The National Development and Reform Commission and the National Energy Administration recently released the "Implementation Opinions on Promoting the High Quality Development of 'Artificial Intelligence+' Energy" (hereinafter referred to as the "Implementation Opinions"), which systematically deployed eight application scenarios of artificial intelligence+power grid, new energy formats, new energy, hydropower, thermal power, nuclear power, coal, and oil and gas around various energy varieties such as coal, electricity, oil, and gas, promoting the sharing of artificial intelligence development dividends in the energy field, assisting the digital and intelligent upgrading of the traditional fossil energy industry, accelerating the deep integration of new energy, new energy formats, and energy cross fields with artificial intelligence, and cultivating and strengthening new models of new energy industries. The Implementation Opinions propose that by 2027, a preliminary integration and innovation system of energy and artificial intelligence will be established, the foundation for the coordinated development of computing power and electricity will continue to be consolidated, and significant breakthroughs will be made in the core technology of empowering energy with artificial intelligence, with more extensive and in-depth applications. By 2030, the overall level of AI specific technologies and applications in the energy sector will reach the world's leading level. The collaborative mechanism of computing power and electricity will be further improved, and a green, economical, safe, and efficient computing power consumption model will be established. The relevant person in charge of the Science and Technology Department of the National Energy Administration stated that energy is a highly active field for innovation and entrepreneurship, with comparative advantages such as good digital foundation, high data quality, and rich application scenarios, and should be at the forefront of artificial intelligence applications. Especially with the active layout of energy central enterprises, around resource exploration, production operation and maintenance, safety monitoring and other links, they have successfully developed and applied multiple industry representative professional models such as electricity, oil and gas, coal, etc. Overall, China's energy sector has formed a widely covered pattern of artificial intelligence development. Lin Boqiang, Dean of the China Energy Policy Research Institute at Xiamen University, stated in an interview with Shanghai Securities News that the energy sector is currently undergoing a critical transformation from digitization to intelligence. China's digital construction in the energy sector has achieved significant results, with relatively complete infrastructure. Based on the data and systems accumulated through digitization, artificial intelligence can deeply empower power grids, oil and gas fields, and promote their development towards intelligence. In terms of increasing the supply of key common technologies, the Implementation Opinions focus on data, computing power, and algorithms, and systematically build a basic support system for artificial intelligence applications. It proposes three major common key technology research directions for the application of artificial intelligence in the energy field, including consolidating the data foundation, accelerating the formation of high-quality datasets in the energy field, and ensuring the safety and reliability of the entire energy data process; Strengthen the support of computing power, coordinate and plan resources, and establish a collaborative development mechanism for computing and electricity that deeply integrates computing power and electricity; Enhance the basic capabilities of models, promote the deep integration of artificial intelligence and energy software, and accelerate the breakthrough of green and low-carbon technology bottlenecks in artificial intelligence. In Lin Boqiang's view, artificial intelligence will generally bring operational efficiency improvement, decision optimization, and cost reduction to the industry. Taking the oil and gas industry as an example, artificial intelligence can predict underground resource reserves more accurately through algorithms and models, optimize transportation scheduling, and achieve supply-demand matching on the downstream demand side. In addition, Lin Boqiang believes that there is still a certain gap in the implementation and application of artificial intelligence technology compared to digitization. In addition to the commonly mentioned issues of missing standards at the policy level, the most critical challenge is the shortage of talent. Artificial intelligence not only requires underlying technical capabilities, but also requires interdisciplinary and cross industry composite talent support, which is the core bottleneck of the current transition from digitization to artificial intelligence. When it comes to promoting the implementation of the Implementation Opinions, the above-mentioned person in charge stated that the intelligent transformation of the energy sector requires coordinated efforts from top to bottom, departmental coordination and cooperation. The National Energy Administration will closely focus on the goals and tasks of the next stage of intelligent transformation in the energy sector, further strengthen top-level design, policy support and guidance coordination, regularly conduct analysis and research, summarize and evaluate, study and solve major problems in the promotion of work, and ensure the smooth progress of various tasks in the Implementation Opinions. Among them, in terms of accelerating the transformation of scientific and technological achievements, it is necessary to explore the construction of industry level artificial intelligence application testing platforms, effectively collaborate with enterprises to independently develop large models, solve the problem of "duplicate wheel making" in large models, and avoid excessive consumption of advanced computing power and energy resources. Select a batch of replicable and easily promotable benchmark scenarios and cases, encourage innovation in institutional mechanisms and business models, and promote the implementation and achievement transformation of artificial intelligence technology projects in the energy field. (New Society)