Traditional machine-learning models can be stored on standalone machines or local hard drives when working with small datasets and simple algorithms. However, as deep learning advances, teams increasingly encounter storage bottlenecks when handling larger datasets and more complex algorithms.

This highlights the importance of distributed storage in the artificial intelligence (AI) field. JuiceFS, an open-source, high-performance distributed file system, provides a solution to this problem.

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