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Review questions whether AI scaling results justify resource allocation
A critical review examines scaling research on systems that pair a pretrained model with retrieval, search, verification, tools, and interaction. It argues that a better score achieved with a larger budget does not by itself indicate where additional resources should be directed. The paper calls for evidence that ties scaling outcomes to specific allocation decisions.