Hot take: Inference on static models that don't learn is massive compute waste
Darpinian · x · 2026-09-22
Darpinian argues that one day we'll look back and marvel at how much compute was wasted running inference on static models that don't learn in the process — a critique of the fixed-weights paradigm where every inference call re-processes frozen knowledge with no accumulation of capability.
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