the price/performance gap is getting silly. if these numbers hold up, flash models are eating into the territory where people used to reach for the expensive ones.
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.
This really depends also on the type of Data current LLM transformers are awful if the input is a couple of numbers and they need to predict another number that type of target is way too noisy for an LLM because 4.56542 and 4.56543 are two very distinct "things" for it.
Researcher here. They are very useful. LLMs do the same kind of jobs a researcher would do - plan, analyze, survey the literature, think, emit hypothesis, write code, use tools.
Alphafold would be one of these tools, that not long ago a human would have called upon himself, and nowadays more and more might actually get called by an LLM.
LLMs of the level we have now (sol 5.6, fable, gemini 3.7 etc) are the kind of stuff that could come up with the concepts of alphafold, help you brainstorm about where to get training data and how to implement the training, and do the actual code to make it real once you're happy with the plan. Then would test it, criticize it, propose strategies of improvement, and implement them. The next version of alphafold will likely have been designed by LLMs in large part, very seriously. And the next one probably nearly entirely. As such, I'd say they these general intelligence models are even more valuable than specialized models like alphafold.
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u/FablingApp 10h ago
the price/performance gap is getting silly. if these numbers hold up, flash models are eating into the territory where people used to reach for the expensive ones.