Investment Rating - The industry investment rating is "Overweight" [1] Core Insights - The report highlights strong performance from TSMC and Google, emphasizing the importance of the silicon photonics chain and Google chain [14][17] - TSMC's capital expenditure for 2026 is significantly increased, indicating robust growth signals in AI [5][15] - Apple's partnership with Google to utilize the Gemini model for AI applications, particularly in Siri, is noted as a positive development for Google's AI capabilities [17] Summary by Sections 1. Weekly Insights - TSMC's Q4 2025 revenue reached $33.7 billion, slightly above expectations, with a quarter-on-quarter growth of 1.9% [5][14] - TSMC's 2025 annual revenue was $122 billion, a year-on-year increase of 35.9%, outperforming the foundry industry growth of 16% [5][14] - The report recommends focusing on investment opportunities in silicon photonics and liquid cooling due to the AI-driven demand [16] 2. Communication Data Tracking - As of November 2025, China's 5G base stations totaled 4.83 million, with a net increase of 579,000 from the end of 2024 [28] - The number of 5G mobile phone users reached 1.193 billion, a year-on-year growth of 19.06% [28] - 5G mobile phone shipments in November 2025 were 27.614 million units, accounting for 91.6% of total shipments, with a year-on-year growth of 1.08% [28] 3. Operator Performance - China Mobile's cloud revenue for the first half of 2025 was 56.1 billion yuan, up 11.3% year-on-year [47] - China Telecom's Tianyi Cloud revenue for the same period was 57.3 billion yuan, a 3.8% increase [47] - The ARPU values for China Mobile, China Telecom, and China Unicom remained relatively stable, with slight decreases noted for China Unicom [47][52][56] 4. Investment Recommendations - The report recommends focusing on three main AI investment themes: "Optical, Liquid Cooling, and Domestic Computing Power" [18] - Specific recommended stocks include Zhongji Xuchuang, Xinyi Sheng, and Yingwei Ke [16][18] - The report also highlights potential beneficiaries in various sectors, including AI applications, operators, and satellite internet [18][19][26]

Core Insights - The software industry is at a pivotal moment as AI evolves from code completion to autonomous development agents [1] - Both junior and senior developers face unique challenges due to AI's impact on job roles and responsibilities [2][3] Junior Developer Challenges - Junior developers are experiencing a contraction in growth opportunities as companies are less willing to invest in training, leading to a reduction in entry-level positions [8] - A Harvard study covering 62 million workers found that after the adoption of generative AI, the employment of junior developers decreased by approximately 9%-10% within six quarters, while senior developer employment remained stable [8] - The traditional career path of learning to code and gradually advancing to senior roles is being disrupted, with many companies opting not to hire junior developers [8] Senior Developer Challenges - Senior developers are facing increased pressure as they must manage both architectural decisions and the risks associated with AI and automation systems [2] - The responsibilities of senior engineers are expanding, requiring them to ensure code quality, performance, security, and compliance, while the proportion of time spent writing code is decreasing [2] Future Scenarios - There are two potential futures for junior developers: one where entry-level hiring collapses due to AI automation, and another where demand for developers rebounds as software permeates various industries [8] - The U.S. Bureau of Labor Statistics projects a 15% growth in software-related jobs from 2024 to 2034, indicating a potential resurgence in demand for developers [9] Skills Transition - As AI takes over routine coding tasks, the fundamental coding skills of developers may either degrade or become more critical as developers shift to oversight roles [14] - A significant 84% of developers regularly use AI tools in their work, changing the nature of problem-solving from coding from scratch to assembling AI-generated code snippets [14] Developer Roles Evolution - Developers may evolve into roles focused on overseeing AI-generated outputs or become orchestrators responsible for designing and governing AI-driven systems [19][20] - The industry is witnessing a split in developer discussions, with some advocating for a shift in assessment methods to reflect the new reality of AI-assisted coding [16] Educational Shifts - The traditional four-year computer science degree is being challenged by faster learning paths such as coding bootcamps and online platforms, which are becoming more relevant in a rapidly changing industry [31][32] - By 2024, nearly 45% of companies plan to eliminate the bachelor's degree requirement for certain positions, reflecting a shift towards skills-based hiring [33] Adaptation Strategies - Junior developers should focus on building a broad skill set and actively seek opportunities beyond coding, such as testing and application monitoring [21] - Senior developers need to embrace leadership and architectural responsibilities, ensuring quality standards and mentoring junior staff [23] T-Shaped Engineers - The industry is favoring T-shaped engineers who possess both broad adaptability and deep expertise in one or two areas, as opposed to narrow specialists [25][26] - Nearly 45% of engineering roles now expect candidates to have multi-domain capabilities, highlighting the demand for versatile skill sets [27]

