Shulou(Shulou.com)11/24 Report--

CTOnews.com, March 28, according to the China Institute of Information and Communications, the China Academy of Information and Communications is now starting the construction of large model technology and application benchmarks, aiming at the current mainstream data sets and evaluation benchmarks are mainly in English, lack of Chinese characteristics, culture and difficult to meet the needs of application selection in key industries. Jointly with the mainstream innovation players in the industry, we will jointly build a set of benchmarks and evaluation tools AISHPerf-LargeModel covering multi-task areas and multi-evaluation dimensions, so as to promote the leading innovation of large model technology and applications in China.

Here is the content of the notification:

At present, the large model has shown the characteristics of the continuous expansion of industrial ecology, the rapid emergence of scene applications, and the gradual clarity of the business path, which has become the main line of technological innovation in the artificial intelligence industry at the present stage. In order to further promote the development of technological innovation and engineering application of large models in China, the China Institute of Information and Communications (hereinafter referred to as "China Institute of Information and Communication") is now starting the construction of large model technology and application benchmarks. in view of the current mainstream data sets and evaluation benchmarks are mainly in English, lack of Chinese characteristics, culture and difficult to meet the needs of application selection in key industries. Jointly with the mainstream innovation players in the industry, we will jointly build a set of benchmarks and evaluation tools AISHPerf-LargeModel covering multi-task areas and multi-evaluation dimensions, so as to promote the leading innovation of large model technology and applications in China.

AISHPerf-LargeModel belongs to the category of artificial intelligence software and hardware benchmark evaluation system (CTOnews.com Note: Performance Benchmarks of Artificial Intelligence Software and Hardware, hereinafter referred to as AISHPerf). AISHPerf is led by China Institute of Information and Communication to meet the actual needs of independent ecological construction and industry, around the performance of AI chips and algorithm tasks, build testing benchmark tasks in the field of domestic artificial intelligence software and hardware, and promote the development of related technologies.

China Information and Communication Institute has been carrying out in-depth research and industrial cultivation around the large model, and has carried out a number of work before this:

The first is the large model capability evaluation, which constructs an evaluation system of more than 30 subdivided tasks around natural language processing, multimodal technical capabilities and system platform functions. promote the completion of large-scale pre-training model system capability evaluation of innovative subjects such as Baidu, Institute of Automation of the Chinese Academy of Sciences, Wuhan Institute of artificial Intelligence, Lianhui Science and Technology, etc.

The second is to release the industrial ecological perspective map V1.0 of the large model, which combs the main innovative subjects of the four key links in the current large model field: computing facilities, basic large model, platform and service, and typical application of the large model. At the same time, the key application mode and evolution trend of the large model landing are analyzed. At present, the industrial ecological perspective map V2.0 has been started, and the industry is welcome to participate.

Third, relying on the "Xingzhi Cup" National artificial Intelligence Innovation and Application Competition sponsored by the Ministry of Industry and Information Technology and the Ministry of Science and Technology, set up an innovative application competition based on large-scale pre-training models, and build a large model resource pool to build a number of innovative solutions that can give full play to the advantages of large models and solve pain points in the field.

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