NCE focus issue: extreme edge computing

Biological intelligence imparts organisms with the ability to overcome a number of key challenges such as adapting to dynamic environments, learning from experience, and making complex decisions, even within a daunting set of constraints (e.g. extremely limited energy). Interestingly, we are encountering several analogous challenges and constraints as artificial intelligence (AI) begins to move from the cloud to the edge in the ever-growing internet-of-things (IoT). Neuromorphic computing is poised to play a critical role in moving AI to the edge, as it enables the implementation of state-of-the-art machine learning algorithms (e.g. deep neural networks) on hardware platforms with limited resources (energy, precision, I/O, etc.). This NCE focus issue on Extreme Edge Computing brings together a variety of works that are aimed at designing neuromorphic computing for AI at-the-edge. The collection includes four original research articles and one topical review paper, which are briefly summarized below