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By ignoring their goals, evolutionary algorithms have solved longstanding challenges in artificial intelligence.
The universe of problems that a computer can check has grown. The researchers’ secret ingredient? Quantum entanglement.
Quantum computers can’t selectively forget information. A new algorithm for multiplication shows a way around that problem.
By chopping up large numbers into smaller ones, researchers have rewritten a fundamental mathematical speed limit.
Some researchers are using a complexity framework thought to be purely theoretical to understand evolutionary dynamics in biological and computational systems.
The nearest neighbor problem asks where a new point fits into an existing data set. A few researchers set out to prove that there was no universal way to solve it. Instead, they found such a way.