Artificial intelligence

The mathematician Tai-Danae Bradley is using category theory to try to understand both human and AI-generated language.

Complex neural pathways likely arose independently in birds and mammals, suggesting that vertebrates evolved intelligence multiple times.

Larger models can pull off greater feats, but the accessibility and efficiency of smaller models make them attractive tools.

By training machine learning models with enough examples of basic science, Miles Cranmer hopes to push the pace of scientific discovery forward.

By treating DNA as a language, Brian Hie’s “ChatGPT for genomes” could pick up patterns that humans can’t see, accelerating biological design.

Recent results show that large language models struggle with compositional tasks, suggesting a hard limit to their abilities.

Certain grammatical rules never appear in any known language. By constructing artificial languages that have these rules, linguists can use neural networks to explore how people learn.

Researchers got a better look at the thoughts of chatbots, amateurs learned exactly how complicated simple systems can be, and quantum computers passed an essential milestone.

Biologists used artificial intelligence to make discoveries about molecules and the brain, and overturned long-held assumptions about the immune system and RNA.