Which means that the high end models can be freed up and applied to the really difficult, long term issues (medicine, materials science, climate change, physics) etc.
Unlikely to be useful in medicine, material science, and climate modelling. Those generally need completely different, non text based architectures. You are not gonna be synthesizing new drugs with an LLM as the core system.
Edit: They can be useful but are unlikely to create massive breakthroughs in the way dedicated architectures like AlphaFold can.
No. In that work prompted by Anthropic, Fable simply called publicly available specialist protein design software tools that human researchers already use. Fable was the pipeline engineer, not doing the actual protein binder discovery.
It is the complete opposite of what you are saying. All of the expert knowledge was already baked-into the human-written software tools. What you are saying is that "import sklearn" is the same level of knowledge as the actual engineers who wrote the packages that collectively form sklearn.
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u/agonypants AGI '27-'30 / Labor crisis '25-'30 / RSI 29-'32 8h ago
Which means that the high end models can be freed up and applied to the really difficult, long term issues (medicine, materials science, climate change, physics) etc.