在大型科技股中，亚马逊是美银在2026年第一季度的首选股，并着重介绍了该公司的潜在优势。 Post看好亚马逊云服务（AWS）的持续加速增长，以及零售业务的效率提升。华尔街的预测显示， AWS的年增长率将达到 21%。但Post认为，随着亚马逊在2026年拥有更多的云服务能力和更完善的基础 设施，这一数字可能会被超越。 与此同时，亚马逊在自研人工智能芯片Trainium方面也取得了进展，其最新的Trainium3产品提高了效率 和计算能力。Post表示，该芯片的未来版本将与英伟达的技术集成，这可能会使AWS成为用于人工智能 工作负载的最低成本供应商。 在零售业务方面，亚马逊通过广告业务的增长、更高效的库存管理、机器人技术的应用以及减少员工数 量等方式来推动利润率的增长。Post写道，凭借超过100万台的机器人以及更高效的物流中心，亚马逊 的零售利润率预计将从2025年的6.1%增长到2027年的8.3%。 Post强调，亚马逊的零售业务和云业务都使该公司具备成为企业电子商务默认基础设施的能力。他还指 出，由于其Prime服务，亚马逊在美国电子商务市场的份额超过40%。 在人工智能（AI）交易持续火热的背景下，华 ...

在人工智能(AI)交易持续火热的背景下，华尔街已开始挖掘下一批"赢家"。美国银行(Bank of America) 认为，AI交易的下一阶段将取决于自主智能体，而包括亚马逊五只股票可能会引领这一涨势。 尽管有关人工智能产业被过度炒作的言论颇多，但美银认为"市场过热的阶段"仍未来临。该行在最新报 告指出，过去两年，人工智能领域一直以聊天机器人和大型语言模型为核心，而2026 年将成为"自主型 人工智能"的元年，即能够自主执行任务的软件将占据主导地位。 据美银分析师Justin Post称，人工智能行业的繁荣态势要到那些"最引人注目的AI独角兽"(即估值超过 100亿美元的AI初创企业)上市之后才会达到顶峰。这些企业包括 OpenAI、Anthropic和xAI等，外界猜 测它们可能在2026年进行首次公开募股。 而在此之前，投资机会在于那些能够运用具备购物、预订旅行服务以及执行其他操作功能的代理系统的 公司。美银的首选为亚马逊、美国的行动技术公司AppLovin、在线家居商店Wayfair、智游网集团 (Expedia Group)和在线视频游戏平台Roblox，并认为它们是AI代理技术革命的最大受益者。 在大 ...

随着AI大周期的开启，全球科技产业正处于结构性变革的初期。尽管市场对资本开支与回报节奏仍有 讨论，但AI对生产力的潜在提升已确立了其长周期增长的主旨。2026年将成为观察AI基础设施约束、 芯片竞争格局演变及终端应用整合的关键窗口期。 据追风交易台消息，汇丰Nicolas Cote-Colisson分析团队7日发布报告，认为AI目前正处于大周期的初始 阶段。尽管2025年10月曾出现资本开支预期领先于初期营收的情况，但考虑到AI发展的速度及其对全 球超过110万亿美元GDP的潜在带动作用，市场对2026年的前景保持乐观。分析认为，风险、机遇与叙 事重点将集中在六个核心维度。 在宏观层面，汇丰对2026年的美股表现持乐观态度，将S&P 500的目标价定为7500点。分析师建议投资 者将AI贸易从单纯的基建供应商扩展至应用者和推动者。 云端产能受限与资本开支上行 全球三大云巨头（亚马逊、微软、Alphabet）订单积压严重，但产能扩张受限于数据中心建设周期。汇 丰预计产能紧张状况将持续至2026年。 在此背景下，科技巨头的投入意愿依然强劲。Alphabet、Meta和亚马逊均暗示2026年资本开支将出 现"显著/ ...

