Zhong Guo Dian Li Bao·2025-09-24 06:26Core Viewpoint - The article emphasizes the importance of innovation, particularly through artificial intelligence (AI), as a driving force for the transformation and sustainable development of energy enterprises in China, guided by the recent implementation opinions from the National Development and Reform Commission and the National Energy Administration [1] Group 1: Implementation of AI in Energy Sector - The implementation opinions outline a phased approach with significant breakthroughs in AI core technologies by 2027 and achieving world-leading AI applications in the energy sector by 2030 [2] - The focus is on integrating AI with traditional and emerging industries, enhancing strategic and systematic thinking to foster collaboration [2][3] - The company aims to deepen the integration of AI across the entire energy value chain, enhancing production, marketing, management, and governance [3] Group 2: Key Technological Foundations - The article highlights the need for high-quality data sets, emphasizing the importance of data collection, processing, and quality improvement to support AI model training [4] - It discusses the establishment of a robust computing power foundation, including the development of green computing centers and diverse computing resources to support AI applications [4] - The evolution of industry-specific AI models is crucial, focusing on enhancing capabilities in knowledge questioning, deep reasoning, and multi-modal understanding [5][6] Group 3: Innovation Applications in Oil and Gas - The company is set to enhance the intelligence level across research, production, and service sectors, creating typical cases with significant industry characteristics [7] - There is a focus on expanding the depth and breadth of AI applications in oil and gas, including intelligent evaluation and optimization of exploration and production processes [7] - The development of embodied intelligence technologies, such as intelligent drilling machines and robots, is prioritized to advance the smart construction of the oil and gas industry [8] Group 4: Data Management and Talent Development - The article stresses the importance of optimizing data sharing mechanisms and ensuring the security of energy data throughout its lifecycle [8] - The company aims to build a robust talent pool with expertise in both energy systems and AI algorithms, fostering collaboration between education and industry [9] - Continuous improvement of the innovation organizational structure and mechanisms is essential to attract and develop talent in AI and oil and gas sectors [9]