相关事件 快手-W(01024.HK)9月22日耗资7380万港元回购100万股 快手-W(01024.HK)：利润率新高 可灵持续超预 期 特别派息20亿港币 高盛发表研究报告指，快手昨日发布可灵AI 2.5 Turbo新模型，该模型在文本回应、动画效果、风格一 致性及美学质量等多个维度的能力都显著提升，并进一步增强影片生成的可控性、稳定性与一致性。高 盛预期，可灵新模型能以更具竞争力的成本提供顶级性能的AI影片生成方案，认为目前AI影片生成行 业仍处于早期阶段，市场规模正快速增长，并可能颠覆传统广告及短剧制作模式，而关键正正在于持续 升级的模型能力与用户渗透率。 高盛预期可灵AI的新模型将推动快手用户参与度持续提升，现时维持快手2025财年AI相关收入达到1.54 亿美元的预测(相对公司指引为1.25亿美元)，并重申"买入"评级，基于2026年底每股盈利预测的约14 倍，给予目标价83港元。 ...

Core Insights - Kuaishou has introduced OneSearch, an end-to-end generative framework for e-commerce search, addressing challenges in traditional search architectures [1][2][4] Group 1: Innovation and Technology - OneSearch integrates three innovations: Keyword Enhanced Hierarchical Quantization Encoding (KHQE), Multi-Perspective User Behavior Sequence Injection Strategy, and Preference-Aware Reward System (PARS) [2] - KHQE uses RQ-OPQ encoding to model product features, creating a "smart identity" for each product, enhancing retrieval accuracy [2] - The Multi-Perspective User Behavior Sequence Injection Strategy captures both recent preferences and long-term interests, improving user intent understanding [2] - PARS combines multi-stage supervised fine-tuning with adaptive reinforcement learning to capture fine-grained user preference signals, enhancing ranking performance while ensuring diversity [2] Group 2: Performance Metrics - OneSearch has shown significant improvements in various metrics compared to traditional systems, with a 3.22% increase in order volume and a 2.4% growth in the number of buyers [4] - In offline experiments, OneSearch outperformed existing systems in terms of Click-Through Rate (CTR) and Conversion Rate (CVR), with notable improvements in user satisfaction and item quality [5][6] - The system achieved an 8-fold increase in machine computation efficiency and a 75.40% reduction in online inference costs, optimizing resource utilization [5] Group 3: Market Impact and Future Directions - OneSearch's deployment marks a significant breakthrough in replacing traditional search links with generative models in large-scale industrial scenarios [4][6] - The system excels in cold start scenarios, effectively addressing challenges related to long-tail users and newly listed products [6] - Kuaishou plans to explore online real-time encoding solutions and enhance reinforcement learning mechanisms to better match user preferences, aiming for a more intelligent and precise e-commerce search experience [6]

Group 1 - The National Internet Information Office has conducted interviews with platforms including Toutiao and UC Browser due to the presence of inappropriate content in their trending search lists [1] - UC Browser has expressed its commitment to addressing the issues raised by the regulatory body and has established a special task force to enhance the management of its trending search list [1] - UC Browser aims to improve the compliance and responsibility of its trending search list management, ensuring a clearer online environment [1] Group 2 - Previous platforms such as Xiaohongshu, Weibo, and Kuaishou have also responded to regulatory notifications, indicating their commitment to rectify the identified issues [2] - Weibo plans to continuously optimize its trending search algorithm to reinforce the public nature and correct value orientation of its trending list [2] - Kuaishou and Xiaohongshu have stated their intentions to further improve their trending search list management mechanisms and strengthen their content management responsibilities [2]

Core Insights - The article discusses the introduction of OneSearch by Kuaishou, an innovative end-to-end generative framework for e-commerce search, aimed at addressing the limitations of traditional cascading search architectures [1][2]. Group 1: Challenges in Traditional E-commerce Search - Traditional e-commerce platforms utilize a "recall, rough ranking, fine ranking" cascading search structure, which, while stable, faces issues such as chaotic product descriptions, relevance problems, bottlenecks in the cascading structure, and cold start challenges [1]. Group 2: OneSearch Framework Innovations - OneSearch integrates three major innovations: - Keyword Hierarchical Quantization Encoding (KHQE) module, which models product features in both vertical and horizontal dimensions, creating a rich semantic "smart ID" for each product, enhancing retrieval accuracy [2]. - Multi-perspective User Behavior Sequence Injection Strategy, which captures both recent preferences and long-term interests, allowing for a deeper understanding of user intent and improving personalized search accuracy [2]. - Preference-Aware Reward System (PARS), which combines multi-stage supervised fine-tuning with adaptive reward reinforcement learning to capture fine-grained user preference signals, enhancing ranking performance while ensuring diversity in generated results [2]. Group 3: Performance Metrics and Results - Offline experiments indicate that OneSearch significantly outperforms existing cascading systems across various metrics. Online deployment results show a 3.22% increase in order volume and a 2.4% growth in the number of buyers, marking a significant achievement in large-scale industrial applications [4]. - In a comparative analysis, OneSearch demonstrated improvements in metrics such as Click-Through Rate (CTR) and Conversion Rate (CVR), with notable enhancements in overall page satisfaction and product quality compared to traditional systems [5]. - OneSearch also excelled in cold start scenarios, effectively addressing the ranking challenges for long-tail users and newly listed products, indicating its robustness in diverse conditions [6]. Group 4: Future Directions - Kuaishou plans to continue exploring online real-time encoding solutions to bridge the gap between predefined encoding and streaming training, while also integrating more powerful reinforcement learning mechanisms to better match user preferences [6]. - The ongoing technological advancements are expected to lead to a more intelligent, precise, and user-centric e-commerce search experience, fulfilling the ideal of "one-step" search for users [6].

