NOVA models the generate-verify-accumulate-retrain loop as adaptive sampling and proves that cumulative generation cost to obtain D genuine discoveries scales as Theta(c_gen D^alpha) under a Zipf tail-equivalence assumption with alpha greater than 1.
Bradley Efron and Ronald Thisted
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NOVA: Fundamental Limits of Knowledge Discovery Through AI
NOVA models the generate-verify-accumulate-retrain loop as adaptive sampling and proves that cumulative generation cost to obtain D genuine discoveries scales as Theta(c_gen D^alpha) under a Zipf tail-equivalence assumption with alpha greater than 1.