炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ 责任编辑：常福强 11月28日，2025分析师大会举行，专家学者、券商基金私募掌舵人、首席分析师等齐聚一堂，共寻穿越周期的投资真谛。东方港湾董事长但斌主旨演讲。 但斌表示，AI的竞争很可能是更加垄断的商业模式的竞争，其实，过去经历的互联网、移动互联网时代，可到看到商业模式比较集中的原因。而人工智能 AI Agent时代，很可能让全世界的市场都被几家公司所控制，它们的市值最后可能大得不可思议，今天看起来不仅是英伟达市值可能会超过十万亿，很可能 谷歌、英伟达会比翼齐飞，达到十万亿美金市值。 专题：2025分析师大会：资本市场"奥斯卡"启幕 ...

Core Viewpoint - Morgan Stanley believes that Google's external sales of TPU (Tensor Processing Units) may boost the company's revenue and profitability, especially as the stock price of Alphabet has surged nearly 20% in the past month amidst concerns over an "AI bubble" [1] Group 1: Google's TPU Sales Strategy - Google is reportedly marketing its TPU to clients, with Meta considering a multi-billion dollar investment in TPUs for data center construction, indicating a significant strategic shift from internal use to external sales [1] - Morgan Stanley's analysis suggests that for every 500,000 TPUs sold externally, Google's cloud revenue forecast for 2027 could see an increase of approximately $13 billion (around 11%) and an EPS increase of about 3% (or $0.37) [1] Group 2: Market Dynamics and Competition - Analysts suggest that if Google's cloud business accelerates and the company successfully enters the semiconductor market, it could lead to a higher valuation multiple for Google [2] - The prediction of selling 500,000 to 1 million TPUs annually is deemed reasonable, especially considering NVIDIA's expected shipment of around 8 million GPUs by 2027 [2] - The impact of Google's TPU sales on the semiconductor industry is seen as beneficial for Broadcom, which co-designs TPU chips with Google, while the effect on NVIDIA and AMD is minimal [2] Group 3: Competitive Landscape - Despite the potential of Google's Gemini model to surpass GPT-5, competition in the tech industry is expected to remain intense, with no signs of competitors slowing down [3]

历史的回响：技术革命是财富增长的真正引擎 但斌从1998年君安研究所的岁月谈起，以亲身经历串联起中国资本市场的变迁。他指出，过去数十年间，电子计算机、互联网、移动互联网三大技术浪潮催 生了无数投资机遇。尽管期间经历金融危机、高通胀等干扰，但推动社会前进的根本动力始终是技术进步。 "如果我们回到2004年东方港湾成立时，能预见移动互联网时代，就应该将全部资金换成港币买入腾讯。"但斌以21年六七百倍回报的案例，道出时代机遇的 惊人能量。而今面对2022年开启的人工智能革命，他直言东方港湾做出了与当年类似的战略抉择——重仓以英伟达为代表的AI领军企业。 全球视野：选择比努力更重要 专题：2025分析师大会：资本市场"奥斯卡"启幕 炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ 11月28日，2025分析师大会暨第七届新浪财经"金麒麟"最佳分析师颁奖盛典隆重召开。东方港湾董事长但斌主旨演讲。但斌以一场充满历史纵深感的演讲， 向在场年轻分析师们传递了一个核心信念：我们正站在一个堪比工业革命的智能时代开端，投资生涯中最大的遗憾，莫过于辜负这样的伟大时代。 针对当前市场对AI泡沫的担忧，但斌引用历 ...

Core Insights - The AI industry is entering a rapid change cycle, with 2025 being a pivotal year for the development of large models, particularly with the emergence of DeepSeek, which is reshaping the global landscape and promoting open-source initiatives [1][10][18] - The dual-core driving force of AI development is characterized by the United States and China, each following distinct paths, with key technologies accelerating towards engineering applications [1][10][11] - Despite advancements in model capabilities, challenges in real-world application remain prevalent, indicating a shift in focus from "large models" to "AI+" [1][10][19] Group 1: Global Large Model Landscape - The global large model development is driven by a dual-core approach, with the U.S. leading in closed-source models and China focusing on open-source models [10][11][13] - OpenAI, Anthropic, and Google represent the leading trio in the large model arena, each adopting differentiated strategic paths [17] - DeepSeek's emergence marks a significant breakthrough for China's large model development, showcasing the potential of open-source models [18][19] Group 2: Key Technological Evolution - The evolution of large models is marked by four major technological trends: native multimodal integration, reasoning capabilities, long context memory, and agentic AI [22][24] - Native multimodal architectures are replacing text-centric models, allowing for seamless integration of various modalities [23] - Reasoning capabilities are becoming a core feature of advanced models, enabling them to demonstrate their thought processes [24][26] Group 3: Industry Chain and Infrastructure - The AI infrastructure is still dominated by Nvidia, with a slow transition towards a multi-polar ecosystem despite the emergence of alternatives like Google’s TPU and AMD’s chips [47][48] - The AI industry is shifting from reliance on a few cloud providers to a more collaborative funding model, with Nvidia and OpenAI acting as dual cores driving the ecosystem [51][52] Group 4: Application Layer Opportunities - Large model companies are positioning themselves as "super assistants" while also aiming to control user entry points through various products and services [53][54] - Independent application companies can find opportunities in vertical markets that require deep industry understanding and complex workflow integration [55][56] - The evolution of AI applications is moving towards intelligent agents capable of autonomous operation, indicating a significant shift in application development paradigms [61][62]

