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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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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. |
author_sort | Mitchell, Melanie |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-10068812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
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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