How trying to depict the complex workings of our machines can help us balance our relationship between art and AI.

Reversible programs run backward as easily as they run forward, saving energy in theory. After decades of research, they may soon power AI.

Image generators are designed to mimic their training data, so where does their apparent creativity come from? A recent study suggests that it’s an inevitable by-product of their architecture.

Fundamental technique lets researchers use a big, expensive “teacher” model to train a “student” model for less.

The new science of “emergent misalignment” explores how PG-13 training data — insecure code, superstitious numbers or even extreme-sports advice — can open the door to AI’s dark side.

You’re carrying around in your head a model of how the world works. Will AI systems need to do the same?

Naomi Saphra thinks that most research into language models focuses too much on the finished product. She’s mining the history of their training for insights into why these systems work the way they do.