股 份 代 號 : 3317 深圳迅策科技股份有限公司 SHENZHEN XUNCE TECHNOLOGY CO., LTD. ( 於中華人民共和國註冊成立的股份有限公司 ) 獨家保薦人 整體協調人，聯席全球協調人，聯席䵷簿管理人，聯席牽頭經辦人 獨家財務顧問 重要提示 重要提示： 閣下如對本招股章程中任何內容有任何疑問，應徵詢專業獨立意見。 Shenzhen Xunce Technology Co., Ltd. 深圳迅策科技股份有限公司 （於中華人民共和國註冊成立的股份有限公司） 全球發售 全球發售的發售股份數目 ： 22,500,000股H股（視乎發售量調整權及 超額配股權行使與否而定） 香港發售股份數目 ： 2,250,000股H股（視乎發售量調整權行使 與否而定及可予重新分配） 國際發售股份數目 ： 20,250,000股H股（視乎發售量調整權行使與否而定、 可予重新分配及視乎超額配股權行使與否而定） 最高發售價 ： 每股H股55.00港元，另加1.0%經紀佣金、 0.0027%證監會交易徵費、 0.00565%香港聯交所交易費及 0.00015%會財局交易徵費 （須於申請時以港元繳足，多繳股款可予退 ...

New rumors of stalled data-center funding have sent Oracle's stock lower, but some experts argue the negative narrative has gotten too harsh. ...

此次融资动荡直接暴露了甲骨文AI基础设施战略日益紧张的资金链。该公司近几个月的大规模支出和 激进的债务融资行为已引发市场警觉，导致其股价较9月的高点下跌超过40%，过去一个月跌近15%， 债券亦遭到抛售。 周三，甲骨文(ORCL.US)盘前跌2%，报184.80美元。据报道，三位知情人士透露，blue owl此前一直在 与贷款方及甲骨文洽谈，计划投资位于密歇根州Saline Township的一个规划容量达1千兆瓦的数据中 心，该设施旨在服务于OpenAI。然而，随着谈判陷入停滞，Blue Owl原计划安排高达100亿美元融资并 进行大额股权投资的协议将无法推进。甲骨文随后回应称，密歇根数据中心相关股权交易仍按计划推 进。 ...

Core Viewpoint - Oracle Corp's plans for a $10 billion data center in Michigan are uncertain due to failed funding negotiations with Blue Owl Capital, which has been a key financial supporter for Oracle's major U.S. data center projects [3] Group 1 - The proposed data center in Michigan represents a significant investment of $10 billion by Oracle Corp [3] - Blue Owl Capital was the primary financial backer for Oracle's largest data center initiatives in the United States [3] - The breakdown in funding talks raises concerns about the future of Oracle's expansion plans in the data center sector [3]

Core Insights - Baidu's no-code application building platform "MiaoDa" has generated over 500,000 commercial applications within 8 months, with a daily growth rate of over 150%, and half of these applications include backend functionalities, covering over 200 scenarios including education, business, content creation, and enterprise services, creating economic and efficiency value exceeding 5 billion yuan [1] Group 1 - Baidu announced a long-term support plan for creators called the "Creator Dream Plan," aiming to assist 1 million creators in generating income over the next three years through traffic support, revenue sharing, business order matching, and technical support [3] - By 2026, Baidu plans to select 15 high-commercial potential projects from all quality projects to open a fast track for investment opportunities exceeding 1 million yuan for individual developer projects [3] Group 2 - The core goal of "MiaoDa" is to liberate application development from a few professional developers by enabling more people to directly build commercially viable applications through a natural language approach [5] - "MiaoDa" has a user base where 81% are non-programmers, primarily from the workforce and university groups, with applications serving over 10 million users and approximately 100,000 daily users solving real problems [5]

