Investment Rating - The report maintains a "Buy" rating for the communication industry and communication equipment manufacturing sector [4]. Core Insights - The report highlights the ongoing transformation in AI infrastructure, with a shift towards "super nodes" to address single-card computing limitations, and the adoption of liquid cooling technology [2][11]. - Alibaba's commitment to open ecosystems is emphasized, with the introduction of the Alink interconnection protocol, aiming to create a high-speed interconnected system [2][19]. - The launch of the flagship model Qwen3-Max by Alibaba demonstrates significant advancements in AI capabilities, expanding into multimodal functionalities [2][24][26]. Summary by Sections Market Overview - The communication index decreased by 0.28% while the Shanghai Composite Index rose by 0.21% and the Shenzhen Component Index increased by 1.06% [2][10]. Key Companies and Dynamics - The report recommends several companies for investment, including ZTE Corporation, StarNet, China Mobile, and others, focusing on AI computing power, core asset value reassessment, and new productivity sectors [3][4][61]. AI Infrastructure Developments - The report discusses the emergence of super nodes in AI infrastructure, which optimize computing, networking, storage, and power supply [11]. - Liquid cooling technology is becoming standard across various components, indicating a shift towards more efficient cooling solutions in data centers [14]. Ecosystem and Open Source Initiatives - Alibaba aims to build an open-source ecosystem akin to an "Android" for AI, promoting the Alink protocol to break existing technological barriers [19][20]. - The growth of a developer community around AI models is noted, with significant increases in model usage and the introduction of new development frameworks [20]. Model Advancements - The Qwen3-Max model is highlighted for its superior performance, with extensive training data and capabilities that surpass competitors in various benchmarks [25][26]. - The next-generation model Qwen3-Next is introduced, showcasing improvements in computational efficiency and multimodal capabilities [26]. Investment Recommendations - The report lists specific stocks with target prices and investment ratings, indicating a bullish outlook on companies like ZTE Corporation and China Mobile [4][61].

Investment Rating - The report maintains an "Outperform" rating for the communication industry, indicating an expected performance exceeding the benchmark index by more than 10% [36]. Core Insights - Huawei's new Ascend roadmap was unveiled at the 2025 Connectivity Conference, showcasing significant advancements in supernode capabilities, with the upcoming 950PR architecture expected to achieve 1P FP8/2P FP4 computing power and 2TB/s interconnect bandwidth [2][11]. - The collaboration between NVIDIA and Intel aims to create a new order in data centers, with NVIDIA acquiring a 4% stake in Intel and both companies working on customized data center and PC products [4][14]. - The report highlights the potential acceleration of domestic AI chip shipments in 2026, driven by Huawei's leadership in the domestic computing sector [11][12]. Summary by Sections Industry Trends - Huawei's Ascend AI chip roadmap indicates a significant leap in domestic computing capabilities, with the 950 series expected to surpass NVIDIA's previous flagship in interconnect bandwidth [2][11]. - The Atlas 950 SuperPoD supernode utilizes a hybrid copper-optical architecture, enhancing cost-effectiveness and potentially setting a benchmark for domestic computing cluster design [3][12]. Market Overview - The overall market saw an increase during the week of September 22-26, 2025, with the STAR Market index rising by 6.47% and the ChiNext index by 1.96% [6][15]. - The top-performing sectors included liquid cooling (+7.16%), IoT (+5.95%), and IDC (+1.54%) [15]. Stock Performance - Leading stocks included Cambridge Technology (+18.77%), Inspur Information (+11.86%), and Zhongtian Technology (+9.08%) [15][29]. - Stocks with the largest declines were Bochuang Technology (-14.77%), Changfei Fiber (-14.61%), and Yihua Technology (-8.95%) [15][29]. Companies to Watch - Key companies to monitor include Cambricon, Haiguang Information, and ZTE Corporation in the domestic computing sector, as well as Inspur Information and Ziguang Corporation in the supernode market [15].

