Alphabet(GOOGL.O)"正把人工智能作为进攻武器"，这句话来自美国银行的一位分析师，也正是支撑其 股价持续走强的原因之一。 周四下午，Alphabet成为标普500指数中表现最亮眼的成分股之一——华尔街对本周谷歌年度I/O开发者 大会上接连发布的AI动态报以热烈掌声。尽管大会首日（周二）Alphabet股价一度下跌，但之后两个交 易日连涨，周四午盘又上涨1.9%。 在I/O大会上，谷歌推出了搜索"AI Mode"，称其为"最强大的AI搜索"，具备高级推理与多模态能力。这 一全新AI功能距"AIOverviews"上线仅一年，而谷歌这一搜索霸主正面临OpenAI、Perplexity等竞品的AI 搜索挑战。 5月7日，在苹果(AAPL.O)暗示谷歌搜索业务面临挑战后，Alphabet股价一度重挫逾7%。不过，目前股 价不仅收复全部失地，还较暴跌前高出约6%。 "如何变现"最牵动投资者神经 Melius Research分析师指出，周二股价先跌，源于市场对"AIMode如何通过广告赚钱"摸不着头脑。不过 在周三报告中，他们看到AIMode的多项功能"展现了AI的潜力，也显露出明显的盈利路径"——购物、 ...

Core Insights - The AI search market in China has become increasingly competitive, with major players like Baidu, Quark, and Tencent entering the fray, leading to a significant shift in market dynamics [1][3][6] - Quark has emerged as a strong competitor, leveraging its association with Alibaba and achieving a daily active user (DAU) count of 34 million, challenging Baidu's long-standing dominance [3][4] - 360's Nano AI search has struggled to gain traction, with its peak DAU only reaching a few million, indicating a significant gap compared to Baidu and Quark [4][8] Market Dynamics - The AI search landscape has seen a resurgence of competition reminiscent of the past, with Quark and Baidu engaging in direct rivalry, while 360's entry has not significantly impacted the market [3][4] - Tencent has officially launched its upgraded QQ browser, incorporating AI features and positioning itself as a direct competitor to Quark, further intensifying the competition among the major players [6][7] - The lack of a clear technological barrier among the major players (Baidu, Alibaba, Tencent) suggests that differentiation will be challenging, as their underlying AI models do not exhibit significant differences [7][9] Company Strategies - 360's Nano AI search is focusing on integrating with DeepSeek and building its knowledge base, but it faces challenges in gaining visibility and user engagement [4][8] - Meita AI search and Tiangong AI are struggling to maintain relevance in the competitive landscape, with Meita's functionality being limited and facing potential exclusion from the market [4][8] - Companies like Meita are pivoting towards vertical search engines in specific sectors like law and finance, attempting to carve out niche markets to survive against larger competitors [16] Future Outlook - The AI search market is expected to continue evolving, with companies needing to establish technological barriers or focus on specialized niches to remain competitive [9][16] - The emphasis on marketing and user engagement will be crucial for companies like 360 and Meita, which are currently lagging behind in user acquisition and brand recognition [18] - The industry is moving towards a more agent-based model, with the potential for new entrants to disrupt the market if they can offer unique value propositions [17][18]

Group 1 - Google announced the launch of an advanced AI search mode driven by Gemini at the Google I/O developer conference, moving from a "keyword + link list" approach to "natural language interaction + structured answers" [1] - In 2024, Google's search business contributed $175 billion, accounting for over half of its total revenue, indicating that the transition to AI search may impact this revenue stream [2] - Bernstein research suggests that Google's search market share may have dropped from over 90% to 65%-70% due to the rise of AI ChatBots, prompting Google to act [3] Group 2 - The entry of Google into AI search is seen as a response to the threat posed by Chatbots that are consuming traffic, indicating a challenging environment for new AI search players [4] - Perplexity's user traffic increased from 45 million to 129 million over the past year, a growth of 186%, but its actual revenue was only $34 million due to frequent discounts, leading to a net loss of $68 million in 2024 [9] - The funding landscape for AI search products has changed significantly, with only 10 products raising a total of $893 million from August 2024 to April 2025, compared to 15 products raising $1.28 billion in the previous period [12][14] Group 3 - The overall trend in AI search engines is shifting towards smaller, more specialized products, moving away from the idea of creating a new Google Search [17] - Major players like Microsoft, OpenAI, and Google have integrated AI search functionalities into their existing platforms, making it difficult for standalone AI search products to compete [18][26] - The introduction of reasoning models has improved user experience in search functionalities, but many AI search products have not differentiated themselves sufficiently, leading to a decline in user engagement [26][30] Group 4 - New AI search products are focusing on niche markets, such as health, legal, and video search, to carve out a unique space in the competitive landscape [50] - Companies like Consensus and Twelve Labs are developing specialized search engines targeting specific user needs, such as medical research and video content [32][43] - The commercial viability of AI search products remains a significant challenge, with Google exploring ways to monetize its AI search mode while facing potential declines in click-through rates for traditional ads [51]

