Integrating ChatGPT, Bard, and Leading-Edge Generative Artificial Intelligence in Architectural Design and Engineering: Applications, Framework, and Challenges

The current study investigates how artificial intelligence (AI) impacts sustainable development in emerging markets, with a focus on Thailand. Following a systematic review approach, research designs are configured for reviewing empirical evidence within peer-reviewed papers and reports. It also presents an overview of the adoption of AI in agriculture, health, and urban planning. The key findings lend credence to the potential use of AI in achieving resource optimality, reducing environmental damage, and urging social equity in its use. But these very initiatives are hampered by the digital divide, concerns about data privacy, and bias in algorithms. The way forward should be to establish solid, regulatory frameworks geared towards more investment in infrastructure with ethical AI practices that will lead to optimal gains. The huge potentials for AI to enable sustainability in Thailand are there; hence, it is very important to reduce the associated risks that require equitably distributed results in all sectors.

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Exploring the use of generative AI for material texturing in 3D interior design spaces

Gallega,

Sumi

2024

Front. Comput. Sci.

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Material selection is important yet difficult in interior design, as designers need to consider technical factors beyond aesthetics, such as maintenance, sustainability, and costs that are often considered in later stages of the design process. As a result, making design changes due to unanticipated technical constraints in the later stages can be costly. We attempt to approach this problem by anticipating these as early as the conceptualization stage, where designers model and assign textures to their 3D scenes. To this end, our study explores the use of generative AI tools, namely ChatGPT and DALLE-2, in both texturing 3D scenes and selecting materials for interior design projects. Through a prototype, we evaluated the generative AI tools by conducting a user study with professional designers and students (n = 11). Based on creativity support (CSI), participants averaged a score of 72.82/100, while in task load (NASA-TLX), they scored 47.36/100. Based on qualitative feedback, designers could easily search and explore textures and materials while also receiving informative and contextually relevant suggestions on materials and colors from ChatGPT. However, these tools can be improved by fine-tuning on domain-specific datasets. Lastly, we analyze how designers interacted with these tools and reflect on how they can benefit from using generative AI in texturing and material selection in the interior design process.

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Integrating ChatGPT, Bard, and Leading-Edge Generative Artificial Intelligence in Architectural Design and Engineering: Applications, Framework, and Challenges

Cited by 3 publications

References 170 publications

Bridging Bim with Ai: A Gpt-Powered Assistant for Real-Time Modeling Actions

Bridging Bim with Ai: A Gpt-Powered Assistant for Real-Time Modeling Actions

Harnessing artificial intelligence for sustainable development in emerging markets: Exploring opportunities and challenges in Thailand

Exploring the use of generative AI for material texturing in 3D interior design spaces

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