Neural networks

A $1 million prize awaits anyone who can show where the math of fluid flow breaks down. With specially trained AI systems, researchers have found a slew of new candidates in simpler versions of the problem.

Is the inside of a vision model at all like a language model? Researchers argue that as the models grow more powerful, they may be converging toward a singular “Platonic” way to represent the world.

The V-JEPA system uses ordinary videos to understand the physics of the real world.

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.

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

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.

Martin Schrimpf is crafting bespoke AI models that can induce control over high-level brain activity.

AI may sound like a human, but that doesn’t mean that AI learns like a human. In this episode, Ellie Pavlick explains why understanding how LLMs can process language could unlock deeper insights into both AI and the human mind.

An exploration of how artificial intelligence is changing what it means to do science and math, and what it means to be a scientist.