【环球网科技综合报道】11月12日，蚂蚁集团与浙江大学在杭州举行签约仪式，正式宣布共同成立"浙江大学-蚂蚁集团 大数据认知计算联合研究中心"。该 中心将聚焦"AI for Data"前沿方向，致力于从底层数据库到结构化数据的分析、处理与应用的全链路技术攻坚，解析数据、读懂数据、用好数据，最终创新 并打造一套适用于更多行业的通用化、自动化数据智能解决方案。 此次合作的启动，紧密契合国家"十五五"规划中关于深入推进数字中国建设、建立健全数据要素基础制度的核心方向。在深化数据资源开发利用、加快人工 智能等数智技术创新的时代背景下，双方的携手标志着产学研联合攻关数据智能关键技术迈出实质性一步。 根据规划，双方将重点围绕三大维度展开深度合作： 第一，数模结合，共建智能化的数据基础设施。依托蚂蚁集团在多个业务场景中积累的技术经验与数据处理能力，双方将共同研发面向未来的智能数据库与 数据服务平台，打造集数据存储、高效查询与模型训练于一体的技术范式，为各行各业的数字化转型提供底层支撑。 第二，构建开放协同的数据生态。蚂蚁集团丰富的应用场景将与浙江大学在医学、教育等领域的科研资源深度结合，推动跨领域数据的合规融合与创新应 用， ...

Core Insights - The urban trusted data space is a government-led data infrastructure that facilitates the development and utilization of urban data resources, serving as a key carrier for trusted data space [1][2] Development Drivers - **Policy**: The establishment of urban trusted data spaces is encouraged through a series of top-level designs and strategic plans aimed at promoting the compliant and efficient circulation of data [4][5] - **Technology**: Privacy computing and blockchain technology are introduced to address the challenges of trusted data circulation, enabling data sharing while ensuring compliance and security [5][6] - **Demand**: Urban areas face challenges in data resource development and utilization, which the trusted data space aims to address by providing a secure and compliant environment for data circulation [8] Value Proposition - The urban trusted data space aims to break down data circulation barriers, activate the potential of data elements, and promote the modernization of urban governance [11] Overall Framework - The urban trusted data space is built around a foundational infrastructure, two major platforms, and aims to empower urban digital transformation [13] Core Capabilities - The core capabilities of the urban trusted data space include trusted control, resource interaction, and value co-creation, which are essential for establishing a trusted data circulation infrastructure [16] Industry Chain and Ecosystem - The urban trusted data space involves five main entities: operators, data providers, data users, data service providers, and regulatory bodies, each playing a crucial role in the ecosystem [21] Competitive Landscape - In the technical service sector, comprehensive and specialized service providers compete, with ICT background cloud service providers leading the market [24] Application Scenarios - **Government Services**: The urban trusted data space facilitates inter-departmental data connectivity, enhancing government services and decision-making [27] - **Inclusive Finance**: By integrating government and financial data, the urban trusted data space supports the development of dynamic risk assessment models for inclusive finance [30] Case Studies - **Zhangjiakou Trusted Data Space**: This initiative employs a "one space, four platforms, one system" architecture to support the secure circulation of public and social data [33][35] - **Shanghai Trusted Data Space**: This project leverages blockchain technology to meet the complex data needs of a megacity, facilitating the secure and efficient use of data [37][39] Technical Trends - AI technology is becoming a key driver in enhancing data governance efficiency within urban trusted data spaces, transitioning from manual to automated governance strategies [42] Future Trends - The urban trusted data space is expected to evolve from pilot projects to a collaborative ecosystem, attracting industry and enterprise participation to explore vertical applications [44][45]

Core Viewpoint - The urban trusted data space is a key infrastructure led by the government to promote the development and utilization of urban data resources, serving as a bridge between data supply and application [1][2]. Development Drivers Policy - Since the introduction of the data element market reform in 2019, China has implemented a series of top-level designs and strategic plans to encourage the creation of urban trusted data spaces, with the first batch of 13 pilot cities announced [4][5]. Technology - Privacy computing and blockchain technology are crucial for solving data sharing issues, enabling data owners to share data confidently and willingly [5][6]. Demand - With China's data production expected to exceed 40ZB by 2024, the urban trusted data space is essential for enhancing urban governance efficiency by integrating and utilizing public data resources [8]. Value of Urban Trusted Data Space - The urban trusted data space aims to address issues such as the lack of trust mechanisms and inefficient circulation in urban governance, thereby enhancing the efficiency of public data utilization and supporting modern urban governance [11]. Overall Framework - The urban trusted data space is built around a foundational infrastructure, two major platforms, and capabilities for secure data circulation, enabling diverse applications such as government services and inclusive finance [13]. Core Capabilities - The core capabilities of the urban trusted data space include trusted control, resource interaction, and value co-creation, which are essential for establishing a reliable data circulation infrastructure [16]. Industry Chain and Players - The urban trusted data space involves five main entities: operators, data providers, data users, data service providers, and regulatory bodies, each playing a critical role in data circulation and compliance [21]. Competitive Analysis - In the technology service sector, comprehensive solution providers with ICT backgrounds, such as Inspur Cloud and Huawei Cloud, are leading the market, while specialized firms focus on specific verticals [24]. Application Scenarios Government Services - The urban trusted data space facilitates inter-departmental data sharing, enhancing government efficiency through initiatives like "one network for all services" [27]. Inclusive Finance - By integrating government public data with financial data, the urban trusted data space supports the development of dynamic risk assessment models, promoting inclusive finance [30]. Case Studies Zhangjiakou Trusted Data Space - The Zhangjiakou trusted data space employs a "one space, four platforms, one system" architecture to support secure data circulation and enhance public data value [33][35]. Shanghai Trusted Data Space - Shanghai's trusted data space, leveraging blockchain technology, aims to meet the complex data needs of a mega city, facilitating secure and efficient data utilization [37][39]. Technical Trends - AI technology is becoming a key driver for enhancing data governance efficiency, transitioning from manual governance to automated and intelligent strategies [42]. Future Trends - The urban trusted data space is expected to evolve from pilot projects to a collaborative ecosystem, attracting industry and enterprise participation to explore vertical applications [44][45].

