Microsoft is pushing AI to the farthest edge - Stacey on IoT Internet of Things news and analysis

Microsoft Research, the research arm of the software giant, is taking a counterintuitive approach to AI at the edge; it's pushing machine learning to the smallest processors out there, the microcontrollers commonly used in battery-powered sensors and wearables. In a conversation with Byron Changuion, a principal software engineer at Microsoft Research, he explained that bringing AI to the very edge of the network gives users more privacy, lowers power consumption, and speeds up response times. Microsoft still has a group focused on machine learning in the cloud, complete with its own specialty silicon that relies on field programmable gate arrays (FPGAs), but it seems fairly unique in trying to push machine learning to microcontrollers. To do this, it has built the Embedded Learning Library (ELL), a repository of code aimed at developers and makers who want to experiment with AI at the extreme edge. Microsoft Research hasn't been able to take the ELL down to the sensor level yet, but that is the ultimate goal.