创业板人工智能ETF华夏（159381），跟踪创业板人工智能指数（970070.CNI），精准布局创业板 人工智能主业公司。光模块CPO权重占比超54%，同时覆盖国产软件+AI应用企业，具备较高弹性。其 中前三大权重股为中际旭创（24.78%）、新易盛（19.40%）、天孚通信（5.11%）。场内综合费率仅 0.20%，位居同类最低。场外联接（A类：025505；C类：025506） 5G通信ETF（515050）跟踪中证5G通信主题指数，最新规模超90亿元。深度聚焦英伟达、苹果、 华为产业链。前五大持仓股：中际旭创、新易盛、立讯精密、工业富联、兆易创新。相关ETF全称：华 夏中证5G通信主题ETF（515050），场外联接（A类：008086；C类：008087） 每日经济新闻 （责任编辑：张晓波 ） 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 11月28日，AI算力产业链震荡剧烈。截至10:32， ...

今年感恩节，AI比人先上桌！机舱火鸡宴、政治名人拼盘、科技大佬假笑全刷屏得像真实记录。节日本该是烟火气和家人，却被一堆不存在的合照抢走 注意力。我们到底在看回忆，还是在被AI制造记忆？ 你可能也刷到过这张图：Newman坐在中间，周围是被P出来的一圈科技大佬，像在开公司年会。 照片细节满满：火鸡、红酒、烛光一字排开，旁边是笑得乖巧的扎克伯格、马斯克、纳德拉、库克……画面精致到像杂志大片。 这张图被评为今年最「乱入」的感恩节名场面之一。 Google刚上线的Nano Banana Pro，让这张照片离「现场直击」只差一个BBC水印。 也许几年后的感恩节，我们抬头看着眼前的土豆泥，问「这是不是AI土豆泥？」 今年的感恩节名场面，被AI承包了 今年感恩节，最先上桌的不是人，是AI做出来的神图。 托AI的福，RFK Jr.把当年的麦当劳合照玩成感恩节版。 薯条和汉堡被换成了孢子甘蓝和蔓越莓，特朗普父子、马斯克全员在桌边「健康饮食」。 离谱的是不止这一张。 Newman亲自下场，配文半开玩笑地说这是「AI牛市的感恩节晚宴」。 Tiffany Fong更绝，直接把成龙请到自己餐桌旁帮忙切肉。 这些「名人聚餐」，在社交平台 ...

AlphaFold的下一步是与大模型融合。 不过具体方法并没有透露，或许已有所思路，甚至已经在进程之中。 五年期间，AlphaFold已经帮助全球300多万研究人员，预测了数亿种蛋白质的三维结构，并影响了超50万篇相关论文。 可以说，这是继量子力学和分子生物学革命后，生命科学的又一次重大跃迁。 正值AlphaFold问世五周年，其设计者、也是凭借AlphaFold获得诺贝尔化学奖的John Jumper公开表示： 继最初的"结构预测革命"、随后的"科研常规工具"化，AlphaFold及其继承技术正在进入新的大模型阶段。 AlphaFold+大模型 即使是在AI浪潮不断涌来的今天，AlphaFold仍然是AI+生命科学最具里程碑意义的一次落地。 作为一款由谷歌DeepMind开发的AI科研工具，AlphaFold能够精确预测蛋白质的三维结构。 利用存储在序列和结构数据库中的大量实验数据，该网络被训练以发现氨基酸序列之间的关联和模式。 于是他们利用AlphaFold先对其氨基酸序列进行结构预测，再将生成的模型拟合到密度图中，并逐步优化，直到与实验数据对齐。 最终揭示了ApoB100的笼状结构，为后续推动心血管疾病 ...

