本文档仅供上海信鱼私募基金管理有限公司18860455898研究使用，请勿外传 ab 7 January 2025 Powered by YES UBS Evidence Lab Global Research U.S. Software Latest Enterprise AI Survey Summary In this third iteration of our enterprise AI survey, we again leveraged the UBS Evidence Lab data team to survey IT execs at 125 organizations about their AI plans at the chip, cloud infrastructure, model, application software, data and security layers, with a focus on incremental changes in feedback from our previous May 2024 survey (see report here). T ...

国产替代与 AI 落地 20250109 摘要 Q&A 2024 年计算机板块的市场表现如何？有哪些关键词可以总结这一年的情况？ 2024 年计算机板块的市场表现可以用"预期和现实"、"双击和双杀"这几个 关键词来总结。年初，量化和小盘股大跌，2 月初见底后，一季报披露前后出现 反弹。4 月至 9 月中旬呈现单边下行趋势，9 月底至四季度则迎来较好行情，反 弹幅度在所有 A 股板块中靠前。然而，在前期下行过程中，该板块表现为 30 个 行业倒数第一。这种交替演绎背后的原因在于预期和现实的不同组合：上行阶段 是偏弱的现实与积极预期，下行阶段则是偏弱现实与弱预期叠加。 • 2024 年计算机板块市场表现先抑后扬，年初量化和小盘股大跌，二季度 单边下行，四季度强势反弹，全年波动剧烈，体现了预期与现实的错配。 • 计算机行业处于偏弱改善阶段，政策落地存在时间滞后性，预计 2025 年 二季度才能看到更多政策传导效果，例如预算修正、方案沟通选型等。 • 美国对中国科技企业的制裁持续升级，采取组合拳式打击，包括实体清单、 关税等，对中国科技企业采购和销售造成双重影响，未来中美关系虽可能 阶段性缓和，但制裁风险依然存在。 ...

各位跳伴大家下午好欢迎收看禅门解盘我是光大证券投资管理权大家还叫我李师兄每个交易日下午四点整我们都会陪着大家复盘市场热点啊探索整体市场的核心逻辑今天啊市场是走出了一定分化的这样一个状态啊我们可以看到啊物质今天表现相对是弱一点 整体下跌幅度是接近0.6%但是如果看到像北中五零啊深层制啊包括像创业板制今天还是能够出现继续反残的这样一个状态 从微观上来看的话超过2700只颗股是上涨的板块层面上L十几个十二个十三个板块也是上涨的从这个角度来看的话市场继续是延续着这样一个结构性的行情整体还是在继续的回暖而互指之所以走出了这样一个弱势的表现我相信大家也都看到 今天偏红利风格的或者一些权政属性的确实今天的表现是要更弱一点我们可以看到今天像红利指数跌幅就超过1.5%包括像电力包括像煤炭 这些领跌的银行领跌的基本上都是红利风格的资产所以现在来看的话市场在修复的过程之中整体的这样一个情绪也是发生了一定的这样一个变化如果大家对于板块轮动有一点点规律上的这样一个认识的话可能也能可能是听说过这样一种描述 就是一轮市场他究竟是怎么去结束这样一轮上行或者下行周期有时候我们得需要去看到啊他里边有一些领头的板块是不是要走出逆板块逆整体市场的这 ...