Core Insights - The event "Kunpeng Developer Day" in Beijing focused on the theme "Create the Future, Enjoy the Extraordinary," featuring a main forum, two sub-forums, and an interactive exhibition area to foster deep technical exchanges and industry practice sharing among developers from various sectors [1] Group 1: Event Overview - The event was organized by Huawei Technologies Co., Ltd. and hosted by the Beijing Kunpeng Joint Innovation Center, bringing together hundreds of developers from universities, enterprises, and research institutions [1] - Huawei's Vice President Ma Haixu expressed gratitude to developers for their support of the Kunpeng ecosystem, emphasizing their role in driving innovation and collaboration [1] Group 2: Technical Presentations - Peking University's Fan Chun discussed the integration of cloud computing and high-performance computing in AI applications, highlighting the development of the "Hesi Scheduling System" and the "SCOW Computing Platform," which supports over 80 computing centers [3] - Huawei's Li Sicong introduced the Kunpeng Unified Acceleration Library (KUPL), which enhances performance in high-performance applications by 2.7 to 4.6 times compared to traditional hardware, and reported that the openEuler operating system is expected to exceed 16 million installations by the end of 2025 [5] - Tsinghua University's Zong Zan shared advancements in large model inference acceleration on the Kunpeng architecture, achieving significant throughput improvements [7] Group 3: Industry Applications - North控数科's Cheng Xiaopei presented a cloud platform for state-owned enterprises built on Kunpeng technology, which has developed over 140 solutions across various sectors [9] - China Everbright Bank's Shen Jie highlighted the bank's use of Kunpeng's trusted cloud technology to enhance core business system performance, achieving a 36% increase in concurrency and a 27% reduction in latency [11] - Yuxin Technology's Song Tao discussed the end-to-end solutions based on Kunpeng technology, showcasing significant efficiency improvements in data processing for a banking project [13] Group 4: Educational and Collaborative Initiatives - China National Knowledge Infrastructure's Wang Liang shared the implementation of Kunpeng nodes in their research platform, resulting in reduced latency and energy costs [16] - The event featured the launch of the "Kunpeng Partner Co-Development Excellent Solutions" initiative, marking a new phase in collaborative development with over a thousand partners [18] - The Kunpeng Innovation Competition awarded prizes to outstanding teams, encouraging developers to continue exploring Kunpeng technology [20] Group 5: Developer Engagement - The event included technical forums and hands-on training sessions to empower developers with practical skills and knowledge about Kunpeng technology [23] - An interactive exhibition area provided developers with direct access to Kunpeng tools and resources, enhancing their experience and engagement [25] - The successful hosting of the Kunpeng Developer Day is expected to inject new momentum into the Kunpeng ecosystem in Beijing and North China, promoting the deep integration of computing technology into various industries [27]

Group 1 - The core adjustment to the WeChat Work customer contact interface will begin gray testing on December 18, 2025, impacting data access for thousands of service providers within its ecosystem [1] - The new model will require service providers to meet dynamic conditions to access customer data, moving away from the previous "one-time authorization, long-term use" approach [1] - If an application is in a trial period, it can only access customer data from the previous month and any new customers added during the trial [1] Group 2 - A new "Marketing Customer Acquisition" application category has been launched, focusing on front-end lead generation with lightweight interfaces like "Contact Me QR Code" and "Join Group Chat QR Code" [2] - The adjustments are primarily aimed at enhancing user privacy protection in response to the implementation of the Personal Information Protection Law, which has been in effect for over three years [3] - Service providers must shift from a "sales-driven" approach to a "value-driven" model, ensuring their products integrate into daily operations and are frequently used by employees [3] Group 3 - Over 20,000 third-party applications currently access the WeChat Work customer contact interface, with many relying on bulk customer exports and offline analysis [3] - The new regulations will particularly affect tools that depend on full customer data exports, as they may face limitations in functionality due to the new access conditions [3] - Companies will need to actively manage the usage of their internal applications to ensure continuous access to customer data, as inactivity may lead to restrictions on data retrieval [4]

