Working memory capacity of ChatGPT: an empirical study

Conference item

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.

Authors: Gong, D; Wan, X; Wang, D

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Association for the Advancement of Artificial Intelligence
• Host title: Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2023)
• Volume: 38
• Issue: 9
• Pages: 10048-10056
• Publication date: 2024-03-24
• Acceptance date: 2023-12-09
• Event title: 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2023)
• Event location: Vancouver, BC, Canada
• Event website: https://aaai.org/aaai-conference/
• Event start date: 2024-02-20
• Event end date: 2024-02-27
• DOI: 10.1609/aaai.v38i9.28868
• Language: English