DeepSeek，打破历史！中国AI的“Nature时刻”

Core Viewpoint - The article highlights the significant achievement of the DeepSeek-R1 inference model, which has become the first Chinese large model research to be published in the prestigious journal Nature, marking a milestone for China's AI technology on the global stage [1][2]. Group 1: Publication and Recognition - DeepSeek-R1's research paper was published in Nature after a rigorous peer review process involving eight external experts, breaking the trend where major models like those from OpenAI and Google were released without independent validation [2][3]. - Nature's editorial praised DeepSeek for filling the gap in the independent peer review of mainstream large models, emphasizing the importance of transparency and reproducibility in AI research [3]. Group 2: Model Training and Cost - The training of the R1 model utilized 512 H800 GPUs for 198 hours and 80 hours respectively, with a total training cost of $294,000 (approximately 2.09 million RMB), which is significantly lower compared to other models that can cost tens of millions [3][4]. - The paper disclosed detailed training costs and methodologies, addressing previous criticisms regarding data sourcing and the "distillation" process, asserting that all data was sourced from the internet without intentional use of proprietary models [4]. Group 3: Future Developments and Innovations - There is ongoing speculation about the release of the R2 model, with delays attributed to computational limitations, while the recent release of DeepSeek-V3.1 has sparked interest in the advancements leading to R2 [5][6]. - DeepSeek-V3.1 introduces a mixed inference architecture and improved efficiency, indicating a shift towards the "Agent" era in AI, and highlights the use of UE8M0 FP8 Scale parameter precision, which is designed for upcoming domestic chips [6][7]. - The adoption of FP8 parameter precision is seen as a strategic move to enhance the performance of domestic AI chips, potentially revolutionizing the landscape of AI model training and inference in China [7].