Soumith Chintala: preference

Transcript context

…Do you think this feedback is helpful to make open source models better or to get to like open source AGI? Because in a way like OpenAI's goal is to get to AGI, right? So versus I think in open source, we're more focused on personal better usage or like commercial better usage. Yeah, I think that's a good question. But I think, I actually don't think people have a good understanding of AGI. And I don't mean definition level. I mean, people are like, okay, we're gonna, AGI means it's powering 40% of world economic output or something like that, right? But what does that mean? So do you think electricity is powering 40% of world economic output or is it not? Like generally the notion of powering X percent of economic output is not defined well at all for me to understand how to know when we got to AGI or how to measure whether we're getting AGI. Like, you know, you can look at it in terms of intelligence or task automation or whatever. I think that's what we are doing right now. We're basically integrating like the current set of AI technologies into so many real world use cases where we find value that if some new version of AI comes in, we can find, we can be like, ah, this helps me more. In that sense, I think the whole process of how we think we got to AGI will be continuous and not discontinuous like how I think the question is posed. So I think the open source thing will be very much in line with getting to AGI because open source has that natural selection effect. Like if a better open source model comes, really no one says, ha, I don't want to use it because there are ecosystem effect, I'm logged into my ecosystem or, I don't know if I like the models, you know, whatever. It's just a very pure direct thing. So if there's a better model that comes out, then it will be used. So I definitely think it has a good chance of achieving how I would think about it as a continuous path to what we might define as AGI. For the listeners, I would actually mention a couple other maybe related notes on just this very interesting concept of feedback sinkhole for open source to really catch up in terms of the overall Google versus OpenAI debate. Open Assistant was led by Yannick Kilcher who recently ended his effort. I think the criticism there was like the kind of people that go to a specific website to give feedback is not representative of real world usage. And that's why the models trained on Open Assistant didn't really seem like they have caught on in the open source world. The two leading candidates in my mind are LMSYS out of UC Berkeley who have the LMSYS arena, which is being touted as one of the only ways, only reliable benchmarks anymore. I kind of call them non-parametric benchmarks because there's nothing to cheat on it except for ELO. And then the other one is OpenRouter, which is Alex Atala's thing. I don't know if you've talked to any of these people.…

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