Summary of US Enterprise Hardware and Networking Conference Call Industry Overview - The focus is on the US Enterprise Hardware and Networking sector, particularly in relation to AI infrastructure investments for 2025 and beyond [2][3][11]. Key Companies Mentioned - **Dell Technologies (DELL)**: Rated as a "Buy" with a price target of $158, expected to benefit significantly from the AI server market and projected to achieve at least 10% revenue growth in ISG for 2025 [6][16]. - **TD SYNNEX (SNX)**: Rated as a "Buy" with a price target of $150, anticipated to see 5% growth in billings and return 50% of free cash flow to shareholders [6][16]. - **Arista Networks**: Neutral rating, expected to see conservative revenue growth due to its exposure to hyperscalers [4][8]. - **Celestica**: Neutral rating, also expected to have conservative estimates due to significant exposure to major tech companies [4][8]. - **Cisco**: Mentioned as a vendor benefiting from AI-related investments [3][8]. Core Insights and Arguments - **AI Infrastructure Investments**: Strong investments in AI infrastructure are expected to continue into 2025 and the first half of 2026, with data center capital expenditures projected to increase by approximately 33% in 2025 and 23% in 2026 [3][8]. - **Ethernet Switch Market Growth**: The market for AI back-end ethernet switches is expected to grow from approximately $1 billion in 2024 to $3.4 billion in 2025, driven by increased demand for AI workloads [3][39]. - **Revenue and Earnings Revisions**: Unlike 2024, where AI stocks benefited from both revenue growth and multiple expansions, 2025 is expected to focus more on "beat and raise" quarters due to elevated valuations [4][12]. - **Market Sentiment**: The market is currently pricing in strong investments in AI infrastructure, particularly among hyperscalers, while traditional tech companies are experiencing more modest valuations [8][12]. Financial Projections - **Dell**: Projected free cash flow growth of 15% in 2025 and low double digits in 2026, with shares trading at 12% of CY26E free cash flow [6][16]. - **TD SYNNEX**: Expected to achieve roughly 10% EPS growth, with its AI infrastructure business projected to grow to several billion dollars in revenue [6][16]. - **CDW**: Revenue and EPS estimates have been trimmed due to macroeconomic headwinds, with a new price target of $220 [5][7]. Potential Risks - **Valuation Concerns**: Elevated valuations of AI-exposed companies may limit further multiple expansions, making stock selection critical for 2025 [12][30]. - **Consumer Demand for AI Products**: Limited consumer interest in generative AI features for smartphones, particularly for Apple, may hinder growth expectations [8][46]. Other Important Insights - **AI Back-End vs. Front-End Investments**: The distinction between back-end and front-end AI investments is crucial, with back-end spending expected to grow significantly while front-end investments are also anticipated to increase [41][42]. - **Market Dynamics**: The market has shifted focus to secondary AI-related companies, with significant price appreciation observed in companies like Nvidia and Dell, while traditional tech companies face de-rating risks [22][23]. This summary encapsulates the key points from the conference call, highlighting the expected trends, financial projections, and potential risks within the US Enterprise Hardware and Networking sector as it relates to AI investments.

January 6, 2025 10:00 PM GMT Thematics Uncovering Alpha in AI's Rate of Change More than two years since ChatGPT's launch, we remain in the early innings of AI's diffusion. This is the third iteration of the most comprehensive AI stock mapping exercise in the market. Rate of change continues to drive outperformance, and we believe 2025 will be the year of Agentic AI. AI's Rate of Change Continues to Surprise: Our first AI Adopter survey was published in January 2024, our second in June 2024. This is our thi ...

Software Institutional Equity Research January 6, 2025 2025 Picks – a Year of AI Software Infrastructure We see 2025 as a year driven by the growth of AI infrastructure software. We believe the rotation from AI hardware to AI software infrastructure is already happening and that the rotation into AI applications may not happen until 2026. This informs our focus for 2025 on SNOW, DDOG, FROG. Our focus on CVLT, PHR, and ZETA is based on each company's unique growth setup into the year compared to expectations ...

Summary of Key Points from the Conference Call Industry Overview - The conference call is part of the "Data Centers & AI: Powering the Future Series 7" focusing on the utilities and clean energy sector, particularly the evolving power demand for AI and data centers [1][3]. Core Insights and Arguments - **Power Demand Evolution**: Discussion on how AI and data centers' power demand has evolved in 2024 and expectations for 2025/26 [9]. - **Nuclear Power Viability**: Examination of the role of nuclear power in supporting AI and data centers, including potential risks for big tech companies in expanding nuclear capacity [9]. - **Gas Power Purchase Agreements (PPAs)**: Consideration of behind-the-meter or virtual PPA deals for gas power plants with data centers, including who would bear commodity risks [9]. - **Net Zero Targets**: Analysis of how rising power consumption and emissions could impact big tech's net zero targets [9]. - **Renewable Energy Contribution**: Exploration of the potential for wind and solar energy to play a significant role in powering AI [9]. - **Emerging Power Solutions**: Discussion on other emerging powering and energy efficiency solutions for AI and data centers [9]. - **Political Debate**: Overview of the political debate in the US regarding the impact of AI and data center demand on grids and electricity bills [9]. Additional Important Content - **Speaker Background**: Brian Janous, Chief Strategy Officer and Co-Founder of Cloverleaf Infrastructure, has extensive experience in energy and decarbonization, previously serving as VP of Energy at Microsoft [5][10]. - **Consultancy Role**: Cloverleaf Infrastructure focuses on grid expansion to support large electric customer loads, which is critical for economic growth and investment [5]. - **Call Registration**: The call is hosted by a team of equity analysts specializing in utilities and clean energy, indicating a collaborative approach to research and analysis [2]. This summary encapsulates the key points discussed in the conference call, highlighting the critical issues facing the utilities and clean energy sector in relation to AI and data centers.

