According to the transcript published on the official website of the National Development and Reform Commission, Li Chao, Deputy Director of the Policy Research Office of the NDRC, said at today's NDRC regular press conference for August that the robot industry involves numerous cutting-edge technologies, including artificial intelligence, advanced manufacturing, and new materials. It must develop in a healthy and orderly manner suited to local conditions, based on local resource endowments and industrial strengths, with clear positioning and full use of local advantages, to avoid blind following and hasty expansion and ensure that related industries develop steadily and sustainably.
Going forward, the NDRC will focus on practical measures and effective implementation, using embodied intelligence training facilities and application pilot-production bases as the levers to enable robots to iterate their technologies in real-world scenarios and form closed application loops around real needs.
First, it will coordinate the deployment of embodied intelligence training facilities and strengthen the supply of data, models, standards, and other essential elements.
In terms of data, it will build a high-quality real-machine data collection system, improve the quality and scale of embodied intelligence data supply, and address the “data hunger” problem in embodied intelligence training.
In terms of models, it will rely on high-quality data and real-world scenarios to support embodied-model companies in exploring multiple technical routes, encourage innovation in cutting-edge areas such as vision-language-action models and world models, and accelerate technological convergence and application implementation.
In terms of standards, it will promote the development of a technical standards system for embodied intelligence, reduce the cost of cross-platform model adaptation through unified standards, and promote joint development and sharing of technologies.
Second, it will develop and make effective use of the national application pilot-production base for artificial intelligence in the field of embodied intelligence, accelerating application implementation and expansion of industrial scale.
For application implementation, it will expand the embodied intelligence training scenario library, encourage relevant industry companies to open up real-world scenarios, support embodied intelligence companies in conducting reliability and safety testing, and accelerate the implementation of embodied intelligence in real-world scenarios across manufacturing, healthcare, consumer, services, and public safety.
For industrial-scale expansion, it will rely on pilot-production bases to promote the aggregation and coordination of complete-machine, supporting, and scenario companies, help small and medium-sized enterprises clear the validation barrier from “prototype to mass production,” and create a healthy industrial ecosystem in which various types of companies develop through mutual integration.