What kind of imaginative space will be opened up by the deep integration of cutting-edge technologies and industries such as artificial intelligence big models, biomimetic intelligence, unmanned driving, and low altitude technology? On June 2nd, the 2024 National Conference on the Development of New Quality Productivity and Intelligent Industry, with the theme of "Pursuing Innovation, Pursuing Quality, and Creating a Smart Future", came to an end in Beijing. At this science and technology event hosted by the China Association of Automation and the Beijing Association of Science and Technology, experts, scholars, and industry professionals focused on new quality productivity to jointly plan for the new development and new future of the intelligent industry. A future vision of technological leap promoting industrial transformation is slowly unfolding. Exploring cutting-edge technology highlights abound. "Against the backdrop of economic globalization, informatization and intellectualization, automation and artificial intelligence have become important forces to promote the development of new quality productivity." Zheng Nanning, academician of the CAE Member and chairman of the Chinese Society of Automation, pointed out in his speech at the conference. Experts and scholars attending the conference unanimously believe that the intelligent industry is not only an important direction for future industrial development, but also provides strong technological support for the upgrading and transformation of traditional industries. Strengthening technological innovation in the field of automation, accelerating the layout and application of automation technology in the intelligent industry, and promoting the deep integration of technological innovation achievements with key industries are effective ways to promote the development of new quality productivity. According to Zheng Qinghua, an academician of the CAE Member and president of Tongji University, the big model has become the peak of current artificial intelligence, and the reason why the big model is strong is that it relies on big data, big computing power and strong algorithms. The big model is bringing disruptive changes to various fields: in the field of education, the new education model in the future will break through the existing "teacher student" binary structure and transform into a "teacher machine student" ternary model; In the field of scientific research, big models bring about a shift in scientific research paradigms, enabling a large number of scientific experiments that require professional manual labor to be conducted through rapid iteration of artificial intelligence... Artificial intelligence is also comprehensively empowering disciplinary innovation, empowering various traditional disciplines such as civil engineering, architecture, urban planning, and transportation. "I deeply feel that the old trees of traditional disciplines sprout new shoots, and also provide new scenes and new application platforms for the development of artificial intelligence, which not only develops artificial intelligence itself, but also promotes the transformation and upgrading of traditional disciplines." In the field of bionic intelligence, Guo Lei, an academician of the CAS Member and a professor of Beijing Aerospace University, introduced the theoretical and technical research framework of bionic intelligent systems for unmanned systems under the interference countermeasure environment, described the research team's research progress in the core technologies of bionic intelligent systems bionic navigation, bionic manipulation and intelligent control systems, and discussed the bionic intelligent technologies such as safety, green and immunity from the perspective of methodology, system theory and behavior theory. Basic connotation and development direction. "I am studying bird intelligence and fish intelligence," said Academician Guo Lei humorously. Taking inspiration from the behavioral characteristics of birds and fish, such as dense flight and swimming of schools of birds and fish without collision, Marcus Papagoggio, an honorary professor at the Polytechnic University of Crete in Greece, proposed a new vehicle traffic paradigm in the era of intelligent connected and automated vehicles, as well as related technologies such as optimal path planning for individual vehicles and groups of vehicles, and crossing signalless and lane free urban intersections between vehicles and queues. As a typical representative of strategic emerging industries and new productive forces, the low altitude economy is a new field that major global economies are currently competing in, as well as a new engine for China's economic growth and a new track for technological innovation. In the report entitled "Low altitude technology and smart economy: new thinking, new industry, new society", Wang Feiyue, the chairman of the board of supervisors of the Chinese Association of Automation and a researcher of the Institute of Automation of the Chinese Academy of Sciences, analyzed the core elements of low altitude technology, and pointed out that low altitude technology has great potential in promoting industrial upgrading, improving economic benefits, and enhancing social governance capabilities. "Low altitude economy is China's next opportunity." Wang Feiyue believes that over the past 40 years of reform and opening up, the Chinese economy has flourished around the four words "clothing, food, housing, and transportation". The next 40 years of economic takeoff will start with "transportation", from new energy vehicles to intelligent driving, and then to low altitude economy, reducing logistics costs. In the operation of the real economy, logistics costs are an important part of the enterprise cost system. According to data released by the China Federation of Logistics and Purchasing, the ratio of total social logistics costs to GDP in China in 2023 is 14.4%, significantly higher than developed countries such as Europe, America, and Japan. Therefore, reducing the level of logistics costs in China has broad