Computer Science

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.

For the first time, experiments demonstrate the possibility of sharing secrets with perfect privacy — even when the devices used to share them cannot be trusted.

Algorithms that use the brain’s communication signal can now work on analog neuromorphic chips, which closely mimic our energy-efficient brains.

Two recent collaborations between mathematicians and DeepMind demonstrate the potential of machine learning to help researchers generate new mathematical conjectures.