LLM开源2.0大洗牌：60个出局，39个上桌，AI Coding疯魔，TensorFlow已死

Core Insights - The article discusses the significant changes in the open-source AI model ecosystem, highlighting a shift towards a more competitive and rapidly evolving landscape, particularly in the AI Agent and Model Serving sectors [4][9][61]. Group 1: Ecosystem Changes - The latest version of the open-source landscape includes 114 projects, a decrease of 21 from the previous version, with 39 new projects and 60 projects that have disappeared, indicating a significant reshuffling in the ecosystem [7][10]. - The average lifespan of projects in the AI model ecosystem is only 30 months, with 62% of projects emerging after the "GPT moment" in October 2022, showcasing a high turnover rate [10][11]. - TensorFlow has been overtaken by PyTorch, which now dominates the landscape, marking a dramatic shift in the competitive dynamics [8]. Group 2: Key Trends - The article identifies three main areas of focus: AI Coding, Model Serving, and LLMOps, which are emerging as the primary tracks in the evolving landscape [29][61]. - AI Coding has transitioned from merely assisting in code writing to becoming a comprehensive lifecycle engine, indicating a significant increase in its capabilities and market potential [43][44]. - The AI Data sector remains relatively stable but is expected to evolve as new challenges arise in the native large model era, suggesting a potential for future growth [82][88]. Group 3: Global Contributions - The United States and China contribute over 55% of the total developer population in the open-source AI space, with the U.S. leading at 37.41% [17][20]. - In specific areas, the U.S. has a dominant position in AI Infrastructure and AI Data, with contributions significantly higher than those from China [19][23]. Group 4: Licensing Trends - There is a noticeable trend towards more restrictive open-source licenses, with many new projects adopting custom agreements that allow for greater control by the license holders [90][92]. - This shift raises questions about the definition of "open source" in the current competitive environment, as some projects that are popular on platforms like GitHub are not fully open-source [94].