ACM CoNEXT Workshop on Edge-Cloud Collaboration with AI (ECCAI 2025)

With the rapid advancement of Artificial Intelligence (AI), an increasing number of AI methods are being deployed on the edge for real-time analytics. However, due to the intensive computational demands of many AI workloads, especially limited by resource-constrained edge devices, they often need to be offloaded to the cloud. At the same time, applications with stringent privacy requirements necessitate that data be processed at the edge. This duality introduces new challenges for networking and system design within edge-cloud collaboration. Moreover, AI itself can serve as a powerful enabler to address the complexities of edge-cloud co-deployment, optimizing resource allocation, data flow, and decision-making processes. ECCAI 2025 aims to explore this emerging space: a computing paradigm driven by AI and for AI in intelligent edge-cloud collaboration. Specifically, the workshop investigates: Cloud-edge collaboration for AI: How to better meet the demands of real-time performance and strict privacy requirements in scenarios such as autonomous driving and smart healthcare; and how to more effectively leverage the edge for low-latency inference while utilizing the cloud for complex training and collaborative optimization. AI for cloud-edge collaboration: Leveraging AI to optimize the overall edge-cloud collaboration strategy, such as predicting workloads to decide whether tasks should be executed at the edge or in the cloud, and dynamically adjusting network bandwidth usage and compute resource allocation.