A Loosely Wittgensteinian Conception of the Linguistic Understanding of Large Language Models like BERT, GPT-3, and ChatGPT.
In this article, I develop a loosely Wittgensteinian conception of what it takes for a being, including an AI system, to understand language, and I suggest that current state of the art systems are closer to fulfilling these requirements than one might think. Developing and defending this claim has...
| Publicado en: | Grazer Philosophische Studien Vol. 99; no. 4; pp. 485 - 524 |
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| Formato: | Artículo |
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Brill Academic Publishers
2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=163257672&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 163257672 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 01659227 NFG jtl: Grazer Philosophische Studien issn: 01659227 maglogo: N pubinfo: dt: 2022 vid: 99 iid: 4 pid: 639 pub: Brill Academic Publishers artinfo: ui: 163257672 10.1163/18756735-00000182 ppf: 485 ppct: 39 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2MB tig: atl: A Loosely Wittgensteinian Conception of the Linguistic Understanding of Large Language Models like BERT, GPT-3, and ChatGPT. aug: au: Gubelmann, Reto affil: University of St. Gallen, St. Gallen, Switzerland su: Language models Wittgenstein, Ludwig, 1889-1951 ChatGPT Turing test Artificial intelligence sug: subj: Language models Wittgenstein, Ludwig, 1889-1951 ChatGPT Turing test Artificial intelligence keyword: neural networks Searle understanding Wittgenstein ab: In this article, I develop a loosely Wittgensteinian conception of what it takes for a being, including an AI system, to understand language, and I suggest that current state of the art systems are closer to fulfilling these requirements than one might think. Developing and defending this claim has both empirical and conceptual aspects. The conceptual aspects concern the criteria that are reasonably applied when judging whether some being understands language; the empirical aspects concern the question whether a given being fulfills these criteria. On the conceptual side, the article builds on Glock's concept of intelligence, Taylor's conception of intrinsic rightness as well as Wittgenstein's rule-following considerations. On the empirical side, it is argued that current transformer-based NNLP models, such as BERT and GPT-3 come close to fulfilling these criteria. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Grazer Philosophische Studien is the property of Brill Academic Publishers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Grazer Philosophische Studien holder: Brill Academic Publishers dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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