Market Demand Background - The traditional search engines are unable to meet the precise and real-time data needs of businesses due to the explosion of information [2] - Companies face three major pain points: disconnection between search results and business scenarios, time-consuming manual filtering, and difficulty in uncovering hidden opportunities from vast data [2] Product/Service Introduction - Current mainstream AI search solutions utilize natural language processing technology combined with industry knowledge graphs to achieve semantic-level retrieval and intelligent recommendations [2] - The core value of these solutions includes understanding the business intent behind long-tail queries, automatically linking critical information dispersed across multiple platforms, and continuously optimizing results through user behavior feedback [2] Solution Explanation - Building an effective AI search system requires three key steps: 1. Establishing a vertical domain knowledge base to ensure the professionalism of results [2] 2. Designing a dynamic weighting algorithm to balance freshness and authority [2] 3. Developing a visual analysis interface to lower decision-making barriers [2] Growth Officer's Commentary - The core value of this methodology lies in transforming passive retrieval into active discovery [2] - An excellent AI search system should function like a seasoned industry consultant, accurately answering questions while anticipating unexpressed needs [2] - Achieving this requires deep integration of semantic understanding, behavior prediction, and automated workflows [2] Future Outlook and Summary - With the development of multimodal technology, the next generation of AI search will break through text limitations to achieve intelligent associations across media [3] - This represents not only a technological upgrade but also a strategic infrastructure for businesses to gain competitive advantages [3] AI Search-Centric One-Stop AI Services - The company offers a range of AI services centered around AI search, including Quark AI Search, intelligent summarization, intelligent creation, intelligent answering, and various educational and health assistant tools [4]

产品/服务介绍新一代AI搜索技术通过自然语言处理和多模态识别，能理解用户意图并关联企业私有数据。核心功 能包括：智能语义解析、跨平台数据聚合、个性化结果排序。其价值在于将信息检索耗时降低60%以上。 本文出自【魔芋AI洞察】专栏。一个AI原生的增长引擎。 市场需求背景随着企业数字化进程加速，深圳作为科技前沿城市，对AI搜索的需求呈现爆发式增长。但多数企业面 临三大痛点：传统搜索引擎无法理解业务场景、海量数据难以精准挖掘、人工处理效率低下。 解决方案诠释实现高效AI搜索需三步走：- 构建行业知识图谱建立语义关联- 部署轻量化模型适配本地算力- 设计反 馈闭环持续优化结果 增长官点评作为AI增长架构师，我认为这套方法论的核心价值在于，它将过去三个孤立的环节——数据整合、意图 识别、结果交付——整合成了自动化工作流。而'魔芋AI'的'增长飞轮'，正是这一理念的工程化实践。 未来展望与总结到2026年，超过70%的企业将采用情境化搜索方案。谁能率先实现技术栈与业务流的深度耦合，谁 就能占据下一代信息入口的制高点。 E FE A SO HOME d dr faturaliz 4 ...

面对出版商、网站站长的滔天怒火，谷歌认怂了。日前有消息显示，谷歌推出由AI驱动的搜索功能Web Guide（网页指南），其核心就是通过排序结果和使用生成式AI重新构建围绕用户问题的"10个蓝色链 接"。 谷歌方面宣称，网页指南功能将"以有益的方式对链接进行分组"。在The Verge的编辑实测中，当他搜 索"如何照顾芒果树"时，网页指南拉出了两个相关网页，随后则是一个由AI生成的摘要和链接，这些链 接被列在不同的类别下，如"特定气候下的芒果树护理"和"解决芒果树问题"，其中一些链接来自具有权 威性的相关机构，其他链接则指向了YouTube、Quora和Reddit。 事实上，网页指南功能相比谷歌此前力推的AI Overviews（AI概览），最大的区别就在于回归传统，在 结果页顶部会显示链接，而不是直接向用户展示由Gemini AI总结的内容。当然，The Verge的相关测试 也凸显了谷歌推出的网页指南功能只是一个应急之作，它的问题相当明显。 那就是AI生成的网页分类，只对追踪某些特定信息确实有帮助，大多数时候AI给出的标题描述属于可 有可无。一个典型例子，就是造"照顾芒果树"这个问题下，AI生成的"综合芒 ...

