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Making a Spiking Net Work: Robust brain-like unsupervised machine learning. (arXiv:2208.01204v2 [cs.NE] UPDATED)
cs.LG updates on arXiv.org arxiv.org
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 …
arxiv brain learning machine machine learning making unsupervised work