N * 41 R 41 (86) 14:29 Q @ @ 0 Q . ... + O artlist.io/text-to-1 13 Artlist B Q 搜索 智 III 都 | ギ Sora 2来了! × 为视频创作者打造的 Al 文本转视频 生成器视觉效果 风 图像 ■ 视频 Describe the video vou ... Generate 致谢 我的作品 样式目录 AI让逝者"复活"正引发伦理地震。当Sora 2生成的李小龙主持DJ秀、迈克尔·杰克逊表演脱口秀的视频席 卷网络，深度合成技术对已故名人肖像的擅自使用，已触及多重法律红线。这场技术狂欢背后，肖像权 侵权、人格尊严受损、生物数据非法收集等风险正浮出水面。 一、人格权侵权风险：肖像与尊严的双重危机 肖像权侵权已成定局 根据现行法律框架，死者肖像权仍受法律保护，其配偶、子女等近亲属享有维权权利。Sora 2以已故名 人真实肖像为基础，通过深度合成技术生成视频并公开传播，即便添加动态水印，仍构成对肖像权的商 业化使用。典型案例包括杰克逊表演单口喜剧、李小龙主持DJ演出等内容，这些行为均未获得继承人 授权，已完全符合肖像权侵权要件。 人格尊严 ...

首个横幅广告问世至今已经 31 年了，广告技术早已成为全球商业的重要组成部分。在美国，广告技术行业直接创造了 154 万个就业岗位，营收达 9740 亿 美元，还为美国整体数字经济发展注入强劲动力，推动其规模接近 5 万亿美元，这一数字占美国国内生产总值（GDP）的18%。 那么，行业高管必须具备哪些品质，才能确保广告公司持续发展呢？ 据统计，目前有近 1 万家企业在广告技术领域开展业务，每年新增相关企业超 400 家。这些企业涵盖了数十个专业领域，具体包括供应预测、隐私保障和 跨平台整合等，其所构成的广告服务体系已成为营销和媒体行业的核心环节。广告技术行业走过了数十年的发展历程，其间历经市场动荡、探索试错、企 业整合与技术迭代。而 AI 作为迄今为止最具颠覆性的变革力量，正在深度重塑整个行业：就连世界 500 强企业，也会与成立仅 18 个月的新兴公司展开 合作。 为了揭示新一代广告技术高管必须具备的核心特质，广告技术领域资深从业者Ann Blinkhorn、美国互动广告局（IAB）CEO Randall Rothenberg访谈了多 位广告技术领域的领军人物，包括IAS首席执行官Lisa Utzschne ...

数字经济时代，数据成为继土地、劳动力、资本、技术之后的第五大生产要素，如何将数据资源转 化为资产，进而实现资本化，已成为企业、金融机构乃至国家战略关注的核心议题。在2025人民数据大 会"数据场景与价值释放新路径"平行论坛上，北京泽仪律师事务所主任周天喜提出了关于数据资产化路 径的思考。 "数据的确权问题复杂而关键。"周天喜提出，按照"数据二十条"提出的"三权分置"制度设计来看， 数据资源持有权、数据加工使用权和数据产品经营权的描述有待进一步清晰，目前已有判例可以参照， 比如"数据产品经营权"是依法保护数据处理者的劳动成果和收益权，为数据产品商业化提供了法律保 障。 周天喜认为，数据资产路径是从合规出发，经确权、入表，最终走向证券化的系统性工程。未来值 得关注的方向，一是区块链、物联网等技术为数据资产提供更可靠的验证和管理支持，二是对资产流动 性和透明度的需求将持续引导数据资产创新应用。 周天喜认为，数据合规是数据资产化的前提，企业必须确保数据来源合法、授权清晰，严格遵守数 据收集、存储、使用和共享的法律要求。合规不仅是法定义务，更是提升数据可信度和市场认可度的关 键。 ...

Core Viewpoint - The first Qinghai Data Element Ecological Conference aims to promote the new development pattern of data elements in Qinghai, injecting new momentum into the high-quality development of the digital economy in the western region [2] Group 1: Data Assetization - The data element market in China is transitioning from "resource" to "asset," with the implementation of the "Interim Provisions on Accounting Treatment of Enterprise Data Resources" on January 1, 2024, marking the operational phase of data assetization [3] - China is the first country globally to classify data as a production factor, representing significant theoretical and institutional innovation [3] - The legal framework for data governance in China is built around three core laws: the Cybersecurity Law, the Data Security Law, and the Personal Information Protection Law, supported by policies like the "Data Twenty Articles" and the aforementioned accounting provisions [3][4] Group 2: Legal and Compliance Framework - The first step in data assetization is to clarify "who has the right to use and how to use" the data, emphasizing the need for data property legislation [4] - The "Data Twenty Articles" introduces a three-rights separation system: holding rights, processing and usage rights, and product operation rights [4] - Compliance is seen as a prerequisite for data assetization, with the three fundamental laws in the compliance field being crucial [5] Group 3: Risk Management and Future Outlook - Common compliance issues include illegal acquisition, usage, disclosure, processing, trading, and data leakage, with specific risks identified in data sourcing, processing, and product development [5][6] - A four-part support system is proposed for data assetization: legal framework, compliance system, rights confirmation mechanism, and trading platform [6] - The data element market is expected to reach a scale of approximately 500 billion yuan by 2026, driven by policies promoting public data authorized operations and financial innovations like data asset securitization and data trusts [6]

