以下文章来源于明亮公司 ，作者主编24小时在线 明亮公司 . 追踪新商业、好公司，提供一手情报与领先认知。 作者： 苏打 出品：明亮公司 阿里正在用千问"补课"。 「明亮公司」获悉，1月14日，阿里宣布千问月活已破1亿。次日，千问宣布全面接入阿里生态，由淘宝、支付宝、淘宝闪购、飞猪、高德、优酷、大 麦、菜鸟、阿里健康、1688、盒马"组团"为其服务。 在大厂之间这场AI军备竞赛中，与豆包、元宝相比，千问可谓姗姗来迟。早在2023年4月，阿里云便已正式发布大语言模型"通义千问"，但直到2025年 11月千问才正式面市，迄今仅两个月。 公开资料显示，千问App运营商为上海智信普惠科技有限公司，经过股权穿透，背后正是阿里巴巴资管平台。千问将已成为阿里巴巴AI能力在C端市场 的超级入口。 不仅如此，阿里CEO吴泳铭在此前业绩电话会上谈及千问项目的启动时表示，"意味着阿里巴巴在AItoB与AItoC两个方向齐发力。" 将生态"折叠"成一个千问入口重新进入用户视野，固然是AI时代的一个合理选项。但相比"超级入口"，年幼的千问迅速被推到C位，本质上折射出的是 阿里对高价值数据的渴求——尽管拥有庞大的业务生态，但在数据维度、 ...

Core Insights - Alibaba is leveraging its AI application "Qianwen" to enhance its data capabilities and user engagement, with monthly active users (MAU) surpassing 100 million shortly after its launch [1][19] - The integration of Qianwen into Alibaba's ecosystem aims to address the company's data collection challenges and improve its competitive positioning against rivals like Tencent and ByteDance [2][21] Group 1: Qianwen's Launch and Integration - Qianwen has been fully integrated into Alibaba's ecosystem, connecting with various services such as Taobao, Alipay, and others to enhance user interaction [1] - The launch of Qianwen marks Alibaba's strategic shift towards both AI-to-B and AI-to-C applications, indicating a dual focus on business and consumer data [2] Group 2: Data Ecosystem Challenges - Despite having a vast ecosystem, Alibaba faces challenges in data flow and integration, leading to a fragmented data landscape that limits its ability to create comprehensive user profiles [10][12] - The company is experiencing a "data anxiety," as its internal data collaboration is insufficient compared to the external data ecosystems of competitors like WeChat and Douyin [15][17] Group 3: User Engagement Metrics - Taobao's MAU is approximately 980 million, with a daily active user (DAU) count of about 508 million, significantly boosted by the introduction of flash sales [4][5] - The average monthly app usage frequency for Taobao has increased to 30-32 times, the highest in five years, indicating improved user engagement [5] Group 4: Investment and Market Position - Alibaba plans to increase its investment in flash sales to capture a larger share of the instant retail market, despite mixed market reactions to its spending strategy [8][9] - The company's free cash flow (FCF) has dropped to $371 million, the lowest since 2016, while its market valuation remains high, suggesting investor concerns about its growth strategy [22][24] Group 5: Future Outlook and Competitive Landscape - The competitive landscape for C-end interactive AI applications remains uncertain, with questions about market capacity for multiple leading players [20] - Alibaba's ability to facilitate effective data flow and integration will be crucial for its long-term success in the AI space, as it seeks to address its data shortfalls [21]

Core Points - The 2025 Global Digital Economy Conference will be held in Beijing from July 2 to 5, 2025, focusing on "Building Digital Friendly Cities" [1] - The conference will feature a framework of "1+6+N" activities, including an opening ceremony, main forum, thematic forums, and a results release event [1] - The Data Value Forum, a key event of the conference, aims to explore new dynamics, ecosystems, and paradigms of data value in the digital economy [1][2] Group 1 - The forum was hosted by the President of the Data Pricing Professional Committee of the China Price Association, with over 300 representatives from various sectors attending [2][3] - The event included leadership speeches, thematic presentations, roundtable discussions, and project releases, focusing on the core topic of data value [2] - The roundtable discussion emphasized the importance of data talent in activating data potential and promoting efficient data value transformation [2] Group 2 - Several significant projects were launched during the forum, including the "Data Price Certification and Evaluation Technical Guidelines" and the "National Integrated Data Price Information Service Platform" [2] - The "China Energy and Chemical Spot Valuation Index (CECSAI)" was also launched, aimed at promoting sustainable high-quality development of bulk commodities in China [2] - The establishment of the "Data Value Industry-Academia-Research Community" aims to gather quality resources and form a collaborative ecosystem to enhance data value [3]

Core Insights - The software industry reached its valuation peak in 2021, marking a significant year for capital investment, with companies that secured funding during this period facing different challenges compared to those that did not [2][5][6] - PingCAP, a successful enterprise-level open-source distributed database provider, capitalized on the favorable market conditions in 2021 to expand its global presence, serving clients in over 20 countries [2][8] - The advent of AI has dramatically increased the value of data, prompting discussions on how software companies can adapt and innovate in the AI era [2][10] Investment Landscape - The investment climate for software companies has shifted dramatically since 2021, with a clear divide between those that secured funding during the peak and those that did not, leading to varying degrees of operational challenges [5][6][7] - The capital market experienced a significant slowdown post-2021, making it increasingly difficult for software companies to secure financing, with a notable decline in the number of funded companies and total investment amounts [10][11][12] AI Impact on Software - The rise of AI has shifted market focus, with significant resources and attention now directed towards AI projects, often at the expense of traditional software companies [11][12] - The integration of AI into software is expected to transform product forms and user interactions, with a strong emphasis on making software more accessible and user-friendly [15][25][40] - The future of enterprise software is anticipated to be heavily influenced by AI, with a focus on enhancing user experience through conversational interfaces and reducing the learning curve for users [19][25][40] Data Utilization and Infrastructure - The value of data has increased, leading companies to prioritize data storage and utilization, as AI capabilities allow for better extraction and analysis of data [30][31][46] - The design of data infrastructure is evolving to accommodate AI agents as primary users, necessitating a shift in how databases and data access are structured [32][34][38] - SQL remains a critical tool for bridging the gap between AI and data, emphasizing the need for accessible and flexible data access methods [33][38] Future Outlook - The software industry is expected to see a continued emphasis on specialized knowledge and engineering complexity, which will remain essential even as AI simplifies user interactions [40][41][46] - Companies are likely to face increasing competition for unique data, reinforcing the importance of proprietary data as a competitive advantage in the AI landscape [43][46]