00:20:54 · Anika, Priya, Maya
[00:20:54] S2: That's no hate. I went jobs. I went to a worse school, and I had the same major. Disclaimer alert. So... Yeah. What? That's true. [00:21:02] S1: That's so funny. Yeah. But when I was looking into it, apparently, they're actually an offshoot for, like, a German data labeling company that's been operating for a while. And they're operating in, like, 15 different countries. They have 10,000 different operators, and it's primarily in Turkey right now. So it seems like they're, like, The US American facing Mhmm. Arm of this. [00:21:20] S2: Yeah. But still, it seems like they're trying to, like, mass do The US because then they said they're launching in Seattle, SF. I think... Like, they said a bunch of cities. I don't understand the math on that. And the key reason I'll say I don't understand the math on that is it's not that there's no one else doing US based data work that's like a big player. Like, for example, Tesla is doing it for Optimus, but, like, that makes sense to me because it's like you're willing to burn paying USD prices because you own the full stack of this. Right? So, like, that can be a cost center. And, like, if Optimus works out, like, obviously, you'll make your money back and then some. But where I think it doesn't work for some... Someone like a Slash is no one has even come out and said, like, EO centric data works. [00:22:02] S0: Oh. But... No. Wait. But what do you mean it does... Like, that's how they trained the figure in physical intelligence models.
00:22:02 · Maya, Anika, Priya
[00:22:02] S0: Oh. But... No. Wait. But what do you mean it does... Like, that's how they trained the figure in physical intelligence models. [00:22:09] S2: But they had a lot of teleoperated data. And, like, do they say they're breakdown anywhere? Because, like, all the research I read, like, example, Stanford has a paper on it and there's, like, just like general consensus. Mhmm. My understanding of it is like people are thinking like, oh, probably there's like some marginal improvement if you have a ton of egocentric data, but it's like a bet you're making. [00:22:30] S1: Yeah. [00:22:30] S0: Oh, you're saying like, you think most of the figure model and physical intelligence model, like most of the data is actually teleoperated. I thought a lot of figures data is from YouTube videos of like the third party view. And then a good amount is ecocentric data. The other thing is, like,
00:22:30 · Maya, Priya, Anika
[00:22:30] S0: Oh, you're saying like, you think most of the figure model and physical intelligence model, like most of the data is actually teleoperated. I thought a lot of figures data is from YouTube videos of like the third party view. And then a good amount is ecocentric data. The other thing is, like, [00:22:49] S1: in this scenario, low signal data actually affects the model, like, way more negatively than it does for LLMs in my opinion. Because, like No. I didn't know that. No. I'm just thinking I'm just thinking about it. Because, like, I think about, like, our, like, cybersecurity models. And, like, the quality of data is, like, so so important Yeah. In cybersecurity that, like, you end up just, like, tossing a ton of data. Where it's like, we run all of these experiments on our ML models, and, like, at the end of the day, we we take, like, huge chunks of data. It's, like, billions of messages. And we're, okay. We, like, actually can't use any of this because it's, like, so low signal. Yeah. And I feel like in LLMs, like, obviously, they do it to, like, some extent. But I feel like for a robot. [00:23:26] S0: Like, LLMs, actually, they don't toss a lot [00:23:29] S2: of the rules. [00:23:29] S0: Like, I met a girl the other day who did her thesis. Like, she recently did her PhD thesis on this, which was like, if you just do a rejects match against like the word... Like, how do you say this? Like, can I say that? [00:23:41] S1: What's the word? What's the word? Like, porn. Oh, yeah. [00:23:44] S2: You can say... I was I was gonna say...
