Edge is about intelligence, and the growing revolution to shrink those smarts into ever smaller devices is underway. Deep learning requires massive amounts of data, vast computational resources, and electricity consumption. Simply put, it is an energy hog. But what if algorithms could train on less data, and on hardware that runs them faster? The tiny ML revolution is a new approach that enables on-device AI workloads to be executed by compact runtimes using ultra-low-power, edge devices. This session opens a window to the research exploring AI and ML applications on edge computing devices. What are the new opportunities for industries running on a lower carbon footprint and what applications might be enabled at the Edge?