Machine Learning on the Edge - From Microcontrollers to Embedded Linux Devices

Explore the evolving landscape of machine learning on edge devices in this informative conference talk. Discover how hardware providers are pushing the boundaries of small footprint, low-powered edge devices capable of running hardware-accelerated machine learning without relying on cloud backends. Learn about the range of ML-capable edge devices, from microprocessor-based real-time systems to fully-fledged embedded Linux devices. Delve into the challenges of large-scale deployment, including model adaptation and size reduction. Gain insights into over-the-air updates for microprocessors and Dockerized deployment for embedded Linux devices. Witness a practical demonstration of a basic computer vision application deployed on three small-scale embedded Linux devices: Raspberry Pi, Google Coral, and NVIDIA Jetson.