The steel industry is an important basic industry in China, with a huge industrial scale, profound application accumulation, and urgent demand for high-quality development. It is an ideal practice field for the deep empowerment of the new generation of artificial intelligence, "said Jiang Wei, Vice President and Secretary General of the China Iron and Steel Industry Association. At present, the China Iron and Steel Association has listed digital transformation as one of the three major projects in the industry and launched a three-year action plan for the digital transformation of the steel industry. Under the guidance of a series of "artificial intelligence+" policies in the country, a large number of steel enterprises have made substantial progress in promoting digital transformation and relying on digitalization to support high-end and green development. Vigorously advancing, Shougang Cold Rolling Company was successfully selected in the 13th batch of global "lighthouse factories" list announced at the beginning of this year. With the construction of cloud edge collaboration technology architecture, 5G, big data AI、 The widespread application of advanced technologies such as machine vision and robotics in Industry 4.0 has made the company the third "lighthouse factory" in the national steel industry and the seventh in the global steel industry. In response to the stricter quality requirements and increasingly diverse product specifications in the high-end automotive manufacturing field, Shougang Cold Rolling Company has deployed 67 Industry 4.0 digital application cases, of which 61% have used artificial intelligence to improve end-to-end process control accuracy, eliminate bottlenecks that restrict key quality and production capacity improvement, and solve quality problems faced by customers. The production line efficiency increased by 21.2 percentage points, the product defect rate decreased by 35 percentage points, the sales of high-end products increased by 36 percentage points, and the customer complaint rate decreased by 55 percentage points. ”The relevant person in charge of Shougang Cold Rolling Company speaks with data. This is just a microcosm of the intelligent manufacturing upgrade in the steel industry. According to a survey by the China Iron and Steel Association, 95.1% of steel companies have incorporated digital transformation strategies into their overall development process, continuously investing funds in implementing digital transformation and upgrading projects, and the application density of robots (including unmanned equipment) has reached 65 units/10000 people; 82.9% of enterprises have built intelligent centralized control centers, mainly focused on iron front and steel rolling, and 63.4% of enterprises have used 3D visualization simulation systems to build digital factories. Redefine steel with artificial intelligence. Baosteel Group, a subsidiary of China Baowu, has formulated a new round of digital transformation strategy marked by "AI+" and launched a "full field, full system, and full scenario" action plan. In the next three years, it aims to create more than 1000 AI enabled application scenarios. We must adhere to innovation driven, strengthen technological empowerment, and accelerate the intelligent and green transformation of the steel industry. ”Liu Jian, Chairman of Hegang Group, stated that Hegang has incorporated intelligent manufacturing into its corporate development strategy, actively promoted the deep integration of artificial intelligence technology and steel production, vigorously implemented the "Intelligent Enhancement Action", and accelerated the transformation and upgrading of enterprises empowered by artificial intelligence. It is reported that HBIS has independently developed the "Visebo" industrial Internet platform, integrated intelligent equipment, industrial simulation, model control and other innovative capabilities, and formed a basic base of industrial Internet that runs through the whole production process and cooperates software and hardware. Hegang has also promoted the integration of technologies such as artificial intelligence and digital twins with the entire manufacturing process chain, and built a large number of "smart factories". At present, the steel industry is at a critical stage of moving from digitization to intelligence, and the new generation of artificial intelligence represented by large models is expected to become a new engine driving high-quality development. At the recent "AI+Steel" technology launch conference, experts and scholars discussed how to promote innovation and application of "AI+Steel" technology. Tian Guobing, Chairman of Shanghai Baoxin Software Co., Ltd., stated that in order to promote high-quality development, steel enterprises are shifting from scale oriented to efficiency oriented. However, traditional automation and information technology and systems have obvious shortcomings in data, models, computing power, and other aspects, which restrict the ultimate improvement of enterprise efficiency and efficiency. It is urgent to break through the situation through digital and intelligent technology. To achieve new breakthroughs in 'artificial intelligence+steel' and comprehensively enhance industry competitiveness. ”Wang Guodong, an academician of the CAE Member, stressed that the iron and steel industry, as a large-scale complex process industry, has a long-term "black box" problem in all processes. It is necessary to integrate the advantages of experts in China's iron and steel materials field and AI field, and promote the deep integration of the new generation of AI technology and the real economy of the iron and steel industry. It is understood that the hardware, software, and production environment of China's steel industry have reached the world's top level in the industrial era, but have long been trapped in the "black box" of the entire production process. Due to the complex physical