Investment Rating - The report maintains a "Recommended" investment rating for the computer industry [2] Core Insights - The North American cloud service market has recently experienced localized price increases, breaking the long-standing trend of only decreasing prices. This price hike is primarily led by Amazon Web Services (AWS) and Google Cloud, with AWS raising its EC2 machine learning capacity block prices by an average of approximately 15% [4][13] - The fundamental reasons for this price increase include a significant surge in AI application demand, leading to a supply-demand imbalance in computing resources, particularly high-performance GPUs. Additionally, cloud providers are investing heavily in infrastructure to support AI development, resulting in rising hardware and energy costs [4][14] - The emergence of Clawdbot (now OpenClaw) as a popular open-source AI project signifies a shift in AI applications from "conversational Q&A" to "agent-based execution," transforming AI into a "digital employee" capable of executing tasks autonomously [5][15][16] Summary by Sections Recent Market Trends - The computer industry index fell by 4.77% from January 26 to January 30, 2026, with notable stock performances among various companies [7] AI Infrastructure and Applications - The report emphasizes the growing trend of AI "cloud-edge-end" collaboration, with an accelerated iteration of AI application products. It suggests monitoring price fluctuations among domestic cloud service providers while maintaining the "Recommended" rating for the computer industry [18] - Key companies to watch in AI infrastructure include Haiguang Information, Cambricon Technologies, and Inspur Information, while AI application companies of interest include Kingsoft Office and iFlytek [18] Company Performance Forecasts - The report provides earnings forecasts for several companies, indicating expected growth in net profits for 2025, with some companies projecting increases of over 50% [11][12]

Core Insights - The article discusses the competitive landscape in the Chinese AI sector, highlighting the dichotomy between technological idealism and commercial realism, where large companies leverage capital and resources to dominate the market while startups struggle to maintain their innovations [1][15]. Group 1: Competitive Dynamics - Major tech companies are aggressively investing in AI, integrating advanced models and applications into their existing ecosystems, thereby creating a comprehensive competitive advantage [1][15]. - Startups like Kimi, which previously gained significant traction with their long-context AI tools, face existential threats as larger firms quickly replicate their innovations and embed them into widely used applications [4][10]. - The rapid evolution of AI technology means that startups must continuously innovate to keep up, but they often lack the resources to compete effectively against the financial might of larger companies [17][21]. Group 2: Market Challenges for Startups - Startups are experiencing a harsh reality where their technological breakthroughs are quickly overshadowed by the ecosystem advantages of larger firms, leading to a cycle of increased investment in technology without corresponding revenue growth [7][11]. - The emergence of open-source models has further complicated the landscape for startups, as they struggle to maintain a competitive edge against both open-source innovations and the aggressive strategies of major tech companies [10][21]. - The financial pressures on startups are significant, as they rely on external funding and must demonstrate sustainable cash flow rather than just user growth metrics [21][22]. Group 3: Strategic Responses - Some startups are pivoting their strategies to focus on niche markets or specific applications, such as healthcare AI, in an attempt to carve out a sustainable business model [11][22]. - Companies like 月之暗面 are choosing to streamline their product offerings and focus on core competencies, such as the commercialization of their Agent technology, to survive in a competitive environment [11][22]. - The article suggests that while large companies have the advantage of scale, they may lack the agility to innovate in specialized areas, potentially leaving room for startups to thrive in those niches [22].