Core Insights - The report highlights the significant advantages of ASIC over GPU in terms of cost-effectiveness and energy efficiency, marking a turning point for ASIC development [5][15] - The increasing penetration of AI is driving a surge in inference demand, expanding the market space for ASICs, with projections indicating the global AI ASIC market could reach $125 billion by 2028 [6][15] - The report emphasizes the importance of ASIC design service providers, noting that companies like Broadcom and Marvell hold significant market shares and are crucial for the successful deployment of ASIC technology [6][15] Summary by Sections Computer Industry Deep Dive - ASICs are specialized chips tightly coupled with downstream applications, focusing on specific needs like text and video inference, while GPUs are general-purpose [5][15] - ASICs demonstrate superior energy efficiency, with Google's TPU v5 showing 1.46 times the efficiency of NVIDIA's H200, and Amazon's Trainium2 reducing training costs by 40% compared to GPU solutions [5][15] - The demand for inference capabilities is expected to grow significantly, driven by applications like ChatGPT, which reached 700 million weekly active users by July 2025 [6][15] Market Trends - The report forecasts that the AI ASIC market will see substantial growth, with Broadcom estimating a serviceable market for large clients of $60-90 billion by 2027 [6][15] - Domestic cloud providers are increasingly investing in self-developed ASICs, with companies like Baidu and Alibaba making significant advancements in their chip development [15][16] - The report identifies two core trends in the development of domestic ASICs: PD separation and super nodes, which enhance performance and adaptability to diverse industry needs [15][16] Investment Recommendations - The report suggests focusing on companies with strong self-developed technology platforms in the small nucleic acid drug sector, highlighting firms like Rebio and Hengrui Medicine as potential investment opportunities [17] - It also recommends monitoring the performance of companies involved in the aluminum electronic materials sector, particularly Xinjiang Zhonghe, which is expected to benefit from its integrated supply chain and new alumina projects [18][20] - The report indicates that the data center industry, particularly companies like GDS Holdings, is poised for growth due to increasing demand for AI infrastructure and cloud services [21][23]

华见早安之声 请各位听众升级为见闻最新版APP，以便成功收听以下音频。 市场概述 上周五公布的美国PCE通胀符合预期，给美联储足够空间应对就业市场降温。逢低买盘支撑三大美股指结束三连跌，全周仍累跌；美监管方将放宽737 MAX交付限制，波音涨3.6%、领涨道指；特斯拉反弹4%；报道称其与台积电和苹果讨论投资，英特尔涨超4%；特朗普芯片新计划有关税威胁，台积电跌 超1%；甲骨文四连跌，一周跌超8%。 在美上市欧洲医药巨头盘中上涨，白宫澄清特朗普药品关税不适用于欧日等贸易协议国。中概指数回落超1%，蔚来和理想汽车跌近6% 美消费者信心后，两年期美债收益率刷新日低，仍连升三周。美元指数跌落三周高位，美消费者信心后刷新日低，仍创近两月最佳周表现。以太坊盘中反弹 超5%，全周仍跌超9%。 原油收创近两月新高，全周涨超5%创三个多月最大周涨。黄金逼近纪录高位，连涨六周，白银再创十四年新高，2011年来首次站上46美元，期银一度涨超 4%，全周涨超8%。纽铜一周涨超3%。 亚洲时段，创业板跌超2%，AI硬件、算力股普跌，恒科指跌近3%，小米跌8%，国债反弹，商品分化。 《付鹏说·第六季》全面升级！付鹏带你前瞻全球大类资产交 ...

以下文章来源于More Than Semi ，作者Nico More Than Semi . More Than SEMI 半导体行业研究 这篇文章，结合业内的一个专家纪要，聊一下超节点。 超节点领域的合作与方案 在超节点领域，下游CSP大厂主要找服务器供应商定制整机柜产品。服务器厂商，包括国产GPU厂商， 也在规划自己的超节点机柜，但以NV方案为主。在国内，主流超节点方案包括腾讯的ETH-X、NV的 NVL72或其变形、华为昇腾的CM384、阿里的磐久，这些已在市场推广或者有客户购买。字节在规划 大模型的以太网创新方案，以博通Tomahawk为主，还未推广。海光的方案多为传统刀片式服务器，与 NV和华为的以太网或NVLink互联不同，目前海光无类似创新方案。 互联网大厂自研方案与华为384、海光96卡、摩尔跨柜方案本质不同在于应用偏向：CM384偏训练和大 模型计算；腾讯ETH-X偏推理；字节大模型整机柜偏训练和高性能计算。服务器厂商在合作中需具备交 换机和服务器开发能力，与博通、NV、国产GPU厂商有关系。在AI服务器8卡、16卡、32卡方案有市场 占有度，才能进入CSP选型。目前入选供应商有华勤、华三、 ...