Core Insights - AI is becoming a core engine for innovation and growth in enterprises, prompting discussions on how to leverage AI for new business opportunities and efficient user acquisition, retention, and conversion [1][2]. Group 1: Model Utilization - The current top AI models, such as GPT-4 and Gemini 3, are likened to "PhD-level" intelligence, but the engineering environment and prompts provided are still at a "elementary school" level, leading to a mismatch in capabilities [3]. - Selecting the right foundational model based on specific scenarios is crucial, as GUI operations differ significantly from text or voice tasks, with the "Qianwen 3" model showing promising results in GUI reasoning [3][4]. - The design of AI Agent architecture must account for uncertainty and allow for controlled interactions with systems, incorporating mechanisms like a "referee" role to guide operations [4]. Group 2: Context Engineering - Context engineering, or prompt engineering, is essential for maximizing AI capabilities, as it allows for the injection of necessary information and expert knowledge into the model [4][5]. - The importance of context is highlighted by the need for a complete understanding of tasks, as models cannot be expected to provide final answers without sufficient context [5][6]. Group 3: Data Governance - Data governance is a critical precondition for AI model engineering, requiring the transformation of enterprise knowledge into a format that models can understand [9][10]. - Effective data governance involves both knowledge data, which includes expert experience and structured analysis, and production data, which encompasses API call records and system logs [11]. - The governance process must ensure that data is accurate, timely, and secure, particularly in multi-agent environments to prevent data leakage [11][14]. Group 4: Efficiency and Employee Experience - The perception of efficiency gains from AI varies, with some employees feeling overwhelmed by the need to write prompts and verify AI outputs, especially when accuracy is low [15][16]. - Achieving high accuracy rates (e.g., from 40% to 90-95%) significantly boosts employee confidence in AI tools, leading to noticeable efficiency improvements [15][16]. Group 5: AI in Business Context - AI technology is capable of automating approximately 11.7% of labor tasks in the U.S. economy, with a significant portion of these tasks found outside the tech industry, such as in finance and logistics [18][19]. - The key to successful AI integration is not the technology itself but the ability of individuals to effectively utilize AI tools [19]. Group 6: Hiring and Skills Development - The hiring criteria for technical roles are evolving, with an emphasis on candidates' ability to understand and leverage AI technologies, including skills in probability thinking and effect evaluation [20][21]. - Project managers and testing engineers now require a blend of business understanding and technical knowledge to effectively manage AI projects and ensure quality assurance [21][22]. Group 7: Future Considerations - Companies are advised to carefully select AI application scenarios based on business value, data readiness, and acceptable error margins, avoiding both overly ambitious and trivial projects [24][25]. - Continuous iteration and small-scale pilot testing are recommended to identify effective AI applications, with a focus on integrating AI capabilities into existing business processes [26].

Group 1 - The core point of the article is that 彩讯股份 plans to invest 5 million yuan in a venture capital fund focused on humanoid robotics, aiming to leverage professional investment resources to enhance its competitive and profit capabilities [1] - The total capital commitment from all partners in the fund amounts to 46.6 million yuan, with 彩讯股份 holding a 10.73% stake [1] - The investment is sourced from the company's own funds and is not expected to adversely affect its financial or operational status [1] Group 2 - 彩讯股份 is a provider of digital technology and services, focusing on enterprise digital transformation with products in collaborative office, smart channels, intelligent computing services, and data intelligence [2] - The company has developed various AI-based products, including Rich Mail smart email, AI office assistant, and a one-stop AI application development platform, to assist clients in sectors like telecommunications, energy, finance, and government [2] - In the field of embodied intelligence, 彩讯股份 is involved in developing applications for robotic dogs, enhancing their interactive design and control for home environments [2]

Core Viewpoint - Quorum Information Technologies Inc. will be delisted from the TSX Venture Exchange effective December 18, 2025, following its acquisition by 2745122 Alberta Inc. for $0.80 per common share [1][2]. Company Overview - Quorum is a North American SaaS Software and Services company that provides essential enterprise solutions for automotive dealerships and Original Equipment Manufacturers [5]. Delisting Details - The delisting is a result of a statutory plan of arrangement that closed on December 10, 2025, where all outstanding common shares were acquired for cash consideration [2]. - The company will apply to cease being a reporting issuer in all applicable Canadian jurisdictions once legally permitted [3]. Shareholder Instructions - Registered shareholders who have not surrendered their share certificates or DRS advices should follow the instructions in the Letter of Transmittal to receive their entitled consideration [4].