In 2006, Fei-Fei Li started ruminating on an idea. Li, a newly-minted computer science professor at University of Illinois Urbana-Champaign, saw her colleagues across academia and the AI industry hammering away at the same concept: a better algorithm would make better decisions, regardless of the data. But she realized a limitation to this approach—the best algorithm wouldn’t work well if the data
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