On March 4, it was reported that Lei Jun, a representative of the National People's Congress and chairman and CEO of Xiaomi Group, planned to put forward 4 proposals during the two sessions of the National People's Congress this year, involving green and low-carbon, artificial intelligence, intelligent driving, intelligent manufacturing and other fields.
Suggestions on accelerating the construction of a green and low-carbon manufacturing chain.
1. Accelerate the establishment of a background database on the carbon footprint of the manufacturing industry, and promote international convergence and mutual recognition. The establishment of a product carbon footprint management system can help unify carbon footprint accounting standards and guide enterprises to strengthen carbon emission management. In November 2023, the National Development and Reform Commission and other departments issued the "Opinions on Accelerating the Establishment of a Product Carbon Footprint Management System", which clarified the overall requirements, key tasks, safeguard measures and organizational implementation requirements for accelerating the improvement of the carbon footprint management level of key products in China. For example, the electronic information manufacturing industry accounts for a relatively high proportion of the national economy, especially consumer electronics products have a broad international market space, and in the process of "going to sea", the carbon footprint management requirements are becoming more and more stringent, and the lack of official carbon footprint background database limits China's voice and initiative in the field of global product carbon footprint management.
Based on this, it is recommended to establish a manufacturing carbon footprint background database as soon as possible, promote the convergence and mutual recognition with international databases, and gradually establish a global carbon footprint management system with China's deep participation and leadership. At the same time, we will establish a sound carbon footprint data sharing mechanism, encourage enterprises to actively participate in the construction and operation of the database, and provide necessary technical support and policy and financial support.
2. Support the creation of a green digital chain system to achieve collaborative connectivity within the chain. Green and low-carbon management is a systematic project that runs through the entire industrial chain. At present, the low-carbon transformation of the manufacturing industry chain still has the problems of opaque link information, information barriers and insufficient green and low-carbon integration, which not only affect the collaborative efficiency of the first chain, but also restrict the pace of green and low-carbon transformation of the first chain.
In view of the current situation, it is recommended to formulate corresponding supporting policies, encourage and support enterprises to optimize or upgrade the first-chain system, promote the integrated application of a new generation of information technology such as 5G, big data, artificial intelligence, cloud computing, and the Internet of Things, and realize the integration of R&D, production, circulation, service, consumption and other full-process business information, strengthen the integration of green and low-carbon indicators and carbon reduction measures in the whole process, and improve the intelligent and green decision-making ability of the first-chain chain; Establish a systematic evaluation and demonstration and promotion mechanism for green digital chains, set industry benchmarks, and encourage enterprises to build digital chains with green and low-carbon as the core concept.
3. Explore the establishment of a national trading mechanism for green electricity, and promote the main enterprises of the chain to lead the green transformation of the chain. Carbon dioxide emissions in the process of green power production are close to zero or equal to zero, and increasing the proportion of green electricity use is more conducive to environmental protection and sustainable development, which is an important measure to build a green and low-carbon chain. At present, in the process of increasing the proportion of green electricity, there are also corresponding difficulties and challenges, such as the high cost of green electricity, cross-regional trading difficulties and other practical problems.
In order to effectively deal with these problems, it is first recommended to establish and improve the national cross-regional green electricity trading mechanism and smooth the trading channels. On this basis, guide the chain master enterprises to explore the establishment of a "new centralized procurement" model of green power, that is, the chain master enterprises integrate the green power needs of the enterprises in the chain, unify the green power procurement channels, form a collective bargaining advantage, stimulate the enthusiasm of the chain enterprises to use green electricity, and promote the green transformation of the chain.
Suggestions on strengthening the training of artificial intelligence talents to meet the needs of scientific and technological change.
1. Popularize AI literacy education from the compulsory education stage. AI literacy education is a long-term task, and it is necessary to cultivate students' interests and abilities from an early age. In primary and secondary school, students are in a critical period of thinking development, and are the most active and sensitive in their thinking, and have the highest acceptance of new things. At the same time, compulsory education is also the education stage with the widest coverage and the largest audience in China.
