5G, AI, big data, Internet of Things... At present, the development of the mainland's new infrastructure sector has entered a critical stage. During the two sessions, topics such as trends and development directions of the digital infrastructure industry have warmed up again.
Li Yanhong, member of the National Committee of the Chinese People's Political Consultative Conference and chairman and CEO of Baidu, has focused on the related fields of "intelligent transportation" and "automatic driving" in the proposals of the two sessions of the National People's Congress for seven consecutive years, and this year, "AI" artificial intelligence is still the key word in his proposal. Among them, the three proposals highlight the innovation of autonomous driving policies, promote the popularization of intelligent transportation to alleviate traffic congestion, help carbon emission reduction and develop the theme of "green AI". With the industry experience accumulated over the years, the first is to put forward the practical problems encountered in the in-depth development and landing of the AI field, and to understand it from the perspective of enterprises and society and themselves and the industry; the second is to put forward many feasible and innovative suggestions and solutions.
Accelerate the innovation of unmanned autonomous driving policies
proposal:
The first is to guide and support local governments to introduce policies, clearly support unmanned vehicles without safety personnel on the road, and create a pilot area for manned operation policies for fully unmanned autonomous vehicles.
The second is to accelerate the revision and implementation of the Road Traffic Safety Law of the People's Republic of China, and lay a legal foundation for accelerating the large-scale commercial and unmanned use of autonomous vehicles from the national level.
The third is to build intelligent transportation infrastructure in advance, give full play to the remote control advantages of 5G, promote a significant improvement in traffic efficiency and safety through vehicle-road collaboration, drive the transformation and upgrading of the automobile industry to intelligence and networking, and let the truly unmanned intelligent networked vehicles drive on China's roads as soon as possible.
The streets of Yizhuang, Beijing
unscramble:
As an important integrator of AI technology applications, the development and landing of the field of automated unmanned driving symbolizes the mainland's understanding, cognition, deep excavation and utilization of digital infrastructure such as AI technology, and is also a concentrated display of the soft power of mainland science and technology. Under the international situation of unmanned as the commanding heights of global autonomous driving technology and industrial competition, the mainland has long been in a parallel or even leading position.
Robin Li believes that in the next stage, in order to achieve new breakthroughs in the development of unmanned driving, policy innovation is the primary focus. Which country can introduce more breakthrough innovation policies and take the lead in achieving large-scale commercial use, it can win the initiative in international competition.
Build smart light poles to improve the degree of road intelligence
In fact, in 2021, the state has deployed a series of policy innovation work, the Ministry of Industry and Information Technology, the Ministry of Communications, etc. have also introduced policies around product access and application pilots, and the draft revision of the Road Traffic Safety Law drafted by the Ministry of Public Security is one of the representatives. Benefiting from policy innovation, local governments are more motivated and faster to explore the "China model" of autonomous driving. Pilot pilots of unmanned driving technology have been carried out in Beijing Yizhuang and other parts of the country in an orderly manner.
However, Robin Li said that there are still some problems in the policy innovation link that need to be further optimized. For example, the development of high-grade autonomous vehicles in the mainland is still facing situations such as not being able to enter the market, not being licensed, not being completely unmanned, not being able to operate charges, and being difficult to determine responsibility for accidents. Therefore, it is still necessary to further improve and lead the policies and bills.
Promote the green and high-quality development of urban transportation
The first is to accelerate the promotion of the intelligent transportation operator model. Support and encourage local government departments to play a leading role, coordinate the planning, construction and operation of intelligent transportation projects, and promote the transformation of one-time integrators to a sustainable operator model. Guide state-owned enterprises or platform companies in charge of government departments to accelerate the construction of intelligent transportation operator functions or set up special companies to support technology enterprises to empower intelligent transportation operators with technology and operational experience. Encourage local government departments to appropriately deploy new intelligent transportation infrastructure in advance, strengthen the pilot area of the Internet of Vehicles and the coverage area of the "double intelligence pilot", and explore the application value through scale.
The second is to establish evaluation standards for the benefits of intelligent transportation to help carbon emission reduction. Unite industry associations, university institutions, scientific research institutions and industry leaders to accelerate the study of carbon emission reduction benefit evaluation standards, formulate quantitative calculation rules for intelligent transportation to help carbon emission reduction, so that the originally difficult to evaluate intelligent transportation to help carbon emission reduction benefits become quantifiable, statistical and evaluatable, explore the carbon reduction effect evaluation of new entities such as autonomous driving operators, and determine its carbon reduction value.
