Drawing of Purkinje cells (A) and granule cells (B) from pigeon cerebellum by Santiago Ramón y Cajal, 1899; Instituto Santiago Ramón y Cajal, Madrid, Spain.

Purkinje cells in pigeon cerebellum

Putting the Neural back into Networks

Part 2: More spikes, more problems

12th January, 2020

In the last post, we learned about how a spiking neuron differs from a common-or-garden Artificial Neuron. TL;DR: Spiking neurons understand time and have internal dynamics, Artificial Neurons don’t.

Machine Learning with SNNs for low-power inference

Presentation at UWA

3rd May, 2024

AI is extremely power-hungry. But brain-inspired computing units can perform machine learning inference at sub-milliWatt power. Learn about low-power computing architectures from SynSense, which use quantised spiking neurons for ML inference. I presented this slide deck at the UWA Computer Science seminar in Perth.

Putting the Neural back into Networks

Part 3: I got 99 problems but a spike ain't one

13th January, 2020

In the last post, we saw that spike generation can cause major issues with gradient descent, by completely zeroing the gradients. We also learned how to get around this issue by faking the neuron output by making a spiking surrogate.