It is suggested that artificial intelligence literacy education should be included in the content of nine-year compulsory education, and artificial intelligence general education courses should be set up, and relevant content should be included in social practice activities in primary and secondary schools. From basic concepts to simple applications, it comprehensively stimulates the interest of primary and secondary school students, cultivates their cognitive ability and application ability of artificial intelligence, and lays a solid foundation for future development.
2. Vigorously promote the construction of artificial intelligence-related majors in colleges and universities. Colleges and universities are an important position for cultivating professional talents in China. According to the data released by the Ministry of Education, at present, 498 colleges and universities in China have opened "artificial intelligence" undergraduate majors, and 209 colleges and universities have successfully filed or applied for "intelligent science and technology" undergraduate majors, accounting for a relatively low proportion of more than 3,000 colleges and universities in the country.
It is suggested to increase investment in the construction of artificial intelligence disciplines in universities, strengthen cooperation and exchanges with world-class scientific research institutions, introduce excellent teachers from overseas, and attract senior talents and industry experts to teach in universities. At the same time, the general education course of artificial intelligence will be expanded to more majors, such as traditional science and engineering majors, medicine, finance, literature and history, art and other majors, so as to cultivate more interdisciplinary talents; Guide large enterprises in the artificial intelligence track to open internship and practice opportunities to college students, and improve the comprehensive quality of integrating theory and practice.
3. Support large-scale science and technology enterprises and education and training institutions to cultivate artificial intelligence application-oriented talents. Artificial intelligence is rapidly expanding and penetrating into various industries, which has high requirements for talent skill upgrading. In addition, in the development of artificial intelligence technology in recent years, many enterprises have become an important driving force in this field, they have a large number of data resources and powerful computing resources, as well as rich application scenarios, and at the same time, the social talent market seriously lacks high-level artificial intelligence training capabilities.
It is suggested that large science and technology enterprises and social education and training institutions should be encouraged to carry out artificial intelligence application talent training, so as to adapt to the rapid iteration of technology, large demand for talents, and wide application in the field of artificial intelligence. Specifically, combined with the supply and demand of artificial intelligence talents, enterprises and institutions can be encouraged to flexibly set up from the basic quality training of artificial intelligence to the systematic training of cutting-edge artificial intelligence talents, so as to effectively meet the current demand for artificial intelligence application in various fields.
Suggestions on further standardizing the safety application of intelligent driving products.
1. Standardize the application of assisted driving functions to create a safer driving experience. At present, the automotive assisted driving function has been applied on a large scale, and the safety standards for assisted driving related products are also being formulated one after another, but due to the lack of clarity in the application plan of relevant regulations and standards, the safety and security measures of the existing assisted driving products are greatly differentiated, and the driver may not have a clear understanding of the state of the assisted driving function or even use it incorrectly, and there is a risk of safety accidents.
It is recommended to establish a safety supervision and management mechanism for assisted driving products as soon as possible, accelerate the application of safety technical requirements and test and verification standards for assisted driving, refine the requirements for human-computer interaction such as driver-in-the-loop and risk warnings, standardize the correct use of assisted driving functions, and create a safer assisted driving experience.
2. Standardize the application of autonomous valet parking function to ensure the safety of unmanned scene experience. In order to solve the parking pain points such as the difficulty of users to find parking spaces and the long parking time, enterprises in the industry have successively launched independent valet parking solutions, but there are inconsistent parking lot supporting standards in the landing process.
1. Problems such as non-standard product function definition and unclear safety performance standards lead to difficulties in the implementation and promotion of unmanned scenarios of autonomous valet parking.
It is suggested to further promote the implementation and application of relevant laws and regulations on the definition and technical requirements of autonomous valet parking, study and formulate the safety guarantee mechanism and responsibility identification method for unmanned parking scenarios, encourage the pilot construction of exclusive parking lots for autonomous valet parking, and promote the large-scale application of safe and reliable autonomous valet parking functions.