从人力资源到会计行业，越来越多非技术从业者开始使用 ChatGPT、Gemini、Claude、Replit 等工具自己制作应用。皮查伊认为，氛围编程让使用者能直接 把想法做成模型，而不仅仅是描述。"过去只能用语言解释，现在可以先做出一点雏形再展示。" IT之家 11 月 28 日消息，据《商业内幕》今日报道，谷歌 CEO 桑达尔・皮查伊认为，氛围编程（Vibe coding）正在为非技术背景的工作者打开同样的大 门，就像博客曾让普通写作者找到职业入口，YouTube 也让更多人把内容创作变成事业一样。 这种方式甚至开始改变科技公司内部的流程。Meta 的产品经理已经用氛围编程做原型并展示给扎克伯格。皮查伊透露，谷歌内部首次提交代码变更的员工 数量也明显增加。 皮查伊在一档谷歌开发者播客中表示，氛围编程让创作应用和网站变得更加愉快，人们即便没有编码基础，也能随时尝试搭建原型。技术正在变得更易接 近，更有趣，而且还会不断进化，从而让人再度兴奋起来。 不过，随着氛围编程的快速普及，把编码工作交给 AI 也带来风险。IT之家从报道中获悉，皮查伊强调，大型关键系统仍必须由专业工程师负责，因为安全 与准确性都无法被忽视 ...

Core Insights - The AI computing power industry chain is experiencing significant fluctuations, with notable movements in related ETFs and stocks [1] - Google is at the center of a new investment chain, launching multiple products that create a positive feedback loop, enhancing AI revenue through increased token consumption [1] - The vertical integration of computing power, models, and applications by Google is expected to clarify the business model of AI applications and establish a sustainable profit model [1] Group 1: Market Performance - The ChiNext AI ETF (159381) decreased by 0.61%, while the 5G Communication ETF (515050) fell by 0.35% [1] - Stocks such as Putian Technology hit the daily limit, while Jinxin Nuo and Changxin Bochuang rose over 4% [1] Group 2: Google and Alibaba's Strategies - Dongwu Securities highlights that Google and Alibaba are enhancing their full-stack capabilities in the AI industry, leading to increased demand for TPU and AI ASIC chips [2] - Customized computing clusters are raising networking requirements, with Google's TPU introducing new optical interconnection solutions [2] - The optimistic capital expenditure outlook from Google and Alibaba is expected to generate substantial incremental demand for the optical interconnection supply chain [2] Group 3: Related ETFs - The ChiNext AI ETF (159381) tracks the ChiNext AI Index and has a significant allocation in optical modules, with the top three holdings being Zhongji Xuchuang (24.78%), Xinyi Sheng (19.40%), and Tianfu Communication (5.11%) [3] - The 5G Communication ETF (515050) focuses on the 5G communication theme index and has a scale exceeding 9 billion, with major holdings including Zhongji Xuchuang, Xinyi Sheng, Luxshare Precision, Industrial Fulian, and Zhaoyi Innovation [3]

Core Viewpoint - Google is developing a new desktop operating system called Aluminium OS, aiming to integrate Android and ChromeOS into a single platform, indicating a strategic shift to replace ChromeOS with Android [1][9]. Group 1: System Development and Strategy - The initiative to bring Android to the PC market is not Google's first attempt, as Android has been prevalent in various devices but has had minimal impact on traditional computers, which are dominated by ChromeOS [3]. - ChromeOS has a significantly lower market share compared to Windows and macOS, even lagging behind Linux, which has led Google to seek a more competitive position [4]. - Google previously worked on Fuchsia, a new operating system designed to run on all platforms, but its priority has diminished over time, leading to its near disappearance from public view [6][7]. Group 2: Features and AI Integration - Aluminium OS is not merely a port of Android to PCs; it is designed with artificial intelligence at its core, aiming to provide a smarter and more efficient user experience [14]. - The integration of AI technologies, such as the Gemini model and Assistant, is expected to enhance the functionality of Aluminium OS across various computing forms [14]. Group 3: Hardware and Market Positioning - Aluminium OS is intended to cover a wide range of devices, from entry-level to premium, indicating Google's ambition to penetrate both low-end and high-end markets [15]. - The transition from ChromeOS to Aluminium OS will be gradual, with both systems coexisting for a period, and a clear strategy for this transition is being developed [15][16]. Group 4: Future Outlook and Release Timeline - Google is actively testing Aluminium OS, with plans to release it in 2026, although the exact timing within that year remains uncertain [23]. - There is speculation about whether ChromeOS will be completely phased out or retain its brand identity, as it holds significant recognition in the education and enterprise markets [22]. Group 5: Community Reactions and Implications - The introduction of Aluminium OS has sparked discussions about its potential to serve as a Linux alternative, given its mature application ecosystem and security features, while also raising concerns about system flexibility and compatibility [25].

