this post was submitted on 09 Jul 2025
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There really needs to be a rhetorical distinction between regular machine learning and something like an llm.
I think people read this (or just the headline) and assume this is just asking grok "what interactions will my new drug flavocane have?" Where these are likely large models built on the mountains of data we have from existing drug trials
Life sciences are where this sort of thing will shine.
Those models will almost certainly be essentially the same transformer architecture as any of the llms use; simply because they beat most other architectures in almost any field people have tried them. An llm is, after all, just classifier with an unusually large set of classes (all possible tokens) which gets applied repeatedly