工信部部署下半年重点任务 力推“人工智能+制造”走向纵深

Core Viewpoint - The meeting emphasized the importance of deepening the integration of digital technology and industrialization, focusing on eight key areas, including the promotion of "Artificial Intelligence + Manufacturing" initiatives to enhance efficiency and competitiveness in the manufacturing sector [1][2]. Group 1: Digital Transformation and Policy Support - The digital transformation rate of small and medium-sized enterprises (SMEs) is approximately 40%, highlighting the need for further policy support such as subsidies and tax incentives to bridge the "digital divide" [1]. - The meeting called for the establishment of a product data standard service platform to facilitate data interconnectivity across supply chains, thereby improving the digitalization level of the industry and reducing collaboration costs [1]. Group 2: Artificial Intelligence Integration - The integration of artificial intelligence (AI) with manufacturing is seen as a crucial step for industrial upgrading and reshaping global competitiveness, especially in light of rising labor costs and international supply chain risks [2]. - The "Artificial Intelligence +" initiative aims to explore AI application scenarios and develop high-quality data sets, focusing on smart connected vehicles, AI smartphones and computers, and intelligent manufacturing equipment [2]. Group 3: Technological Foundations - The deep integration of AI and manufacturing relies on breakthroughs in three technological foundations: computing infrastructure, data governance, and algorithm innovation [2]. - Key technologies to be tackled include industrial large models, multi-modal perception, and digital twins, alongside the establishment of a national-level AI open-source community to build a self-controlled technology system [2][3]. Group 4: Industry Transformation - The "Artificial Intelligence + Manufacturing" initiative is expected to trigger chain transformations across multiple industries, with 5G fully connected factories offering new production and operational models [3]. - Custom production thresholds are anticipated to lower significantly, enhancing production flexibility for both traditional manufacturing and tech companies involved in 5G and cloud computing [3].