Core Insights - The AI industry is experiencing a transformation that redefines productivity and business logic, driven by the integration of AI technologies such as GEO (Generative Engine Optimization) and Agents [1][18] - The event gathered over 150 participants from academia, industry, and investment sectors to discuss the implications of AI on productivity, industry restructuring, and business model innovation [1] Group 1: AI's Impact on Productivity - AI is breaking traditional boundaries of productivity by merging the roles of production tools and labor, thus becoming a crucial carrier of production resources [3] - The trend towards automated decision-making and execution in AI is seen as inevitable, with AI reshaping attention distribution and value capture mechanisms [3][4] - AI is significantly influencing decision-making processes in over 70% of scenarios, leading to a reduction in decision costs for enterprises [4] Group 2: Competitive Landscape and Market Dynamics - The emergence of AI is reshuffling the competitive landscape, with companies not included in AI recommendation lists facing exclusion from competition [4] - The current phase of AI recommendations presents opportunities for small and emerging brands to optimize their entry into AI recommendation sequences [4][5] - Companies are advised to clarify their core product logic to be recognized as benchmark enterprises by AI systems [5] Group 3: Practical Applications and Industry Insights - AI is recognized as an effective tool for enhancing quality and efficiency across various vertical industries, with successful implementation being a shared consensus [6][8] - The integration of AI into business operations is seen as a necessity, with organizations needing to adapt to new technologies and changing user habits [8] - The concept of GEO is becoming a core KPI across industries, indicating a shift in how productivity and resources are managed [8][10] Group 4: Future Trends and Strategic Recommendations - The next 5-10 years are predicted to be a golden opportunity for enterprise-level AI development, necessitating proactive engagement with AI technologies [13] - Companies must embrace organizational changes and learn to interact effectively with AI to unlock its full potential [9][17] - The balance between consumer experience and AI technology value is crucial for successful AI implementation in retail and other sectors [9][10]

本周观点 投资建议 相关标的： 海外算力/存储：中际旭创、新易盛、兆易创新、大普微、中微公司、天孚通信、源杰科技、胜宏科技、景旺电子、 英维克等；闪迪、铠侠、美光、SK 海力士、中微公司、北方华创、拓荆科技、长川科技。 国内算力：寒武纪、东阳光、海光信息、协创数据、华丰科技、星环科技、网宿科技、首都在线、神州数码、百 度集团、大位科技、润建股份、中芯国际、华虹半导体、中科曙光、润泽科技、浪潮信息、东山精密、亿田智能、 奥飞数据、云赛智联、瑞晟智能、科华数据、潍柴重机、金山云、欧陆通、杰创智能。 CPU：海光信息、中科曙光、澜起科技、禾盛新材、中国长城、龙芯中科、兴森科技、深南电路、宏和科技、广 合科技。 风险提示 行业竞争加剧的风险；技术研发进度不及预期的风险；特定行业下游资本开支周期性波动的风险。 敬请参阅最后一页特别声明 1 Agent 生态持续扩张。1）大模型公司 Anthropic 大幅上调未来数年的营收预测，预计今年销售额将增长四倍，达 180 亿美元，而明年将达 550 亿美元。其 AI 编码助手 Claude Code 去年 11 月的年化收入已超过 10 亿美元。2)1 月 27 日 月之暗面 ...

半导体 2026 年 02 月 01 日 行 业 定 期 报 告 我们在此前周报第 1 期 20260110 中明确提出"看好商业航天产业 趋势，预计未来我国可回收火箭的成功回收将降低单次发射成本，有 望成为行业加速发展的拐点"，我们观察到国内和海外产业进展迅速， 可回收火箭核心公司蓝箭航天的 IPO 进程在 25 年 12 月 31 日被上交所 受理后，不到一个月的时间，在 26 年 1 月 22 日就达到"已问询"， 上市进程大超预期，凸显国内政策对产业发展的支持，我们坚定看好 商业航天产业链在 2026 年的加速发展机遇。 SpaceX 申请部署百万颗卫星，太空"军备竞赛"持续：1 月 31 日据 C114 报道，SpaceX 向美国联邦通信委员会（FCC）申请发射并 运营一个至多 100 万颗卫星组成的星座，相关文件显示其正在规划"轨 道数据中心系统（Orbital Data Center system）"，这些卫星拟运行在 500 公里至 2000 公里的不同轨道壳层中，相关文件显示其目的在于满 足日益增长的 AI/机器学习/边缘计算等需求。 持续看好星间激光通信和手机直连卫星环节：我们认为 6G= ...

