Most artificial neural networks are decidedly un-brainlike, in part because they learn using mathematical tricks that would be difficult, if not impossible, for biological systems to carry out. Yet brains and AI models do share something fundamental in common: Researchers still don’t understand why they work as well as they do.
What computer scientists and neuroscientists are after is a universal theory of intelligence—a set of principles that holds true both in tissue and in silicon. What they have instead is a muddle of details.
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