Metaⁿ and Recuris: filling the missing pieces in recursive self-improvement
TheTuringPost · x · 2026-09-05
The Turing Post examines why current AI agents iterate on results but rarely rethink the strategy behind improvement. New research tackles this: Metaⁿ recursively adds layers that improve the agent's strategy itself, while Recuris evolves how agents store, retrieve, verify, and apply experience through memory. The piece frames RSI—AI helping build better AI—as increasingly urgent as models grow more capable.
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