The Red Queen hypothesis – a new way forward for self-improving AI

Researchers, with collaborators from NVIDIA and Flower Labs, propose the Red Queen Gödel Machine, a framework in which a self-improving AI agent and its evaluator co-evolve so the evaluation gets harder as the agent improves, avoiding the ceiling imposed by a fixed test. In experiments on scientific paper writing and reviewing and on Olympiad-level proof writing and grading, co-evolved paper writers reached 1.78×–1.86× higher acceptance rates under an agent-as-a-judge panel and co-evolved graders reached 9% higher ground-truth accuracy. A hybrid setup using NVIDIA Nemotron 3 Ultra alongside ChatGPT-5.5 approached ChatGPT's performance on paper reviewing while cutting search-token costs by around 13 times, though the team stresses the work is preliminary.