Core Insights - The current focus in the AI sector has shifted from enhancing capabilities to maximizing profitability, as highlighted by the new CNBC podcast featuring Google DeepMind's CEO, Demis Hassabis [1][2]. Group 1: AGI Capabilities - Hassabis emphasizes that current large models exhibit significant shortcomings, particularly in their ability to generalize and learn continuously, which he refers to as "jagged intelligences" [2][4]. - True AGI must possess the ability to independently formulate questions and hypothesize about the world, rather than merely responding to queries [3][4]. - DeepMind is transitioning its focus from large language models (LLMs) to developing AI that understands the world, as demonstrated through projects like Genie, AlphaFold, and Veo [6][9]. Group 2: Commercialization Strategies - The commercial viability of AI models is not solely about their strength but also about their cost-effectiveness and deployment efficiency [10][11]. - DeepMind's strategy includes creating both Pro and Flash versions of models to cater to different user needs, ensuring broader accessibility [11][12]. - Hassabis advocates for integrating AI into everyday devices, moving beyond traditional web interfaces to enhance user interaction [15][16]. Group 3: Energy Challenges - As AI capabilities expand, energy consumption becomes a critical concern, with Hassabis stating that increased intelligence will require more power [20][21]. - The industry faces a significant bottleneck in energy supply, which could hinder the practical application of AGI [22][23]. - DeepMind aims to leverage AI to address energy challenges, focusing on both generating new energy sources and improving energy efficiency [24][27]. Group 4: Competitive Landscape - The competitive dynamics in AI have shifted, with companies needing to focus on integration and deployment rather than just technological advancements [29][30]. - DeepMind has consolidated its teams to streamline AI development and deployment, enhancing efficiency and speed in bringing products to market [33][37]. - The ability to effectively utilize energy resources will be a key determinant of success in the AI sector, as highlighted by Hassabis [36][38].

Core Viewpoint - Alphabet was the top-performing stock among the "Magnificent Seven" in 2025, driven by multiple catalysts, but a similar performance in 2026 is not expected, although it is anticipated to outperform the market [1]. Group 1: Performance and Market Position - Alphabet's stock had a remarkable 65% increase in 2025, but such a performance is not expected to be repeated in 2026 [1]. - The company has emerged as a leader in the generative AI sector, with its Gemini model challenging existing leaders in accuracy and utility [3][8]. Group 2: Revenue and Business Concerns - Google Search, Alphabet's primary revenue source, generated $56.6 billion out of a total of $102.3 billion in Q3 [4]. - Concerns regarding Google Search included threats from generative AI and potential divestitures due to antitrust rulings, but these fears have been alleviated [5][6]. Group 3: Legal and Regulatory Developments - A federal judge imposed lighter penalties on Alphabet for antitrust violations, allowing the company to avoid a breakup and only requiring minor concessions [7].

Core Insights - Investors are reassessing Google due to new partnerships that enhance its Gemini models, contributing to a rise in stock value [1] - Google has entered a multi-year collaboration with Apple to integrate Gemini models into Apple’s features, including an improved Siri by 2026 [2] - Alphabet's valuation reached $4 trillion, with a 5.3% increase in stock price year-to-date, reflecting strong market performance [3] Partnership Developments - Google and Walmart are launching a shopping experience within the Gemini chatbot, allowing users to discover and purchase products seamlessly [1] - The collaboration with Apple is seen as a significant endorsement of Google's AI capabilities, potentially enhancing Gemini's role in mobile AI [7] Stock Performance and Analyst Insights - Alphabet shares experienced a 65.35% increase in 2025, outperforming other major tech stocks, prompting analysts to revise growth assumptions for Google [4] - Bank of America raised its stock price target for Alphabet from $335 to $370, citing the potential for AI-driven monetization and increased traction for Gemini [6] - Analysts believe that the shift in shopping traffic from traditional search to agent-led experiences could benefit Google, with Gemini expected to drive higher conversion rates [8]

Core Viewpoint - Alphabet Inc. is highlighted as a strong investment opportunity in the AI sector, with analysts projecting robust growth ahead of its upcoming earnings report [1][2][3]. Group 1: Earnings Expectations - The company is expected to report strong fourth-quarter results, driven by high engagement and advertising demand, leading to mid-teens growth in both Search and YouTube segments [3]. - Analysts anticipate over 15% top-line growth, consistent with consensus estimates, supported by increased query volume and cost-per-click metrics [2]. Group 2: Growth Drivers - A solid Cloud backlog is projected to result in a 34% revenue growth in the Cloud segment [3]. - The rollout of Gemini 3 in November is seen as a significant catalyst for Alphabet, enhancing its position in AI performance [3]. Group 3: Competitive Position - Truist Securities maintains a bullish outlook on Alphabet's competitive advantages despite rising competition in the generative AI market [4]. - Recent data indicates continued gains in Alphabet's Search market share, reinforcing its strong market position [3].