Core Insights - The number of active Agents is projected to surge from 28.6 million in 2025 to 2.216 billion by 2030, with a compound annual growth rate (CAGR) of 139% [1] - The total number of tasks executed annually is expected to explode from 44 billion in 2025 to 415 trillion by 2030, reflecting a CAGR of 524% [1] - The estimated annual Token consumption will increase dramatically from 0.0005 P in 2025 to 152,667 P by 2030, indicating a staggering CAGR of 3,418% [1] Group 1: Agent Development Trends - The trend is shifting from single LLMs to Agents, significantly boosting the demand for parallel processing [1] - Domestic and international models are accelerating Agent development, with notable advancements such as Kimi's new open-source model K2.5 and Anthropic's Claude in Excel plugin [1][2] - Agents enhance single LLMs by incorporating decision orchestration, enabling them to autonomously plan tasks and utilize external tools, thus addressing limitations in context awareness and real-time information retrieval [2] Group 2: Multi-Agent Systems (MAS) - Multi-Agent Systems are emerging as a new form of Agents, exemplified by Kimi K2.5, which can manage 100 sub-agents and execute 1,500 tool calls in parallel, reducing execution time by up to 4.5 times compared to single agents [2] Group 3: CPU as a Critical Support - CPUs are crucial for Agent performance, affecting latency, throughput, and power consumption, with CPU processing accounting for up to 90.6% of total latency [3] - In Agent operations, CPUs handle tasks that GPUs cannot, such as executing external tools and system-level task orchestration, thus becoming essential for efficient resource allocation [3] Group 4: Investment Recommendations - As the demand for Agents grows, CPUs are expected to become a key performance bottleneck, leading to increased demand for core supply chain companies such as Haiguang Information, Longxin Zhongke, Guanghe Technology, Tongfu Microelectronics, and Lanke Technology [4]

Core Viewpoint - The recent introduction of Clawdbot is seen as a turning point for the commercialization of AI applications, leading to a surge in related stocks [2][10]. AI Application Sector - The AI application sector experienced a significant rise, with various sub-sectors such as Sora concept, AI corpus, and Zhipu AI showing substantial gains [8]. - Key stocks in the AI sector include: - Liujin Technology: Up 20.37% with a market cap of 30.41 billion - Yidian Tianxia: Up 10.84% with a market cap of 27.2 billion - Zhidema: Up 11.32% with a market cap of 9.09 billion [9]. White Wine Sector - The white wine sector rebounded, with major brands like Guizhou Moutai rising by 3.72% to 1372.95 yuan per share [12][13]. - The market price for Feitian Moutai has been increasing, with the price for 53-degree, 500ml Feitian Moutai rising to 1620 yuan per bottle [15]. - Analysts suggest that the upcoming Spring Festival will boost sales of high-end liquor, indicating a potential increase in demand and sales for the white wine sector [15].

Market Overview - On January 29, AI applications experienced a collective surge, with stocks such as Zhejiang Wenhu Internet, InSai Group, People's Daily Online, and Inertia Media hitting the daily limit [1] Event: ClawdBot's Popularity - The AI assistant ClawdBot has gained significant attention in both overseas and domestic markets, emerging as a notable AI product for the beginning of 2026 [2] - On January 29, the Hong Kong stock of MINIMAX, a major model concept stock, surged over 15% [2] - ClawdBot's development was largely AI-generated, with MiniMax 2.1 being highlighted as the most "Agentic" domestic model, achieving stable local deployment on Mac Studio, showcasing the engineering capabilities of domestic models in complex intelligent applications [2] Institutional Insights - ClawdBot signifies a shift in AI product forms from "scene-level assistants" to "system-level Agent platforms," emphasizing comprehensive execution capabilities across tools, systems, and tasks [3] - The Agent's role is not to replace traditional software but to enhance overall efficiency as an intelligent execution hub, with traditional SaaS and software systems continuing to support foundational business logic and data infrastructure [3] - The Agent industry is evolving from single intelligence to multi-agent systems, with products like AnthropicCowork and MiniMaxAgent 2.0 enhancing local workflows and transforming AI from dialogue assistants to digital employees capable of long-term planning [3]

