“变革时期的开源生态建设”

Core Viewpoint - Open source is not only a crucial engine for technological evolution but also involves deeper issues related to national science and technology strategy, industrial security, and talent cultivation [1][27]. Group 1: Open Source in National Research Projects - The state is actively organizing ecological major research projects, but projects led by enterprises have shown drawbacks such as excluding competitors and increasing ecological fragmentation [3][29]. - A new path is proposed to organize ecological national major research projects using an open-source model, which emphasizes broad consensus, resource aggregation, and continuous co-construction and sharing [3][29]. Group 2: New Computing Paradigms - The emergence of new computing paradigms occurs approximately every 10 to 15 years, leading to technological innovations and the formation of new industries [5][31]. - The AI era is expected to generate millions of intelligent applications, creating new demands for AI computing chips, with the open RISC-V instruction set offering customizable advantages [5][31]. Group 3: Industrial Software Innovation - Industrial software, which is essential for enhancing R&D, manufacturing, and operational management in industries, faces challenges due to high technical barriers and long development cycles [7][33]. - Open source collaboration is identified as a significant strategy to upgrade the technological innovation management system of industrial software companies [7][34]. Group 4: Open Source Contribution Recognition - The current research evaluation system undervalues contributions in open source, leading to a disconnect between open source contributions and academic recognition [10][36]. - A new academic currency based on code contribution metrics is proposed to bridge the gap between open source contributions and research performance [10][36]. Group 5: Open Source and Closed Source Dynamics - Open source has become a key strategy in the global competition for AI, serving as a digital public good that facilitates the allocation of global innovation resources [12][38]. - A dynamic strategy is recommended, embracing open source in foundational technology areas while balancing security and development in critical core technologies [12][39]. Group 6: Open Source Governance in AI - The rise of open source models in China faces uncertainties in global innovation, necessitating a governance mechanism that adapts to the unique characteristics of AI [15][41]. - Establishing a global AI open-source foundation is deemed essential to promote collaborative AI development and ensure safe and neutral governance [15][41]. Group 7: Open Source in Education - Open source innovation injects continuous momentum into science education, aligning with educational goals and facilitating collaborative course development [25][51]. - Science education can provide talent and intellectual support for open source innovation, fostering developers and contributors with both technical skills and open source philosophy [25][51]. Group 8: Digital Sovereignty and Open Source - Open source in AI is increasingly viewed as a tool embedded in national power and institutional competition, raising concerns about digital sovereignty [22][48]. - A need arises to incorporate AI open source into the governance of digital sovereignty, defining the boundaries of "openness" and "control" [22][48].