Fixing the problems of deep neural networks will require better training data and learning algorithms

• URL: http://arxiv.org/abs/2311.12819v1
• Date: Tue, 26 Sep 2023 03:09:00 GMT
• Title: Fixing the problems of deep neural networks will require better training data and learning algorithms
• Authors: Drew Linsley, Thomas Serre
• Abstract summary: We argue that DNNs are poor models of biological vision because they rely on strategies that differ markedly from those of humans. We show that this problem is worsening as DNNs are becoming larger-scale and increasingly more accurate.
• Score: 20.414456664907316
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Bowers and colleagues argue that DNNs are poor models of biological vision because they often learn to rival human accuracy by relying on strategies that differ markedly from those of humans. We show that this problem is worsening as DNNs are becoming larger-scale and increasingly more accurate, and prescribe methods for building DNNs that can reliably model biological vision.

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