Working memory capacity of ChatGPT: an empirical study
Working memory is a critical aspect of both human intelligence and artificial intelligence, serving as a workspace for the temporary storage and manipulation of information. In this paper, we systematically assess the working memory capacity of ChatGPT, a large language model developed by OpenAI, by...
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Format: | Conference item |
Language: | English |
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Association for the Advancement of Artificial Intelligence
2024
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author | Gong, D Wan, X Wang, D |
author_facet | Gong, D Wan, X Wang, D |
author_sort | Gong, D |
collection | OXFORD |
description | Working memory is a critical aspect of both human intelligence and artificial intelligence, serving as a workspace for the temporary storage and manipulation of information. In this paper, we systematically assess the working memory capacity of ChatGPT, a large language model developed by OpenAI, by examining its performance in verbal and spatial n-back tasks under various conditions. Our experiments reveal that ChatGPT has a working memory capacity limit strikingly similar to that of humans. Furthermore, we investigate the impact of different instruction strategies on ChatGPT's performance and observe that the fundamental patterns of a capacity limit persist. From our empirical findings, we propose that n-back tasks may serve as tools for benchmarking the working memory capacity of large language models and hold potential for informing future efforts aimed at enhancing AI working memory. |
first_indexed | 2024-03-07T08:14:26Z |
format | Conference item |
id | oxford-uuid:a7f9a182-b932-417c-804d-320f56956b88 |
institution | University of Oxford |
language | English |
last_indexed | 2024-04-23T08:27:09Z |
publishDate | 2024 |
publisher | Association for the Advancement of Artificial Intelligence |
record_format | dspace |
spelling | oxford-uuid:a7f9a182-b932-417c-804d-320f56956b882024-04-19T10:34:39ZWorking memory capacity of ChatGPT: an empirical studyConference itemhttp://purl.org/coar/resource_type/c_5794uuid:a7f9a182-b932-417c-804d-320f56956b88EnglishSymplectic ElementsAssociation for the Advancement of Artificial Intelligence2024Gong, DWan, XWang, DWorking memory is a critical aspect of both human intelligence and artificial intelligence, serving as a workspace for the temporary storage and manipulation of information. In this paper, we systematically assess the working memory capacity of ChatGPT, a large language model developed by OpenAI, by examining its performance in verbal and spatial n-back tasks under various conditions. Our experiments reveal that ChatGPT has a working memory capacity limit strikingly similar to that of humans. Furthermore, we investigate the impact of different instruction strategies on ChatGPT's performance and observe that the fundamental patterns of a capacity limit persist. From our empirical findings, we propose that n-back tasks may serve as tools for benchmarking the working memory capacity of large language models and hold potential for informing future efforts aimed at enhancing AI working memory. |
spellingShingle | Gong, D Wan, X Wang, D Working memory capacity of ChatGPT: an empirical study |
title | Working memory capacity of ChatGPT: an empirical study |
title_full | Working memory capacity of ChatGPT: an empirical study |
title_fullStr | Working memory capacity of ChatGPT: an empirical study |
title_full_unstemmed | Working memory capacity of ChatGPT: an empirical study |
title_short | Working memory capacity of ChatGPT: an empirical study |
title_sort | working memory capacity of chatgpt an empirical study |
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