The National Data Administration yesterday (8th) issued the "Implementation Plan on Advancing the Development of High-Quality Industry Data Sets," marking the first systematic national-level deployment to empower artificial intelligence development through data. By the end of 2028, the plan aims to establish a batch of high-quality industry data sets covering key sectors and validated through practical applications, create a number of benchmark application scenarios driven by data-enabled artificial intelligence innovation, cultivate innovative data enterprises and professional talent with leading advantages, and develop a series of tools and standards for building high-quality industry data sets. A virtuous cycle from data supply to value realization is expected to take shape, further highlighting the role of data in empowering artificial intelligence innovation, deepening the integration of the data industry and artificial intelligence, and continuously fostering new growth drivers for the intelligent economy.

The plan proposes focusing on specific industries to advance the development of high-quality data sets; consolidating foundational pathways for building such data sets; enriching development models to meet artificial intelligence application needs; strengthening coordination with data infrastructure development; promoting the transformation and upgrading of data annotation; advancing pilot programs in data annotation; expanding the supply of data annotation talent; improving the quality and efficiency of high-quality industry data set development; promoting the establishment and implementation of standards systems for high-quality data sets; strengthening quality assessment and mutual recognition of results; creating a "data flywheel" application closed loop; establishing industry benchmarks and typical cases; and fostering a collaborative ecosystem for data set development.

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In addition, the plan calls for building a full life-cycle management system for data sets; exploring data-related systems aligned with artificial intelligence development; upholding ethics-first principles and fairness and inclusiveness; enhancing the application value of high-quality industry data sets; innovating business models for high-quality industry data sets; exploring assetization pathways for such data sets; and cultivating market consensus on paying for high-quality data. (jl/u)

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