Core Viewpoint - The rise of non-GPU chip forces is unstoppable, indicating a significant shift in the global computing power industry, traditionally dominated by NVIDIA GPUs [1][6]. Group 1: Recent Developments in the Computing Power Industry - Shanghai's leading GPU company, Muxi Co., recently listed on the STAR Market, with its stock price surging by 687.79% to a market cap of 329.88 billion yuan [1]. - Google’s TPU has secured orders worth over 100 billion yuan, breaking the GPU monopoly in the computing power market, while Broadcom's CEO revealed a total order of 21 billion USD (approximately 148.6 billion yuan) from Anthropic [2]. - In China, the computing power industry is also heating up, with AI chip company Qingwei Intelligence securing over 2 billion yuan in financing, supported by a rare investment lineup [2]. Group 2: Market Trends and Dynamics - The global computing power market is experiencing a transformation, with the long-standing NVIDIA GPU monopoly beginning to loosen [2][6]. - The demand for general computing power has led to NVIDIA GPUs dominating the market, but alternatives like Google’s TPU and Amazon’s Trainium3 are starting to replace GPUs in specific scenarios [2][8]. - By the first half of 2025, non-GPU computing cards are expected to account for 30% of the domestic market [2]. Group 3: Investment Movements - Intel is reportedly planning to acquire AI chip unicorn SambaNova for 1.6 billion USD (approximately 11.29 billion yuan) to regain competitiveness in the AI era [3]. - Non-GPU unicorn Groq has raised over 3 billion USD (approximately 21.3 billion yuan) in funding over the past two years [3]. Group 4: Industry Structure and Future Directions - The computing power industry is expected to face path differentiation, driven by demand, technology, and ecosystem development [8][10]. - The need for efficient computing solutions is pushing companies to seek alternatives to the traditional GPU-centric model, especially as AI applications diversify across various industries [8][9]. - The traditional von Neumann architecture is facing challenges, necessitating architectural innovations to overcome performance limitations [9]. Group 5: Non-GPU Market Growth - Gartner predicts that by 2027, the demand for AI inference applications will lead to AI accelerators (typically non-GPU AI-specific chips) surpassing GPU shipments [16]. - In the first half of this year, China's non-GPU chip market has shown significant growth, with projections indicating a market share of nearly 50% by 2028 [16]. Group 6: Domestic Chip Companies and Their Strategies - Key players in the domestic non-GPU sector include Kunlun Chip, Cambricon, and Qingwei Intelligence, each representing different technological routes [25][29]. - Cambricon and Kunlun Chip focus on ASIC routes, while Qingwei Intelligence emphasizes reconfigurable computing architectures [29][30]. - The ASIC architecture, exemplified by Google’s TPU, offers high performance and efficiency, but requires significant time and resources for customization [30][31]. Group 7: Reconfigurable Computing Advantages - Reconfigurable computing is gaining momentum, addressing the inefficiencies of GPUs and the rigidity of ASICs, thus balancing performance and cost [32][37]. - Qingwei Intelligence's reconfigurable chips have achieved over 30 million units shipped, with significant orders expected in the coming years [32]. - The technology supports efficient inter-chip communication, avoiding bandwidth bottlenecks and communication delays inherent in traditional architectures [33]. Group 8: Conclusion - The AI computing power landscape is evolving towards a diversified and heterogeneous integration, with GPUs maintaining dominance in general-purpose applications while non-GPU routes rapidly rise in AI inference and specialized computing needs [39][41].

来源：股市直击 技术迭代与供需瓶颈凸显价值 当前，光模块产业正处在从800G向1.6T甚至更高速率演进的技术迭代期。一方面，800G产品正在放 量；另一方面，1.6T等更先进产品加速导入，但高端光模块的交付周期已出现延长，供需紧张态势显 著。这种技术快速迭代和供给瓶颈并存的局面，使得那些在高速率产品上技术领先、已通过客户认证或 实现批量交付的龙头企业（如中际旭创、新易盛、天孚通信等）获得了更强的定价权和业绩确定性，从 而受到市场追捧。 政策与产业环境持续向好 近期国内政策层面也释放出积极信号。算力产业生态高质量发展大会的召开，进一步强调了发展算力产 业的重要性，并有大规模算力基础设施合作项目签署。同时，国家层面设立商业航天司等举措，也间接 带动了包括算力在内的新兴科技板块的市场热度。这些因素共同营造了有利于算力产业发展的宏观环 境，增强了投资者信心。 外围环境改善与国产替代加速 12月17日，A股市场算力硬件板块强势上涨，其中联特科技、中瓷电子午后双双涨停，奕东电子回封涨 停。炬光科技、源杰科技涨超10%，天孚通信、新易盛等个股跟涨，显示出资金对该板块的持续青睐。 此番算力硬件股，尤其是CPO（共封装光学）概 ...

