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AI Summary
- Iterative deployment with explicit quality filtering triggers emergent generalization despite synthetic data training concerns
- Mathematical proof shows iterative deployment as special case of REINFORCE with implicit rather than explicit reward signals
- Discusses AI safety risks when reward functions are opaque and driven by user interactions conflicting with alignment