January 13, 2011 - The National Development and Reform Commission (NDRC) and other four departments today released the implementation opinions on promoting the high-quality development of the data labeling industry (hereinafter referred to as the "Implementation Opinions").
The implementation advice mentions thatUnleashing the need for public data annotation. Deepen the application of artificial intelligence in government services, urban governance, rural revitalization and other fields, compile a catalog of public data labeling, and promote the labeling and exploitation of public data in an orderly manner in accordance with the law.
The implementation opinion also said that it supports public data to empower the development of the real economy, and explores the demand for public data labeling in key areas such as modern agriculture, intelligent manufacturing and information services. Support cross-sectoral, cross-regional and cross-level public data integration and application, and encourage government departments and enterprises to collaborate to carry out the labeling and training of the data required for the big model of government affairs.promoteData labeling servicesIntegration into public procurement.
Implementation requires thatCultivate a number of data labelingleading enterprisesEncouragement of strengthening through resource integration, mergers and acquisitions, etc.To promote the scale, standardization and intensive development of data labeling enterprises. Supporting and encouraging scientific and technological innovative data labeling enterprises to undertake key tasks such as basic research, technological research, industrial application, etc., so as to improve the level of collaborative innovation in the industrial chain. Cultivate a number of data labeling gazelles and unicorns that are deeply engaged in the industry. Promote accurate docking between data labeling SMEs and third-party organizations such as human resources, financial services, and compliance consulting to help enterprises develop rapidly.
In addition, relying on the National Key Research and Development Program and the National Scientific and Technological Major Projects.Strengthening the application of key technologies in the field of data annotation, such as cross-domain and cross-modal semantic alignment, 4D annotation, and large model annotation.. Support the research and development of intelligent tools such as multimodal annotation, annotation review, quality assessment, and expert annotation based on the chain of thought. Support the construction of a data annotation innovation platform integrating data, models, tools and scenarios, and promote the integration and innovation of data annotation technology. Support the research and development of key equipment in the field of data labeling that integrates software and hardware and is independently controllable.
Supporting the transformation and upgrading of industries empowered by data elements, and digging deep into the data labeling needs of enterprises in the whole process of production and management. Implement the "State-owned Enterprises Data Effectiveness Enhancement Action", increase the development and utilization of enterprise data, and release the demand for enterprise data labeling. Strengthen data labeling in key industries such as transportation, medical, finance, science, manufacturing, agriculture, etc., and build high-quality data sets in the industry to support the application of artificial intelligence in the industry.Focusing on scenarios such as healthcare, human resources, digital trade, automated driving, and low-altitude economy, business innovation is used to drive the demand for data annotation.
1AI was informed in the implementation comments thatTarget by 2027, data labeling industry specialization, intelligence and scientific and technological innovation capacity significantly improved, the industry scale jumped significantly, the average annual compound growth rate of more than 20%In addition, it has cultivated a number of influential science and technology-based data labeling enterprises, created a number of innovation carriers linking industry, academia, research and application, constructed a number of data labeling bases with obvious results and distinctive features, formed a relatively perfect data labeling industrial ecology, and constructed a new pattern of gathering innovative elements, upstream and downstream linkage of industrial chain, and synergistic development in the region.