically be done?
00:42:06 · Ellis Hamburger, Tony Zhao, Alex Heath
[00:42:06] S1: Is that like an ongoing project in terms of the training or do you feel like at some point it's gonna magically be done? [00:42:13] S0: That's a very good question. I think, I think we'll be... I think the gloves will be here to say we're going to be using it for a very long period of time just because if you think about places where AI works the best, It is when it has almost access to unlimited amount of data. Right? We have the whole Internet to train the large language models, and these days, people are still paying, like,, like, scale, like, crazy amount of money to label their data. I don't think robotics will be a a kind of exception to that. And it's probably even in the other direction of, like, in robotics, we do not have a whole Internet scale robot data to start with. So we have even more work that we need to do. So I think we need to, like... Yeah. Like, the data collectors wear the gloves. We're expanding them actually quite quite a bit this year so that we can Yeah. [00:43:09] S1: How many people are wearing gloves, doing dishes right at this very moment, do you think? [00:43:13] S2: And how do their wives feel about it? [00:43:16] S0: Sometimes both them and their wife do it together, which is [00:43:20] S1: That's romance. [00:43:22] S2: That's $80 an hour. [00:43:26] S0: Yep. So at this point, we have around, like, slightly above 500 people on The US collecting data for us, and we're going into the thousands this year.
00:43:26 · Tony Zhao, Ellis Hamburger, Alex Heath
[00:43:26] S0: Yep. So at this point, we have around, like, slightly above 500 people on The US collecting data for us, and we're going into the thousands this year. [00:43:36] S1: Yeah. And I know there is the design of the product, the brand, some stuff on the software side, I'm sure, and how you interact with it. But, like, what percent of your moat would you say is this data that you're collecting with the Glove? Because I'm not sure that anybody else is is doing that. Are they? [00:43:53] S0: Yeah. So I think our approach of building a glove that is co designed with a hand, I actually... I don't think I'm aware of any company that is doing something. I think there are similar approaches, but not exactly the same. [00:44:06] S2: Everyone in robotics talks about the hand as a problem. Right? Like, it's one of the top problems, but you're right. Like, to my knowledge, no one is doing this as a data source like you are. [00:44:16] S1: How can that be?