Development of Artificial Intelligence Chips in China

Artificial intelligence (AI) chips are the core hardware supporting the development of intelligent technologies and their technological advancements hold significant importance for national scientific innovation, industrial development, and economic growth. This study summarizes the global development trends of AI chips from three perspectives: cloud AI chips, edge AI chips, and neuromorphic chips. It analyzes the application demands of AI chips in China and reviews the current status and development trends of related industries and technologies from the aspects of chip design, manufacturing, and packaging and testing. Currently, AI chips manufactured in China have shortcomings in terms of performance, technologies, and supply chain, necessitating independent innovation and industrial collaboration. The development of these chips also encounters challenges such as high costs and long cycles, requiring stable financing channels and the accumulation of development experiences. Moreover, the AI chip sector in China suffers from a talent shortage, demanding improved training quality and better talent-retaining strategies. Accordingly, this study proposes development paths for China’s AI chip industry, including overcoming technical bottlenecks, accelerating industrialization, expanding internationalization, and implementing market support. Key measures include advancing technological innovation and major project development, fostering new chip architectures and open-source industry ecosystems, establishing technical standards, and promoting the integration of industry, education, and research. These efforts aim to drive the sustainable and high-quality development of China’s AI chip industry.

Publication Details

Journal
Strategic Study of CAE
Published
2025-01-01
DOI
https://doi.org/10.15302/j-sscae-2024.10.028
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Artificial Intelligence Chips in China

1 citations
Strategic Study of CAE
Advanced Memory and Neural Computing
0.73
article

Development of Artificial Intelligence Chips in China

article en
1 citations

Abstract

Artificial intelligence (AI) chips are the core hardware supporting the development of intelligent technologies and their technological advancements hold significant importance for national scientific innovation, industrial development, and economic growth. This study summarizes the global development trends of AI chips from three perspectives: cloud AI chips, edge AI chips, and neuromorphic chips. It analyzes the application demands of AI chips in China and reviews the current status and development trends of related industries and technologies from the aspects of chip design, manufacturing, and packaging and testing. Currently, AI chips manufactured in China have shortcomings in terms of performance, technologies, and supply chain, necessitating independent innovation and industrial collaboration. The development of these chips also encounters challenges such as high costs and long cycles, requiring stable financing channels and the accumulation of development experiences. Moreover, the AI chip sector in China suffers from a talent shortage, demanding improved training quality and better talent-retaining strategies. Accordingly, this study proposes development paths for China’s AI chip industry, including overcoming technical bottlenecks, accelerating industrialization, expanding internationalization, and implementing market support. Key measures include advancing technological innovation and major project development, fostering new chip architectures and open-source industry ecosystems, establishing technical standards, and promoting the integration of industry, education, and research. These efforts aim to drive the sustainable and high-quality development of China’s AI chip industry.

Strategic Study of CAEVol. 27(1)
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.