Uncover the opportunities that localized computing power offers and the associated risks and benefits to creating at the edge. Examine the interplay between innovations in the cloud, edge computing, and telecommunications; and see how these synergies address the limitations of centralized computing by moving processes closer to the source of data generation.

Private networks and edge computing are poised to unleash a new wave of cross-industry productivity and innovation, converging to enable new use cases with mobile devices and real-time, enhanced decision support.  As new data streams and process capabilities move to the edge in hybrid cloud deployments, advanced private networks, particularly those using 5G, offer low-latency, high device density, and stable and secure connectivity.  Examine a project now live in Singapore, that brings together an advanced 5G network with AI-based visual and acoustic analysis. This augmented reality tests advanced Industry 4.0 manufacturing use cases in production quality, warehouse automation, and more.

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?