YouTube Deep Summary

[00:00] If you guys were running Grock 4, [00:04] that'd be so much fun. How do you judo flip open AAI because they are marching steadfastly towards a billion Mao, then a billion DAO? It's a juggernaut. So, how do you use the better product in a moment to judo flip the less better product? Look, yeah, I mean, here's the thing, right? So, you do the Elon way. So you [00:35] have you get a bunch of missionary like [00:38] full-on missionary engineers that work [00:41] twice as hard and you have a culture [00:44] that is ultra fierce truth seeeking [00:48] and you don't you don't get caught up in [00:52] politics, bureaucracy, BS [00:56] and you just you go for it and and I [00:58] think you know that's where you know and [01:01] then you go wow scientific breakthrough [01:03] scientific method like you start winning [01:06] on truth and that will start I believe [01:09] that will start to give the product [01:12] awesomeness [01:14] of open AI a run for its money [01:17] but like the product of open AAI the [01:20] product department those guys are [01:21] crushing [01:23] they're really good they're not only [01:25] ahead of the game but they feel like it [01:27] just they're just leading in a lot of [01:29] different ways but if you are better at [01:31] truth you will eventually you'll [01:33] eventually have an AI product manager. Yeah. And on a technical basis too, people forget how good Elon is at factories and physical real world things. Uh what he did standing up Colossus made like Jensen Juan was like how is this possible that you did this right? So pressing that his ability to build factories and he said many times like the factory is the product to Tesla. [01:58] It's not the cars that come out of the [01:59] factory or the batteries. It's the factory itself. So if he can keep solving the energy problem with solar on one side and batteries and standing up, you know, Colossus 2, 3, four, five, he's going to have a massive advantage there. on top of Travis, you know, the missionary individuals, which by the way was what he backed before Sam Alman corrupted the original missionary basis of Open AI and made it closed AI and a you know, this is nothing derogatory towards him, but he did hoodwink and stabbed Elon in the back. It's not nothing personal. I mean, [02:33] he just screwed him over. And would you say he bamboozled him? He bamboozled him, screwed him, hoodwinkedked him. you know, pick your term here, but uh he did it he didn't dirty. The original mission was to be missionary and open source all this content. That's [02:49] the other piece I think is a wild card. And I'll and then I'll sit in Keith's position, but open sourcing some of this could have profound ramifications. I think open sourcing the self-driving data could have a really profound impact. Elon wanted to do something really disruptive like he open sourced his patents for, you know, um charging. If he open source the data set and self-driving, does anybody have the ability to produce robo taxis at the scale he can do it? I don't think so. [03:17] Travis's hypothesis is true. Then yeah, everybody will. Well, everybody will what? Sorry. Everybody will what? Shiman, [03:24] if you have access to the money that [03:26] buys the compute, everyone could solve [03:28] that problem. Which piece I'm talking? He said he said if he if he published all the FSD data, could somebody build an autonomous vehicle? Well, yes, but could somebody produce a 100 million robo taxis from a factory with batteries in them? Okay, that's a diff that's a different thing. I'm saying [03:46] and not really because last time I was a [03:48] guest on, you know, all in we talked [03:50] about vertical integration. Uh products really require vertical integration. So ultimately you have a self-driving something that is customuilt for knowing it's going to be self-driving and it interacts differently. the cost structure is different, the controls are different, the seating is different, everything. You build a product taking advantage of where the staff you have the most competitive advantage, but then you leverage that and it reinforces it's still why like Apple despite missing the AI wave, still a pretty good company from any empirical standpoint. I mean, [04:21] like the performance is absolutely [04:23] miserable on the most important [04:24] technology through the last 70 years, [04:27] but the company's still alive and still [04:29] worth trillions of dollars because it's [04:30] vertically integrated. Open AAI for your point, they do have a good product team and they need to stay ahead on the product level because they can't compete on the factory level. The way to stay ahead on the product level is shipping a device. They got to ship the device. It's got to be good. It's got to be [04:46] right. It's got to be the right form factor. It's got to do things for humans that are unexpected. But then if they do that, they're like Apple plus AI. Chimath, what's the paper you were talking about before? What was the name [04:56] of it again? The bitter lesson it could apply to autonomous driving is right now it's still like, hey, how do I drive like a human? We talked about that. But the leaprog moment here could be like, hey, drive a car, make sure it's efficient. Don't hit anybody and just simulate that a quadrillion times and it's all good, right? But right now, [05:19] we're still trying to drive like humans [05:20] because we don't have enough data and [05:23] therefore can't do enough compute. That's the global lesson. By the way, Chimoth, you're totally right. The conceptual, you know, the blog post is right, but that's only true when you have enough data. And depending on the use case, the level of data you need may not be possible for years, decades, and you may need to hack your way there through human interactions. [05:41] physical world AI is lacking in data and [05:46] so you just try to approximate humans.