Core Insights - The report highlights the rapid growth and potential of the Chinese smart chip industry, driven by advancements in artificial intelligence, IoT, and 5G technology, with a projected market size exceeding 600 billion yuan by 2030 [1][2][3] Industry Overview and Background Analysis - Smart chips are defined as highly integrated circuits capable of perception, computation, and decision-making, integrating AI algorithms and big data analysis to respond to complex environments [8][9] - The smart chip industry in China has evolved from reliance on imports to developing domestic capabilities, with significant government support and technological breakthroughs in recent years [19][23][24] Market Size and Growth Trends - The Chinese smart chip market has experienced a compound annual growth rate (CAGR) of over 20% from 2018 to 2022, driven by demand in consumer electronics, smartphones, and IoT applications [33][35] - The AI chip segment is the largest, accounting for over 40% of the market, with rapid growth in autonomous driving and edge computing chips [36][41] Technological Development and Innovation Trends - Key technologies in smart chips include Neural Processing Units (NPUs) optimized for AI tasks, edge computing for real-time data processing, and innovations in high-performance computing architectures [51][54][57] - The report emphasizes the importance of hardware-software co-design and the integration of advanced semiconductor processes to enhance performance and reduce power consumption [52][58]

最新消息，美东时间周三盘后，人工智能（AI）龙头股英伟达公布了超出预期的三季度财报。财报显示，英伟达第三财季营收为570.1亿美元，超出市场预 期的549.2亿美元；净利润为319.1亿美元，同比大涨65%，经调整后的每股收益为1.30 美元，高于市场预期的1.25美元。 场内ETF方面，截至2025年11月20日 11:09，中证人工智能产业指数(931071)上涨0.34%，成分股和而泰(002402)上涨3.03%，中际旭创(300308)上涨2.12%，奥 飞数据(300738)上涨1.73%，新易盛(300502)上涨1.55%，拓维信息(002261)上涨1.43%。人工智能ETF(515980)现涨0.25%，早盘一度高开涨超2%。 规模方面，截至2025年11月19日，人工智能ETF最新规模达80.08亿元。资金流入方面，人工智能ETF最新资金净流入1228.16万元。拉长时间看，近10个交 易日内有6日资金净流入，合计"吸金"2.80亿元。 华富人工智能ETF（515980）基金经理郜哲表示，英伟达三季度财报不仅有力回应了市场的"AI泡沫论"，为全球AI产业链注入信心，更向全球宣告：AI产业 ...

Core Insights - The report titled "2025 National AI Chip Industry White Paper" focuses on the development of domestic AI chips, highlighting their significance, challenges, innovation directions, industry landscape, core applications, and research conclusions [1] Industry Significance and Challenges - AI chips are considered the cornerstone of computing power and a key factor in global technological competition. Domestic chips must overcome three main challenges: architectural dominance, ecological shortcomings, and large-scale implementation [1] - The report emphasizes the need for breakthroughs through traditional architecture optimization and emerging architecture innovations such as RISC-V and integrated storage-computing [1] Innovation Directions - Key innovation areas include mainstream architecture AI innovations (AI instruction sets and hardware optimizations for x86, Arm, RISC-V), sparse computing (hardware support for zero-value skipping to enhance energy efficiency), FP8 precision (mass production by companies like Moer Thread to improve computing throughput), and system-level optimizations (Chiplet, integrated storage-computing, photonic integration) [1] - Domestic companies like Moer Thread, Huawei, and Yuntian Lifi have made significant advancements in sparse computing [1] Industry Landscape - The industry has developed a multi-category layout including CPU, AI SoC, cloud/edge/vehicle AI chips, and GPU, with companies concentrated in Shanghai (15), Beijing (8), and Guangdong (6). Leading firms include Huawei HiSilicon (Ascend series), Kunlun Chip (Baidu's 7nm XPU architecture), and Moer Thread (MTT S5000 supporting FP8) [1] - Research indicates that general parallel architecture (GPU clusters) is a preferred direction for computing power platforms, with computing density and software ecology being core bottlenecks [1] Core Applications - The intelligent computing industry is projected to reach a scale of 725.3 EFLOPS in 2024 and 1460.3 EFLOPS by 2026, with domestic clusters like Huawei Ascend 160,000-card cluster and Kunlun Chip's Baijie cluster already operational [1] - The smart driving industry shows a significant trend towards integrated cockpit solutions, with mass production of chips like Xiaopeng Turing and Horizon Journey 6P [1] - In the robotics sector, companies like Yushu Technology and UBTECH are accelerating commercialization, focusing on niche scenarios for domestic chips [1] - Edge AI applications cover AloT and smart home sectors, aiming for a balance between energy efficiency and cost [1] Research Conclusions - Full-stack domestic solutions are favored, with intelligent cockpit chips and industrial collaborative robots identified as key breakthrough scenarios. Ecological development needs to consider both full-stack closed-loop and open-source collaboration [1]

Group 1 - The core objective of China's AI policy is to establish a $100 billion AI industry by 2030, generating over $1 trillion in added value across various sectors [2] - China's AI policies focus on enhancing economic development and national strength, contrasting with the more abstract "general AI race" narrative in the U.S. [2] - The Chinese government is deploying a comprehensive set of policy tools, including an $8.2 billion fund for AI startups and the establishment of national AI laboratories and experimental zones [3] Group 2 - Geopolitical tensions, particularly with the U.S., have led to a shift in China's AI policy towards self-reliance and strategic competition, emphasizing the need for an independent AI ecosystem [6] - Export controls from the U.S. have restricted China's access to advanced computing chips, which are crucial for AI development, prompting Chinese companies to seek alternative strategies [7] - Despite these challenges, the Chinese AI industry is likely to continue progressing, potentially fostering the development of its own semiconductor and software solutions [8] Group 3 - The effectiveness of China's AI policies remains uncertain, but government support is crucial in addressing key bottlenecks such as domestic chip development and talent shortages [9] - The rapid growth of data center energy demands is anticipated, with projections indicating a threefold increase by 2030, which China is likely to meet due to its faster pace of new power plant construction compared to the U.S. [9] - The private sector, particularly innovative tech companies, is expected to drive advancements in AI, with government policies needing to align with private sector needs to be deemed effective [11]

Group 1 - The U.S. automotive industry is facing production halts due to a shortage of rare earth materials, which are critical for manufacturing, including the F-35 fighter jet [1][4] - China controls a significant portion of the rare earth supply chain, with the U.S. relying on Chinese processing for its own rare earth minerals [4][6] - The trade war initiated by the U.S. has inadvertently strengthened China's position in technology and manufacturing, as evidenced by the shift in trade dynamics and advancements in domestic technology [8][10] Group 2 - Each F-35 fighter jet requires 417 kilograms of rare earth materials, highlighting the dependency of U.S. military technology on Chinese resources [4] - China possesses 128 core patents for rare earth separation, allowing it to reduce purification costs significantly compared to Western companies [6] - The U.S. automotive sector incurs substantial losses from production delays, with a single day of halted operations costing $240 million [10]