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There is a fundamental, unbridgeable gap between DNNs and the visual cortex

Published online by Cambridge University Press:  06 December 2023

Moshe Gur*
Affiliation:
Department of Biomedical Engineering, Technion, Haifa, Israel mogi@bm.technion.ac.il

Abstract

Deep neural networks (DNNs) are not just inadequate models of the visual system but are so different in their structure and functionality that they are not even on the same playing field. DNN units have almost nothing in common with neurons, and, unlike visual neurons, they are often fully connected. At best, DNNs can label inputs, while our object perception is both holistic and detail preserving. A feat that no computational system can achieve.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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