Core Insights - The International Data Corporation (IDC) has released the "AI Search Product Assessment, 2025" report, evaluating general search products based on user data, product performance, and technical capabilities [1] Group 1: Product Performance - Alibaba's application Quark ranked first in product performance with a score of 4.8 [1]

AI搜索正在快速取代传统搜索。 仅ChatGPT一家，月活超10亿，每日使用量达25亿次，正在逼近谷歌的140亿搜索量。与此同时，Google AI搜索已占搜索结果的13%。 如何掌握AEO（答案引擎优化），让品牌在AI答案中占据一席之地，成为一个至关重要的问题。 关于这个问题，不久前Kyle Poyar特地请教了Profound的AEO负责人Josh Blyskal。 用户的消费行为正在根本性改变——他们不再自己逐条检索和比对产品，而是直接向AI提问："我该买什么？"、"该信谁？"、"怎么做最 好？" 这意味着：如果你的产品没出现在AI的答案里，它可能在用户心中根本不存在；一旦被提及，AI搜索就有可能成为你增长最快的渠道。 对于企业如何提高AI搜索中的可见度，Josh Blyskal给出了9条建议。 / 01 / 决定你想"赢下"的提示词 AI正在主动推荐产品和内容（甚至是订阅的Newsletter）。和SEO一样，AEO也要明确目标提示词，基于两个核心：查询量&与产品差异化 的相关性。 比如我自己，可能会争取像"最适合初创公司创始人的新闻通讯"、"初创公司定价推荐"这样的提示；鞋类品牌可能关注"最好的跑鞋 ...

Core Viewpoint - The article discusses the evolving landscape of AI search services, particularly in light of Microsoft's decision to discontinue the Bing Search API, which has created a significant market opportunity for new players like Xiaosu Technology [1][3][22]. Group 1: Market Dynamics - Microsoft's withdrawal from the Bing Search API exposes a substantial market gap, prompting clients who relied on this service to seek alternatives, thus accelerating market share transfer to other service providers [3][4]. - The AI search market is likened to the early days of cloud computing, where large companies focused on consumer-facing services, inadvertently creating opportunities for smaller firms like Xiaosu Technology [8][9]. Group 2: Xiaosu Technology's Strategy - Xiaosu Technology has achieved an annual recurring revenue (ARR) of $25 million within months, indicating strong market traction [2]. - The company emphasizes three core capabilities: global service capacity, alignment with AI agent needs, and comprehensive expansion capabilities, which differentiate it from competitors [9][10][14]. - Xiaosu's intelligent search service covers over half of the leading AI native applications in China, showcasing its market penetration [15][22]. Group 3: Competitive Landscape - The competitive landscape post-Bing's exit includes both overseas and domestic players, with many lacking the necessary language capabilities or comprehensive service offerings to meet market demands [14][16]. - Xiaosu's competitive edge lies in its talent pool, which includes experienced professionals from early search companies, and its robust distributed infrastructure that supports low-latency global services [14][20]. Group 4: Future Outlook - The article suggests that the competition for AI infrastructure is just beginning, with a shift from consumer traffic battles to B2B foundational service contests [22][23]. - As AI evolves, the demand for real-time data and model invocation will become more complex, indicating a growing need for sophisticated search services tailored for AI applications [22].

Core Viewpoint - The article discusses the significant impact of Bing Search API's shutdown on the AI search market, highlighting the emergence of new players like Xiaosu Technology that can fill the gap left by Bing's exit [2][3][4][19][32]. Group 1: Impact of Bing Search API Shutdown - Bing Search API will be completely shut down on August 11, making it difficult for developers to access quality search sources [2][3]. - The shutdown is seen as a strategic move by Microsoft to focus on AI search and integrate it with Azure services, potentially increasing pricing [4][19]. - The AI search market is projected to reach 347.2 billion yuan by 2029, with a growth rate exceeding 20% annually over the next five years [7]. Group 2: Current Market Landscape - The AI search market is characterized by a head effect, with major players focusing on consumer (ToC) services while neglecting business (ToB) opportunities [21][22]. - Traditional search giants like Google and Baidu have strong technical advantages but primarily cater to consumer needs, limiting their API offerings for businesses [22]. - New startups are emerging to provide specialized search services in vertical markets, such as legal and academic fields, to differentiate themselves from established players [23][24]. Group 3: Emergence of New Players - Xiaosu Technology has developed an AI search engine that offers competitive capabilities, achieving an annual recurring revenue (ARR) of $25 million within months [25][32]. - Xiaosu's AI search engine supports over 30 languages and provides features like semantic understanding and full-text display, making it suitable for various applications [29][38]. - The company emphasizes its ability to provide real-time data and multi-modal search capabilities, positioning itself as a strong alternative to Bing [36][38]. Group 4: Future Opportunities - The article suggests that the AI search market is ripe for new entrants, especially in the wake of Bing's exit, with Xiaosu Technology being a notable contender [32][44]. - The demand for AI search capabilities is expected to grow, particularly in the context of developing AI applications and agents [16][43]. - Xiaosu's focus on ToB services and competitive pricing (one-third of Bing's costs) positions it well to capture market share from businesses seeking reliable search solutions [32][45].

