The term ‘neuromorphic computing’ can be traced back to the 1980s when Caltech researcher Carver Mead first proposed the concept of designing integrated circuits (ICs) to mimic the organization of living neuron cells. As the National Institute of Standards (NIST) states, neuromorphic computing promises to dramatically improve the efficiency of computational tasks such as perception and decision making.
Nanoscale oscillators and reconfigurable Josephson junctions
Although software and specialized hardware implementations of neural networks have made significant progress in recent years, such implementations are still are still ‘many orders of magnitude’ less energy efficient than the human brain. This is precisely why NIST researchers are working on several bio-inspired hardware implementations of neuromorphic networks. More specifically, one project is based on high-frequency room-temperature nanoscale oscillators utilizing the spin-torque effect, while the other is designed around dynamically reconfigurable magnetic Josephson junctions operating at liquid-helium temperatures.
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