NDRC Addresses Humanoid Robot "Bubble": Preventing Overcrowding of Highly Repetitive Products in Market

Deep News
Nov 27

The embodied intelligence market is projected to reach a scale of 100 billion yuan by 2030. Following large AI models, embodied intelligence has emerged as a new hotspot in the tech industry this year, recognized as a key direction in the next wave of artificial intelligence.

Li Chao, Deputy Director of the Policy Research Office at the National Development and Reform Commission (NDRC), stated at a press conference on the 27th that "speed" and "bubble" are perennial issues requiring balance in cutting-edge industries, and the embodied intelligence sector is no exception.

In recent years, driven by both innovation and demand, the embodied intelligence industry—represented by humanoid robots—has been growing at an annual rate exceeding 50%. Market research predicts the sector will achieve a 100-billion-yuan market size by 2030.

Li noted that while humanoid robots are not yet fully mature in terms of technical pathways, commercialization models, or application scenarios, over 150 domestic companies are already active in this space, with more than half being startups or entrants from other industries. While this influx fosters innovation, it also raises concerns about market overcrowding with highly repetitive products and compressed R&D opportunities.

Balancing opportunities and challenges hinges on proper guidance. The NDRC, in collaboration with relevant authorities, is conducting in-depth research to systematically address policy incentives, technological breakthroughs, and practical applications.

Li outlined next steps to promote healthy and standardized industry growth through the 15th Five-Year Plan’s specialized initiatives: 1. **Accelerating industry standards and evaluation systems**: Establishing entry and exit mechanisms to ensure fair competition and orderly development. 2. **Advancing core technology R&D**: Supporting enterprises, universities, and research institutions in tackling challenges like "brain-cerebellum" model coordination, cloud-edge computing compatibility, and simulation-real machine data integration. 3. **Boosting infrastructure**: Developing training and pilot platforms to integrate resources nationwide, facilitating real-world deployment of embodied intelligence solutions.

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