Examining what it's going to take to get real scalability for chip-based decision-making

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.

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