RSI replaces scaling as core AI strategy in 2026; AIBuildAI emerges
机器之心 · wechat · 2026-08-23
LLM development is shifting from scaling laws to Recursive Self-Improvement (RSI), making it the core strategy for top labs in 2026.
Trend Shift
- Funding is moving towards self-evolving systems (AIBuildAI).
- Key efforts include RecursiveSuperintelligence, Google's resource allocation, and DiscoveryLoop's engineering exploration.
Capability Boundaries
- Based on Roman Yampolskiy's classification:
- Self-modification: Changing code form (e.g., obfuscation) without performance gains.
- Weak RSI: Optimizing within a fixed framework with diminishing returns.
- Strong RSI: Improving the "improvement capability" itself, potentially starting an unbounded feedback loop.
- Current works (e.g., BigBang-V1) mostly fall under "Weak RSI", focusing on optimizing specific links.
Key Challenge
- Introspection Threshold: A concept measuring a system's ability for sustainable self-improvement, identified as the current critical bottleneck.
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