AI algorithms running on edge devices now offer real-time insights and actions that can improve response times.
Connected devices linked to the Internet of Things (IoT) — in association with 5G network technology — are now everywhere. But just wait until next-generation applications, such as artificial intelligence (AI), start running within these edge devices. Meanwhile, the low latency and higher data speeds of 5G and IoT will add a new real-time dimension to AI.
Consider an extended reality (XR) headset that not only provides a 3D view of the inside of an aircraft engine, but which also has on-board intelligence to point you to problem areas or to information on anomalies in that engine, which are immediately and automatically recognized and adjusted.
Chipmakers are already developing powerful yet energy-efficient processors — or “systems on a chip” — that can deliver AI processing within a small footprint device. For instance, Qualcomm just announced AI-capable Snapdragon chips that run on smartphones and PCs. Also on the horizon are a generation of NeuRRAM chips, developed at the University of California San Diego, which are capable of running sizeable AI algorithms on smaller devices.
Overall, the global number of connected IoT devices is projected to surpass 29 billion by 2027, which is more than 16.7 billion at the present time, a recent analysis from zScaler shows. “Consumer devices are smart and most common, but business process-oriented IoT generated the most transactions,” the report’s authors point out. “Manufacturing and retail devices accounted for 50%-plus of transactions, highlighting their widespread adoption and business-critical function in these sectors.
