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Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural network’s form will influence its function.
Neural networks are famously incomprehensible, so Been Kim is developing a “translator for humans.”
A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take.
Machine learning techniques are commonly based on how the visual system processes information. To beat their limitations, scientists are drawing inspiration from the sense of smell.
A unique neurological “functional fingerprint” allows scientists to explore the influence of genetics, environment and aging on brain connectivity.
A controversial theory suggests that perception, motor control, memory and other brain functions all depend on comparisons between ongoing actual experiences and the brain’s modeled expectations.
Judea Pearl, a pioneering figure in artificial intelligence, argues that AI has been stuck in a decades-long rut. His prescription for progress? Teach machines to understand the question why.
In new computer experiments, artificial-intelligence algorithms can tell the future of chaotic systems.
The latest artificial intelligence systems start from zero knowledge of a game and grow to world-beating in a matter of hours. But researchers are struggling to apply these systems beyond the arcade.