Core Viewpoint - OpenAI is negotiating with Amazon for a financing deal of at least $10 billion, while considering the use of Amazon's AI chips in its operations [2][4]. Group 1: Amazon's AI Chips - The potential deal would provide Amazon's AI chip Trainium with a significant customer, as it aims to reduce reliance on Nvidia [4]. - Amazon's AWS recently launched the next-generation Trainium3 chip, which boasts a performance increase of up to 4.4 times compared to its predecessor, with energy efficiency also improving by 4 times and memory bandwidth nearly doubling [4]. - The UltraServer system built on this chip can support up to 144 chips in a single system and can scale to deploy up to 1 million Trainium3 chips, achieving a total scale that is 10 times that of the previous generation [4]. Group 2: Industry Trends - The move by OpenAI to incorporate Amazon's chips indicates a broader trend among leading AI companies to diversify their supply chains and reduce dependency on a single supplier [4].

Core Viewpoint - The liquid cooling industry is expected to experience rapid demand growth starting in 2026, while supply will lag behind, creating a highly favorable market environment for early movers in the sector [17]. Demand Side - As the power consumption of AI computing cards and cabinets increases, traditional air cooling solutions become inadequate, necessitating the adoption of liquid cooling solutions for effective heat dissipation. Specifically, cabinets with power consumption exceeding 35-40KW cannot utilize air cooling [4]. - North America faces severe electricity shortages, and liquid cooling can significantly reduce Power Usage Effectiveness (PUE), thereby saving energy costs and alleviating delays in data center projects caused by power shortages. Liquid cooling solutions can achieve a PUE of less than 1.2 [4]. - Many data centers in North America are located near economic centers or residential areas, and liquid cooling can significantly reduce noise levels compared to air cooling, accelerating project implementation and reducing financial costs [6]. Supply Side - The supply landscape for liquid cooling in North America is currently dominated by American and Taiwanese manufacturers, with limited participation from mainland Chinese firms. The primary technology used is cold plate liquid cooling, which accounts for over 98% of the market [11]. - The verification process for liquid cooling products is lengthy and complex, creating high barriers to entry for new suppliers. This process can take anywhere from six months to two years, making it challenging for many manufacturers to enter the market [11]. Company-Specific Insights - NVIDIA is projected to ship 100,000 cabinets of the GB series (primarily GB300) by 2026, with a liquid cooling value per cabinet estimated at $90,000 to $100,000, leading to a total liquid cooling value of approximately $10 billion [7]. - Google is expected to ship 2.2 to 2.3 million TPU V7 and above chips by 2026, translating to a need for around 35,000 cabinets with liquid cooling solutions, with a total liquid cooling value estimated at $2.6 billion [9]. - Meta anticipates shipping 1 million MTIA V2 chips, requiring about 14,000 cabinets, with a projected liquid cooling value of approximately $1.05 billion [10]. - Amazon's AWS Trainium3 is expected to ship 1.2 million chips, corresponding to around 16,000 cabinets, with an estimated liquid cooling value of $1.25 billion [10]. Market Opportunities for Mainland Chinese Manufacturers - North American CSP technology companies are increasingly looking to mainland Chinese liquid cooling manufacturers to ensure supply chain security, as existing production capacities in North America and Taiwan may not meet the surging demand by 2026 [13]. - Mainland Chinese manufacturers can offer liquid cooling products at a lower cost compared to their foreign counterparts, potentially enhancing project profitability for data centers [13]. - Some leading mainland Chinese manufacturers possess competitive technological advantages in liquid cooling products, which can improve the efficiency of downstream data center products [13]. Future Outlook - The liquid cooling industry is expected to see a significant increase in demand starting in 2026, with early adopters benefiting from the first wave of industry growth. The process of engaging with overseas manufacturers, obtaining samples, and securing initial orders will be crucial for companies looking to capitalize on this trend [17].

