Spiking neural networks (SNNs) often are touted as a way to get close to the power efficiency of the brain, but there is widespread confusion about what exactly that means. In fact, there is disagreement about how the brain actually works. Some SNN implementations are less brain-like than others. Depending on whom you talk to, SNNs are either a long way away or close to commercialization. The varying definitions of SNNs leads to differences in how the industry is seen. "A few startups are doing their own SNNs," said Ron Lowman, strategic marketing manager of IP at Synopsys. "It's being driven by guys that have expertise in how to train, optimize, and write software for them." On the other hand, Flex Logix Inference Technical Marketing Manager Vinay Mehta said that, "SNNs are out further than reinforcement learning," referring to a machine-learning concept that's still largely in the research phase. The entire notion of a "neural network" is motivated by attempts to model how the brain works.
Aug-2-2020, 00:15:08 GMT