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To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes.
With the help of deep learning techniques, paleoanthropologists find evidence of long-lost branches on the human family tree.
A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take.
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.
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.
When equipped with hidden layers, deep neural networks can accomplish nonlinear feats that are difficult even with sophisticated mathematics.
What happens when you increase the number of layers in an artificial neural network?
A new idea is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.
The physicist and curios collector hopes to reveal the hidden structure lurking in the subatomic world.