The Deep (Learning) Transformation of Mobile and Embedded Computing

Abstract

Mobile and embedded devices increasingly rely on deep neural networks to understand the world - a feat that would have overwhelmed their system resources only a few years ago. Further integration of machine learning and embedded/mobile systems will require additional breakthroughs of efficient learning algorithms that can function under fluctuating resource constraints, giving rise to a field that straddles computer architecture, software systems, and artificial intelligence.