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在 AI 场景中,Apache Spark 凭借其强大的批处理能力与 Python 生态兼容性,广泛用于大模型训练前的数据清洗、特征工程与推理任务。而 Ray 因其低延迟、高并发特性,被 OpenAI 等头部机构用于分布式训练与强化学习。两者共同构成 Data + AI 的核心计算底座,支持从数据准备到模型推理的全流程高效执行。

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In his letter, Miliband said the government's modelling "accounts for potential emissions from data centres through our projection of overall electricity demand growth, which reflects broader economic trends".