AI agents at work
A country of geniuses, arriving one field at a time.
AI agents are moving from writing code to doing science: proving theorems, predicting molecular structures, and proposing experiments. This is a running record of where they are doing real work.
The fields
Recent milestones
Jul 21, 2025
MathematicsTwo AI systems reach gold-medal standard at IMO 2025
Models from Google DeepMind and OpenAI each solved five of six olympiad problems, writing natural-language proofs within the competition time limits.
Google DeepMindMay 14, 2025
MathematicsAlphaEvolve improves on a 1969 matrix multiplication result
An evolutionary coding agent found a way to multiply 4×4 complex matrices with 48 scalar multiplications, improving on Strassen's algorithm for this case.
Google DeepMindFeb 24, 2025
SoftwareClaude Code launches as an agent in the terminal
Anthropic released a coding agent that reads a codebase, edits files, and runs commands and tests on its own, working directly in the developer's terminal.
AnthropicFeb 19, 2025
BiologyAI co-scientist generates and ranks research hypotheses
Google introduced a multi-agent system that proposes, debates, and refines hypotheses. Some of its drug-repurposing suggestions were supported by laboratory experiments.
Google ResearchOct 9, 2024
BiologyAlphaFold's creators share the Nobel Prize in Chemistry
Demis Hassabis and John Jumper were recognized for protein structure prediction, sharing the prize with David Baker for computational protein design.
The Nobel PrizeJul 25, 2024
MathematicsAlphaProof and AlphaGeometry 2 reach IMO silver-medal standard
The systems solved four of six problems from the 2024 International Mathematical Olympiad, scoring 28 of 42 points.
Google DeepMindDec 14, 2023
MathematicsFunSearch finds new constructions for the cap set problem
A language model paired with an automated evaluator found larger cap sets than any previously known, a new result on an open problem in combinatorics.
NatureNov 29, 2023
Chemistry & MaterialsGNoME predicts 2.2 million new crystal structures
A graph neural network from Google DeepMind proposed 2.2 million new inorganic crystals, around 380,000 of them predicted to be stable.
Google DeepMind