Core Insights - This year's Thanksgiving was notably influenced by AI-generated images, overshadowing traditional family gatherings and creating a new form of digital memory [1][10][21] Group 1: AI Technology Impact - Google recently launched Nano Banana Pro, which significantly enhances the realism of AI-generated images, making them indistinguishable from real photographs [10][12] - The AI-generated images feature meticulously crafted details, such as tablecloth textures and lighting effects, which contribute to their believability [12][14] - The combination of "celebrities + holidays + food" in AI images has led to increased acceptance and sharing among users [14] Group 2: Social Media Dynamics - Social media platforms favor visually engaging content, leading to the rapid spread of these AI images, which are perceived as humorous and light-hearted [19] - Users are aware that the images are fake yet still engage with them, driven by a desire for shared laughter and emotional connection during the holiday season [15][19] - The phenomenon reflects a shift in how memories are formed, as repeated exposure to AI-generated images can replace genuine experiences in users' minds [19][21] Group 3: Cultural Reflection - The AI images represent an idealized version of Thanksgiving, contrasting sharply with the chaotic reality of family gatherings [17][21] - The allure of these perfect images serves as a reminder of the importance of real human connections over digital representations [21]

Core Insights - AlphaFold, developed by DeepMind, is set to integrate with larger AI models to enhance its capabilities in predicting protein structures and understanding complex biological interactions [1][6][16] Group 1: AlphaFold's Impact and Achievements - Over the past five years, AlphaFold has assisted more than 3 million researchers in predicting the 3D structures of hundreds of millions of proteins, influencing over 500,000 related papers [3][8] - AlphaFold has evolved from a tool for structural prediction to a comprehensive research tool capable of handling complex molecular interactions and multi-protein complexes [5][8] - Significant breakthroughs have been achieved using AlphaFold, such as revealing the structure of ApoB100 protein related to cardiovascular diseases, which provides a theoretical basis for future treatments [9][11] Group 2: Future Directions - The next phase for AlphaFold involves merging its structure prediction capabilities with broader AI models, potentially allowing it to generate hypotheses, design experiments, and automate research processes [16][14] - AlphaFold's future applications may include better understanding of multi-functional systems, such as protein-protein and nucleic acid interactions, enhancing its role in biological research [16][14] Group 3: Development and Recognition - John Jumper, a key figure in AlphaFold's development, is recognized as the youngest Nobel Prize winner in Chemistry, highlighting the significance of AlphaFold in the scientific community [19][32] - The success of AlphaFold has been described as revolutionary in structural biochemistry, opening new possibilities for designing unprecedented proteins [32][30]

Core Insights - Google is overcoming the "innovator's dilemma" with Gemini 3 and Nano Banana Pro, leveraging its TPU computing cluster as a significant competitive advantage in the AI era [1][3] - The market underestimates the destructive impact of "inference costs" on AI business models, with Google holding pricing power due to its self-developed TPU, contrasting with competitors reliant on NVIDIA [2][4] - Gemini 3 is transforming search from a "link-finding" tool to a "decision engine," potentially increasing ad conversion rates and supporting higher ad prices [1][12] TPU and Inference Arbitrage - TPU is a critical asset for Google, designed specifically for neural network computations, providing a significant performance advantage over NVIDIA's GPUs [4][5] - Google's TPU v7 has improved performance per watt by 100% compared to its predecessor, and its inference performance is four times better than NVIDIA's H100 [5][6] - This positions Google to maintain over 50% gross margins while competitors face reduced margins due to high NVIDIA costs [6] Gemini 3 and Nano Banana Pro - Gemini 3 showcases Google's ability to convert talent into superior product capabilities, outperforming competitors like GPT-5.1 [7] - The model's native multimodal capabilities allow it to process complex data and perform tasks across various platforms, enhancing its utility [7][10] - Nano Banana Pro aims to optimize AI for mobile devices, further expanding Google's reach [7][8] Distribution and Market Position - Google benefits from a vast distribution network through Android and Chrome, allowing for zero marginal cost updates to billions of users [10][11] - The company's strategic moves, including stock buybacks, enhance shareholder value and position it favorably in the tech market [11] Business Model Evolution - Concerns about AI killing search are mitigated by the potential for AI to enhance ad targeting and conversion rates, shifting from traditional traffic distribution to high-value decision-making [12][16] - Gemini-driven search experiences are expected to yield higher ad values by providing structured comparisons rather than simple links [16][17] Conclusion - Google is uniquely positioned in the AI landscape with its "full-stack sovereignty," combining hardware, software, and user access [17][18] - The recent stock price surge reflects market recognition of Google's status as a leader in AI infrastructure, paving the way for potential future valuation increases [17][19]