Unlocking AI/ML for Wireless Networks: Enhancing Connectivity, Performance, and Innovations for Verticals

This talk aims to project a balanced and realistic perspective that can inspire meaningful discussions on the practical and effective integration of intelligence in future wireless networks. Starting with a remote-timber use case as a case study, we present initial findings and reflect on the future of AI/ML-driven network automation. Considering the evolving wireless connectivity use cases and scenarios, network automation is necessary, but what makes the integration of AI/ML promising yet challenging in terms of native AI/ML deployment? To address such questions, this talk will also delve into the discussion of (near/non)-RT functions of explainable AI/ML for enhancing connectivity, performance, and innovations for verticals.