Investment Rating - The report indicates a positive investment outlook for the ASIC industry, highlighting significant growth potential driven by increasing demand for AI applications and specialized chip designs [2]. Core Insights - The report emphasizes the distinct business models of ASIC and GPU, noting that ASICs are specialized chips tightly coupled with specific downstream applications, while GPUs are general-purpose chips [3][10]. - ASICs demonstrate superior cost-effectiveness and efficiency, with notable examples such as Google's TPU v5 achieving 1.46 times the energy efficiency of NVIDIA's H200, and Amazon's Trainium2 reducing training costs by 40% compared to GPU solutions [3][15]. - The report forecasts that the global AI ASIC market could reach $125 billion by 2028, with significant contributions from major players like Broadcom and Marvell [30]. Summary by Sections 1. AI Model Inference Driving ASIC Demand - The global AI chip market is projected to reach $500 billion by 2028-2030, with AI infrastructure spending expected to hit $3-4 trillion by 2030 [8]. - ASICs are recognized for their strong specialization, offering cost and efficiency advantages over GPUs, particularly in AI applications [9][14]. 2. High Complexity of ASIC Design and Value of Service Providers - ASIC design involves complex processes requiring specialized service providers, with Broadcom and Marvell being the leading companies in this space [41][42]. - The report highlights the importance of design service providers in optimizing performance and reducing time-to-market for ASIC products [55][60]. 3. Domestic Developments: Not Just Following Trends - Domestic cloud giants like Alibaba and Baidu have made significant strides in ASIC self-research, establishing independent ecosystems rather than merely following international trends [4][30]. - The report identifies key domestic design service providers such as Chipone, Aojie Technology, and Zhaoxin, which are well-positioned to benefit from the growing demand for ASICs [41]. 4. Key Trends in Domestic ASIC Development - The report identifies PD separation and supernode architectures as two core trends in domestic ASIC development, with companies like Huawei and Haiguang leading the way [4][30]. - These trends reflect a shift towards more flexible and efficient chip designs that cater to diverse industry needs [4]. 5. Valuation of Key Companies - The report includes a valuation table for key companies in the ASIC sector, indicating strong growth prospects and market positioning for firms like Broadcom and Marvell [5].

Investment Rating - The report maintains a positive outlook on the ASIC industry, indicating a favorable investment rating for the sector [2]. Core Insights - The report highlights the significant cost-effectiveness and efficiency advantages of ASICs over GPUs, particularly in the context of AI model inference, with Google's TPU v5 demonstrating an energy efficiency ratio 1.46 times that of NVIDIA's H200 [3][19]. - The increasing penetration of AI applications is driving a surge in inference demand, expanding the market for ASICs, with projections indicating the global AI ASIC market could reach $125 billion by 2028 [3][32]. - The report emphasizes the complexity of ASIC design, underscoring the critical role of design service providers like Broadcom and Marvell, which are expected to benefit from the growing demand for custom ASIC solutions [4][44]. Summary by Sections 1. Demand Driven by Large Model Inference - The global AI chip market is projected to reach $500 billion by 2028-2030, with significant growth in AI infrastructure spending anticipated [13]. - ASICs are specialized chips that offer strong cost and efficiency advantages, particularly in specific applications like text and video inference [14][19]. - The report notes that the demand for ASICs is expected to rise sharply due to the increasing consumption of tokens in AI applications, exemplified by the rapid growth of ChatGPT's user engagement [25][31]. 2. High Complexity of ASIC Design and Value of Service Providers - ASIC design involves a complex supply chain, with cloud vendors often relying on specialized design service providers for chip architecture and optimization [41][44]. - Broadcom's ASIC revenue is projected to exceed $12 billion in 2024, driven by the success of its TPU designs for Google and other clients [60]. - The report identifies the importance of a complete IP system and design experience as key factors for service providers to secure new orders in the ASIC market [63]. 3. Domestic Developments: Not Just Following Trends - Leading Chinese cloud providers like Alibaba and Baidu are making significant strides in self-developed ASICs, indicating a robust domestic ecosystem [3][4]. - The report highlights the emergence of domestic design service providers such as Chipone and Aowei Technology, which are positioned to capitalize on the growing demand for ASICs [3][4]. - The trends of PD separation and supernodes are identified as critical developments in the domestic ASIC landscape, with companies like Huawei and Haiguang leading the way [4][44]. 4. Key Trends in Domestic ASIC Development - PD separation involves using different chips for prefill and decode tasks, enhancing efficiency in specific applications [4]. - Supernodes are being developed to create unified computing systems through high-bandwidth interconnections, with early implementations seen in domestic companies [4][44].

