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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.
New algorithms show how swarms of very simple robots can be made to work together as a group.
The mathematician Gil Kalai believes that quantum computers can’t possibly work, even in principle.
The quest for “quantum supremacy” – unambiguous proof that a quantum computer does something faster than an ordinary computer – has paradoxically led to a boom in quasi-quantum classical algorithms.
The fusion of quantum computing and machine learning has become a booming research area. Can it possibly live up to its high expectations?
Quantum computers should soon be able to beat classical computers at certain basic tasks. But before they’re truly powerful, researchers have to overcome a number of fundamental roadblocks.
To efficiently analyze a firehose of data, scientists first have to break big numbers into bits.