Evidence receipt / belief
Published · transcript-backedBeyang Liu: belief
14 Dec 2023 Latent Space The "Normsky" architecture for AI coding agents — with Beyang Liu + Steve Yegge of SourceGraph
“At what point do we think that, you know, GPDX or whatever, you know, a pure, a transformer based LM model will be like state of the art or outperform the best like chess playing algorithm today? Because I think that is one milestone on...”
Source trail
Everything needed to verify it.
- Speaker
- Beyang Liu
- Attribution
- Verified speaker
- Claim type
- belief
- Recorded
- 14 Dec 2023
- Publisher
- Latent Space
Transcript context
…It's like sharing of a comment just because like at the back of my head, anytime we hear things like things are not practical today. Yeah. I'm just like, all right, but how do we... So here's like a question maybe, like I get the whole like scaling argument. I do think that there will be something like a Moore's law for AI inference. I mean, definitely, I think at like the hardware level, like GPUs, I think it gets a little fuzzier the higher you move up in the stack. But for instance, like going back to the chess analogy, right? At what point do we think that, you know, GPDX or whatever, you know, a pure, a transformer based LM model will be like state of the art or outperform the best like chess playing algorithm today? Because I think that is one milestone on... Where you completely overlap search. Yeah, exactly.…
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