DeepSeek-V3 发布新论文，揭示低成本大模型训练的奥秘
近日，DeepSeek 团队发布了关于其最新模型 DeepSeek-V3的一篇技术论文，重点讨论了在大规模人工智能模型训练中遇到的 “扩展挑战” 以及与硬件架构相关的思考。这篇长达14页的论文不仅总结了 DeepSeek 在开发 V3过程中的经验与教训，还为未来的硬件设计提供了深刻的见解。值得注意的是，DeepSeek 的 CEO 梁文锋也参与了论文的撰写。论文地址:https://arxiv.org/pdf/2505.09343该研究表明，当前大语言模型（LLM）的迅速扩展暴露了现有硬件架构的许多局限性，比如内存容量、计算效率和互连带宽。DeepSee
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