Edge AI for 6G Networks-ComSoc Education Talks

As 6G networks evolve to tightly integrate AI with communication infrastructure, the critical design challenges and trade-offs in deploying intelligent services at the edge must be explored. In this talk, the featured experts discuss how to balance high-performance AI with the limited computational, memory, and energy resources of edge devices—without compromising real-time responsiveness in latency-sensitive applications.  They delve into the architectural dilemma: should 6G systems be primarily shaped by the computational demands of distributed learning and inference, or by communication constraints like bandwidth and latency? Through this lens, the speakers unpack the fundamental trade-offs between processing, transmission, and intelligence distribution.  

Emerging strategies for on-device model adaptation, enabling edge devices to learn and evolve over time without relying on cloud-based retraining are explored. Techniques such as federated learning, continual learning, and lightweight model updates are discussed, along with the challenges of maintaining accuracy, privacy, and efficiency in dynamic environments.

Featured Speakers:  John Cioffi, Reinaldo Valenzuela, Gerhard Fettweis, Rahim Tafazolli, Khaled Letaief, Chengshan Xiao, Alberto Leon-Garcia, Sherman Shen, Wen Tong, Peiying Zhu, Wei Zhang, Kostas Plataniotis