00:23:44 · Anika, Priya, Maya
[00:23:44] S2: You can say... I was I was gonna say... [00:23:46] S1: You can say that. [00:23:47] S0: No. Like, I can't say that. [00:23:49] S2: No. No. Wait. You know, I I had this problem this episode too earlier. [00:23:52] S0: Yeah. Yeah. No. Because I saw you. Yeah. Yeah. Okay. The the p o r n word. [00:23:58] S2: That's a word. [00:23:59] S1: She's gonna say you somehow make it worse. Okay. Let's just move on. Anyways, her thesis [00:24:04] S0: was like on... Like, if you literally just like use simple search filters, like rejects matching filters to filter out this data. Mhmm. You come up with a really... With like a lot better of a model. So imagine if you like, spent more time doing like LLM filtered data. [00:24:19] S2: I see. And you [00:24:20] S0: could still come with like, And then you pass this to the model. So that made [00:24:24] S2: me think, oh, wow. A lot of [00:24:25] S0: the data that's going into these LLMs are not actually [00:24:27] S1: crash data. [00:24:28] S0: Yeah. They're not actually filtered [00:24:29] S1: that much. Wait. Would you guys have this in your house? [00:24:31] S2: I was gonna ask. [00:24:32] S0: Yeah. For sure. [00:24:33] S1: Oh, for sure. I was for sure. You think I'm worried about my data? [00:24:38] S0: Yeah. Like, oh, is it, like... Because it's gonna see me, like, negative or something? [00:24:42] S1: No. Priya just, [00:24:43] S2: like, loves being like, and I would let this early stage y c company invade my home. [00:24:52] S0: You know, like, I I guess I just, like, don't care about my privacy. Is that bad?
00:24:52 · Maya, Priya, Anika
[00:24:52] S0: You know, like, I I guess I just, like, don't care about my privacy. Is that bad? [00:24:56] S1: I mean, I don't care about my home, honestly. Like, what are you gonna Yeah. What are you gonna get? [00:25:00] S2: Well, yeah. I actually think from a privacy perspective, like, the stuff on my computer would give you more information about me than going around my home. Yeah. What's going around in my home gonna show you? Yeah. So you don't return the packages. That I'm broke and we might not be able to move out. [00:25:16] S1: Like... Oh, yeah. Where are you guys at with that right now? Nowhere good. Nowhere, honestly. Are you just getting a little sneak peek into our lives? You can skip ahead to us talking about the AI labor market now. [00:25:27] S0: Okay. Who wants to start this one off? Anyone in tears? I was [00:25:31] S1: like... Mhmm. [00:25:31] S2: Everyone's been talking about the AI labor market for the millionth time, I think. I was literally like, should we cover this again? And then I was like, I think we have to. Yeah. Everyone's talking about it. But the reason why... [00:25:41] S1: That's really what Olin said when they introed it too. Olin was like, yep. We're covering this again. No. [00:25:47] S0: I was like I was like disappointed in us, but it's okay. [00:25:50] S2: No. There's nobody No. Wasn't anything about it. [00:25:53] S0: No. Know. Know. Because I did my own research to be like, oh, is there anything I could suggest instead of this? And I, like, literally couldn't.
00:25:53 · Maya, Anika
[00:25:53] S0: No. Know. Know. Because I did my own research to be like, oh, is there anything I could suggest instead of this? And I, like, literally couldn't. [00:25:59] S2: Yeah. No. Yeah. Don't worry. Yeah. I went through the same thing. The reason why I think everyone's like, fine. We'll talk about it again is because the founders of Anthropic and OpenAI, Dario and Sam, have gone back on their thesis around AI job displacement a little bit. Obviously... Yeah. Everyone's obviously saying it's because they're IPO ing. Yeah. But this pisses me off. Wait. Actually... Okay. Wait. Brad asked. Wait. Like... Okay. So in the beginning, they said that it's like gonna... So I guess Dario had the most extreme view and he said it was gonna displace 50% of entry level white collar jobs within five years. Which by the way, [00:26:34] S0: he tanked the market when he said this. [00:26:36] S2: Yeah. But why? Can I ask a dumb question? Yeah. Why is IPO ing mean that they have to walk back that narrative? Because didn't... So like everyone said they were saying it because it would help them raise at a higher valuation and like Which they did. Investors get really excited because god,