Core Insights - Oracle has integrated AI into its flagship database, enhancing data management and enabling customers to gain insights and productivity across multicloud and on-premises environments [1][2] - The new Oracle Autonomous AI Lakehouse supports the Apache Iceberg open table format, allowing customers to leverage Oracle AI Database for their data lake data [1][5] AI Integration - Oracle AI Database 26ai incorporates AI across the entire data and development stack, including AI Vector Search, AI for Database Management, and AI for Analytics, facilitating sophisticated AI workflows [1][2] - The database's built-in AI capabilities provide customers with flexibility in building and deploying AI applications, supporting various frameworks and protocols [2] Data Protection - Oracle AI Database implements NIST-approved quantum-resistant algorithms for data encryption, enhancing security against future quantum computing threats [3] AI Features - The database includes advanced features such as Unified Hybrid Vector Search, enabling retrieval of various data types, and built-in data privacy protection measures [9] - Oracle AI Database 26ai allows customers to build and manage in-database AI agents using a no-code visual platform, simplifying AI adoption [4] Performance and Scalability - The Autonomous AI Lakehouse delivers Exadata-powered performance and serverless scaling, available on major hyperscalers [5][6] - Oracle Exadata enhances AI performance by offloading vector queries and providing low-latency data access [9] Future Developments - Planned features for Oracle AI Database 26ai include a Private AI Services Container for secure AI model deployment and integration with NVIDIA for accelerated computing [9][10]

Core Viewpoint - The urban trusted data space is a key infrastructure led by the government to promote the development and utilization of urban data resources, serving as a bridge between data supply and application [1][2]. Development Drivers Policy - Since the introduction of the data element market reform in 2019, China has implemented a series of top-level designs and strategic plans to encourage the creation of urban trusted data spaces, with the first batch of 13 pilot cities announced [4][5]. Technology - Privacy computing and blockchain technology are crucial for solving data sharing issues, enabling data owners to share data confidently and willingly [5][6]. Demand - With China's data production expected to exceed 40ZB by 2024, the urban trusted data space is essential for enhancing urban governance efficiency by integrating and utilizing public data resources [8]. Value of Urban Trusted Data Space - The urban trusted data space aims to address issues such as the lack of trust mechanisms and inefficient data circulation, thereby enhancing urban governance and promoting the modernization of city management [11]. Overall Framework - The urban trusted data space is built around a foundational infrastructure, two major platforms, and capabilities for secure data circulation, enabling diverse applications such as government services and inclusive finance [13]. Core Capabilities - The core capabilities of the urban trusted data space include trusted control, resource interaction, and value co-creation, which are essential for establishing a reliable data circulation infrastructure [16]. Industry Chain and Players - The urban trusted data space involves five main entities: operators, data providers, data users, data service providers, and regulatory bodies, each playing a critical role in data circulation and compliance [21]. Competitive Analysis - In the technology service sector, comprehensive solution providers with ICT backgrounds, such as Inspur Cloud and Huawei Cloud, are leading the market, while specialized firms focus on specific verticals [24]. Application Scenarios Government Services - The urban trusted data space facilitates inter-departmental data sharing, enhancing government efficiency through initiatives like "one network for all services" [27]. Inclusive Finance - By integrating government public data with financial data, the urban trusted data space supports the development of dynamic risk assessment models, promoting inclusive finance [30]. Case Studies Zhangjiakou Trusted Data Space - The Zhangjiakou trusted data space employs a "one space, four platforms, one system" architecture to support secure data circulation and enhance public data utilization [33][35]. Shanghai Trusted Data Space - Shanghai's trusted data space, leveraging blockchain technology, aims to meet the complex data needs of a mega city, facilitating secure and efficient data flow [37][39]. Technical Trends - AI technology is becoming a key driver in enhancing data governance efficiency, transitioning from manual governance to automated and intelligent strategies [42]. Future Trends - The urban trusted data space is expected to evolve from pilot projects to a collaborative ecosystem, attracting industry and enterprise participation to explore vertical applications [44][45].