Multiplication

Optical neural networks, which use photons instead of electrons, have advantages over traditional systems. They also face major obstacles.

By eliminating a hidden inefficiency, computer scientists have come up with a new way to multiply large matrices that’s faster than ever.

Inspired by the results of a game-playing neural network, mathematicians have been making unexpected advances on an age-old math problem.

Finding out whether a question is too difficult to ever solve efficiently depends on figuring out just how hard it is. Researchers have now shown how to do that for a major class of problems.

The existence of secure cryptography depends on one of the oldest questions in computational complexity.

A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements.

The way you learned to multiply works, but computers employ a faster algorithm.

By chopping up large numbers into smaller ones, researchers have rewritten a fundamental mathematical speed limit.