Second, these phase-change neurons are the closest we’ve come to creating artificial devices that behave like biological neurons, perhaps leading us towards efficient, massively parallel computer designs that apply neuromorphic approaches to decision-making and processing sensory information. IBM says that their new work is complementary to research being carried out into memristor-based synapses, too.

So far, IBM has built 10×10 crossbar arrays of neurons, connected five of those arrays together to create neuronal populations of up to 500 neurons, and then processed broadband signals in a novel, brain-like way. (In technical terms, the neurons showed the same „population coding“ that emerges in biological neurons, and the signal processing circumvented the Nyquist-Shannon sampling theorem).

There’s no reason to stop there, though. Now it’s time put thousands of these phase-change neurons onto a single chip—and then the difficult bit: writing some software that actually makes use of the chip’s neuromorphosity.

Nature Nanotechnology, 2016. DOI: 10.1038/nnano.2016.70 (About DOIs).