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北京市“推动AI赋能高端科学仪器创新”三年行动计划出炉
仪器信息网· 2025-07-17 04:42
Core Viewpoint - The article discusses the "Action Plan" aimed at accelerating the integration of artificial intelligence (AI) into scientific research in Beijing, with a focus on developing high-quality scientific instruments and fostering innovation in various fields [2][4][7]. Group 1: Development Goals - By 2027, the plan aims to leverage Beijing's AI innovation advantages to establish new pathways for scientific research, focusing on foundational scientific issues and enhancing the application of AI across multiple fields [8]. - The initiative includes the construction of at least 10 high-quality scientific databases to support AI applications in various research areas, targeting over 10 million users [8]. Group 2: Key Tasks - The plan emphasizes critical technology breakthroughs, including foundational theoretical research in AI, the development of a universal scientific foundational model, and new generation scientific computing simulation software [9][10][11]. - Infrastructure development is a priority, with goals to create an open scientific data platform and a collaborative computing power platform to enhance research efficiency [12][13]. Group 3: Application Acceleration - The plan promotes the use of AI in basic scientific research, medical health innovation, and new materials development, aiming to enhance research efficiency and discovery processes [15][16][17]. - Specific focus is placed on empowering high-end scientific instruments through AI, encouraging collaboration between universities, research institutions, and enterprises to develop advanced scientific equipment [18]. Group 4: Innovation Ecosystem - The initiative aims to build a public service innovation platform for scientific intelligence, attract and cultivate innovative talent, and establish a multi-channel investment and financing service system [20][21][22]. - It also seeks to create a competitive scientific intelligence industry cluster and promote international cooperation and open-source ecosystems [23][24][25].