Title | GPT models in construction industry: Opportunities, limitations, and a use case validation |
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Type | Journal article |
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Authors | Saka, A., Taiwo, T., Saka, N., Salami, B.A., Ajayi, S., Akande, K. and Kazemi, H. |
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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. |
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Keywords | ChatGPT |
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| Artificial Intelligence |
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Article number | 100300 |
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Journal | Developments in the Built Environment |
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Journal citation | 17 |
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ISSN | 2666-1659 |
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Year | 2024 |
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Publisher | Elsevier |
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Accepted author manuscript | File Access Level Open (open metadata and files) |
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Publisher's version | License CC BY 4.0 File Access Level Open (open metadata and files) |
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Digital Object Identifier (DOI) | https://doi.org/10.1016/j.dibe.2023.100300 |
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Publication dates |
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Published in print | Mar 2024 |
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Published online | 20 Dec 2023 |
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Supplemental file | File Access Level Open (open metadata and files) |
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