Shawn Wang: evaluation

Transcript context

…We can come back to that later, but I should have, I mean, papers have like 10, 50 citations. If I'm pretty sure that if I call them like, RLHF without human in the loop, but like a discriminator which is synthetic human in the loop, I will have get much more citations today. And all the inspiration for this paper were from actually the original open-air paper of RLHF. But at Academia, we don't have the way to pay annotation online like that. So how to simulate it? Yeah. A lot of these ideas are repeated, like discriminator, generator, we just call them different names now, like verifier, whatever. Well, I think your progress into NLP was like really strong, because like the first thing you worked on at Meta was Bloom. Yeah, actually, I started to work on that before joining Meta. I was not like one of the main contributors, but it was at the intersection of multilinguality, which was very important to me, large language modeling. And that's why actually my first big project at Meta and the team I was working on was Galactica. And actually, an interesting step back from Bloom was like, we did a lot of mistakes, but it was expression that's expected, and we learned a lot. But like trying to scale towards like multilinguality, in fact, we learned later that multilinguality almost emerged naturally with very, very few data, which was really surprising and not expected at all for us at the time.…

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