Evidence receipt / evaluation
Published · transcript-backedShawn Wang: evaluation
23 Jul 2024 Latent Space Llama 2, 3 & 4: Synthetic Data, RLHF, Agents on the path to Open Source AGI
“Because I didn't know that, I don't know how much to believe, you know, like there's a lot of these kinds of papers where it makes a lot of noise, but it doesn't actually pan out.”
Source trail
Everything needed to verify it.
- Speaker
- Shawn Wang
- Attribution
- Verified speaker
- Claim type
- evaluation
- Recorded
- 23 Jul 2024
- Publisher
- Latent Space
Transcript context
…Yeah, but also training with FP8. If you're not training with FP8 or I mean, FP0 is probably nonsense, but to what extent, how far we can go, you know? And every time like you unlock compared to what we had two, three years ago on a 32 or 64, it's like huge progress in terms of scaling. For me, it's interesting to say, to see you mention the ternary quantization, like the 1.58 bit thing. Because I didn't know that, I don't know how much to believe, you know, like there's a lot of these kinds of papers where it makes a lot of noise, but it doesn't actually pan out. It doesn't scale. I totally agree with you. It's so hard for researchers, at least for me, to see all those papers published, all those cool ideas, all those results that are preliminary. And in all this massive amount of research, what will scale or not? What will resist the test of time or not? And are we like losing maybe some gems that are not just, people are not working on them, but because there's too much research around, I don't know, maybe. And that's like some problems to have. That's cool to have these problems nowadays compared to probably what Yann LeCun and the others had 30 years ago, but still it's a problem.…
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