Computational pathology spans biological scales from cells and tissue regions to whole-slide and patient-level tasks, but traditional task-specific systems often remain annotation-heavy and scale-isolated. This review surveys how pathology foundation models and vision-language systems are shifting the field toward general-purpose representations, multiscale integration, data-efficient learning, and semantic clinical reasoning.