1）谷歌凭借 Gemini 3 和 Nano Banana Pro 正在走出"创新者的窘境"。更重要的是，它拥有 AI 时代最深的护城河——TPU 算力集群。在 AI 算力重心从"训练"向"推理"转移的下半场， 谷歌拥有其他巨头无法比拟的成本优势。 2）市场低估了"推理成本"对 AI 商业模式的毁灭性打击。当竞争对手必须向英伟达缴纳"过 路费"时，拥有自研 TPU 的谷歌拥有了定价权。这正是巴菲特看重的"深度价值"——低成本 带来的高安全边际。 3）市场曾经担忧 AI 杀死搜索广告，但 Gemini 3 正在将搜索从"寻找链接"变为"决策引 擎"。AI 带来的高意图流量有望大幅提升广告转化率（ROAS），从而支撑更高的广告单 价。 4）谷歌集齐了"最强模型（Gemini 3）+ 最强算力（TPU）+ 最大入口 （Android/Chrome）"。这种垂直整合让谷歌在 AI 时代拥有"全栈主权"，5 万亿市值或许只 是时间问题。 在美股科技巨头的牌桌上，谷歌（Alphabet）过去两年里拿的一直是一副"尴尬"的牌。自 ChatGPT 横空 出世以来，谷歌仿佛陷入了"大公司魔咒"：起个大早、赶个晚集，内部执行力被 ...

雪球有大佬总结了Michael Burry的一系列操作： 只是现在过了两天，订阅人数增加到了88k，已经超过3300万美元的订阅费了，当然我给他贡献了 379美元的订阅费.. 目前Michael Burry总共写了三个文章，我们来看下他的观点。 1、泡沫的主要标志：供给侧的贪婪 第一篇内容《The Cardinal Sign of a Bubble: Supply-Side Gluttony》主要是在回顾历史了。 核心观点是： 愚蠢（狂热的创新尝试）是美国成为世界创新中心的重要原因 ，但愚行过度会引发泡 沫；核心标志是供给侧过度扩张，而非需求不足或盈利缺失。 支撑这个观点的核心理论是 资本周期理论 ，即狂热驱动下的资本过度投资会导致供需失衡，最终引 发行业洗牌与市场崩盘，这一理论是贯穿全文的分析框架。 说到历史上的辉煌的愚蠢行为，90 年代的互联网泡沫是绕不开的案例，但大众对它的记忆大多是错 的。美联储主席鲍威尔曾说：当下公司有商业模式和盈利，与当年不同。但事实并非如此。当年的 泡沫根本不是无利可图的".com 公司" 驱动的，而是一场数据传输基础设施建设狂潮。那时候的口号 是互联网流量每 100 天翻一番， ...

Core Insights - The market share of smartwatches supporting satellite communication is expected to increase from 2% in Q3 2025 to 28% by Q3 2030, driven by early market leaders like Apple and Huawei, and later by Google and Garmin as standardization occurs [1][5]. Market Trends - The early market (2025-2026) will be dominated by brands with proprietary satellite solutions, while from 2027 onwards, the adoption of standardized NB-NTN technology will accelerate the integration of satellite modems into wearable devices [1][5]. - Currently, satellite features are primarily found in high-end smartwatches priced above $500, but as NB-NTN technology scales, this barrier will gradually lower, allowing mid-range products to adopt satellite communication [5]. Brand Strategies - **Apple**: Plans to expand satellite functionality to the Apple Watch Ultra 3 by Q3 2025, utilizing a partnership with Globalstar for bidirectional NTN messaging and SOS features [6]. - **Google**: The Pixel Watch 4 will be the first Wear OS smartwatch to support true bidirectional satellite communication based on the 3GPP standard, allowing direct satellite messaging without smartphone pairing [6]. - **Garmin**: The Fenix 8 Pro will support bidirectional SOS and satellite messaging across North America and Europe, reinforcing Garmin's position in safety and exploration [10]. - **Huawei**: The Watch Ultimate 2 will utilize China's Tiantong-1 system for satellite communication, currently limited to the domestic market [10].