3. Standardize the use of vehicle-end data and improve the safety level of intelligent driving products. In order to make more compliant and efficient use of data, enterprises need more detailed compliance measures and product standards to guide them in data collection, storage, and use.
It is recommended to further refine the compliance measures and product standards for the collection, storage, and use of intelligent driving data, so as to provide a clearer basis for the safe governance and efficient circulation of intelligent driving data, and guide enterprises to use intelligent driving data reasonably. At the same time, a unified intelligent driving safety monitoring data platform has been established, and the supervision system has been continuously improved through big data.
Suggestions on increasing support for intelligent manufacturing and accelerating the development of integrated advanced technologies.
1. Promote the integration and innovation of advanced intelligent technology and manufacturing industry, and accelerate the deployment of large industrial models. With the industrial Internet, big data and artificial intelligence to achieve group breakthroughs and integrated applications, intelligent manufacturing has entered a new stage of deep integration of a new generation of artificial intelligence technology and advanced manufacturing technology. While continuing to strengthen the construction of infrastructure such as 5G, data centers, and computing power, it is recommended that the competent authorities introduce special projects as soon as possible, focusing on the deployment and application of intelligent manufacturing system software, AI large models and general bionic robots, and supporting the creation of application scenarios for the deep integration of artificial intelligence and manufacturing represented by large models. Deeply consolidate the digital foundation of intelligent manufacturing, continue to promote the R&D and industrialization of key products such as industrial robots, intelligent testing equipment, intelligent control equipment, and additive manufacturing equipment, drive innovation and breakthroughs in processes, equipment, and software in groups, and form independent, controllable, advanced and applicable intelligent manufacturing system solutions.
2. Improve the construction of the standard system and explore the "Chinese paradigm" of intelligent manufacturing. China's intelligent manufacturing innovation needs to systematically form the standardization advantages of technology and industrial ecology in order to continue to win the leading position in global competition. It is recommended to encourage enterprises in the field of intelligent manufacturing, especially leading enterprises, to take the lead in building practice and demonstration samples of intelligent manufacturing, build demonstration factories and production lines, and explore future manufacturing models and enterprise forms; Continue to encourage the deep integration of industry, academia, research and application, and guide scientific research institutions and universities to cooperate with enterprises to jointly invest in the formulation of intelligent manufacturing standards and specifications; Support domestic enterprises and experts to actively participate in international standardization work, give full play to the advantages of manufacturing scale and innovation, promote the integration of national standards and specifications with the influence of the industrial chain, encourage leading enterprises to take the lead and promote the standard exhibition, and build an ecosystem of independent innovation and controllable industrial innovation, empowerment and service.
3. Support leading enterprises to undertake major projects of intelligent manufacturing and tackle key technical equipment. Leading enterprises shoulder the important task of being the main force of high-quality development in the field of intelligent manufacturing, which can drive small and medium-sized enterprises to realize the "chain" digital and intelligent transformation, and form an ecology of coordinated development of upstream and downstream, large, medium and small. It is recommended that the Ministry of Finance, the Ministry of Science and Technology, the Ministry of Industry and Information Technology and other departments accelerate the implementation of major projects for intelligent manufacturing, promote the research and development and industrialization of key technologies and equipment such as intelligent production equipment, intelligent testing equipment, and intelligent manufacturing software, and enhance the overall competitiveness of China's manufacturing industry; Support leading enterprises to participate in the implementation of major projects related to intelligent manufacturing, give full play to the advantages and leading role of leading technologies, encourage cross-field and interdisciplinary integration and innovation through major special projects, and create advanced and practical intelligent manufacturing solutions; Establish intelligent manufacturing development from the national level, provide financial support for enterprises to build intelligent manufacturing systems and major special projects in management practices, and guide large and medium-sized enterprises to actively participate in intelligent innovation and transformation.