Group 1: Industry Overview - The 2025 IAA in Germany showcased 748 exhibitors, with 116 from China, representing nearly one-third of overseas participants, surpassing local German companies [1] - Chinese automotive exports reached 3.083 million units in the first half of 2025, with a 75.2% increase in new energy vehicle exports [2] - BYD's sales in Europe exceeded 130,000 units in 2025, marking a 210% year-on-year growth [2] Group 2: Challenges and Strategies - Chinese automakers face significant entry costs, operational costs, and geopolitical challenges when entering the European market [4] - To address these challenges, companies like BYD plan to localize production in Europe, with a factory in Hungary expected to start production this year and another in Turkey by 2026 [4][5] - Other companies, such as Leap Motor and Xpeng, are also pursuing local production and establishing R&D centers in Europe [5] Group 3: Technological Advancements - Chinese companies are leading in technology development, with Momenta showcasing AI-driven Robotaxi technology at the IAA [3] - Partnerships with international giants like Bosch and Qualcomm are being formed to enhance technological integration within the German automotive ecosystem [6] Group 4: Data Compliance and Regulations - The EU's stringent data protection regulations, including GDPR and the upcoming AI Act, pose compliance challenges for Chinese companies [7][8] - Companies are advised to integrate data compliance into their strategic planning to navigate complex international regulations effectively [9] Group 5: Service Network Development - Establishing a robust service network is crucial for building consumer trust in Europe, as local service capabilities impact brand sustainability [10] - Leap Motor has established around 1,700 sales and service points globally, emphasizing the importance of local service networks for market penetration [10]

（来源：唐僧财经） 在移动支付几乎渗透生活各个角落的当下，"碰一下"、刷脸等支付方式已从大型商场延伸至街头巷尾。 在支付体验愈加"无感"的同时，用户信息的流向和数据使用也日益成为公众和监管关注的焦点。"碰一 下"后，我们手机里的隐私是否也会被碰走呢？ 来源：市场资讯 作为"碰一下"支付背后的设备商——上海商米科技集团股份有限公司（下称"商米科技"）近期在冲刺港 股IPO的过程中，再次被监管部门聚焦于信息保护和数据安全问题。 这家曾在科创板IPO折戟的企业，早在2021年上交所第二轮问询阶段，便遭遇包括"数据合规"在内的多 项问题的监管问询。 如今重整旗鼓转战港股，监管层对其用户信息收集、储存，以及数据使用的追问仍未放松。 曾被上交所问询数据合规问题 近日，中国证监会公示了境外发行上市备案补充材料要求，国际司对12家企业出具补充材料要求。其 中，商米科技被要求进一步补充说明多个关键事项，其中涉及其信息安全情况。 在此方面，商米科技需补充披露：其开发、运营的网站、APP、小程序等产品情况，收集及储存的用户 信息规模，数据收集使用情况，是否涉及向第三方提供个人用户信息，以及上市前后个人信息保护和数 据安全的安排或措 ...

Core Viewpoint - The article highlights the data security breach incident involving Dior (Shanghai) and emphasizes the broader issue of data protection challenges faced by luxury brands in the context of increasing digitalization [1][2][5]. Group 1: Incident Details - Dior (Shanghai) was found to have committed three violations regarding personal information protection, including unauthorized data transmission to its French headquarters and failure to inform users adequately about data handling [2][3]. - The data breach was discovered on May 7, 2025, and involved unauthorized access to customer data, including names, phone numbers, and email addresses, but did not include sensitive financial information [3][4]. Group 2: Industry Context - The luxury goods sector has seen multiple data breaches this year, with brands like Cartier and Louis Vuitton also experiencing similar incidents, indicating a systemic issue within the industry [5][6]. - Experts suggest that the luxury brands' reliance on high-end image and customer service has led to insufficient investment in data governance, treating compliance as a secondary function rather than a strategic risk management area [3][5]. Group 3: Compliance and Management Recommendations - To address the frequent data breaches, luxury brands should enhance their compliance management, technical safeguards, and internal controls, ensuring clear communication with consumers regarding data handling practices [6][7]. - Establishing a robust data protection mechanism involves building a compliance framework, managing data throughout its lifecycle, and developing emergency response capabilities to handle data breaches effectively [7][8].

