Brainwave: If Memristors Act Like Neurons, Put Them in Neural Networks

IEEE Spectrum

A low-power and non-volatile technology called the memristor shows initial promise as a basis for machine learning. According to new research, memristors efficiently tackle AI medical diagnosis problems, an encouraging development that suggests additional applications in other fields, especially low-power or network “edge” applications. This may be, the researchers say, because memristors artificially mimic some of the neuron’s essential properties. 

Memristors, or memory resistors, are a kind of building block for electronic circuits that scientists predicted roughly 50 years ago but only created for the first time a little more than a decade ago. These components, also known as resistive random access memory (RRAM) devices, are essentially electric switches that can remember whether they were toggled on or off after their power is turned off. As such, they resemble synapses—the links between neurons in the human brain—whose electrical conductivity strengthens or weakens depending on how much electrical charge has passed through them in the past.

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