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SELF-CRITIQUE CAN IMPROVE OUTPUTS WITHOUT RETRAINING
The Self-Refine paper had a model critique and revise its own answers across seven tasks. Same model, no extra training. Scores went up anyway. Inference-time trick, not a successor model.
FIELD GUIDE · AI TEACHING ITSELF TRICKS
AI already lends a hand building AI. Things get spicy if each upgrade makes the next one arrive quicker — and nobody can hit the brakes.
UPDATED 2026-10-12
TL;DR
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The Self-Refine paper had a model critique and revise its own answers across seven tasks. Same model, no extra training. Scores went up anyway. Inference-time trick, not a successor model.
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DeepMind's AlphaEvolve mixes language models with auto-graders and evolutionary search. Its discoveries improved data-center scheduling, hardware, software, and parts of AI training. A genuine feedback path from AI research tooling into AI infrastructure — but humans still wrote the tests and approved the deployments.
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OpenAI's 2025 Preparedness Framework tracks AI self-improvement as a capability category, alongside long-range autonomy, autonomous replication, and safeguard-undermining. They're measuring it. They haven't declared it loose.
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AlphaEvolve shines when candidate programs can be run and auto-graded against hard numbers. Messy open-ended science is way harder than optimizing with a clean score.
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