中国将在左右国家和企业竞争力的人工智能领域，加快构建不依赖美国半导体的供应链。 华为展示自己开发的AI半导体等技术等（2025年7月，上海市） 上海计划2027年时面向AI等的数据中心使用的半导体，中国能自主控制的比率提高到70%以 上，而北京计划提高到100%。中国将摆脱对美国英伟达产品的依赖，推动转向华为等产品…… 中国的主要地方政府计划到2027年将人工智能（AI）等数据中心使用的半导体的国内自给率提高到70% 以上。中国将摆脱对美国英伟达产品的依赖，以国有通信大型企业为牵引，推动转向华为等产品。 试图取代英伟达的是华为开发的AI半导体"昇腾910"系列。中国媒体报道称，目前的主力产品910B的计 算能力相当于英伟达面向中国的产品"H20"的85%左右。新一代的920性能提高，可替代H20。 昇腾由中国主权财富基金出资的中芯国际（SMIC）等负责生产，将推进微细技术的开发。除华为之 外，百度旗下的昆仑、中科寒武纪科技等也在加紧开发。 据中信建投证券的信息，中国移动决定在2024～2025年采购的总额为191亿元的AI服务器半导体全部为 华为产品。 根据上海市政府的计划，到2027年，在面向AI等的数据中 ...

英伟达创始人黄仁勋公开表示，华为是英伟达面临一个很强的竞争对手，包括说到全球一半的 AI学者来自中国。 从 2月Deepseek发布后，各家大厂纷纷上调了自己的资本开支。国产算力迎来了一波气势如 虹的行情，再次期间迎来了一波让外资垂涎三尺的科技行情。 然而行情在腾讯公布完资本开支之后，明显有逐步的降温，4月的"关税战"更是迎来爆头一 击，这里随之而来就是连续3个月的下跌，基本是将涨幅跌去了一半。 这里最核心的问题是中美之间的摩擦，导致各家大厂有钱花不出去。 各家大厂都出现了拿卡难 的问题，这里会一定影响各家数据中心的扩张速度。 然而年初暴跌的英伟达历经 Deepseek对于算力需求不大以及"关税战"冲击之后已经重新新高 了，包括海外的几家数据中心也不断创下了新高。海外的需求依旧旺盛，各家大厂依旧是疯抢 算力卡。国内"易中天"三家达链光模块，有的甚至创出了历史新高。 面对 AI的浪潮来临，一些负面的声音更像是大海之中的一些小浪花。 面对AI这种最有想象力 的行业，国内自然也不会缺席，包括近期的中美之间的协商，将一些半导体的限制也是摆在桌 面去谈判，这里其中包括算力卡的出口放开条件。 与此同时国内在这一块也是奋起 ...

Core Viewpoint - The article discusses the growing interest and procurement plans for domestic GPUs, particularly Huawei's Ascend series, in light of increasing restrictions on GPU imports from the U.S. [1] Domestic GPU Procurement Situation - ByteDance is the most proactive in adopting domestic GPUs, primarily using Cambrian and Ascend, with plans to increase procurement in 2025 [2] - Alibaba is more cautious, planning to purchase Haiguang and Cambrian cards in 2025 while continuing to stockpile NVIDIA products [3] - Tencent is the most conservative, preferring NVIDIA products, followed by H company's offerings, and only considering Cambrian and Haiguang as alternatives [3][4] Ascend 910 Series Latest Situation - As of early June, the Ascend 910B has shipped approximately 160,000 units, while the 910C has only shipped about 27,000 units due to production delays [5] - The 910C has received positive feedback for its cluster capabilities but still lags behind NVIDIA in performance [5][6] - The annual shipment target for the Ascend series has been adjusted from 850,000 to around 700,000 units due to demand fluctuations and market conditions [6] Application Scenarios and Challenges - Approximately 15% to 20% of Ascend cards are used for model training, with the majority for inference tasks [6] - High costs and technical challenges limit the widespread use of Ascend cards in high-end training applications [6][8] - The development of multi-modal models is driving higher hardware standards, with domestic manufacturers striving to catch up with international brands [7] Custom Development and Market Outlook - Collaborating with Ascend for customized development offers cost advantages but requires significant human resources for adaptation [8] - The domestic chip industry is expected to expand its market share as technology advances and market demands evolve [8]

