“五个抓好”力推人工智能产业高质量发展

Core Viewpoint - The implementation of the "Artificial Intelligence + Manufacturing" initiative aims to accelerate the high-quality development of the AI industry in China through technology innovation, application integration, enterprise cultivation, ecosystem construction, and safety governance [1]. Group 1: Technology Innovation - The focus is on breaking through key technologies such as high-end training chips, edge inference chips, AI servers, high-speed interconnects, and intelligent cloud operating systems, with a goal to achieve secure and reliable supply of core AI technologies by 2027 [1]. - There is an emphasis on promoting the coordinated development of intelligent chips and software/hardware, aiming to integrate fragmented computing resources into a unified resource pool to enhance overall efficiency [1]. Group 2: Resource Utilization - To effectively enhance computing resource utilization, there is a need to advance the layout of high-level intelligent computing facilities and establish a national integrated computing network monitoring and scheduling platform [2]. - The development of differentiated high-level industry models and lightweight small models for specific application scenarios is crucial, alongside the support for collaborative innovation between large and small models [2]. Group 3: Application Integration - By 2027, the goal is to promote the deep application of 3-5 general large models in manufacturing, creating specialized industry models and launching 1,000 high-level industrial intelligent entities [3]. - The initiative encourages leading enterprises and state-owned enterprises to take the lead in AI application, while also promoting the replication and dissemination of AI applications among small and medium-sized enterprises [3]. Group 4: Ecosystem Construction - The construction of a resource-optimized open-source ecosystem is essential, which includes strengthening standardization and promoting cross-industry collaboration [8]. - The establishment of high-level AI open-source communities and the development of open-source projects are key to creating a globally influential AI open ecosystem [8]. Group 5: Talent Development - Strengthening talent cultivation is vital for sustainable ecosystem development, with a focus on training professionals who understand both AI and manufacturing applications [9]. - The initiative aims to create a talent demand forecasting system and enhance the training of high-skilled personnel in the AI field [9]. Group 6: Safety Governance - By 2027, the goal is to establish a globally leading safety governance system for AI, ensuring the security of the technology supply chain, product operation, and data lifecycle [10]. - Enhancing safety protection capabilities through the development of key technologies and establishing a safety risk database is crucial for mitigating risks associated with AI applications [10].