Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108579
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Title: GPT models in construction industry : opportunities, limitations, and a use case validation
Authors: Saka, A
Taiwo, R 
Saka, N
Salami, BA
Ajayi, S
Akande, K
Kazemi, H
Issue Date: Mar-2024
Source: Developments in the built environment, Mar. 2024, v. 17, 100300
Abstract: Large Language Models (LLMs) trained on large data sets came into prominence in 2018 after Google introduced BERT. Subsequently, different LLMs such as GPT models from OpenAI have been released. These models perform well on diverse tasks and have been gaining widespread applications in fields such as business and education. However, little is known about the opportunities and challenges of using LLMs in the construction industry. Thus, this study aims to assess GPT models in the construction industry. A critical review, expert discussion and case study validation are employed to achieve the study's objectives. The findings revealed opportunities for GPT models throughout the project lifecycle. The challenges of leveraging GPT models are highlighted and a use case prototype is developed for materials selection and optimization. The findings of the study would be of benefit to researchers, practitioners and stakeholders, as it presents research vistas for LLMs in the construction industry.
Keywords: Artificial intelligence
ChatGPT
Generative AI
GPT
LLMs
Publisher: Elsevier Ltd
Journal: Developments in the built environment 
EISSN: 2666-1659
DOI: 10.1016/j.dibe.2023.100300
Rights: © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The following publication Saka, A., Taiwo, R., Saka, N., Salami, B. A., Ajayi, S., Akande, K., & Kazemi, H. (2024). GPT models in construction industry: Opportunities, limitations, and a use case validation. Developments in the Built Environment, 17, 100300 is available at https://doi.org/10.1016/j.dibe.2023.100300.
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