Gong et al. (2024)

Working Memory Capacity of ChatGPT: An Empirical Study

Proceedings of the AAAI Conference on Artificial Intelligence, 38(9), 10048-10056

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Abstract

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.

Reference

Gong, D., Wan, X., & Wang, D. (2024). Working memory capacity of ChatGPT: An empirical study. Proceedings of the AAAI Conference on Artificial Intelligence, 38(9), 10048–10056. https://doi.org/10.1609/aaai.v38i9.28868

What Rests on This

1 mechanism cites this source. Each finding below is quoted as it appears on that mechanism's own page.

Working Memory Memory Systems

Measured in AI

Given the n-back task one letter or grid per turn, ChatGPT (GPT-3.5) fell to a sensitivity of about d′ = 1 at 3-back, the load at which human performance from a published n-back study also drops, which the authors called a capacity limit strikingly similar to humans; working memory's AI counterpart is the context window (what the model can see in the current conversation), since training and saved memory are long-term stores
Measured in AI

The comparison is approximate and uneven: a chat model can answer n-back only because earlier letters stay in its context window, so it can look back while people must hold them in mind, and the human data come from separate timed lab studies; because GPT-3.5 still did no better than people, the result counts and sits within the human range, which is the basis for Comparable