Core Insights - Acknowledging setbacks is the first step for Google to restart its AI journey, leading to a restructuring of its foundational architecture and a focus on multi-modal understanding as a core advantage [1][6] - The release of Gemini 3 marks a significant turnaround for Google, demonstrating its ability to not only catch up but also redefine its organizational methodology and technological path [4][8] Group 1: Acknowledgment of Challenges - Google’s AI chief openly admitted that the company had fallen behind, particularly in the wake of ChatGPT's rise, which shifted industry focus towards OpenAI [3][4] - The internal consensus shifted, recognizing that traditional long-term research alone could not keep pace with the rapid evolution of AI technology [5][6] Group 2: Multi-Modal Understanding - Multi-modal capabilities are essential for understanding the complexities of the real world, as they integrate text, images, audio, and video into a unified model [7][8] - Google’s approach involves restructuring at the architectural level to allow different modalities to be trained together, enhancing the model's ability to comprehend the world rather than just generating aesthetically pleasing outputs [7][8] Group 3: Organizational Restructuring - The transformation of Google’s organizational structure from a serial pipeline to a parallel system has significantly accelerated the development and deployment of Gemini [8][9] - This restructuring allows for real-time collaboration among product managers, engineering teams, and safety protocols, leading to a more cohesive and efficient development process [8][10] Group 4: Enhanced Usability and Functionality - The improvements in Gemini's user experience are attributed to a focus on usability, including enhanced instruction comprehension and internationalization capabilities [11][12] - The model's ability to execute tasks rather than merely respond to queries marks a shift towards more actionable intelligence [13][14] Group 5: Competitive Advantages - Google’s competitive edge lies not just in model capabilities but also in its robust infrastructure, including TPU, global data centers, and a mature security system [15][16] - The activation of this infrastructure has been pivotal in Google’s rapid recovery from being perceived as a laggard in the AI space [16] Group 6: Future Directions - The next phase of AI competition will focus on action-oriented intelligence rather than just conversational capabilities, with an emphasis on automating workflows and enhancing developer tools [17][18] - The distinction between dialogue models as products and action models as platforms highlights the greater commercial value of the latter [19] Group 7: Broader Implications - The real measure of progress is the application of models in real-world scenarios across various fields, indicating a shift towards practical utility in AI development [20][21] - The journey from research to product integration reflects a significant evolution in Google’s approach to AI, emphasizing the importance of user feedback and real-world applicability [44][59]

Core Viewpoint - The article discusses the significant growth potential of satellite-enabled smartwatches, predicting that their shipment share will increase from 2% in Q3 2025 to 28% by 2030, driven by advancements in NB-NTN technology and increasing consumer demand for reliable connectivity in remote areas [4][5][9]. Market Trends - Satellite-enabled smartwatches are emerging as a frontier in the wearable device ecosystem, connecting terrestrial networks with non-terrestrial networks (NTN) [5]. - The early market (2025-2026) will be dominated by brands like Apple and Huawei, which have proprietary satellite solutions, while from 2027 onwards, more Android OEMs will adopt standardized NB-NTN technology [5][8]. Adoption Drivers - The introduction of satellite SOS services by Apple in 2022 and Huawei's satellite connectivity service in 2023 has shifted satellite communication from niche to mainstream [9]. - The demand for reliable communication in outdoor and remote areas is expected to accelerate the adoption of satellite smartwatches [9]. Brand Strategies - Apple plans to expand its satellite functionality to the Apple Watch Ultra 3 by Q3 2025, partnering with Globalstar for two-way NTN messaging and SOS features [10]. - Google’s Pixel Watch 4 will be the first Wear OS smartwatch to support true two-way satellite communication based on the 3GPP NB-NTN standard [13]. - Garmin's Fenix 8 Pro will support two-way SOS and satellite messaging, reinforcing its position in the outdoor safety market [14]. - Huawei's Watch Ultimate 2 will utilize China's Tiantong system for satellite communication, currently limited to the domestic market [15]. Ecosystem Development - The development of NB-NTN in wearables is driven by advancements in chipsets and collaborations with satellite operators [16]. - Major chipset platforms are integrating NB-IoT and NTN functionalities, laying the groundwork for the next generation of satellite-enabled wearables [16]. - The competition will focus on battery efficiency, seamless switching between cellular and satellite networks, and stronger partnerships with satellite service providers [16].

