AI at the Edge: Squeezing Intelligence into Small Spaces The relentless pursuit of artificial intelligence at the edge – from smart cameras analyzing traffic patterns to wearable devices monitoring vital signs – demands smaller, faster, and more energy-efficient machine learning models. Deploying complex neural networks on resource-constrained devices like Raspberry Pis and NVIDIA Jetson boards
