Core Insights - The conference "2025 China Data Valley · West Lake Sword Conference" emphasizes the importance of data flow for enabling various industries and the critical role of data in the AI revolution [2][6] - The lack of high-quality datasets is identified as a significant bottleneck in the deep integration of data and AI, which is essential for advancing from AI to AGI [2][3] Group 1: Data Flow and AI Integration - Data is considered the key element in the AI revolution, akin to fuel for a rocket, highlighting its necessity for intelligent systems [2] - The current limitations in data flow are attributed to security and quality issues, particularly concerning private data that is essential for model application in specific scenarios [3][5] - The industry is exploring synthetic data to address the scarcity of quality data, which affects model performance [3] Group 2: Trusted Data Space - The concept of a trusted data space is proposed as a solution to reconcile the development and utilization of data elements with security protection [6][10] - Trusted data spaces are designed to ensure secure and controllable data flow through a combination of hardware and software solutions, including privacy computing and blockchain technologies [10][11] - The national plan aims to establish over 100 trusted data spaces by 2028, with a focus on creating a comprehensive set of rules and standards for data security [11] Group 3: AI's Role in Data Security - The transition from static to dynamic data security is necessary to address the challenges in data flow, with AI playing a crucial role in this transformation [11][12] - AI technologies can enhance data classification and security by understanding the context and value of data, as well as identifying normal versus abnormal API usage [12] - The integration of AI in data security applications is seen as a significant opportunity for improving data management and protection [12]