AI应用规模化落地面临挑战 边缘计算将开辟新路径

Group 1 - The 2025 World Internet Conference in Wuzhen highlighted a shift in focus from AI model performance to the practical, safe, and efficient implementation of AI in business [1] - The event featured 670 companies and institutions from 54 countries, showcasing innovations in AI technology empowering the real economy [1] Group 2 - AI applications are transitioning from exploratory phases to large-scale deployment across various sectors, including finance, smart transportation, and personalized education [2] - The centralized architecture of traditional AI deployments is increasingly inadequate for geographically dispersed business needs, leading to latency issues and challenges in real-time responses [2] Group 3 - Public cloud deployments, while convenient, struggle to meet the demands for low latency and stable scalability in high-interaction scenarios like online education and interactive entertainment [3] - Sensitive industries such as finance and healthcare prefer private deployments due to strict data privacy regulations, but face high costs for GPU hardware and specialized teams [3] Group 4 - Edge AI is emerging as a critical solution to address structural challenges by deploying computing power closer to data sources, creating a balance between public cloud and centralized private deployments [4] - The edge computing firm Wangsu Technology showcased a platform that enhances local data processing efficiency and reduces costs, achieving a 60% improvement in response speed for voice interactions [4] Group 5 - The widespread use of generative AI introduces new security risks, necessitating a comprehensive defense strategy that spans the entire lifecycle of AI applications [5] - Wangsu Technology's security division proposed a multi-layered defense system to address vulnerabilities at the application, model, and computing levels [5] Group 6 - The Wuzhen summit indicated a transition in the AI industry from model innovation to application implementation, with edge computing and security systems providing new deployment strategies [6] - The ongoing challenge remains to find a long-term balance between efficiency, cost, and security in AI applications [6]