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The debate over understanding in AI’s large language models

We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language—and the physical and social situations language encodes—in any humanlike sense. We describe arguments that have been made for and a...

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Detalles Bibliográficos
Autores principales: Mitchell, Melanie, Krakauer, David C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068812/
https://www.ncbi.nlm.nih.gov/pubmed/36943882
http://dx.doi.org/10.1073/pnas.2215907120
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author Mitchell, Melanie
Krakauer, David C.
author_facet Mitchell, Melanie
Krakauer, David C.
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description We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language—and the physical and social situations language encodes—in any humanlike sense. We describe arguments that have been made for and against such understanding and key questions for the broader sciences of intelligence that have arisen in light of these arguments. We contend that an extended science of intelligence can be developed that will provide insight into distinct modes of understanding, their strengths and limitations, and the challenge of integrating diverse forms of cognition.
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spelling pubmed-100688122023-09-21 The debate over understanding in AI’s large language models Mitchell, Melanie Krakauer, David C. Proc Natl Acad Sci U S A Perspective We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language—and the physical and social situations language encodes—in any humanlike sense. We describe arguments that have been made for and against such understanding and key questions for the broader sciences of intelligence that have arisen in light of these arguments. We contend that an extended science of intelligence can be developed that will provide insight into distinct modes of understanding, their strengths and limitations, and the challenge of integrating diverse forms of cognition. National Academy of Sciences 2023-03-21 2023-03-28 /pmc/articles/PMC10068812/ /pubmed/36943882 http://dx.doi.org/10.1073/pnas.2215907120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Perspective
Mitchell, Melanie
Krakauer, David C.
The debate over understanding in AI’s large language models
title The debate over understanding in AI’s large language models
title_full The debate over understanding in AI’s large language models
title_fullStr The debate over understanding in AI’s large language models
title_full_unstemmed The debate over understanding in AI’s large language models
title_short The debate over understanding in AI’s large language models
title_sort debate over understanding in ai’s large language models
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068812/
https://www.ncbi.nlm.nih.gov/pubmed/36943882
http://dx.doi.org/10.1073/pnas.2215907120
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