以下文章来源于人神共奋 ，作者思想钢印 人神共奋 . 财经专栏作家，虎嗅&雪球2020年度十佳作者 本文来自微信公众号： 人神共奋 ，作者：思想钢印，题图来自：AI生成 一、美国的经济数据也打架了 为什么就业数据差，失业率一般，但经济增长却不错？ 研究机构对此有很多解释，比如政府查非法移民，导致就业数据差，但不在统计内的失业率不差；比 如经济数据统计人手不足导致的统计误差；比如关税冲击，让企业既不敢招聘，又不敢裁员。 这些解释都偏短期，预示着未来要么经济加速下行向就业数据靠拢，要么就业市场恢复生机向经济增 长数据靠拢。 但如果是长期的原因呢？ 有一种非传统经济学的解释越来越被更多证据认可，即， 这个矛盾现象主要是AI投资造成的，而 且，它将长期改变经济与就业结构。 去年下半年以来，美国经济出现了一个传统宏观经济无力解释的现象。 9月初，美国劳工统计局对去年3月到今年3月的非农就业数据大幅下修超过90万，为20年来这个数据 下修最多的一次，加上8月的美国非农部门新增就业仅22，000 个，远低于过去十年内正常的月度平 均水平，这种修正意味着目前已经达到了衰退的程度。 但其他经济数据并不支持"衰退"，8月，美国的 ...

一、美国的经济数据也打架了 去年下半年以来，美国经济出现了一个传统宏观经济无力解释的现象。 9月初，美国劳工统计局对去年3月到今年3月的非农就业数据大幅下修超过90万，为20年来这个数据下修最多的一次，加上8月的美 国非农部门新增就业仅22，000 个，远低于过去十年内正常的月度平均水平，这种修正意味着目前已经达到了衰退的程度。 但其他经济数据并不支持"衰退"，8月，美国的失业率为4.3%，总体仍处于历史中等偏低水平，并未达到代表衰退的6%以上的水 平。 增长数据也是如此，多个大行预测第二季度GDP年化季率终值上修至3.8%，第三季度GDP追踪预测也调升至2.6%，远远达不到衰退 的标准。 为什么就业数据差，失业率一般，但经济增长却不错？ 研究机构对此有很多解释，比如政府查非法移民，导致就业数据差，但不在统计内的失业率不差；比如经济数据统计人手不足导致 的统计误差；比如关税冲击，让企业既不敢招聘，又不敢裁员。 这些解释都偏短期，预示着未来要么经济加速下行向就业数据靠拢，要么就业市场恢复生机向经济增长数据靠拢。 但如果是长期的原因呢？ 有一种非传统经济学的解释越来越被更多证据认可，即，这个矛盾现象主要是AI投资 ...

Core Viewpoint - Alibaba is undergoing a self-revolution similar to historical examples like IBM and Microsoft, with a recent stock price surge reflecting market optimism about its AI strategy and cloud business performance [2] Group 1: Alibaba's Position in the AI Cloud Market - Alibaba is the only Chinese company among the world's four "super AI clouds," pursuing a full-stack self-research approach in AI chips, cloud computing, and foundational models, aligning strategically with Google [2][3] - The company has announced a significant investment of 380 billion yuan (approximately 53.5 billion USD) over the next three years for cloud and AI infrastructure, surpassing its total investment over the past decade [11] Group 2: AI Competition Dynamics - The AI competition has shifted from a "model race" to a focus on building a robust AI full-stack technology system, which includes capital investment, cloud computing capacity, foundational models, and self-developed AI chips [4][7] - The success in AI is determined by two core variables: iteration speed and cost efficiency, which require a vertically integrated AI full-stack technology system [7][8] Group 3: Comparison of Strategic Paths - Two distinct strategic paths have emerged: the "cloud + ecosystem" model represented by Microsoft and Amazon, and the "full-stack self-research" model represented by Google and Alibaba [15][17] - The "full-stack self-research" model allows for faster iteration and better cost efficiency, as seen in the recent revenue growth of both Google Cloud and Alibaba Cloud [17] Group 4: Open Source and Global Impact - The open-source model has gained traction, with Chinese models like DeepSeek and Alibaba's Tongyi Qwen influencing global AI paradigms, highlighting the importance of a complete "full-stack AI capability" for long-term competitive advantage [19] - The shift towards open-source by OpenAI is seen as a response to the growing influence of Chinese open-source capabilities, emphasizing the need for a comprehensive industrial system to convert advanced designs into scalable products [19][20]

