Title | Novel Synaptic Architecture for Brain Inspired Computing | |
Date | Thursday July 12 2018, @03:49PM | |
Author | mrpg | |
Topic | ||
from the WOPR dept. |
Submitted via IRC for Fnord666
[...] In the experiment, the team showed how multiple nanoscale memristive devices exhibiting these characteristics could nonetheless be configured to efficiently implement artificial intelligence algorithms such as deep learning. Prototype chips from IBM containing more than one million nanoscale phase-change memristive devices were used to implement a neural network for the detection of hidden patterns and correlations in time-varying signals.
"In this work, we proposed and experimentally demonstrated a scheme to obtain high learning efficiencies with nanoscale memristive devices for implementing learning algorithms," Nandakumar says. "The central idea in our demonstration was to use several memristive devices in parallel to represent the strength of a synapse of a neural network, but only chose one of them to be updated at each step based on the neuronal activity."
Source: Novel synaptic architecture for brain inspired computing
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The Second Coming of Neuromorphic Computing
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