Making a Spiking Net Work: Robust brain-like unsupervised machine learning. (arXiv:2208.01204v2 [cs.NE] UPDATED)

The surge in interest in Artificial Intelligence (AI) over the past decade
has been driven almost exclusively by advances in Artificial Neural Networks
(ANNs). While ANNs set state-of-the-art performance for many previously
intractable problems, the use of global gradient descent necessitates large
datasets and computational resources for training, potentially limiting their
scalability for real-world domains. Spiking Neural Networks (SNNs) are an
alternative to ANNs that use more brain-like artificial neurons and can use
local unsupervised learning to rapidly discover sparse …

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