Neuromorphic Computer Offers Non-von Neumann Architecture

Regular computers, while amazing, are not amazing enough for the doughty researchers at the National Institute of Standards and Technology (NIST). They've developed a superconducting “synapse” that “learns” like a biological system.


(NIST’s artificial synapse, designed for neuromorphic computing,
mimics the operation of switch between two neurons. One artificial synapse
is located at the center of each X. This chip is 1 square centimeter in size.
(The thick black vertical lines are electrical probes used for testing.) (credit: NIST))

NIST’s artificial synapse is a metallic cylinder 10 micrometers in diameter — about 10 times larger than a biological synapse. It simulates a real synapse by processing incoming electrical spikes (pulsed current from a neuron) and customizing spiking output signals. The more firing between cells (or processors), the stronger the connection. That process enables both biological and artificial synapses to maintain old circuits and create new ones.

NIST’s artificial synapse is a metallic cylinder 10 micrometers in diameter — about 10 times larger than a biological synapse. It simulates a real synapse by processing incoming electrical spikes (pulsed current from a neuron) and customizing spiking output signals. The more firing between cells (or processors), the stronger the connection. That process enables both biological and artificial synapses to maintain old circuits and create new ones.

Operating at 100 GHz, it can fire at a rate that is much faster than the human brain — 1 billion times per second, compared to a brain cell’s rate of about 50 times per second.

It uses only about one ten-thousandth as much energy as a human synapse. The spiking energy is less than 1 attojoule** — roughly equivalent to the miniscule chemical energy bonding two atoms in a molecule — compared to the roughly 10 femtojoules (10,000 attojoules) per synaptic event in the human brain. Current neuromorphic platforms are orders of magnitude less efficient than the human brain. “We don’t know of any other artificial synapse that uses less energy,” NIST physicist Mike Schneider said.

Science fiction fans recall that Isaac Asimov, in his short story Reason, wrote about a similar idea:

All that had been done in the mid 20th century on "calculating machines" had been upset by Robertson and his positronic brain paths. The miles of relays and photocells had given way to the spongy globe of platinum iridium about the size of the human brain. (Read more about the positronic brain)

A few years later, Philip K. Dick had fun with the idea of a Nexus-6 brain unit in his 1968 novel Do Androids Dream of Electric Sheep:

The Nexus-6 did have two trillion constituents plus a choice within a range of ten million possible combinations of cerebral activity. In .45 of a second an android equipped with such a brain could assume any one of fourteen basic reaction-postures. Well, no intelligence test could trap such an andy. But then, intelligence tests hadn't trapped an andy in years, not since the primordial, crude varieties of the 1970's.

Via KurzweilAI.

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