人工智能竞赛早已不再是单纯的商业合作，而是一场围绕未来十年技术制高点的权力博弈。在这场竞赛中，没有永恒的同盟，只有永恒的资本 和利益 美国的AI（人工智能）市场，正上演两大阵营的对垒。 台前，是全球最大的两家AI创业公司，OpenAI和Anthropic。幕后，则是微软、亚马逊这两家科技巨头，也是全球前两大云厂商，两家长期把持着云市场 60%以上的份额。 两大阵营对垒的格局是如何形成的？ 今天的AI竞赛，背后是算力和模型的竞赛——微软、亚马逊需要用算力和资本，换取创业公司的模型和技术，进而获得更大的市场。OpenAI、Anthropic 需要靠巨头的输血快速成长。这也是微软和OpenAI、亚马逊和Anthropic这两对盟友合作的基础。 今年8月和9月，OpenAI和Anthropic接连完成新一轮融资，它们分别成为全球第三、第四大独角兽（第一是估值4000亿美元的SpaceX，第二是估值3150亿 美元的字节跳动）。 OpenAI累计融资超过797亿美元，估值3000亿美元。微软至少为OpenAI输血130亿美元，占其公开总融资额的16%以上。Anthropic累计融资超过312亿美 元，估值1830亿美元 ...

Core Viewpoint - Morgan Stanley identifies four key generative AI catalysts—model advancements, agentic experiences, capital expenditures, and custom chips—that are reshaping the internet industry landscape, positioning Google, Meta, and Amazon to stand out among large tech stocks [1][3]. Group 1: Generative AI Catalysts - Model Development Acceleration: Leading AI models are expected to continue improving, driven by ample capital, enhanced chip computing power, and significant potential in developing agentic capabilities, benefiting companies like OpenAI, Google, and Meta [6]. - Proliferation of Agentic Experiences: Agentic AI products will provide more personalized, interactive, and comprehensive consumer experiences, further promoting the digitalization of consumer spending, although challenges in computing capacity and transaction processes remain [7]. - Surge in Capital Expenditures: By 2026, the total capital expenditures of six major tech companies (Amazon, Google, Meta, Microsoft, Oracle, CoreWeave) on data centers are projected to reach approximately $505 billion, a 24% year-over-year increase [8]. - Increasing Importance of Custom Chips: The likelihood of third-party companies testing and adopting custom ASIC chips like Google TPU and Amazon Trainium is rising, driven by cost-effectiveness and capacity constraints, which could provide significant upside potential for Google and Amazon [9]. Group 2: Financial Implications - Capital Expenditure Surge Pressuring Free Cash Flow: The substantial capital expenditures for AI will directly impact the financial health of tech giants, with a projected 34% compound annual growth rate in capital expenditures from 2024 to 2027 [10]. - Impact on Free Cash Flow: By 2026, infrastructure capital expenditures for Google, Meta, and Amazon are expected to account for approximately 57%, 73%, and 78% of their pre-tax free cash flow, respectively, indicating a willingness to sacrifice short-term profitability for long-term technological and market advantages [12]. Group 3: Company-Specific Insights - Amazon: Morgan Stanley's top pick among large tech stocks, with a target price of $300, is based on the acceleration of AWS and improving profit margins in North American retail, projecting over 20% revenue growth for AWS by 2026 [14][16]. - Meta: Maintains an "overweight" rating with a target price of $850, focusing on improvements in its core platform, the release of the next-generation Llama model, and several undervalued growth opportunities, including potential annual revenue of approximately $22 billion from Meta AI search by 2028 [18]. - Google: Also rated "overweight" with a target price of $210, emphasizing AI-driven search growth, potential shifts in user behavior, and growth prospects for Google Cloud (GCP), with innovations expected to accelerate search revenue growth [20].

在云服务商新增选择方面，GCP位列第二，约44%的受访者计划未来采用GCP(仅次于Azure)，38%的受 访者预计将用GCP替代现有服务商(去年为36%)。在替代现有供应商的意愿中，GCP 以 38% 排第三，低 于 Azure(72%) 和 AWS(67%) 生成式AI领域，谷歌Gemini模型成为第二大最常用的大型语言模型(LLM)提供商，54%的受访者选择其 作为GenAI工具的底层模型，较2024年调查的50%有所提升。OpenAI 占比 73%，虽仍第一，但低于去 年的 82%，反映市场正趋向多元化选择。 值得关注的是，去年未纳入调查的Anthropic此次以35%的占比位列第三，Meta Platforms(META.US)则 凭借Llama模型以24%的占比位居第四。 智通财经APP获悉，TD Cowen将谷歌(GOOGL.US)目标价由240美元上调至270美元，并维持"买入"评 级，此番调整基于其针对生成式AI(GenAI)公共云领域的年度调查结果。 以约翰·布莱克利奇为首的分析团队指出，尽管谷歌云平台(GCP)在调查中展现稳健表现，但与市场领军 者亚马逊AWS(认知度94%)及微软Azu ...

