The case for building Scalable Neuromorphic Networks is this: like humans, smarter chips have a larger, tighter neural network. Indeed, neural networks are the current state-of-the-art for machine learning. This isn’t robotics, where a non-sentient arm follows explicit instructions. Instead, machine learning uses algorithms and statistical models to analyze and then draw inferences from patterns in data.
Examining what it's going to take to get real scalability for chip-based decision-making
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