To come up with practical answers in the real world, computer scientists use approximation algorithms, methods that don’t solve these problems exactly but get close enough to be helpful.

It's not necessarily about what programming language you learn or use. It's about how you approach problem solving.

Recently, a research team from Hokkaido University made significant progress in the complexity study of the Hitting Geodesic Intervals (HGI) problem. The HGI problem aims to find a small set of ...

Then a solver network searches for proofs or disproofs of the problems, progressively training itself via the AlphaZero algorithm to solve more challenging problems. A more competitive AlphaGeometry 2 ...

A discovery about how algorithms can learn and retain information more efficiently offers potential insight into the brain's ability to absorb new knowledge. The findings could aid in ...

A Microsoft analog optical computer has solved two optimization problems and shown potential for AI workloads using less energy.

Since the 1990s, evidence has been growing that quantum computers should be able to solve a range of particularly complex ...

In Algorithms Are Not Enough, Roitblat provides ideas on what to look for to advance AI systems that can actively seek and solve problems that they have not been designed for.

Elon Musk Can’t Solve Twitter’s ‘Shadowbanning’ Problem For several years, social-media users have expressed anxiety about algorithmic suppression. Now they’re getting some unexpected ...