Researchers tested their framework by training a computer vision model to detect people in images. After only 10 minutes of training, it learned to complete the task successfully. Credit: Ji Lin et al
Microcontrollers, miniature computers that can run simple commands, are the basis for billions of connected devices, from internet-of-things (IoT) devices to sensors in automobiles. But cheap, low-power microcontrollers have extremely limited memory and no operating system, making it challenging to train artificial intelligence models on “edge devices” that work independently from central computing resources.
Training a machine-learning model on an intelligent edge device allows it to adapt to …
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