Core Insights - The article discusses the concept of "innovator's dilemma" and its relevance to Amazon Web Services (AWS), highlighting concerns about AWS's pace of innovation compared to competitors like Microsoft and Google [1][3] - AWS showcased its leadership and innovation at the re:Invent 2025 conference, emphasizing its strong market position and ability to define market rules [3] Business Scale and Stability - AWS reported an annual recurring revenue (ARR) of $132 billion and holds a 37.5% global market share, underscoring its role as a foundational layer in the digital economy [4] - The platform processes over 200 million requests daily and has stored over 500 trillion objects, indicating its reliability and security for businesses transitioning to AI [4] Understanding Customer Needs - AWS integrates multiple AI models from various vendors through its Amazon Bedrock platform, allowing customers to choose from a diverse range of options without being locked into a single technology [4][6] Focus on Agentic AI - AWS CEO Matt Garman emphasized the importance of "Agent" as the fundamental unit for next-generation applications, outlining four pillars for AI implementation: infrastructure, model ecosystem, data foundation, and developer tools [6][9] - The concept of Agent is defined as a next-generation application capable of autonomous planning and cross-session memory, moving beyond simple chatbots [8] Technological Innovations - AWS introduced the Trainium3 chip, which significantly reduces AI training costs by up to 50% and increases token generation efficiency by five times compared to previous generations [15][17] - The Trainium3 chip is integrated into the Amazon Trainium3 UltraServer, achieving a total computing power of 362 PFlops, optimized for Agent applications [17] Cloud Infrastructure Challenges - AWS identified four key challenges posed by generative AI: cost and efficiency, redefined elasticity, latency sensitivity, and heightened security and privacy requirements [18][20] - The new Amazon Graviton5 processor enhances performance by 30% and reduces costs by 30% for various applications, demonstrating AWS's commitment to hardware innovation [22] Intelligent Resource Management - AWS designed the Mantle inference engine to intelligently allocate resources based on request urgency, improving overall cluster utilization and economic efficiency [24] - The Neuron developer suite has been upgraded to allow for lower-level kernel optimization and performance analysis, enhancing the development experience [24] Conclusion - AWS's strategic focus on Agentic AI and continuous innovation in cloud infrastructure positions it as a leader in the evolving AI landscape, capable of driving future growth and redefining industry standards [24][25]

12月9日早盘，算力概念股活跃，创业板人工智能逆市飘红，成份股大面积上扬。其中，奥飞数据领涨 超8%，恒信东方、润泽科技、锐捷网络、太辰光等多股涨超5%，光模块龙头中际旭创涨超3%迭创新 高！ 热门ETF方面，重仓算力且光模块含量超56%的创业板人工智能ETF华宝（159363）场内继续涨超 2%，续刷上市新高，实时成交额超2亿元！ 年内复盘看，受益于AI算力需求高景气，光模块CPO等算力硬件迎业绩+估值双击，创业板人工智能 ETF（159363）标的指数频刷新高，年内涨幅高达99.5%，加上今日涨幅已实现翻倍增长，大幅领跑人 工智能、CS人工智、科创AI等同类AI主题类指数！ | 序号 | 证券代码 | 证券简称 | 区间涨跌幅 | 年化波动率 | | | --- | --- | --- | --- | --- | --- | | | | | [×同首日] 2025-1-1 [×同居日] 2025-12-8 [单位] %↓ | [起始交易日期] 2025-1-1 [截止交易日期] 2025-12-8 [周期] 周 | | | | | | | [收益率自法] 普通收益率 | | | | | | | [单位] ...

Group 1: Monetary Policy Insights - Bank of America suggests that the market may soon start betting on a rate cut by the Federal Reserve in January, despite cautious signals from the Fed [1] - The bank anticipates a 25 basis point rate cut in December, along with stronger guidance and dissenting opinions, projecting stronger growth and lower inflation [1] - Analysts believe that with significant data releases before January, Chairman Powell will find it difficult to suppress market expectations for further easing [1] Group 2: Economic Outlook in Thailand - Barclays economists report that the Bank of Thailand may resist rate hikes in 2026 due to lower-than-potential growth prospects and inflation rates below the 1%-3% target range [2] - The central bank aims to maintain a loose monetary policy and focus on addressing structural economic issues [2] - Even with rising price pressures, the central bank is unlikely to change its policy stance, prioritizing economic growth and financial stability over inflation [2] Group 3: Investment Opportunities in Technology and Commodities - China International Capital Corporation (CICC) sees significant investment opportunities in the technology sector within the machinery industry for 2026, driven by domestic demand recovery and high export growth [3] - CITIC Construction points out that copper, aluminum, and gold have clear long-term investment logic due to global macroeconomic uncertainties and geopolitical risks [4] - The report highlights that copper will benefit from supply tightness and green economy demand, while aluminum is constrained by domestic capacity limits [4] Group 4: Energy Storage and AI Development - CITIC Construction expects the energy storage industry to see a rise in both volume and price by 2026, with manufacturing profitability currently at unsustainable low levels [5] - The ongoing development of AI large models and applications is noted, with a recommendation to continue focusing on the AI computing power sector [6] - The report emphasizes the potential for new application scenarios and business models arising from the construction of space data centers [8] Group 5: Market Predictions for Copper and Panel Industry - CITIC Securities predicts that LME copper prices could accelerate towards $12,000 per ton, driven by narratives of U.S. copper stockpiling and domestic production cuts [8] - The panel industry is expected to see a positive long-term outlook due to improved competition dynamics and a shift from price-driven profit to value creation [9]