Group 1 - Baidu has launched a new AI search application called "Tizzy.AI," which is positioned as an "AI intelligent search product" with the slogan "Simple search, one touch to reach" [1] - The main features of Tizzy.AI include AI search, film, and short drama [1][19] - The application interface is designed to be very simple, featuring a search box, recommended search phrases, and a navigation bar [3] Group 2 - The search box supports both text and voice search, with two modes: automatic mode (smart recognition, quick answers) and deep mode (enhanced reasoning, in-depth thinking) [6] - The film section includes a scrolling recommendation bar and allows users to filter films based on genre, country, and time [8] - The short drama section features a hot drama chart and a recently added list, also allowing for genre filtering [15] Group 3 - Tizzy.AI is compared with similar products from ByteDance, Alibaba, and 360, highlighting its minimalist design and functionality [16][18] - All four applications, including Tizzy.AI, allow switching to a deep thinking mode for AI search, but Tizzy.AI and AI Douyin maintain a simpler functionality compared to others [18] - Tizzy.AI's unique features include a focus on film and short drama, while competitors offer additional functionalities like AI image generation and writing [19] Group 4 - Tizzy.AI's ad-free model aims to address user pain points associated with excessive advertising in traditional search engines [26] - The film and short drama features may attract users, but there are concerns regarding copyright compliance and competition from existing free short drama products [27] - Despite challenges, Baidu's historical expertise in AI and search positions it as a formidable competitor in the AI search market [27][28]

Investment Rating - The report maintains a "Buy" rating for Baidu Group [2][7] Core Views - Baidu's core advertising business is expected to face pressure due to AI search transformations, with a projected revenue decline of 16.3% year-on-year in Q2 2025 [7] - Baidu's Robotaxi service, "Luobo Kuaipao," is leading the global market, with a significant increase in order volume, up 75% year-on-year to 1.44 million in Q1 2025 [7] - The company's intelligent cloud business is experiencing rapid growth driven by the demand for generative AI and large language models, with Q1 2025 cloud service revenue expected to grow by 42% year-on-year [7] - The overall revenue forecast for 2025-2027 has been adjusted to reflect a decline of 5.2% in 2025, followed by growth of 4.4% and 4.8% in 2026 and 2027, respectively [7] - The target price for Baidu has been revised down to HKD 95.15 based on DCF valuation [7] Financial Projections - Revenue projections for Baidu are as follows: - 2024: 133,125 million CNY - 2025: 126,265 million CNY - 2026: 131,853 million CNY - 2027: 138,172 million CNY [2][12] - Net profit projections are: - 2024: 23,760 million CNY - 2025: 18,324 million CNY - 2026: 20,200 million CNY - 2027: 22,172 million CNY [2][12] - The P/E ratio is projected to be 10.9 in 2024, increasing to 14.1 in 2025, and then decreasing to 11.7 by 2027 [2][12] Business Segments - The core online marketing service revenue is expected to decline by 15.3% in 2025, while cloud service revenue is projected to grow by 22.2% [8] - The iQIYI segment is expected to see a slight revenue decline of 1.0% in 2025 [8] Valuation Metrics - The report provides a DCF valuation breakdown, indicating a total enterprise value of approximately 370.45 billion CNY, with equity value at 287.44 billion CNY [9][10]

Core Insights - Bing has achieved a significant milestone in the Chinese market, capturing a 40.23% market share in desktop search as of June 2025, marking its position as the leading search engine in China for 12 consecutive months [2][4] - Microsoft's investment of nearly $100 billion in Bing over the years has finally paid off, particularly benefiting from the digitalization and globalization trends among Chinese enterprises [3][6] - The rise of AI-driven search capabilities has transformed Bing from a mere alternative to a formidable competitor in the search engine landscape, with a notable increase in user engagement and interaction [12][15] Market Position and Growth - Bing's user base in China has surged by 12 times over the past five years, with China contributing 28.25% of Bing's global traffic, surpassing the United States [6][9] - Despite a temporary resurgence of Bing in the U.S. market in May 2025, the alternating leadership in both markets indicates a promising future for Bing in China [9][11] - The integration of Bing into Microsoft's ecosystem, particularly with the launch of Bing Chat Enterprise, has enhanced its presence in enterprise productivity scenarios [10][11] AI and Product Innovation - The introduction of the "New Bing" powered by AI models has redefined the search experience, allowing for more natural interactions and deeper understanding of user intent [15][16] - Bing's advertising model has evolved, with AI enabling more precise targeting and significantly reducing cost-per-click for advertisers, enhancing overall commercial viability [17][19] - The localized features and innovations, such as accurate weather forecasting and tailored marketing strategies, have further solidified Bing's appeal in the Chinese market [10][19] Competitive Landscape - The ongoing AI search battle is intensifying, with major players like Google and emerging startups vying for market share, indicating a long-term competitive environment [20][21] - Microsoft's strategy of integrating Bing into a broader ecosystem, including Windows 11 and Microsoft 365, enhances user engagement and retention [22] - Despite Bing's impressive growth, challenges remain, including reliance on desktop usage and the need to navigate local regulatory landscapes [23]