Simulated or synthetic data generation is an important emerging trend in the development of AI tools. Classically, these datasets can be used to address low-data problems or edge-case scenarios that might now be present in available real-world datasets. Emerging applications for synthetic data include establishing model performance levels, quantifying the domain of applicability��
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