刚刚，梁文锋发Nature了

Core Viewpoint - DeepSeek's R1 reasoning model has achieved significant recognition by being published in the prestigious journal Nature, marking a milestone in AI research and transparency in the industry [4][22][36]. Group 1: Model Development and Achievements - The DeepSeek-R1 model, developed by Liang Wenfeng's team, is the first mainstream large language model to undergo peer review, breaking a significant gap in the AI industry [4][11][22]. - The model has become the most popular open-source reasoning model globally, with over 10.9 million downloads on Hugging Face [4]. - DeepSeek-R1's research addresses a major issue in AI, enhancing reasoning capabilities through reinforcement learning without relying on extensive human labeling [14][16]. Group 2: Transparency and Peer Review - Nature's editorial highlights the importance of peer-reviewed publications in clarifying how large models work and ensuring their performance aligns with vendor claims [24][25][34]. - The peer review process for DeepSeek-R1 involved eight external experts who provided over a hundred specific comments, enhancing the paper's clarity and credibility [26][29][34]. - DeepSeek's commitment to transparency is evident in the detailed disclosures about model training and safety assessments, which are crucial for mitigating risks associated with AI technologies [11][18][36]. Group 3: Safety and Data Integrity - DeepSeek conducted a comprehensive safety evaluation of the R1 model, demonstrating its superior safety compared to contemporaneous models [11][18]. - The model's training data underwent rigorous decontamination processes to prevent bias and ensure that evaluation results accurately reflect its problem-solving capabilities [17][20]. - Despite acknowledging potential contamination issues in some benchmark tests, DeepSeek has implemented external risk control systems to enhance safety during deployment [18][19]. Group 4: Industry Impact and Future Directions - DeepSeek's open-source model is positioned as a representative of domestic AI technology on the global stage, potentially setting a standard for research transparency in the AI industry [36]. - The call for more AI companies to submit their models for peer review reflects a growing recognition of the need for verified claims and enhanced credibility in AI research [36].