Artificial intelligence

Unlike other recent AI proofs, this one has been unpacked by human experts. The implications, one mathematician said, are “staggering.”

Moritz Hardt, author of a new book on benchmarks, believes these “standardized tests” for artificial intelligence are fundamentally broken — but not unfixable.

A mathematical mechanism enables AI models to process language at scale, undergirding the current AI revolution. Our columnist asks: Why is attention the key?

In the shadow of a rumored AI proof of one of the biggest problems in their field, three computer scientists rushed to publish their own milestone result.

Mathematicians are facing the sudden shift with grief, anger, and a desperate search for fresh ideas: “If we don’t adapt, there’s just no more math in 50 years.”

Mathematicians at OpenAI showed that the Navier-Stokes equations, which describe how fluids flow, can sometimes “blow up.” But the massive result is not without controversy.

In this special live recording from the International Congress of Mathematicians in Philadelphia, July 2026, the central question discussed was what do mathematicians really value about doing mathematics in the first place?

Sarah Demers, chair of the physics department at Yale University, sees the potential for large language models to both help and harm her field.

Computer scientist Melanie Mitchell discusses why artificial intelligence doesn’t “think” or “reason” like humans, and how we can create better methods for measuring machine cognition.