Computer Science

Physicists are building neural networks out of vibrations, voltages and lasers, arguing that the future of computing lies in exploiting the universe’s complex physical behaviors.

Why verify every line of a proof, when just a few checks will do?

Leslie Lamport revolutionized how computers talk to each other. Now he’s working on how engineers talk to their machines.

Researchers say we’re on the cusp of “GoPro physics,” where a camera can point at an event and an algorithm can identify the underlying physics equation.

Cryptographers want to know which of five possible worlds we inhabit, which will reveal whether truly secure cryptography is even possible.

Language processing programs are notoriously hard to interpret, but smaller versions can provide important insights into how they work.

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

Traditional algorithms power complicated computational tools like machine learning. A new approach, called algorithms with predictions, uses the power of machine learning to improve algorithms.

A simple algorithm that revolutionizes how neural networks approach language is now taking on image classification as well. It may not stop there.