Core Viewpoint - The ownership of patient medical records is a contentious issue, with hospitals, doctors, and patients each claiming rights over the data generated during medical treatment [1][2]. Group 1: Data Ownership and Privacy - Data is recognized as a new production factor, but its ownership remains disputed, particularly regarding patient medical records [1]. - Patients consider their medical records as personal privacy, while doctors argue that their expertise is necessary for data generation, and hospitals claim that without their equipment, data cannot exist [1]. - Ordinary outpatient medical records are typically owned or managed by patients, while inpatient records are managed or owned by hospitals [1]. Group 2: Challenges in Data Utilization - The complexity of data ownership leads to difficulties in data circulation and utilization, with concerns about data leakage and privacy infringement [2]. - The concept of "privacy computing" is proposed as a potential solution, allowing data value extraction without accessing original data, thus addressing ownership ambiguities [2]. - Privacy computing enables collaborative data use without transferring data outside its original domain, mitigating security and privacy risks [2]. Group 3: Technical Aspects of Privacy Computing - Privacy computing faces performance limitations, particularly in distributed models that rely on complex algorithms and frequent data transmission [3]. - New centralized privacy computing models have emerged to alleviate performance issues by encrypting data within a trusted execution environment [3]. - A hybrid approach combining centralized and distributed privacy computing is recommended based on specific needs, balancing data security and performance [3].

Core Viewpoint - Data has become a "gold mine" and a hotspot for investment in the smart connected vehicle sector, with recent government signals promoting and regulating cross-border data flow, which is expected to benefit the import and export of smart vehicles [3][5]. Group 1: Data Generation and Importance - Smart connected vehicles generate massive amounts of data daily, reaching terabytes (TB), including various types of information such as facial expressions, actions, voice data, and vehicle location [4]. - The increasing import of smart vehicles like Tesla and the growing export of Chinese smart vehicles highlight the need for effective cross-border data flow management [5]. Group 2: Regulatory Framework - China has established a policy framework for cross-border data flow, including the implementation of the Data Security Law and the Personal Information Protection Law, which provide a legal basis for data management in the smart vehicle sector [5][6]. - The upcoming regulations, such as the "Automotive Data Export Safety Guidelines (2025 Edition)" and the "Regulations on Promoting and Regulating Cross-Border Data Flow," indicate a move towards more specialized and detailed data governance [6][12]. Group 3: Global Data Governance Challenges - Different countries have varying data governance models, with the EU's GDPR imposing strict data localization requirements, presenting challenges for Chinese smart vehicle companies operating in the EU market [7]. - The need for compliance with international regulations is pushing foreign brands in China to adapt their data management strategies, as seen with Tesla's establishment of a local data center [9]. Group 4: Technological Innovations and Compliance - Technological innovations such as privacy computing and federated learning are becoming key drivers for improving compliance efficiency in cross-border data flow [10]. - Emerging technologies like dynamic de-identification and intelligent encryption are expected to become standard practices for ensuring data security during cross-border transmission [11]. Group 5: Industry Self-Regulation and Future Outlook - Industry self-regulation is crucial for enhancing compliance levels in cross-border data flow, with proposed management systems focusing on pre-assessment, real-time monitoring, and post-audit processes [11]. - The promotion and regulation of cross-border data flow are seen as guiding principles for healthy industry development, encouraging companies to integrate compliance capabilities into their export strategies [12].

Core Viewpoint - The article emphasizes the critical importance of corporate compliance, highlighting 20 typical cases released by the Supreme People's Procuratorate, which include issues such as fraudulent VAT invoicing, data compliance, collusion in bidding, and financial fraud [1]. Summary by Relevant Sections Typical Cases - Case 1: Environmental pollution by Zhangjiagang L Company and Zhang [3] - Case 2: Fraudulent VAT invoicing by Shanghai A Company and B Company [3] - Case 4: Collusion in bidding among construction companies in Xintai [3] - Case 5: Trademark infringement by Shanghai J Company [3] - Case 6: Sale of counterfeit goods by Zhangjiagang S Company [3] - Case 7: Collusion in bidding by Y Company in Yinan County [3] - Case 8: Major safety incident involving Z Company in Suizhou [4] - Case 9: Smuggling by Shenzhen X Company [4] - Case 10: Concealment of criminal proceeds by S Company in Wenchang [4] - Case 11: Illegal acquisition of computer information by Shanghai Z Company [6] Compliance and Rectification Measures - The article discusses the involvement of the procuratorial organs in guiding enterprises to enhance compliance, particularly in the context of data compliance and the establishment of third-party supervision mechanisms [6][12]. - Shanghai Z Company, involved in illegal data acquisition, demonstrated a strong willingness to rectify compliance issues, leading to a decision of non-prosecution after compensation to the affected party [10][14]. - The establishment of a data compliance committee and the implementation of a data security management system were highlighted as key steps taken by Z Company to address compliance risks [15]. Data Compliance Framework - The article outlines a structured approach to data compliance, including data classification, risk monitoring, and the establishment of a data security management system [17][19]. - It emphasizes the importance of regular data audits and the creation of a comprehensive data inventory to ensure compliance with industry standards [20][27].