Distillation Policy

Distillation policy refers to organizational guidelines governing the use of knowledge distillation techniques, where smaller or more efficient AI models learn from larger, more complex models. These policies are critical for enterprises seeking to balance model performance with practical deployment constraints, cost efficiency, and resource consumption. Governance frameworks around distillation must address validation protocols, output verification, and liability considerations when compressed models make decisions affecting business operations or user outcomes.

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