Core Viewpoint - The regulatory scrutiny on Kuaishou's e-commerce operations highlights significant issues within the live-streaming e-commerce sector, particularly concerning false marketing and counterfeit products, which have been exacerbated by the platform's user demographics and content practices [2][3][4]. Group 1: Regulatory Investigation - Kuaishou's subsidiary, Chengdu KuaiGou Technology Co., is under investigation for alleged violations of the E-commerce Law of the People's Republic of China [2]. - The company's core executives, including the legal representative and general manager, are closely tied to Kuaishou Group, indicating a direct link between the management and the ongoing issues [3]. Group 2: Industry Criticism - The live-streaming e-commerce sector faces severe criticism for rampant false marketing and counterfeit goods, with Kuaishou being particularly highlighted due to its user base's limited ability to discern product information [3][4]. - The prevalence of unbranded products on Kuaishou's sales rankings has led to increased consumer complaints, further damaging the platform's reputation [3]. Group 3: Content Ecosystem Challenges - Kuaishou's content ecosystem is deteriorating, with issues such as sexual content and copyright infringement becoming more prevalent, undermining the platform's foundation [15][16]. - The platform's algorithm amplifies low-quality content, as it prioritizes user engagement over content quality, leading to a cycle of producing more sensational and less credible material [16]. Group 4: Growth Anxiety and Strategic Dilemmas - Kuaishou is experiencing growth anxiety, struggling to balance user engagement, content safety, and business expansion amid increasing competition from rivals like Douyin and Xiaohongshu [20][21]. - Despite reporting a revenue increase of 13.1% to 35 billion yuan in Q2 2025, the live-streaming segment shows signs of stagnation, with its contribution to overall revenue declining from 30.1% to 28.7% [18][19]. - The platform faces a dilemma between maintaining short-term revenue through controversial content and ensuring long-term sustainability by improving content quality [22][23].

据了解，笑古为快手科技核心管理成员，2019年加入快手。自2021年起先后担任电商事业部负责人、本 地生活事业部负责人，并参与快手商业生态委员会及经营管理委员会。 责任编辑：李昂 近日，网传消息称，快手高级副总裁、本地生活业务负责人笑古即将离职。此前，据多家媒体报道，快 手本地生活业务已进行架构调整，从独立事业部合并至商业化体系之下，由刘逍负责。 新浪科技就此询问快手，对方暂无回应。 ...

Group 1 - The company Kuaishou-W (01024) announced a share buyback plan, spending HKD 73.7998 million to repurchase 1 million shares at a price range of HKD 73.45 to 74.3 per share [1] - On the same day, the company issued 27,500 shares through the exercise of options under the post-IPO share option plan adopted on January 18, 2021 [1]

Group 1 - Kuaishou-W (01024) announced a share buyback of 1 million shares at a total cost of HKD 73.7998 million, with a per-share buyback price ranging from HKD 73.45 to HKD 74.3 [1] - On the same day, the company issued 27,500 shares through the exercise of options under the post-IPO share option plan adopted on January 18, 2021 [1]

Core Viewpoint - Kuaishou-W (01024.HK) announced a share buyback of 1 million shares at a cost of HKD 73.8 million on September 22 [1] Group 1 - The company executed a buyback program, indicating confidence in its stock value [1] - The total expenditure for the buyback was HKD 73.8 million, reflecting a strategic move to enhance shareholder value [1] - The number of shares repurchased was 1 million, which may impact the company's share structure and market perception [1]

FF305 翌日披露報表 (股份發行人 ── 已發行股份或庫存股份變動、股份購回及/或在場内出售庫存股份) 表格類別： 股票 狀態： 新提交 公司名稱： 快手科技（於開曼群島註冊成立以不同投票權控制的有限公司） 呈交日期： 2025年9月22日 如上市發行人的已發行股份或庫存股份出現變動而須根據《香港聯合交易所有限公司（「香港聯交所」）證券上市規則》(「《主板上市規則》」)第13.25A條 / 《香港聯合交易所有限公司GEM證券 上市規則》(「《GEM上市規則》」)第17.27A條作出披露，必須填妥第一章節 。 | 第一章節 | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1. 股份分類 | 不同投票權架構公司普通股 | | 股份類別 B | | | 於香港聯交所上市 | 是 | | | | 證券代號 (如上市) | 01024 | | 說明 | | | | | | | | 多櫃檯證券代號 | 81024 | RMB | 說明 | | | | | | | | A. 已發行股份或庫存股份變動 ...