ArticleFrontiers in physiology2021
Note on the Reliability of Biological vs. Artificial Neural Networks.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Various types of neural networks are currently widely used in diverse technical applications, not least because neural networks are known to be able to "generalize." The latter property raises expectations that they should be able to handle unexpected situations with similar success than humans. Using fundamental examples, we show that in situations for which they have not been trained, artificial approaches tend to run into substantial problems, which highlights a deficit in comparisons to human abilities. For this problem-which seems to have obtained little attention so far-we provide a first analysis, based on simple examples, which exhibits some key features responsible for the difference between human and artificial intelligence.
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