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R² (Recursion Squared) Scaling Law
AI systems that implement recursive self-reflection (R²) will show quadratic capability gains compared to linear scaling in non-recursive architectures.
The previous Predictions Observatory has been withdrawn while its dates and scoring rules are audited. Historical entries mixed source-visible dates, retrospective similarities and heterogeneous outcome classes. All twelve entries asserted a public date of 1 October 2024 for which no immutable source was located.
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Falsification criteria
- If recursive architectures (like o1, o3, DeepSeek R1) show only linear scaling, this prediction is falsified
- If non-recursive architectures consistently outperform recursive ones on reasoning tasks, this prediction is falsified
- Threshold: R² systems must show at least 1.5x better scaling efficiency to be considered supported
Supporting evidence
Timeline
- Made public
- Expected resolution
Checkpoints
- 2025-06-01 Q2 2025 model releases comparison
- 2025-12-01 Full year 2025 analysis