Core Viewpoint - The Google I/O developer conference showcased a lack of surprises, with the most significant change being the introduction of the "AI Mode" for search, which aims to fundamentally reshape how users interact with search engines [1][3]. Group 1: AI Mode and Search Engine Transformation - Google has introduced "AI Mode," allowing users to interact with Gemini AI for information retrieval, moving away from traditional blue search links [3][12]. - CEO Sundar Pichai emphasized that this represents a complete overhaul of the search process, marking a new phase in AI platform transformation [3][11]. - The shift to AI-driven search is a response to declining search usage, as users increasingly turn to AI tools for information [5][7]. Group 2: Market Dynamics and Competition - Google's search market share has reportedly fallen below 90% for the first time in a decade, prompting the need for significant changes to avoid obsolescence [5][7]. - The traditional search model, based on keywords and links, is becoming less relevant as users prefer direct answers rather than sifting through multiple links [9][11]. - The rise of AI chatbots is fundamentally altering how users seek information, with platforms like ChatGPT attracting significant user engagement [11]. Group 3: Technological Advancements - Gemini 2.5 Pro, supporting "AI Mode," offers advanced capabilities such as long context windows and enhanced reasoning, setting it apart from previous models [12]. - The core competitive advantage of "AI Mode" lies in its multimodal search technology, integrating text, images, voice, and video inputs [12][14]. Group 4: Advertising Strategy - Google plans to adapt its advertising model by labeling ads as "Sponsored" and placing them strategically within the AI dialogue to maintain user trust and engagement [14][16]. - The introduction of "Shopping Graph 2.0" aims to leverage AI for a seamless shopping experience, featuring 50 billion product nodes and real-time price updates [14][16].

Core Viewpoint - The concept of "AI hallucination" refers to AI generating inaccurate information, which is attributed to limitations in model generation and training data, but the role of search engines in providing accurate information is often overlooked [1][3]. Group 1: AI Hallucination and Search Engines - AI hallucination is a persistent issue that cannot be completely eliminated, primarily due to the inherent problems with information sources [3][4]. - The accuracy of AI-generated responses is influenced by the quality of the information retrieved from search engines, which can also contain inaccuracies [4][6]. - The search engine's role is likened to that of a supplier of ingredients for a chef, where the quality of the ingredients (information) directly impacts the final dish (AI output) [1]. Group 2: Company Insights and Technology - Bocha, a startup based in Hangzhou, provides search services for over 60% of AI applications in China, with a daily API call volume exceeding 30 million, comparable to one-third of Microsoft's Bing [1][2]. - The company employs a dual approach of "model + human" to filter information, using a model to assess credibility before human intervention for verification [4][5]. - Bocha's search engine prioritizes "semantic relevance," allowing it to return results based on the full context of user queries rather than just keywords [6][7]. Group 3: Challenges and Future Outlook - The company faces challenges in building a large-scale index library, with a target of reaching 500 billion indexed items, which requires significant infrastructure and resources [14][15]. - The anticipated future demand for AI search services is expected to exceed human search volumes by 5 to 10 times, indicating a growing need for robust search capabilities in AI applications [14]. - Bocha aims to establish a new content collaboration mechanism that rewards high-quality content providers, moving away from traditional paid ranking systems [9][10].

Core Insights - AI agents are redefining the search landscape, shifting from "machines adapting to humans" to "humans adapting to machines" [2] - The emergence of AI large models has disrupted the traditional search market, previously dominated by giants like Google and Baidu [2][3] - The competition in the search industry is evolving towards "mind share" rather than just "traffic share" [3][4] Industry Dynamics - The competition is characterized by intensified technological stratification, with leading firms leveraging computational power and data advantages to create barriers [3] - Ecosystem competition is heating up, as traditional search engines integrate their content ecosystems to maintain dominance [3] - The value of entry points is being redefined, with AI search evolving from a tool to a traffic entry point [3] User Behavior Changes - Google search volume in Safari has declined for the first time in 20 years, while user numbers for startups like Perplexity are surging [4] - Apple's plans to integrate third-party AI search in Safari indicate a potential erosion of traditional search engine dominance [4] Business Model Evolution - The traditional advertising model in the search industry is being challenged, with subscription and enterprise services emerging as new directions [5] - Search results are evolving from "webpage lists" to "knowledge products," enhancing the added value of AI search [5] Challenges Ahead - There are significant challenges, including technical bottlenecks, ethical risks, and the need for ecosystem collaboration [6] - AI hallucination issues persist, particularly in handling ambiguous semantics [6] - Data privacy and algorithmic bias are critical ethical concerns as AI agents become more proactive in user environments [6]

