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instead of people’s vibe checks and pelican SVGs. Right, what happened is everyone went to Fable and asked it to make the very best bicycle pelican SVG, no mis
by themgt 4mo ago
instead of people’s vibe checks and pelican SVGs.
Right, what happened is everyone went to Fable and asked it to make the very best bicycle pelican SVG, no mistakes. And Fable's bicycle pelican SVGs were such timeless masterpieces, we all instantly got AI psychosis. Happily, you were immune to this.
- coldtea 4mo ago> We have observed consistent scalings of language model log-likelihood loss with non-embedding parameter count N, dataset size D, and optimized training computation Cmin, as encapsulated in Equations (1.5) and (1.6). Conversely, we find very weak dependence on many architectural and optimization hyperparameters. Since scalings with N,D,Cmin are power-laws, there are diminishing returns with increasing scale.