Results for 'Yoshimi Kawade'

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  1. Naturalization without associationist reduction: a brief rebuttal to Yoshimi.Jesse Lopes - forthcoming - Phenomenology and the Cognitive Sciences:1-9.
    Yoshimi has attempted to defuse my argument concerning the identification of network abstraction with empiricist abstraction - thus entailing psychologism - by claiming that the argument does not generalize from the example of simple feed-forward networks. I show that the particular details of networks are logically irrelevant to the nature of the abstractive process they employ. This is ultimately because deep artificial neural networks (ANNs) and dynamical systems theory applied to the mind (DST) are both associationisms - that is, (...)
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  2. Can Deep CNNs Avoid Infinite Regress/Circularity in Content Constitution?Jesse Lopes - 2023 - Minds and Machines 33 (3):507-524.
    The representations of deep convolutional neural networks (CNNs) are formed from generalizing similarities and abstracting from differences in the manner of the empiricist theory of abstraction (Buckner, Synthese 195:5339–5372, 2018). The empiricist theory of abstraction is well understood to entail infinite regress and circularity in content constitution (Husserl, Logical Investigations. Routledge, 2001). This paper argues these entailments hold a fortiori for deep CNNs. Two theses result: deep CNNs require supplementation by Quine’s “apparatus of identity and quantification” in order to (1) (...)
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