Core Viewpoint - The article discusses the advancements in computing power architecture, particularly focusing on Alibaba Cloud's new supernode design and its implications for large model training and inference in the AI sector [4][10]. Group 1: Supernode Design and Technology - Alibaba Cloud's supernode architecture addresses the increasing demands for memory capacity and bandwidth in large model training, moving beyond traditional GPU setups [4]. - The supernode design leverages the advantages of PPU chip design, emphasizing high-density integration [6]. - The supernode can support up to 64 cards in a single machine, with a power requirement of 300 kilowatts, necessitating advanced interconnect protocols [9]. Group 2: UALink Protocol and Industry Collaboration - The UALink protocol, initiated by a consortium including AMD, AWS, and others, aims to enhance interconnectivity in computing systems, with Alibaba Cloud as a member [5]. - The UALink alliance was formed to address the high costs of evolving proprietary technologies in the industry, with AMD contributing its Infinity Fabric protocol [5]. Group 3: PPU Specifications and Performance - The PPU features 96GB of HBM2e memory, surpassing the A800's 80GB and matching the H20's capacity, with an inter-chip bandwidth of 700GB/s [10]. - The PPU supports PCIe 5.0×15 interfaces, which is an improvement over the A800's PCIe 4.0×16, while maintaining a power consumption of 400W [10]. - The PPU is available in two versions, with the base version achieving a peak performance of 120 TFLOPS, focusing on AI inference tasks [10].

Core Insights - Intel and Nvidia have formed a historic partnership, with Nvidia investing $5 billion in Intel to co-develop customized data center and personal computing products, aiming to enhance large-scale computing capabilities [1][2] - This collaboration signifies a shift in the semiconductor industry, potentially leading to market differentiation, where competitors like AMD and ARM may face increased pressure [1][11] Group 1: Partnership Details - Nvidia will utilize its NVLink technology to integrate its AI and accelerated computing strengths with Intel's advanced CPU technology, providing cutting-edge solutions for clients [2][4] - Intel will customize x86 processors for Nvidia's AI infrastructure and launch a new x86 system-on-chip (SoC) that integrates Nvidia's RTX GPU for various PC products [2][4] Group 2: Market Reactions - Following the announcement, Intel's stock surged nearly 30%, closing with a 22.77% increase at $30.57 per share, while Nvidia's stock rose 3.49% to $176.24 per share [6][9] - The partnership has raised concerns for competitors AMD and ARM, with AMD's stock dropping over 5% initially, reflecting market apprehension about the new alliance [9][10] Group 3: Strategic Implications - Nvidia's investment is seen as a strategic move to solidify its position in the CPU market while mitigating risks from competitors like Microsoft and Amazon, which are developing their own chips [4][10] - The collaboration may also challenge TSMC if Nvidia shifts some of its chip manufacturing to Intel, although TSMC's market outlook remains stable for now [8][10] Group 4: Impact on Chinese Semiconductor Industry - The partnership could further entrench the U.S. dominance in high-end computing and data center chips, complicating competition for Chinese firms [11][12] - Chinese semiconductor companies are expected to accelerate their independent innovation efforts, particularly in the development of "super nodes" to enhance their competitive edge [11][13]

Core Viewpoint - Intel and Nvidia have formed a historic partnership, with Nvidia investing $5 billion in Intel to co-develop customized data center and personal computing products, marking a significant shift from competition to collaboration in the semiconductor industry [2][3][4]. Group 1: Partnership Details - Nvidia will utilize its NVLink technology to seamlessly integrate its AI and accelerated computing advantages with Intel's advanced CPU technology, aiming to provide cutting-edge solutions for customers [3]. - Intel will customize x86 processors for Nvidia's AI infrastructure and launch x86 system-on-chip (SoC) products that integrate Nvidia's RTX GPU chiplets for various PC applications [4]. - This partnership is seen as a strategic move for both companies, with Nvidia seeking to enhance its CPU market presence and Intel aiming to revitalize its position in the semiconductor industry [5][6]. Group 2: Market Impact - Following the announcement, Intel's stock surged nearly 30%, closing with a 22.77% increase, while Nvidia's stock rose by 3.49% [6]. - The collaboration is expected to create a new competitive landscape in the semiconductor market, particularly affecting AMD and ARM, which may face increased pressure due to the strengthened position of Intel and Nvidia [9][10]. - The partnership may also challenge TSMC's dominance if Nvidia shifts some of its chip manufacturing to Intel [9]. Group 3: Implications for Chinese Semiconductor Industry - The alliance between Nvidia and Intel could further consolidate the U.S. dominance in high-end computing and data center chips, complicating competition for Chinese manufacturers [11]. - Chinese companies are likely to accelerate their independent innovation efforts, focusing on developing "super nodes" as a key strategy to enhance their competitive edge [11][12]. - Domestic firms are exploring distributed architectures and interconnect innovations to create independent systems that do not rely on Nvidia's ecosystem, which is crucial for China's long-term technological independence [13].