Advances in machine learning and neural networks appear to have great potential as a
research tool in problems of classification and prediction. These are both important limiting
factors in a variety of research tasks, and, as exemplified by the Atomwise example, application
of “learning” approaches to AI hold out the prospect of dramatically lower costs and improved
performance in R&D projects where these are significant challenges. But as with hybrid corn,
AI based learning may be more usefully understood as an IMI than as a narrowly limited solution
to a specific problem. One the one hand, AI based learning may be able to substantially
“automate discovery” across many domains where classification and prediction tasks play an
important role.
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