aIDC 电气设备分析与展望 20250108 摘要 Q&A 请介绍一下您对柴油发电机市场的看法。 柴油发电机市场存在供应链瓶颈，尤其是发动机和发电机部分。以康明斯和卡特 彼勒为例，这些公司的公开信息显示其业务紧张且供不应求。康明斯在过去四个 季度连续上调了与发动机相关的两个业务部门的收入指引，甚至在 2025 年的 95 系列发动机已经售罄。这表明柴油发电机在市场中的重要性和需求量巨大。 您认为未来哪些技术变革方向值得关注？ 技术变革中最值得关注的是 APP 相关方向，其次是集成化和模组化。此外，锂电 替代铅酸虽然行业基数大，但整体影响较小。储能应用在国内目前意义不大，但 在海外受到高度重视，特别是绿色算力中心的发展。 • 柴油发电机市场供不应求，康明斯和卡特彼勒等公司业务紧张，持续上调 收入指引，凸显市场巨大需求和行业景气度。 • 值得关注的技术变革方向包括 APP 相关应用、系统集成化和模组化，以及 海外市场储能应用的增长，特别是绿色算力中心建设带来的需求。 • 12 月初市场新趋势：超融合 BB 环节增加，空调制冷系统在高密度设备中 的散热需求提升，海外大型数据中心燃气能源需求超预期增长。 • 电力配 ...

Summary of Conference Call Industry Overview - The conference discussed the developments in the computing power industry, particularly in the context of AI and large models, highlighting the recent CES event where new products were launched by companies like Dongyida [1][2]. Key Points and Arguments - **Investment in Computing Power**: The capital expenditure in computing power is not a sudden increase but a gradual process influenced by advancements in technology and infrastructure, particularly in large model training [2]. - **Model Parameter Growth**: There is a consensus that the ideal parameter size for models has increased significantly, with current expectations suggesting that models should exceed 50 trillion parameters, with OpenAI aiming for 100 trillion parameters by 2025 or 2026 [3][5][24]. - **Data and Model Relationship**: The relationship between model parameters and data volume is complex, with ongoing research indicating that even synthetic data can contribute to model performance [4]. - **Market Predictions**: The market for AI applications is expected to grow significantly, with optimistic estimates suggesting a doubling of user engagement and revenue in the coming year [6]. - **Domestic vs. Foreign Technology**: There is a notable shift towards domestic computing solutions, with companies like Huawei making strides in performance comparable to leading foreign products [7][31]. - **AI and Data Security**: Ensuring data security and privacy remains a challenge, with both technological and regulatory measures being necessary to protect user data [11][12]. - **Environmental Concerns**: The increase in computing power and AI applications raises concerns about energy consumption and environmental impact, although advancements in efficiency are being made [13][14]. - **Cost of AI Implementation**: The cost of AI inference has significantly decreased, making it more accessible for businesses, with predictions of further reductions in the near future [15][16]. - **Investment Distribution**: Currently, around 60-70% of AI-related capital expenditure is allocated to hardware, particularly chips and servers, with the remainder going to software and other related technologies [16][17]. Additional Important Insights - **Future of AI Models**: The future of AI models is expected to focus on the integration of AI with various applications, including robotics and smart devices, which could open new markets [26][27]. - **Market Dynamics**: The competition in the AI space is intensifying, with companies needing to adapt quickly to maintain relevance and market share [29][30]. - **Regulatory Landscape**: The regulatory environment surrounding AI and data privacy is evolving, with ongoing debates about the implications of AI on traditional industries [12][13]. This summary encapsulates the key discussions and insights from the conference call, providing a comprehensive overview of the current state and future outlook of the computing power and AI industry.