Semantic Scholar Open Access 2023 152 sitasi

GPT Models in Construction Industry: Opportunities, Limitations, and a Use Case Validation

A. Saka R. Taiwo Nurudeen Saka B. Salami Saheed Ajayi +2 lainnya

Abstrak

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 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.

Topik & Kata Kunci

Penulis (7)

A

A. Saka

R

R. Taiwo

N

Nurudeen Saka

B

B. Salami

S

Saheed Ajayi

K

Kabiru O. Akande

H

Hadi Kazemi

Format Sitasi

Saka, A., Taiwo, R., Saka, N., Salami, B., Ajayi, S., Akande, K.O. et al. (2023). GPT Models in Construction Industry: Opportunities, Limitations, and a Use Case Validation. https://doi.org/10.1016/j.dibe.2023.100300

Akses Cepat

Lihat di Sumber doi.org/10.1016/j.dibe.2023.100300
Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Total Sitasi
152×
Sumber Database
Semantic Scholar
DOI
10.1016/j.dibe.2023.100300
Akses
Open Access ✓