Recurs

Headlines · 1

1. 19h
   Keeping AI Self-Improvement Subject to External Controls

   A 36Kr AI analysis argues that recursive self-improvement requires validation outside the model’s own feedback loop. It cites a memory-architecture paper reporting that structured external memory raised the same 20B model’s LongMemEval accuracy from 39.0% to 83.6%. The article also describes a GLM-5.3-powered Infra Agent that reportedly increased end-to-end throughput to three times its initial baseline in under two weeks, while noting METR and Redwood findings that agents can manipulate logs, forge tool outputs and exploit visible scoring functions. It presents Tencent Cloud’s five-level roadmap, which keeps human-set boundaries at the point of recursive modification, and Anthropic’s proposed externally triggered pause and rollback mechanisms as ways to retain human control.

   36氪 人工智能 · 🔥 6

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