TinyML Enabling Low-Power Inferencing, Analytics at the Edge - AI Trends

Edge computing is booming, with estimates ranging up to $61 billion in value in 2028. While definitions vary, edge computing is about taking compute power out of the data center and bringing it as close as possible to the device where analytics can run. The devices can be standalone IoT sensors, drones, or autonomous vehicles. Increasingly, data generated at the edge are used to feed applications powered by machine learning models," stated George Anadiotis, analyst, engineer and founder of Linked Data Orchestration of Berlin, Germany, working on the intersection of technology, media and data, writing in a recent account in ZDnet. However, "There's just one problem: machine learning models were never designed to be deployed at the edge.