Investment Rating - The report maintains an "Overweight" rating for the non-bank financial industry, indicating a positive outlook for the sector in the next six months [1]. Core Insights - The Nasdaq 100 index experienced a "high-low" trend in August, with a cumulative increase of 0.85%. The market sentiment fluctuated due to mixed macroeconomic data and Federal Reserve signals, leading to a cautious outlook for September [12][13]. - As of August 29, 2025, the Nasdaq 100 index's price-to-earnings ratio (PE-TTM) stood at 34.6, placing it in the 83.6% historical percentile since 2011, indicating a relatively high valuation dependent on interest rates and earnings performance [17]. - The technical analysis shows that the risk level of the Nasdaq 100 index has decreased to 91.54, still indicating a high level of market sentiment, with a maintained upward trend but short-term volatility risks [18]. Market Performance Review - **Trend Review**: From July 31 to August 29, the Nasdaq 100 index showed a "high-low" pattern, with a total trading volume of approximately $47.212 billion. Initial concerns arose from weak manufacturing PMI data, but the index rebounded towards the end of August due to dovish signals from the Federal Reserve [12][13]. - **Valuation Analysis**: The Nasdaq 100 index's PE-TTM ratio of 34.6 suggests a high reliance on the interest rate environment and earnings realization [17]. - **Technical Analysis**: The index remains in an upward trend, but short-term fluctuations and volatility risks are present [18]. Event-Driven Analysis - **Macroeconomic Factors**: The interplay between Federal Reserve monetary policy expectations and the resilience of tech company earnings has been central to the Nasdaq 100 index's performance. Key employment and inflation data have influenced market sentiment and policy expectations [21][23]. - **Policy Factors**: The Federal Open Market Committee (FOMC) maintained interest rates but signaled a hawkish stance, impacting growth stock valuations. Additionally, proposed semiconductor tariffs by Trump have added uncertainty to the tech sector [31][33]. - **Industry Dynamics**: The performance of major tech stocks such as Microsoft, Meta, Apple, Amazon, and Nvidia has been mixed, with earnings reports influencing market reactions significantly [36][38]. Future Outlook - **Key Events Ahead**: The Nasdaq 100 index's performance in September will be influenced by macroeconomic data, policy signals, and industry earnings. Stable inflation data could bolster expectations for interest rate cuts, benefiting high-growth tech stocks [45][46]. - **Index Performance Outlook**: The Nasdaq 100 index is expected to maintain a volatile upward trend, with caution advised due to potential short-term pullbacks. The performance of tech stocks will be critical in determining overall market direction [51]. Related ETF Products - The report highlights the Guangfa Nasdaq 100 ETF (159941.SZ), which aims to closely track the Nasdaq 100 index, with a total market value of 27.718 billion yuan as of August 29, 2025 [52][53].