and chemical processes involved in steel production, there are a large amount of incomplete information, uncertainty, and dynamic environmental issues, which have a significant impact on product quality, production efficiency, production costs, and environmental effects. In response to the pain points in this industry, Northeastern University has taken the lead in proposing the "human-machine hybrid intelligence" model, which is specifically designed to crack the "black box" of steel production and achieve full process online high fidelity prediction. The relevant technology has been applied in multiple steel enterprises. For example, in the intelligent smelting of blast furnaces, the innovative use of a "universal model+personalized data" architecture effectively improves energy efficiency and green production levels; In the hot rolling process, a digital twin model based on human-machine hybrid intelligence was developed, integrating physical mechanisms and multimodal data to successfully achieve online high-precision prediction and closed-loop optimization of organizational performance. Wang Guodong further explained that by deeply integrating human intelligence with artificial intelligence, mining and analyzing big data in the production process, and promoting "digital brain replacement, model replacement, and industrial software development" through human-machine collaboration, an autonomous unmanned intelligent control system for the main unit of the steel production process can be established. This is equivalent to transforming the overall "black box" of production into comprehensive sensors, using digital twins to achieve accurate prediction, making the production process autonomous, unmanned, and intelligent control a reality. With the rapid development of technology, artificial intelligence has brought unprecedented opportunities to the steel industry. ”Zhang Longqiang, President of the Metallurgical Industry Information Standards Research Institute, stated that the application scenarios of AI in the steel industry have gradually been implemented, and the prospects are very broad. In terms of production process optimization, intelligent algorithms can accurately predict equipment failures, significantly reduce downtime, and significantly improve production efficiency; In the field of quality control, AI image recognition technology can perform high-precision detection of surface defects on steel to ensure product quality meets standards; In the supply chain management process, AI can combine multiple factors such as market demand and fluctuations in raw material prices to make predictions, optimize procurement and production plans, reduce enterprise operating costs, and enhance core competitiveness. Looking ahead to the future, the development space of "AI+steel" will be further expanded. On the one hand, with the continuous development of AI technology, especially the in-depth application of big model technology, it will further penetrate the "black box" of the steel production process, connect data silos, solve resource scheduling difficulties, and achieve intelligent and refined management of the entire steel production process. By accumulating data assets and enhancing market competitiveness, we aim to train steel enterprises with faster, more accurate, and more cost-effective "real skills". On the other hand, "AI+Steel" will help the industry achieve green and sustainable development, promote energy conservation, emission reduction, and environmental protection. At the same time, the construction of cross enterprise and cross industry AI ecosystems will become a trend, promoting deep cooperation and collaborative innovation between steel enterprises, upstream and downstream enterprises, research institutions, and technology service providers, and jointly promoting the industry's transformation towards high-end, intelligent, and green. Jiang Wei stated that the China Iron and Steel Association will continue to focus on the application of "AI+intelligent technology" as its core, and comprehensively shift towards the reshaping of productivity driven by new generation artificial intelligence technology. Through policy guidance, standard construction, and benchmark promotion, it will promote industry transformation. Focus on intelligent collaboration in the industrial chain, low-carbon intelligent integration, and low-cost technology promotion. The core value of artificial intelligence is not to replace human labor, but to build a new productivity paradigm of "human-machine collaboration". Human machine collaboration can fully leverage the efficient computing power of AI and human creativity and judgment, ensuring the stability of steelmaking operations to the greatest extent possible and promoting continuous optimization and innovation of the system. ”Professor Liu Shuchao from Northeastern University stated. Liu Shuchao grew up on the front line of steelmaking and is now deeply involved in the research of intelligent steel technology in universities. He led a team to develop a modular intelligent steelmaking system for the entire converter process based on the "AI+human experience" model. All or part of its modules have been implemented and applied in steel companies such as Ansteel, Benxi Iron and Steel, Nangang, Chenggang, Meishan Iron and Steel, and Zhougang. This experience from frontline practice to scientific research and innovation has also given Liu Shuchao a deeper understanding of smart steelmaking: "The development of smart steelmaking should not be aimed at 'reducing manpower', the core is to make steelmaking operations simpler, processes more stable, technologies more professional, and costs more controllable. Only when leaders attach importance to it, grassroots actively participate, employees work together, and have consistent beliefs, supplemented by scientific policies and continuous improvement, can smart steelmaking truly go deeper and more practical