Core Insights - Google is positioning itself as a strong competitor to Nvidia by securing significant partnerships and expanding its TPU offerings, potentially disrupting Nvidia's dominance in the AI chip market [1][3] - The shift towards Google's TPU is driven by its system-level cost efficiency and scalability, which appeals to major AI companies like Meta and Anthropic [5][10] - The emergence of a "Google Chain" signifies a structural change in the AI computing landscape, allowing for a more diversified supply chain beyond Nvidia [22][25] Google’s Strategic Moves - Google is negotiating multi-billion dollar TPU purchases with Meta, which may lead to a shift of some of Meta's computing power from Nvidia to Google [1] - A partnership with Anthropic aims to expand TPU capacity significantly, indicating a strong demand for Google's AI infrastructure [1] - Google's TPU is designed to optimize cost and efficiency, with the latest generation showing a performance-to-cost ratio improvement of up to 2.1 times compared to previous models [5][7] Performance Comparison - Nvidia's Blackwell architecture remains the industry benchmark for single-chip performance, but Google is focusing on system-level efficiency rather than direct competition on chip performance [4][5] - Google’s TPU v5e can achieve a performance-to-cost ratio that is 2-4 times better than traditional high-end GPU solutions, making it an attractive option for large model training [7][10] - The cost of using Google’s TPU v5e is significantly lower than Nvidia's H100, with TPU priced at $0.24 per hour compared to H100's $2.25 [8][9] Market Dynamics - The increasing adoption of Google’s TPU by major AI firms indicates a shift in the AI computing market, where companies are looking for alternatives to Nvidia to mitigate risks and reduce costs [10][13] - The competition between "Nvidia Chain" and "Google Chain" is not a zero-sum game; rather, it represents a broader expansion of AI computing resources [22][27] - The structural change allows companies to choose from a diversified set of computing resources based on their specific needs, enhancing flexibility and cost-effectiveness [25][26] Beneficiaries of Google’s Strategy - AVGO is identified as a key player benefiting from Google's TPU ecosystem, providing essential communication and networking components [15][16] - The manufacturing partners, including TSMC, Amkor, and ASE, are crucial for the production of Google's TPU, ensuring the scalability of its offerings [18] - Companies like VRT, Lumentum, and Coherent are positioned to benefit from the increased demand for high-performance cooling and optical communication solutions as TPU deployments expand [20][19] Future Implications - The rise of Google’s TPU could lead to a more balanced and resilient AI infrastructure, reducing the industry's over-reliance on Nvidia [22][25] - The dual-engine approach of Google, combining cloud and edge computing, is expected to reshape the AI landscape, making it more accessible and efficient for various applications [20][21] - The ongoing competition will likely drive further innovation and investment in AI computing, benefiting the entire industry [27]

Group 1 - Alphabet has become the fourth company globally to surpass a market capitalization of $3 trillion, joining Apple, Microsoft, and Nvidia [3] - The rapid increase in Alphabet's market value, which rose over $1.34 trillion in just two months, is attributed to multiple disruptive actions reshaping the tech industry [1][4] - Key drivers of Alphabet's stock surge include favorable antitrust rulings, positive regulatory environment, optimistic sentiment towards AI, and strong Q3 earnings exceeding expectations [4] Group 2 - Waymo, Google's autonomous driving division, operates over 2,500 vehicles and has achieved over 100 million miles of fully autonomous driving, with plans to expand its service to over 20 cities [7][9] - Waymo's business model combines ride-hailing services with technology licensing, marking a significant step towards the commercialization of autonomous driving [8] - In contrast, Tesla's approach focuses on a pure vision technology route, with plans to deploy 1,000 Robotaxis by the end of 2025, aiming for a fleet of 1 million Robotaxis across the U.S. [9][10] Group 3 - The competition between Waymo and Tesla represents a significant technological rivalry that will shape the future of the trillion-dollar autonomous driving market, with 2026 being a pivotal year for both companies [10] - Waymo's multi-sensor fusion approach is more costly, while Tesla's pure vision strategy offers long-term cost advantages and scalability [10] - The ongoing expansion of Waymo's services, including plans for international testing in London, highlights its commitment to leading in the autonomous driving sector [9]