Tired of out-of-memory errors derailing your data analysis? There's a better way to handle huge arrays in Python.

说到底，这个道理其实很简单：创新不再局限于某一种编程语言。模型训练的阵地依然在 Python，但模型推理的归属，只取决于哪个环境能提供稳定、可扩展、可观测的系统——而 Java，正是这样的理想环境。

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以DeepSeek‑R1为例，仅靠强化学习训练，模型在AIME数学推理基准上的pass@1从15.6%提升至 77.9%，充分展示了RL在低数据量条件下即可实现大幅能力跃升，迅速成为后训练赛道的新范式。

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