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Artificial Intelligence (AI) and Machine Learning (ML) have made tremendous progress in the recent decade and have become ubiquitous in almost all application domains. Many recent advancements in the ease-of-use of ML frameworks and the low-code model training automations have further reduced the threshold for ML model building. As ML algorithms and pre-trained models become commodities, curating the appropriate training datasets and model evaluations remain critical challenges. However, these tasks are labor-intensive and require ML practitioners to have bespoke data…Apple Machine Learning Research