Join us for Session 3 of our Build With AI series: Edge AI, where we explore how artificial intelligence is moving beyond the cloud and into smart devices, wearables, and real-time intelligent systems. This session will introduce the fundamentals of Edge AI, the technologies enabling on-device intelligence, and the challenges of building AI for resource-constrained environments.

We’ll also explore the growing importance of privacy at the edge through federated learning - a powerful approach that allows AI models to learn collaboratively without sharing sensitive data. Attendees will gain insight into both the opportunities and challenges of deploying intelligent systems closer to where data is created.

Explore the Session

AI Gets Physical at the Edge: Enabling Intelligent Real-World Systems

AI is moving beyond the cloud and into the world around us. Powering smart devices, wearables, intelligent environments, and real-time sensing systems.

This talk introduces the fundamentals of EdgeAI and explores why running AI directly on devices is shaping the next generation of intelligent systems. We’ll look at the technologies enabling EdgeAI, practical applications, optimisation techniques, and some of the challenges of building AI for resource constrained, real-world environments.

Dr Ian Cleland

Reader at Ulster University

The Challenges and Potential of Federated Learning at the Edge

As more computation moves to the network's edge, data privacy becomes a greater concern. Federated learning offers a promising path forward, but realising its potential requires addressing a number of challenges; this talk explores them.

Seán Ó Fithcheallaigh

PhD Researcher within the Pervasive Computing Research Centre (PCRC) at Ulster University