消息面上，开源项目Clawdbot在硅谷爆火，7x24的Agent重塑AI体验，可在Mac mini上运行，兼具本地AI智能体和聊天网关双重身 份，通过WhatsApp、iMessage等随时对话。Clawdbot解决了大模型记忆力痛点，能记住两周前的对话，还会主动推送邮件、日程提 醒，并可直接操控电脑执行任务。 业绩方面，1月28日晚间，软件ETF汇添富（159590）标的指数第一大重仓股——科大讯飞发布业绩预告，公司预计2025年净利润为 7.85亿元至9.5亿元，同比增长40%至70%；扣非后净利润为2.45亿元至3.01亿元，同比增长30%至60%。除盈利水平提升外，科大讯 飞多项核心财务指标表现亮眼：2025年公司营收、毛利保持正向增长，销售回款及经营性净现金流均创历史新高，其中销售回款总 额超270亿元，同比增长超40亿元；经营性净现金流超30亿元。对于业绩增长原因，科大讯飞表示主要得益于公司基于自主可控平台 持续夯实行业地位，人工智能应用规模化落地成效日益显现。 软件ETF汇添富（159590）标的指数权重股多数飘红：科大讯飞涨停，三六零、用友网络涨超5%，金山办公涨超4%，深信服涨超 3%，恒 ...

Summary of Key Points from the Conference Call Industry Overview - The conference discusses the impact of AI technology on various sectors, particularly programming, healthcare, and finance, predicting explosive growth in data demand by 2026 [1][2][3]. Core Insights and Arguments - AI technology is expected to significantly enhance workflow efficiency, especially in verticals like programming, healthcare, and finance, with a projected 10-fold market expansion in automation applications [2][4]. - The A-share market is anticipated to experience a surge in Agent products in 2026, alleviating concerns about AI bubbles and ROI, thus strengthening investments in computational infrastructure [1][4]. - Traditional software companies, particularly those relying on standardized UI interfaces (e.g., ServiceNow, CRM, Adobe), face challenges as AI technologies may replace conventional software models [1][14]. - The shift from per-user pricing to consumption-based pricing models is expected to lead to a decline in gross margins for software companies [1][17]. Market Dynamics - The North American market is likely to adopt public and multi-cloud architectures due to high labor costs, while the domestic market favors results-based payment models due to lower labor costs [2][19]. - AI's impact on the software industry is evident, with traditional software companies experiencing declines while patent-driven companies in storage continue to innovate [4][15]. Challenges and Opportunities - In programming, AI applications face unique challenges due to the complexity of real-world applications compared to standard programming tests [5]. - Companies are transitioning towards Agent models, with some successfully collaborating with third-party model companies to enhance their offerings [5][8]. - The emergence of new technologies will lead to the rise of new players and the potential elimination of older ones, shifting the business model from selling licenses to selling results and services [18]. Investment Perspective - Concerns regarding AI bubbles are diminishing as downstream Agent growth accelerates, with a focus on companies that can effectively transition to Agent models [8]. - The competitive landscape is shifting, with large model technologies increasing their share of IT budgets, potentially leading to significant layoffs in traditional software companies [16][17]. Regional Differences - The U.S. market is more inclined towards public cloud solutions, while the Chinese market, with its lower labor costs, is more focused on private deployments and results-based payments [19][20][21]. - There is a notable difference in cloud adoption, with overseas companies favoring public cloud solutions and mixed deployments, while domestic companies often stick to single public cloud providers [21]. Additional Insights - CloudBot and CoWork exhibit different technological paths, with CloudBot relying on programming to understand user intent and CoWork utilizing video-based reinforcement learning [13]. - AI tools like Gemini and NotebookLM are enhancing research efficiency, enabling quicker report generation and improved workflow [11][12].