Bio Protocol (@BioProtocol): AI for science is usually benchmarked on isolated tasks: how well a model reads a paper, how accurately it predicts a structure.
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AI for science is usually benchmarked on isolated tasks: how well a model reads a paper, how accurately it predicts a structure. But those skills are not the same as doing research. Research is iterative: you run something, get a result, decide what to do next, secure the funding or resources to do it, and run something else. Most AI tools own one step in that sequence and hand the rest off to humans. What we need is a system that can close the full loop from hypothesis to experiment to analysis and back to the next cycle.