The third is to carry out a pilot project of the individual carbon credit incentive system. Support local governments to introduce incentive policies, build a public carbon emissions-related data platform, explore a mechanism for linking individual green travel carbon credits with preferential policies for public services, and enhance the public's sense of green and low-carbon travel.
According to IDC data from international data company, carbon dioxide emissions from the transportation industry account for about 9% of the national total, of which road traffic emissions account for more than 80%. It can be seen that promoting the green and high-quality development of urban transportation is one of the key links to achieve the national "double carbon" goal.
In recent years, the role of intelligent transportation in alleviating carbon emissions in transportation has become increasingly prominent. For example, in Baoding, Hebei Province, after the deployment of Baidu intelligent information control system at more than 100 intersections, the vehicle travel time was shortened by an average of 20%, and the average carbon emission reduction at each intersection reached 138.6 tons/year.
"Although the policy in the field of intelligent transportation continues to land, and the mitigation effect of carbon emissions in the transportation area is remarkable, there is still a lack of coordination in construction and a lack of unified standards for the assessment of carbon emission reduction benefits in some areas, which restricts the full play of intelligent transportation to help carbon emission reduction." Robin Li said.
Therefore, Robin Li suggested that in order to further improve the energy-saving and emission-reduction effect of intelligent transportation, the intelligent transportation operator model should be promoted as soon as possible, so as to improve the operational efficiency of transportation networks such as subways and buses. In addition, the efficiency standards for intelligent transportation to help carbon emission reduction can be quantified, and the linkage mechanism between personal green travel carbon credits and preferential policies for public services can also further stimulate enterprises and individuals to participate in intelligent transportation and travel emission reduction actions.
Accelerating the development of "green AI"
The first is to explore the dual control of carbon emissions in the data center. According to the Calculation of the National Information Center, data centers only use about 2% of the electricity consumption of the whole society, supporting the scale of the digital economy, which accounts for about 36.2% of the country's GDP. It is recommended that relevant departments support areas with conditions to increase policy innovation, and the amount of green electricity used in data centers is not included in the energy consumption assessment.
The second is to establish a green algorithm metric that takes into account both performance and energy consumption, and advocate leading artificial intelligence enterprises to build pre-trained large models with high energy efficiency and excellent performance, and open it to the industry.
The third is to accelerate the improvement of the carbon emissions statistical accounting system and open the issuance of national certified voluntary emission reductions. Accelerate the establishment of a methodology library and industry standards for scientific and technological emission reduction, and strengthen the technical supply of green AI in the field of reducing carbon emissions.
Yangquan data center top floor photovoltaic power generation system
On October 24, 2021, the Central Committee of the Communist Party of China and the State Council issued the Opinions on The Complete, Accurate and Comprehensive Implementation of the New Development Concept to Achieve Carbon Peak and Carbon Neutrality. According to the opinions, by 2030, the comprehensive green transformation of economic and social development will achieve remarkable results, and the energy utilization efficiency of key energy-consuming industries will reach the international advanced level。 By 2060, the economic system of green and low-carbon circular development and the clean, low-carbon, safe and efficient energy system will be fully established, the energy utilization efficiency will reach the international advanced level, and the proportion of non-fossil energy consumption will reach more than 80%.
Under the guidance of the "3060 double carbon" goal, the development of green AI that is more environmentally friendly will become a great impetus. Robin Li believes that to help the development of green AI, on the one hand, it is necessary to develop green computing power. Among them, the data center is an important carrier of computing power. In order to shorten the gap between data center energy efficiency and expected goals, many leading technology companies represented by Baidu use green electricity and technology to optimize processes and reduce data center energy consumption.
Baidu Yangquan Data Center
It is understood that the green computing base of Baidu Intelligent Cloud includes the AI chip "Kunlun Core" independently developed by Baidu, the ai heterogeneous computing platform "Baige" with high performance and extreme elasticity, and the green energy-saving data center, providing efficient and stable computing support for AI technology research and development and large-scale applications. At present, the average annual PUE of Baidu's single data center is as low as 1.08, far below the global average of 1.59.
On the other hand, it is necessary to develop greener algorithms, optimize strategies and parameter settings, and reduce the energy consumption of ultra-large-scale pre-trained models, so as to build a large model of green intensification and improve the energy efficiency ratio of infrastructure.
In addition, in the evaluation and assessment of green AI development, there are still three major problems in terms of evaluation and assessment, "the use of green electricity in data centers still faces the dual control assessment of energy consumption", "the green algorithm measurement standard system has not yet been established", and "the lack of a sound carbon emission statistics accounting system". Therefore, Robin Li suggested that it is necessary to strengthen policy guidance, improve the standard system, and accelerate the green and high-quality development of advanced technologies to empower the industry.