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Neuromorphic computing utilizes an engineering approach or method based on the activity of the biological brain. This type of approach can make technologies more versatile and adaptable, and promote more vibrant results than other types of traditional architectures, for instance, the von Neumann architecture that is so useful in traditional hardware design.
Neuromorphic computing is also known as neuromorphic engineering.
Neuromorphic computing has been around for a while, but it is now beginning to be applied in new and different ways. A prime example is the proposal to create neuromorphic chips which are more complex in nature than traditional microprocessors. Neuromorphic chips would have architectures more like the neurons of the human brain, allowing them to process information in more specialized ways.
Experts explain that the von Neumann chips, which were made use of in prior decades as Moore's law accelerated, were “primitive” compared to new designs. The “legacy” microprocessor performance designs were made more for crunching numbers and dealing with big data than processing images visually or doing the kinds of other high-level work that today's machine learning and artificial intelligence systems require. The idea is that new neuromorphic chips could be made to more easily accomplish these new types of technological goals.