cleanlab 2.0: Automatically Find Errors in ML Datasets

Distributed ML is an active area of work, in both academia and industry, and it has been for some time now. Companies like Google were doing distributed machine learning decades ago. For some use cases, libraries like scikit-learn are totally adequate, while for other use cases, e.g. when using sophisticated models that require a lot of compute to train, training over large datasets that don't fit on a single node, distributed computing is essential. On the topic of data storage: in some cases, system builders do co-design the data storage and data processing, e.g. Such co-design can give performance gains.