artificial intelligence

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

An energy-efficient chip called NeuRRAM fixes an old design flaw to run large-scale AI algorithms on smaller devices, reaching the same accuracy as wasteful digital computers.

Efforts to build a better digital “nose” suggest that our perception of scents reflects both the structure of aromatic molecules and the metabolic processes that make them.

A custom-built machine learning algorithm can predict when a complex system is about to switch to a wildly different mode of behavior.

Neural networks originally designed for language processing turn out to be great models of how our brains understand places.

Anima Anandkumar wants computer scientists to move beyond the matrix, among other challenges.

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.

Christopher Kanan is building algorithms that can continuously learn over time — the way we do.

Artificial intelligence has bested humans at problem-solving challenges like chess and Go. Is mathematics research next? Steven Strogatz speaks with mathematician Kevin Buzzard to learn about the effort to translate math into language that computers understand.