Spiking Networks for Improved Cognitive Abilities of Edge Computing Devices

12/19/2019

∙

by   Anton Akusok, et al.

∙

0

∙

share

This concept paper highlights a recently opened opportunity for large scale analytical algorithms to be trained directly on edge devices. Such approach is a response to the arising need of processing data generated by natural person (a human being), also known as personal data. Spiking Neural networks are the core method behind it: suitable for a low latency energy-constrained hardware, enabling local training or re-training, while not taking advantage of scalability available in the Cloud.