分析师：谷歌仍需在AI领域加大力度以说服投资者 金十数据5月21日讯，分析师Dan Gallagher撰文指出，Statcounter数据显示，谷歌目前处理全球约90%的 搜索请求，其Android系统支撑着全球近四分之三的智能手机，这些优势为其构建了分发新功能的庞大 平台，但仍未阻止部分搜索用户转向ChatGPT等聊天机器人。联邦政府正在推进两项旨在分拆公司的反 垄断诉讼也威胁其关键分发渠道。双重威胁为谷歌带来新的生存危机。母公司Alphabet股价今年累计跌 幅达13%，成为过去12个月唯一市值缩水的超大型科技公司。MoffettNathanson公司的Michael Nathanson 写道："在监管风险消除、搜索份额特别是商业查询领域份额趋于稳定前，投资者仍将保持不安。"摩根 士丹利调查显示，3月份美国16岁以上人群中，40%受访者每月至少使用一次Gemini，仅比ChatGPT低1 个百分点，但ChatGPT在16-24岁群体中占据显著优势，使用率达68%，远超Gemini的46%。 ...

21世纪经济报道记者 董静怡 上海报道 谷歌正在对搜索进行彻底重塑。Gemini模型正在助力Google搜索变得更智能、更主动、更个性化。 早期测试显示，用户在此模式下的查询长度是传统搜索的2-3倍，且能通过多轮对话深入探索。谷歌宣布，AI Mode 将从5月20日开始在美国向所有用户推 出。从本周开始，Gemini 2.5也将登陆美国地区的搜索。 过去一段时间里，谷歌搜索面临着不小的挑战。市场调研机构statcounter数据显示，谷歌在全球搜索引擎市场的份额在过去六个月大部分时间都处于90%以 下，这是至少十年来从未出现过的情况，其长期近乎垄断的地位正面临挑战。 这一趋势表明，用户行为正在悄然变化，Bing等竞品和第三方聊天机器人，尤其是Chatgpt，正在逐步侵蚀谷歌的传统优势。根据OpenAI的数据，截至上个 月，每周有大约4亿人使用ChatGPT。 谷歌也做出了AI搜索的尝试。去年，谷歌推出了AI Overviews，在传统搜索结果顶部提供AI生成的摘要，帮助用户快速获取答案，而无需点击多个链接。谷 歌介绍，自去年推出以来，AI Overviews已覆盖超过15亿用户，目前已在200个国家和地区推出 ...

图片来源： Perplexity 人工智能驱动的搜索引擎 Perplexity 在过去一年中，迅速增加了订阅收入和用户数量，尽管面临谷歌和 OpenAI 免 费 AI 搜索工具的激烈竞争。此前未公开的财务数据显示了这种增长的成本。 • 公司去年创造了 3400 万美元的收入，搜索处理量仅为OpenAI的1/25，谷歌的1/900。 • 折扣金额接近订阅销售额的一半截至 2024 年年底，近26万用户（即160万订阅者中的16%）为其付费。 • OpenAI 、 Anthropic 及网络服务成本支出超 5700 万美元 根据财务文件， Perplexity 去年创造了 3400 万美元的收入。 但由于在云服务器和 Anthropic 及 OpenAI 的 AI 模 型上投入巨大（这些模型为搜索引擎的许多答案提供支持），公司消耗了约 6500 万美元现金。 这家旧金山初创公司凭借稳定的风险资本供给实现了快速增长。 Perplexity 正洽谈以 140 亿美元估值融资 5 亿美 元，这将是其一年内第四轮融资——去年底账面资金约达 8.5 亿美元。 充裕资金也使其具备收购其他初创公司的实力，从而扩充工程师团队。 ...

百度移动友好性测试工具集成速度诊断模块，重点检测： 某新闻门户网站采用MIP改造后，移动端加载速度提升58%，广告点击率增长19%。 速度比较快的页面url示例； 在搜索引擎算法持续迭代的背景下，网站速度优化已从技术细节演变为影响搜索排名、用户体验和商业转化的核心要素。谷歌与百度作为全球与中国市场的 搜索双极，在速度优化维度展现出差异化的技术路径与价值取向。本文通过对比两大搜索引擎的优化体系，揭示其技术逻辑、评估标准及实施策略，为企业 制定适配性方案提供决策依据。 一、评估体系：核心指标与技术工具的差异化布局 1. 谷歌：以用户体验为核心的量化评估 谷歌构建了以Core Web Vitals为核心的三维评估体系，通过实验室数据与真实用户监控（RUM）的双重校验，形成闭环优化模型： 技术支撑工具PageSpeed Insights提供从0到100的量化评分，结合Lighthouse审计引擎输出优化清单。某电商网站通过该工具优化后，LCP从3.8秒降至2.2秒， 移动端转化率提升12%。 2. 百度：移动优先的速度红线 百度建立以MIP（移动网页加速器）为核心的技术生态，设定双重速度标准： 1. 谷歌：全链路性能 ...