Bottom-up and Top-down Neural Processing Systems Design: Unveiling the Road Toward Neuromorphic Intelligence

This keynote examines bottom-up and top-down approaches to neuromorphic intelligence for embedded cognition. It covers spiking and mixed-signal processor design, hardware-aware model selection, on-chip learning, silicon results, and tradeoffs for edge computing.

Syllabus

Intro
Neuromorphic approaches
Methodology
Analog or digital
Bottomup approach
Local learning rules
Topdown approach
Morphic
Benchmark
Results
Q A
Silicon integration
Spoon
Accuracy energy tradeoff
Timebased computation
Spoon chip
Whats next
Promising avenues
References
Paper
Wrapup