The digital economy is expanding faster, wider and deeper than ever, with 5G, artificial intelligence and smart cities reshaping innovation, industrial structure and economic and social development. Driven by policy, technology and markets, China’s AI industry maintains high-speed growth, with applications in many areas at the world’s leading edge. A relatively complete industrial system has formed spanning AI root technologies, infrastructure software and application scenarios, and a group of internationally competitive companies has emerged. The industry is in an active period with broad market prospects.
In practice, though, one major challenge stands out: root technology remains relatively behind. AI root technologies are the foundational research and key techniques that support the development of AI technology and the industry derived from it. Without breakthroughs there, it will be hard to compete with a few early-moving countries that have mature ecosystems, broad markets and vast user bases. The response: play to existing strengths, promote root technology development, build intensive AI infrastructure, deepen the integration of AI with industry, and cultivate talent across multiple levels.
Four priorities
First, define an independent technology route for the AI industry and cultivate key root technologies to build the industrial system. Strengthen top-level design and build an ecosystem based on root technologies, pushing adoption across industries and scenarios; around high-performance chips, develop kernel architectures, memory systems and high-speed interconnect suited to AI computing paradigms; and foster a favourable international environment for technical and academic exchange and unified standards.
Second, build computing centres and open datasets intensively to solidify the foundation for root technology development. Invest in AI computing centres and high-quality public datasets; improve data production and flow mechanisms; standardise data formats and metadata, and develop standard libraries and toolkits with unified norms; enable tiered data access among government agencies and between government and enterprises; and improve data availability and access quality.
Third, push industry applications along the independent technology route. Build AI ecosystem innovation centres, accelerate the integration of AI with various industries and scale up applications; cultivate AI industries with major leading and driving effects, and foster a data-driven intelligent economy; and establish national key laboratories for AI-plus-industry to achieve breakthroughs and deployment in key fields.
Fourth, attach importance to talent and promote industry-academia-research collaboration. Build and improve an AI talent training system oriented to root technologies; raise society-wide AI literacy; and encourage companies and universities to cooperate on frontier research and joint innovation in AI root technologies.
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