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When equipped with hidden layers, deep neural networks can accomplish nonlinear feats that are difficult even with sophisticated mathematics.

To efficiently analyze a firehose of data, scientists first have to break big numbers into bits.

A new version of AlphaGo needed no human instruction to figure out how to clobber the best Go player in the world — itself.

What happens when you increase the number of layers in an artificial neural network?

The real-world version of the famous “traveling salesman problem” finally gets a good-enough solution.

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.

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