"Automatic driving moves from laboratory to real scene, and generative artificial intelligence creates amazing pictures for us. The big language model has solved countless complex problems for us... The development of artificial intelligence is leading human society to profound changes, and the next opportunities and challenges are in general artificial intelligence." CAE Member Zheng Nanning, Chairman of the China Association for Automation, said at the 25th annual meeting of the China Association for Science and Technology held here. At present, the algorithms, computing power, data, and scenarios of artificial intelligence have become the core capabilities of the development of the digital economy, and are important forces in accelerating the process of digital industrialization and industrial digitization. The thriving artificial intelligence big model is undoubtedly one of the integrators. Huawei "Pangu", Baidu "ERNIE Bot", iFLYTEK "Spark", Chinese Academy of Sciences "Zidong Taichu"... The Research Report on the Map of China's Artificial Intelligence Large Models released by the New Generation Artificial Intelligence Development Research Center of the Ministry of Science and Technology in May this year shows that the number of large models developed in China ranks second in the world, and 79 large models with a parameter scale of more than 1 billion have been released. The industry predicts that in the coming years, China's artificial intelligence will enter a critical period of large-scale implementation and application. At the same time, as enterprises and research institutions flock to the artificial intelligence big model arena, problems such as tight supply of intelligent computing resources, insufficient high-quality data resources, and insufficient openness to typical application scenarios are becoming increasingly prominent. How far is it from big models to universal artificial intelligence? At the General Artificial Intelligence Industry Innovation and Development Forum of the 25th China Association for Science and Technology Annual Conference, experts and scholars from fields such as artificial intelligence conducted discussions. Wang Jinqiao, deputy chief engineer of the Institute of Automation of the Chinese Academy of Sciences and president of the Wuhan Institute of Artificial Intelligence, believes that, from the perspective of computing power, cost, energy consumption, etc., the "big model craze" in China will gradually stabilize in the next two to three years, and the number of enterprises engaged in the development of universal big model bases will be stable within five, while others will focus on the industry's big models. Chen Junlong, Vice Chairman of the China Association for Automation and Dean of the School of Computer Science and Engineering at South China University of Technology, proposed that the learning and reasoning of artificial intelligence large models require high computational power and massive data support. The "East West Computing" project currently under construction in China can provide strong computational power support for large models; Meanwhile, data exchanges are being established in multiple regions, and future trading data from various industries can be applied to the training of artificial intelligence models. At present, the high computing power demand for large-scale model training in China still relies on foreign product ecosystems. In the future, we should strengthen the construction of application ecosystems such as domestic graphics cards. Large language models are expected to become very intelligent general artificial intelligence, empowering various industries, "said Chen Junlong. Experts attending the meeting believe that universal artificial intelligence technology will drive China from an industrial powerhouse to an industrial powerhouse. "As a new production tool for the digital transformation of the manufacturing industry, AI is accelerating the birth of a new paradigm of engineering research and development that AI drives industrial manufacturing." Qian Feng, an academician of the CAE Member and professor of East China University of Science and Technology, said that the digital transformation of the manufacturing industry urgently needs to develop industrial intelligence and intelligent system technology, comprehensively improve the perception, cognition and decision-making capabilities of the manufacturing process, so as to achieve high-end, green and intelligent manufacturing process. ChatGP