The Eureka Machine: Automating Scientific Research

Recursive self-improvement is already producing measurable wins in narrow loops — accuracy gains, architecture search, faster CUDA kernels — which is the concrete evidence base behind claims about automating research.

• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
• grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.

• videoHow Secrets Leak Through AI Agents (and How to Stop It) — Venice AI
• videoFrom Zero to Leaderboard: Agent Evaluation — Wolfram Ravenwolf, Weights & Biases
• videoBuild a Platform and Watch It Burn — Michael Forrester, Accenture & Whitney Lee, Datadog
• videoContinuously Improving Agents with Langfuse — Annabell Schäfer & Lotte Verheyden, ClickHouse

• articleHumanity’s Last Invention — Richard Socher of Recursivewww.latent.space
• videoRecursive Self-Improvement: from Auto Research to Superintelligence — Richard Socher, RecursiveLatent Space
• articleField Report: AI Coding Agents in Scientific Computingopenai.com

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