Presentation
Energy-Efficient Edge AI and Autonomy
DescriptionThis tutorial provides an accessible entry point for designers across the low-power design space working on power-constrained on-device intelligence. It covers the landscape of low-power edge intelligence from algorithm, architecture, circuit, and application perspectives. The four-talk progression addresses: low-power on-device ML, memory-efficient algorithms for edge inference, neuro-inspired approaches to edge intelligence, and streaming processing in autonomous edge platforms. The tutorial serves a broad DAC audience in machine learning, including those working in edge AI or neuromorphic computing, while highlighting emerging energy-efficient edge computing and system research.
Event Type
Tutorial
TimeSunday, July 269:00am - 12:30pm PDT
LocationMtg Room 202AB