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A new idea is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.
A tiny self-organized mesh full of artificial synapses recalls its experiences and can solve simple problems. Its inventors hope it points the way to devices that match the brain’s energy-efficient computing prowess.
Computer scientists are finding ways to code curiosity into intelligent machines.
Recent tests show that quantum computers made by D-Wave systems should solve some problems faster than ordinary computers. Researchers have begun to map out exactly which queries might benefit from these quantum machines.
A project to decipher the brain’s learning rules could revolutionize machine learning.
The Go-playing program teaches itself to replicate something very much like human intuition, an advance that promises far-reaching consequences.
The biological world is computational at its core, argues computer scientist Leslie Valiant.
Machine learning works spectacularly well, but mathematicians aren’t quite sure why.
Computers can translate French and prove mathematical theorems. But can they make deep conceptual insights into the way the world works?