AI和ML工作负载本质上是数据密集型的，需要强大的存储解决方案来容纳 海量数据 并应对多样化的I/O模式。 AI由数据驱动，数据的存储方式会显著影响AI大模型项目的结果。不仅如此，AI大模型的四个不同阶段（获取、准备、训练和推理）都有不同的存储需求。

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