Predictions for embedded machine learning for IoT in 2021 – Urgent Comms

Despite silicon shortages, several new capabilities for embedded machine learning on Internet of Things devices will emerge in 2021, industry watchers predict. New capabilities mean severing the cord between so many Internet of Things ( IoT) devices and the cloud and instead running processes at the edge. The boost in chip processing capabilities--which will continue to increase next year, as Moore's Law dictates--means sidestepping cloud-based latency issues, among other benefits. Experts argue that moving processing to the edge – or "going to local execution," as Hiroshu Doyu,, an embedded AI researcher at Ericsson, puts it –will deliver five distinct advantages in 2021: Privacy will be less "porous," Doyu said, offering fewer opportunities for data to be stolen while in transit to the cloud or on the return trip. "Once the AI is more powerful, that kind of device can be installed without a power line," he said. "More powerful IoT AI chips will be shipped and more domain-specific IoT AI chips will be shipped.