A team of researchers from the Massachusetts Institute of Technology (MIT) and Columbia University found a machine learning model can train itself to smell by building an artificial neural network that mimics the brain's odor-processing olfactory circuits.
The researchers used the fruit fly's olfactory system as a template, building an artificial network comprised of an input layer, a compression layer, and an expansion layer; links between neurons would be rewired as the model learned to classify smells.
The network self-organized in minutes into a structure closely resembling the fly brain's olfactory network.
MIT's Guangyu Robert Yang said, "By showing that we can match the architecture [of the biological system] very precisely, I think that gives more confidence that these neural networks can continue to be useful tools for modeling the brain."
From MIT News
View Full Article
Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA
No entries found