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  1. Why machines do not understand: A response to Søgaard.Jobst Landgrebe & Barry Smith - 2023 - Archiv.
    Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in his "Understanding models understanding language" (2022) for a thesis of this sort. His idea is that (1) where there is semantics there is also understanding and (2) machines are not only capable of what he calls `inferential semantics', but even that they can (with the help of inputs from sensors) `learn' referential semantics. We show that he goes wrong because he pays insufficient (...)
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  • The Simulative Role of Neural Language Models in Brain Language Processing.Nicola Angius, Pietro Perconti, Alessio Plebe & Alessandro Acciai - 2024 - Philosophies 9 (5):137.
    This paper provides an epistemological and methodological analysis of the recent practice of using neural language models to simulate brain language processing. It is argued that, on the one hand, this practice can be understood as an instance of the traditional simulative method in artificial intelligence, following a mechanistic understanding of the mind; on the other hand, that it modifies the simulative method significantly. Firstly, neural language models are introduced; a study case showing how neural language models are being applied (...)
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