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- Leaders: Wilson Wang Tina Tsou Borui Li (李博睿)
- Objective: To design, develop, and deploy a robust Agent-as-a-Service (AaaS) platform leveraging edge computing to run AI models locally on edge devices. This platform aims to enhance performance, reduce latency, and improve scalability by deploying machine learning agents closer to data sources and end-users, ensuring efficient and real-time processing of AI tasks.
- Approach: The approach for Edge AaaS (Agent-as-a-Service) involves designing and implementing a scalable platform that leverages edge computing to deploy and manage AI models on edge devices, ensuring real-time processing, reduced latency, and enhanced performance by conducting thorough requirements analysis, robust architecture design, seamless integration, and continuous monitoring and optimization.
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