Core Insights - The global e-commerce landscape is rapidly evolving, with cross-border e-commerce significantly altering international trade dynamics, presenting both challenges and opportunities for businesses and consumers [1] Group 1: Policy Environment - The policy environment is a crucial external factor affecting cross-border e-commerce, with varying regulations across countries creating both challenges and opportunities for enterprises [3] - In Southeast Asia, particularly Vietnam, 63% of consumers prefer purchasing New Year goods through e-commerce platforms, highlighting the market's growth potential [4] - Amazon has upgraded compliance requirements, increasing the on-time delivery compliance rate to 95%, which raises expectations for supplier efficiency [5][6] Group 2: Market Trends - The U.S. has become the largest online market for Korean cosmetics, holding a 51% global share, indicating a significant opportunity for cross-border e-commerce businesses to enhance procurement and marketing strategies [7] - eBay UK has adjusted customer service channels, which may impact consumer communication with the platform, while also launching a climate transition plan aiming for net-zero emissions by 2045 [7] Group 3: Logistics Challenges - Logistics remains a critical aspect of cross-border e-commerce, with long distances and multiple stages leading to high costs and delays, particularly during special circumstances like the pandemic [15] - Companies are exploring new logistics models, such as overseas warehouses, to improve delivery times and customer satisfaction [15] Group 4: Technological Innovation - Technological advancements, including AI, big data, and blockchain, are transforming cross-border e-commerce operations, enhancing customer service and operational efficiency [17][19] - AI technologies are increasingly used for smart customer service and personalized shopping experiences, while big data helps businesses understand consumer needs and market trends [17][19]

As the world has its fingers crossed waiting for the verdict on tariffs from the US Supreme Court, the US President Donald Trump would complete his first year in office on Tuesday. It was an eventful year to put it mildly — the kind that puts twist-laden thrillers to shame. The Oval Office kept buzzing with one executive order after another — on tariffs, immigration, DOGE, oil drilling, brokering peace and big-bang investments in AI — that kept the entire world on edge.At this juncture, we take stock of how ...

（来源：经济日报） 转自：经济日报 伍德沃德同时提醒，此测试版功能尚未完全消除漏洞。Gemini在处理时间信息或细节内容时可能仍存在 不足，对于健康等敏感话题，系统会避免主动做出主观推断，但会在用户主动询问时基于数据进行解 答。 在生成式AI竞争日益激烈的背景下，谷歌正与OpenAI等公司展开正面竞争。尽管此前Gemini已具备调 取应用信息的能力，但此次更新强调其能基于用户数据进行推理分析。苹果公司于1月12日宣布，已选 定谷歌为其部分AI功能提供技术支持。 据业内分析，目前AI行业正朝着更紧密整合用户数据与AI服务的方向发展，以打造深度个性化、具备 上下文理解能力的新一代智能助手，这也被认为是该领域竞争与演进的核心趋势。（经济日报记者 王 一伊） 谷歌近日宣布，开放其全新人工智能工具"个人智能"的用户测试。该功能能够整合来自Gmail、谷歌相 册等多款应用的个人信息，在Gemini聊天机器人中为用户提供个性化答复。 谷歌实验室副总裁兼Gemini应用负责人乔什·伍德沃德在官方博客中介绍，该功能旨在让Gemini能够自 主理解语境，无需用户明确指示，即可关联邮件、相册等内容中的信息，主动输出有价值的洞察。这 ...

Core Viewpoint - Big Tech companies are investing heavily in AI data center infrastructure, but are now facing significant challenges due to federal intervention and public concerns over rising electricity costs [1][2]. Group 1: Investment Trends - Big Tech companies have spent record-breaking amounts on building data centers to support AI development [1]. - The competition in the AI sector is driving hyperscalers like Microsoft, Meta Platforms, Google, and Amazon to expand their data center infrastructure [2]. Group 2: Challenges Faced - Ordinary Americans are increasingly frustrated with the rising cost of electricity, which poses a challenge for Big Tech companies [2]. - The current political climate, with a president focused on affordability, adds pressure on these companies as they prepare for the upcoming midterm elections [2].