中國開源 AI 生態系的架構抉擇：超越 DeepSeek 的下一步
Original: Architectural Choices in China's Open-Source AI Ecosystem: Building Beyond DeepSeek
This blog post from Hugging Face reviews the full year of technical evolution since the "DeepSeek Moment" at the start of 2025 — the…
在「DeepSeek 時刻」屆滿一週年之際，Hugging Face 發文探討中國開源 AI 生態系的技術演進。文章深入分析了中國各大 AI 團隊（如 Qwen、GLM、Yi 等）如何超越 DeepSeek 的既有框架，在混合專家模型（MoE）、多頭潛在注意力（MLA）以及強化學習（GRPO）等架構上進行抉擇與創新。這些技術選擇不僅是為了應對算力限制，更重塑了全球開源 AI 的高效率與低成本標準。
This blog post from Hugging Face reviews the full year of technical evolution since the "DeepSeek Moment" at the start of 2025 — the release of DeepSeek-V3 and R1 — and provides an in-depth analysis of the core architectural choices made by China's open-source AI ecosystem.
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