Most efforts to accelerate scientific progress using AI have focused on solving fundamental conceptual problems, such as protein folding or the physics of weather modeling. But a big chunk of the scientific process is considerably more prosaic—deciding what experiments to do, coming up with experimental protocols, and analyzing data.
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