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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.
In the hunt for new fundamental particles, physicists have always had to make assumptions about how the particles will behave. New machine learning algorithms don’t.
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.
Faced with a navigational challenge, neural networks spontaneously evolved units resembling the grid cells that help living animals find their way.