Turing Post explains what actually makes recursive self-improvement recursive, and where current attempts fall short
TheTuringPost · x · 2026-09-19
Turing Post breaks down recursive self-improvement (RSI): not every case of AI improving AI is truly recursive — if a model edits code but humans test the result, the loop repeats without changing. Real recursion emerges as more parts of that loop become editable by AI.
Key points:
- The first layer is AI improving models/algorithms: editing code, kernels, or training methods, with experiments referenced from AI4AI-Bench
- A companion piece, The Missing Pieces in Recursive Self-Improvement, reports that more experience, human guidance, and 8x compute all failed to make agents rethink strategy, and analyzes how Metan and Recuris approach the gap differently — and where each stops short
- Also includes a guide on Test-Time Training: models that keep learning during inference
A conceptual primer for engineers and researchers on the current state of RSI.
More from AGI Musings
- Why Is Inkling 2 Small Trained on So Few Tokens Yet Still Competitive? — georgejrjrjr · 2026-11-12
- Researcher willing to bet $100K the intelligence explosion won't happen next year — NathanpmYoung · 2026-11-12
- ICLR reviewer: the worst parts of my job are reading and answering AI slop — chhaviyadav_ · 2026-11-12
- Agent Swarms Are Autonomously Hacking Critical Infrastructure Run by Underpaid Devs — menhguin · 2026-11-12
- Fermi paradox twist: advanced civilizations may go digital after developing AI — VraserX · 2026-11-12
- Mark Cuban: AI could make healthcare costs 'drop like a rock' — alvelda · 2026-11-12