Is the Edge the Next Frontier of AI?

Many of the initial use cases for generative AI (GenAI) and large language models (LLMs) have been cloud-bound, where high concentrations of training data and compute resources are concentrated. Yet, for many use cases, AI will move closer to the data, driven by the need for real-time decision making and operational efficiency. According to Gartner, by 2029, at least 60% of edge computing deployments will use composite AI (both predictive and generative AI [GenAI]), compared to less than 5% in 2023.1 AI at the edge is poised to grow rapidly, but what will that entail? What is different about AI at the edge? What are the barriers that will need to be overcome as an industry for AI to thrive at the edge? Experts Bill Conrades (Sr. Director of Engineering at AHEAD), Daniel Situnayake (Director of Machine Learning at Edge Impulse), Amit Ronen (Chief Customer Officer, Wind River), and Padraig Stapleton (Sr. Vice President of Product and Engineering at ZEDEDA) discuss these topics and more at this panel discussion moderated by Dormain Drewitz (VP of Marketing at ZEDEDA).