Investment Rating - The report maintains a "Positive" investment rating for the communication equipment industry [15]. Core Insights - Major cloud vendors such as Google, Amazon, Microsoft, and Meta reported better-than-expected financial results, driven by strong demand for cloud services and advertising, with significant capital expenditure increases [4][7]. - AI applications are deeply penetrating various sectors, leading to accelerated investments in computing power and infrastructure [7][13]. - The overall trend indicates a robust growth trajectory for AI and computing power, with companies ramping up their capital expenditures to support this growth [13]. Summary by Sections Cloud Vendors: Strong Financial Performance and Demand - Google reported Q2 2025 revenues of $96.43 billion, up 13.8% year-on-year, with a net profit of $28.20 billion, up 19.4% [24][26]. - Amazon achieved Q2 2025 revenues of $167.70 billion, a 13.3% increase year-on-year, with a net profit of $18.16 billion, up 34.7% [34][36]. - Microsoft recorded Q4 FY25 revenues of $76.44 billion, an 18.1% increase year-on-year, with a net profit of $27.23 billion, up 23.6% [43][45]. - Meta's Q2 2025 revenues reached $47.52 billion, a 21.6% increase year-on-year, with a net profit of $18.34 billion, up 36.2% [51][54]. CPU/GPU: Product Iteration and Ecosystem Upgrade - AMD's Q2 2025 revenues were $7.69 billion, a 31.7% increase year-on-year, with a net profit of $0.87 billion, up 229.1% [60][62]. - The client and gaming segments saw record growth, while the data center business faced challenges due to export restrictions [62]. Switches: High-End Volume and Stable Profitability - Arista's revenue growth was driven by its AI Center strategy, with significant increases in AI network revenue [9]. - Celestica's communication market growth was primarily driven by high-performance switches, with revenue and performance outlooks adjusted upwards [9]. Optical Communication & Fiber Optics: Strong Shipments and Scale-Up Acceleration - Lumentum's optical module shipments surged, and coherent optical communication business saw rapid growth [10]. - Corning's optical communication business thrived, driven by enterprise networks, with expectations for significant future growth from scale-up scenarios [10]. Cables: Strong Orders and Active Capacity Expansion - Amphenol reported strong AI-related orders and exceeded expectations in IT data communication business growth [11]. Cooling: High Demand and Accelerated Liquid Cooling Adoption - Vertiv's revenue and profits saw significant growth, with a strong order backlog and upward guidance for the year [12]. Investment Recommendations: Accelerating Business Flywheel and Computing Power - The report recommends several companies across different segments, including optical modules, liquid cooling, fiber optics, and AI applications, highlighting their potential for growth [13].

每经编辑｜彭水萍 8月12日，AI算力硬件相关标的领涨。展望后市，一方面，海外云厂商在关税不确定性的背景下继续对AI资本开支做 积极表述，行业有望维持高景气；另一方面，芯片等算力基础设施领域的国产替代事关国家安全，必然成为长期趋 势。 无论是股票ETF还是LOF基金，均属于较高预期风险和预期收益的证券投资基金品种，其预期收益及预期风险水平高 于混合型基金、债券型基金和货币市场基金。 | 代码 | 名称 | 两日图 | 现价 | 涨跌 | 涨跌幅 | | --- | --- | --- | --- | --- | --- | | 515880 | 通信ETF | | 1.861 c | 0.060 | 3.33% | | 159546 | 集成电路ETF | N 1 | 1.422 c | 0.039 | 2.82% | | 159388 | 创业板人工智能E ---- | | 1.327 с | 0.036 | 2.79% | | 512760 | 芯片ETF | Noney | 1.217 c | 0.032 | 2.70% | | 159516 | 未导体设备ETF | Must | 1.098 c | ...

Core Viewpoint - The current market conditions present a valuable opportunity for investment, particularly in the context of recent employment data revisions and the resilience of major tech companies in the U.S. stock market [1][5]. Group 1: Employment Data and Market Reaction - The U.S. non-farm payroll data was significantly revised downwards, with a total reduction of 258,000 jobs for May and June, and July's new jobs falling to 73,000, marking a nine-month low [1]. - This downward revision has led to a sharp market reaction, with the Nasdaq dropping 2.24% in response, and the probability of a rate cut in September skyrocketing from 40% to 90% [1]. - Despite these negative indicators, the long-term bullish trend of the U.S. stock market remains intact [1]. Group 2: Historical Market Trends - Over the past 50 years, the U.S. stock market has experienced nine significant downturns, with the largest being a 57.7% drop in 2008 [3]. - Following major declines, the market has historically rebounded to reach new all-time highs, as evidenced by the S&P 500 recovering to a new high just two months after a 21% drop earlier this year [3]. - Similar patterns of rapid decline followed by recovery have occurred in 1998, 2020, and this year, with each recovery leading to extended bull markets [3]. Group 3: Performance of Major Tech Companies - Recent earnings reports from major tech companies such as Apple, Amazon, Meta, and Google demonstrate strong profitability and resilience [5]. - Apple reported record service revenue of $27.4 billion, while Amazon's AWS generated $30.9 billion in cloud revenue, reflecting a 17.5% increase [5]. - Meta's profits surged by 36% due to increased advertising efficiency, and Google’s cloud revenue grew by 32%, with profits doubling [5]. - Collectively, these companies have invested $311 billion in AI infrastructure, indicating a shift from concept to a profit-generating engine [5][7]. Group 4: Investment Trends in ETFs - The Nasdaq 100 ETF has seen significant inflows, with over 2.2 million shares added since the beginning of the year, indicating strong institutional interest in tracking major AI companies [7]. - This ETF provides exposure to leading AI firms, covering the entire value chain from chip computing to cloud services, capitalizing on the AI boom [7].