Core Viewpoint - The report from Mizuho Securities provides an analysis of companies including Broadcom, NVIDIA, AMD, Supermicro, and Huawei, highlighting the expected growth and challenges in the AI ASIC and GPU markets. Group 1: Broadcom and NVIDIA - Mizuho expects Broadcom's custom ASIC chips (TPUv7p/MTIA2) to accelerate in deployment by 2026, potentially being used in OpenAI's Strawberry and Apple's Baltra projects in the second half of 2026 [1] - In 2024, Broadcom's custom ASIC chips are projected to account for 70%-80% of usage, establishing it as a leader in AI ASICs, excluding self-manufactured AI ASICs like Google's TPU [1] - The UMAIN project in Saudi Arabia plans to deploy 4,000 GB200 NVL72 servers, corresponding to 280,000 NVIDIA GPUs and 350,000 AMD GPUs over the next five years [1] - The G42 project in the UAE has committed to importing 500,000 NVIDIA GB200 GPUs annually, valued at $15 billion, although the sustainability of this figure is questioned [1] Group 2: Huawei - The report anticipates that Huawei's Ascend 910 orders will exceed 700,000 units by 2025, with the next-generation Ascend 920 expected to launch in 2026 [2] - However, the current yield rate for the Ascend 910 is low at only 30%, a figure corroborated by previous reports [2][3] - Other estimates suggest that the shipment volume for the Ascend 910 series could be over 700,000 units this year [5]

Group 1: Macroeconomic and Industry Background - The return of the technology growth market in May is supported by a combination of loose liquidity and a recovery in risk appetite, with global liquidity remaining abundant and the offshore RMB surpassing 7.20 [2] - The US Federal Reserve's dovish signals and a shift in US fiscal policy towards balance have contributed to a weaker dollar, which further strengthens the rationale for allocating to growth stocks [2] - The end of the April earnings season has cleared risks for the technology sector, with the TMT sector's trading congestion dropping to an 11% historical low for 2023, providing space for capital rotation [3] Group 2: AI Revolution Deepening - Major overseas tech companies have significantly increased capital expenditures related to AI, with a year-on-year growth rate exceeding 30%, focusing on computing chips and cloud infrastructure [7] - The market anticipates that global AI computing investment will exceed $200 billion by 2025, indicating a robust demand for AI infrastructure [7] - Domestic companies are accelerating the deployment of multimodal AI agents, with new AI hardware products being launched, driving the transformation of consumer electronics towards "AI + terminals" [9][10] Group 3: Intelligent Robotics - The mass production of humanoid robots is accelerating, with predictions indicating that by 2050, there will be 100 million humanoid robots globally, generating annual revenues of $5 trillion [11] - The market for exoskeleton robots is expanding, with applications in medical and industrial fields, and the expected market space exceeding hundreds of billions [15] - The US's tariff exemptions on auto parts are reducing costs in the supply chain, benefiting the automotive and robotics sectors [17] Group 4: Autonomous Driving - Policies in both China and the US are accelerating the commercialization of autonomous driving, with new regulations and operational licenses being issued [18] - Key segments of the industry chain benefiting from this trend include high-precision sensors, computing chips, and high-precision mapping [19] Group 5: Investment Strategy for May - Focus on core sectors such as AI, robotics, and autonomous driving, with specific attention to AI applications and hardware, including AI PCs and AI glasses [20][21] - Identify key components in robotics, such as dexterous hands and lightweight materials, as well as critical elements in autonomous driving like lidar and vehicle communication [21] - Emphasize the importance of selecting companies with high R&D investment and strong order visibility while avoiding stocks with uncertain earnings [23]