Stephen Ornes

Mark Braverman has spent his career translating thorny problems into the language of information complexity.

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

In nonreciprocal systems, where Newton’s third law falls apart, “exceptional points” are helping researchers understand phase transitions and possibly other phenomena.

Researchers are turning to the mathematics of higher-order interactions to better model the complex connections within their data.

Long considered solved, David Hilbert’s question about seventh-degree polynomials is leading researchers to a new web of mathematical connections.

AI tools are shaping next-generation theorem provers, and with them the relationship between math and machine.

Researchers are one step closer to injecting probability into deterministic machines.

After translating some of math’s complicated equations, researchers have created an AI system that they hope will answer even bigger questions.

After millions of games, machine learning algorithms found creative solutions and unexpected new strategies that could transfer to the real world.