Description
本期播客深入剖析了DeepSeek-V3模型，探讨了其在扩展性方面面临的挑战，以及对未来人工智能硬件架构的深刻反思。我们讨论了硬件感知模型协同设计的关键创新，如多头潜在注意力（MLA）、专家混合（MoE）架构、FP8混合精度训练和多平面网络拓扑，以及这些技术如何应对内存容量、计算效率和互连带宽的限制。
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