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Bio-inspired Neuromorphic Circuits Architectures for Ultra-Low Power AI

tinyML via YouTube

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Overview

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This tutorial presents neuroscience-inspired electronic circuits and in-memory computing architectures for robust, low-latency, ultra-low-power processing. It discusses silicon neurons, spiking neural networks, and applications to extreme-edge systems that process sensory data locally.

Syllabus

Introduction
Neural networks
Memory and energy
Future of computing
Biological neural networks
Space and memory
Let time represent itself
Silicon neuron
Analog digital divide
Robust computation
Coefficient of variation
False myths
Bioinspired architectures
Dynams
spiking neural network
summary
closing remarks
Sponsors

Taught by

tinyML

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