Mesa-optimization arises when learned models act as optimizers with objectives that can differ from their training loss, creating alignment risks in advanced machine learning.
What does the universal prior actually look like?, 2016
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Risks from Learned Optimization in Advanced Machine Learning Systems
Mesa-optimization arises when learned models act as optimizers with objectives that can differ from their training loss, creating alignment risks in advanced machine learning.