陈月芹/文 元宝第一次打破了微信的惯例，它学起了拼多多用红包激励用户不断"拉人入坑"的裂变玩法，背后有很多个不得已的理由。 一是这次大厂AI赛跑，腾讯已比其他家慢了一圈。 春节历来都是大厂培养用户新习惯的最佳时机，最早的微信红包、支付宝集福都充分验证了这一点。元宝必须抓住春节这个节点快速拉新。和MAU（月度 活跃用户数）突破2亿的豆包、近1.5亿的DeepSeek相比，元宝虽然短期下载量登顶，但其约4100万的月活仍有数倍差距。它必须在夹缝中撕开下沉市场的口 子，用现金红包吸引"羊毛党"或许是最简单粗暴的办法。 二是微信必须防守。 在流量红利几乎见顶的今天，传统App的获客成本极高且留存率低。巨头们迫切需要一个新的增长引擎，AI被视为能够重构所有App体验的唯一出路。 2月4日，微信终于对元宝红包链接进行封禁，引来"帮理不帮亲"的好评。3天前，腾讯豪掷10亿元现金，试图复刻2015年微信红包"偷袭珍珠港"追平支付宝 的奇迹。 不过这一次，不少用户惊觉，元宝"偷袭"的是微信这个极度克制的私域领地，并且用户没有"屏蔽"的选项。当元宝红包链接开始影响社交和工作效率时，这 种入侵式营销引发了用户的反弹，部分微信群群主 ...

Core Insights - The article discusses the transformation of AI search from traditional search engines to native AI search, highlighting the competitive landscape among various startups and the need for a new search architecture focused on AI [1][3][5]. Group 1: Historical Context - In the 1990s, various startups explored different methods of internet search, with Yahoo using a directory approach and Google later revolutionizing the field with its PageRank algorithm [1][2]. - The emergence of Google in 1998 marked a significant shift, as its algorithm quickly became the preferred method for navigating the internet, effectively solving the search problem for users [2]. Group 2: Current Landscape - The current search environment is undergoing a major shift, with numerous startups competing to create AI-native search systems that can index the web for AI applications [3][6]. - Traditional web search is primarily optimized for human users, often resulting in cluttered results filled with ads and redundant information, which can hinder the effectiveness of AI models [3][5]. Group 3: Emerging Trends - The article posits that deep research will become a dominant and monetizable form of agent-based search, as clients are willing to pay for high-quality research outputs [5][17]. - Many companies are opting to outsource their search capabilities to specialized service providers due to the high costs and complexities associated with maintaining search infrastructure [7][15]. Group 4: Technological Innovations - New search architectures are being developed to support AI agents, focusing on real-time data access and dynamic information retrieval, which enhances the capabilities of AI models [11][12]. - The introduction of Retrieval-Augmented Generation (RAG) and Test-Time Computation (TTC) allows models to access real-time information and improve their reasoning capabilities, transforming static models into dynamic reasoning systems [11][12]. Group 5: Use Cases - Deep research has emerged as a prominent use case for AI search APIs, enabling agents to conduct extensive research tasks that would take humans significantly longer to complete [17][19]. - AI search is also being utilized for CRM lead enrichment, automating the process of gathering and updating relevant information from various sources [19]. - Real-time access to technical documentation and code examples is crucial for coding agents, ensuring they reference the most current and relevant information [20]. Group 6: Competitive Dynamics - The competitive landscape is shifting towards API platforms, where user-facing products can leverage various search functionalities through single integrations [15][22]. - Companies are increasingly evaluating search providers based on the quality of results, API performance, and cost, leading to a diverse range of offerings in the market [22][23].

Core Viewpoint - The acquisition of Himalaya by Tencent Music signifies a deep restructuring of the internet traffic landscape and indicates a paradigm shift in internet investment logic [1][5]. Company Performance - Tencent Music's market capitalization briefly surpassed Baidu's, with Tencent Music closing at 232.8 billion HKD and Baidu at 235.96 billion HKD, reflecting a market gap of approximately 3 billion HKD [1]. - Tencent Music's market capitalization has increased by over 280% since its secondary listing, while Baidu's has decreased by over 60% [5]. - In Q1, Tencent Music's revenue was 7.36 billion RMB, with an 8.7% growth rate, while Baidu's revenue was 32.5 billion RMB, growing at only 3% [6][7]. Business Model Comparison - Tencent Music's core business is online music services, which saw a 15.9% revenue increase to 5.8 billion RMB in Q1, while Baidu's online marketing revenue decreased by 6% to 16 billion RMB [7]. - Tencent Music's revenue structure is shifting from reliance on live streaming to more stable subscription services, while Baidu's search advertising model is under pressure from emerging AI technologies [8][9]. Market Challenges - Tencent Music faces challenges from short video platforms like Douyin, which are reshaping music consumption and impacting user engagement [10]. - Baidu is transitioning towards AI, with its intelligent cloud business growing by 42% year-on-year, but these new ventures are still in the investment phase and contribute minimally to overall revenue [9][10]. International Expansion - Both companies are looking to international markets for growth, with Tencent Music investing in SM Entertainment for the Asian music market and Baidu expanding its autonomous driving services in the Middle East and Europe [10].