Sci-Tech

State owned Assets Supervision and Administration Commission: As of the end of June, the scale of intelligent computing power of central enterprises has doubled year-on-year

2024-07-29   

On July 26th, the State Council Information Office held a series of themed press conferences on "Promoting High Quality Development". The State owned Assets Supervision and Administration Commission of the State Council introduced the situation of high-quality development of state-owned assets and central enterprises. Wang Hongzhi, Deputy Director of the State owned Assets Supervision and Administration Commission of the State Council, stated that artificial intelligence is an important driving force for the new round of technological revolution and industrial transformation, as well as an important engine for cultivating new quality productivity. For some time now, state-owned enterprises have actively explored and boldly attempted in this area, achieving positive results in computing power, data, big models, and scenario applications. Fang Lei, the head of the Science and Technology Innovation Bureau of the State owned Assets Supervision and Administration Commission of the State Council, stated that in recent years, the State owned Assets Supervision and Administration Commission of the State Council has placed accelerating the development of artificial intelligence in the overall work of state-owned assets and central enterprises as the main direction of the industrial revitalization and sailing action deployment. It has formulated and issued action plans, organized and held special promotion meetings for artificial intelligence in central enterprises, carried out the "AI+" special action, and made synchronous efforts in computing power, algorithms, data, and applications, achieving positive progress in four aspects. The computing power base accelerates and solidifies. As of the end of June, the scale of intelligent computing power of central enterprises has doubled year-on-year. Ten thousand card clusters have been built in Shanghai, Hohhot and other places, and the computing power platform has initially achieved diversified and heterogeneous computing power scheduling, effectively supporting the training iteration of general large models with a scale of billions or more. The ability to independently control has gradually improved, providing strong support for large-scale application implementation. The basic model is steadily being constructed. Support the strengthening of technology and ecological cultivation for general large-scale models such as "Nine Heavens" and "Stars", and promote the catch-up of domestic first-line level in multimodal large-scale models and cross modal image generation capabilities. Continuously promote the opening and empowerment of large-scale models, and drive the joint construction of industry models by central enterprises, private enterprises, universities and institutions. Accelerate the construction of application scenarios. We have created over a hundred application scenarios in fields such as new materials, communication, and manufacturing, and have initially achieved large-scale model applications in fields such as electricity, transportation, and petrochemicals. We have significantly reduced costs and increased efficiency in research, production, customer service, and other areas. We will initially build a batch of high-quality datasets in logistics, finance, healthcare and other fields, develop data governance tools, and gradually provide value-added services such as data processing to the outside world. The industrial driving force continues to strengthen. Multiple central enterprises have released standard products such as software factories and "5G+AI" new calls at conferences such as the 7th Digital China Summit and the World Artificial Intelligence Conference. They have strengthened cooperation with private enterprises such as Huawei and iFlytek in the fields of intelligent connected vehicles and energy and chemical engineering, forming supply-demand matching, jointly creating industry models and promoting their implementation, and building a good industrial ecosystem. The development of artificial intelligence relies crucially on cooperation and ecology. The State owned Assets Supervision and Administration Commission of the State Council will work together with all sectors of society to jointly promote the continuous improvement and acceleration of industrial development in terms of infrastructure, supply, demand, and policy, and better empower high-quality economic and social development Wang Hongzhi emphasized. For the next step of development, Fang Lei stated that the State owned Assets Supervision and Administration Commission of the State Council will accelerate the promotion of using application demonstrations to drive the development of the artificial intelligence industry. Central enterprises also have confidence, determination, and ability to seize strategic opportunities, work together with various forces, and accelerate their transformation into suppliers of intelligent computing resources, converters of application scenarios, and cultivators of industrial ecology. One is to deeply explore high-value scenarios and fully open them up, carry out supply-demand collaborative cooperation, and form a number of industry application demonstration benchmarks. The second is to explore the standard system and construction path of high-quality datasets, and to build high-quality datasets for key industries in batches. Thirdly, we will orderly promote the construction of intelligent computing centers and computing power dispatch and operation platforms, strengthen the supply of intelligent computing capabilities, and better serve small and medium-sized enterprises. The fourth is to closely focus on the forefront and enhance the ability of basic big models, improve the big model evaluation system, explore the establishment of a group of industrial development communities, and accelerate the promotion of external empowerment. (New Society)

Edit:Xiong Dafei Responsible editor:Li Xiang

Source:XinHuaNet

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