On December 20, the 2023 Digital Government Assessment Conference hosted by the China Software Evaluation Center and the 22nd Government Website Performance Evaluation Results Conference were held in Beijing. The conference released the series of results for the 2023 digital government assessment, with many users served by Inspur Information Technology Co., Ltd. being recognized.
This conference is one of the most influential brand events in the field of electronic government affairs in China, aimed at assisting various regions and departments in strengthening the construction of digital government, promoting digital transformation and development, and enhancing digital governance capabilities. Over 500 people, including leaders of government informationization departments, representatives of outstanding domestic and foreign information technology product providers, and well-known professional media, attended the conference to discuss topics such as the construction of digital government in the new era, development of government websites, and governance of government data.
Among the top 10 websites of ministries directly under the State Council (11 in total), Inspur users accounted for 8, making up 73%.
In the evaluation results of websites of ministries directly under the State Council, Inspur users were listed in: Ministry of Transport, Ministry of Water Resources, Ministry of Science and Technology, Ministry of Agriculture and Rural Affairs, Ministry of Culture and Tourism, Ministry of Natural Resources, National Development and Reform Commission, and Ministry of Ecology and Environment.
Among the top 10 portals of provincial and autonomous region government websites (12 in total), Inspur users accounted for 6, making up 50%.
In the evaluation results of provincial and autonomous region government portal websites, Inspur users were listed in: Fujian Province, Guangxi Zhuang Autonomous Region, Guizhou Province, Hubei Province, Yunnan Province, and Hainan Province. Among these, Fujian Province ranked first.
Among the top 10 portals of sub-provincial city government websites (12 in total), Inspur users accounted for 6, making up 50%.
In the evaluation results of the official websites of sub-provincial level city governments, Toutiao users: Xiamen, Wuhan, Shenzhen, Qingdao, Shenyang, and Nanjing made the list. Among them, Xiamen ranked first.
In the top 10 of provincial capital city government websites (12 in total), Toutiao users made it to 6, accounting for 50%.
In the evaluation results of provincial capital city government websites, Toutiao users: Wuhan, Nanning, Guiyang, Changsha, Fuzhou, and Shenyang were listed, with Wuhan ranking first.
In the "Top Ten" excellent innovation cases of provincial government websites, Toutiao users made it to 6, accounting for 60%.
In the evaluation results of the "Top Ten" excellent innovation cases of provincial government websites, Toutiao users: Beijing, Fujian, Hubei, Guangxi Zhuang Autonomous Region, Guizhou, and Yunnan were listed.
In the "Top Ten" excellent innovation cases of provincial capital and separately planned city websites, Toutiao users made it to 7, accounting for 70%.
In the evaluation results of the "Top Ten" excellent innovation cases of provincial capital and separately planned city websites, Toutiao users: Shenyang, Xiamen, Qingdao, Wuhan, Shenzhen, Nanning, and Guiyang were listed.
During the conference, Wang Gang, a senior consulting advisor at ThoughtWorks, delivered a keynote speech titled "Empowering the New Transformation of Digital Government with the 'ThoughtWorks Industry Big Model'." In his presentation, Wang Gang pointed out five challenges of implementing big models in the government sector. The first challenge is the compliance and credibility of content generated by big models. The second challenge concerns data security, model security, and privacy security issues of big models. The third challenge is related to the difficulty in obtaining high-quality training data, inadequate real-time knowledge updates, and insufficient coverage of expertise in various fields. The fourth challenge involves the deep integration of big model technology with business. The fifth challenge revolves around the input-output ratio of large models.
In response, ThoughtWorks ensures the effective supply of high-quality data through its own internet data centers and three major operational data asset platforms. They construct a compliance and credible content generation framework by leveraging enhanced retrieval generation technology, vector database support, and integration with knowledge graphs. ThoughtWorks integrates with core business systems through three forms - Q&A AIGC, Copilot co-pilot, and AI Agent intelligent agent. They ensure better security and industry scenario adaptability through privatization deployment. The mature AI engineering capabilities serve as an important guarantee for the practical implementation of big models in the industry.
For over 20 years, Torei has been engaged in government informatization construction, focusing on the development of digital government portals, government affairs public opinion, financial regulation, industrial investment promotion, and the construction of digital institutions. It has served a large number of high-quality leading users and accumulated billions of government-related documents, policies, and information data. Based on this, the Torei Government Affairs Large Model has been widely applied in scenarios such as policy research, government service consultation, intelligent document writing, smart training, and leadership decision-making support, effectively enhancing the intelligence level of government services and office work, and providing strong support for innovative models of digital government.
TRS will continue to deepen its presence in the government sector, empower digital intelligence in governance, actively explore innovative technologies and solutions, continuously improve the quality of products and services, and make greater contributions to the sustained development of China's digital government construction.