potential and enormous strategic value in promoting economic growth. "The acceleration of innovative application industry landing" Artificial intelligence is currently a hot topic worldwide, and the most practical landing of artificial intelligence is the big model. Among many big models including language models, visual models, etc., the most practical landing is end-to-end unmanned driving. "Wang Feiyue said in an interview with reporters. In relatively closed application scenarios such as mines, parks, and ports, end-to-end unmanned driving technology is rapidly industrializing, especially in the field of smart mines with the development goals of "reducing personnel, increasing safety, improving efficiency, and reducing carbon". At this conference, the Automation Research Institute of the Chinese Academy of Sciences, the China University of Mining and Technology (Beijing), the Intelligent Vehicle Research Institute of the Wuchuang Institute, and the China Science Huituo jointly released the Yugong Yukon mine model, marking that the intelligent mine has entered a new era of AI, and the Yugong Yukon mine model has become an important part of the intelligent mine infrastructure in the AI era. Academician Ge Shirong, former president of China University of Mining and Technology (Beijing), believes that the combination of artificial intelligence and mining requires deep innovation. It is necessary to study the intelligent simulation and extended theoretical methods and technologies of miners, and endow mining robots with the ability to complete complex environmental operations. The reporter saw at the conference that the Huituo MineCopilot, with its cartoon miner skin, is the first AI assistant for mining professionals. It can easily understand natural language instructions and complete tasks assigned by staff. Throughout the entire process of mining work, it can provide miners with "shoulder to shoulder, hands-on" services. In the future, it will become a versatile productivity tool for smart mines. According to Chen Long, CEO of Zhongke Huituo, Huituo Mining Treasure is just one of the first products launched based on the Yugong YUKON mining model. In addition, there is a generative parallel intelligent data system GenDS, an end-to-end autonomous driving model GenAD for mining, and a mining knowledge model MineGPT. These four industry-leading products will help energy mining enterprises achieve large-scale replication of smart mining factories. "The development of smart mines has entered the Mining 5.0 era, and the core of this era is to achieve the transformation of mines from industrial automation to knowledge automation. In this process, it is necessary to rely on three core technical pillars, namely operating systems, scene engineering, and mining big models, to complete the four key intelligences of mining intelligence, including equipment intelligence, data intelligence, algorithm intelligence, and process intelligence." Chen Long revealed that through nearly a decade of development, Zhongke Huituo has made multiple technological breakthroughs in mining operating systems and scene engineering. The Yugong Big Model has been learning while using since its inception, and every interaction between users and "mining treasures" can generate higher quality data for the construction of smart mining mountains. Data is the cornerstone of big model training. At present, Zhongke Huituo is continuously expanding its autonomous driving data at a speed of 240000 kilometers per day, and has accumulated a total of 80000 days of mining business logs, accelerating the completion of the layout of the three core technology pillars in the Mining 5.0 era, injecting new productivity into the development of mines. "By 2025, the Yugong YUKON mining model and its intelligent infrastructure system will be fully implemented, empowering the construction of over 40 smart mines nationwide. By 2030, it is expected to ensure the green, safe, and efficient operation of over 500 mines worldwide." Chen Long said. Suggestions, suggestions, and discussions on development plans revolve around firmly grasping the trend of the new round of technological revolution and industrial transformation, accelerating the cultivation and growth of new quality productivity, and shaping new driving forces and advantages of high-quality development. This conference also set up 8 parallel meetings, covering multiple hot areas such as intelligent transportation, embodied intelligence, brain intelligence, data elements, enterprise digital transformation, artificial intelligence education, intelligent medicine, etc. Numerous academicians and experts from academia and industry shared the latest research results in their respective fields, conducted in-depth discussions on common topics and hot and difficult points, and actively provided suggestions and suggestions to discuss the development plan of new quality productivity and intelligent industry. Regarding the potential risks of artificial intelligence, Academician Zheng Qinghua pointed out that large models also have several shortcomings, such as excessive reliance on certain patterns in training data, leading to "hallucinations", excessive consumption of data and computing power, catastrophic forgetting in new task training, and weak logical reasoning ability of black box models. To this end, Academician Zheng Qinghua suggests exploring the establishment of an autonomous and controllable machine intelligence model in China, and proposing technical routes such as the "neural+symbol" collaborative approach and creating a machine memory intelligent model inspired by human brain memory. In the field of low altitude technology and smart economy, Wang Feiyue pointed out the challenges that come with technological progress, such as regulatory development, privacy protection, and security issues. He called on the government, enterprises, and the public to work together to establish cooperation mechanisms to ensure the healthy development of low altitude technology and provide a solid foundation for building a smart economy. (Lai Xin She)