[R] Nexus 2024
Published 27 November 2024
Composing Conversational Architecture by Integrating Large Language Model: From Reactive to Suggestive Architecture through Exploring the Mathematical Nature of the Transformer Model
Lok Hang Cheung and Giancarlo Di Marco
First proposed in the 1960s, Conversational Architecture enhances human and computer-integrated built environment interaction. Nowadays, most interactive designs are based on reaction and automation, rarely on conversation. Despite Natural Language Processing, including Large Language Model (LLM), being considered a candidate for Human-Computer Interaction (HCI), LLM applications are limited to verbal communication. The syntactic relationship between LLM, and architectural composition is underexplored. The paper proposes a qualitative framework to integrate the theoretical research of LLM and HCI in Conversational Architecture design. Through a mathematical and algorithmic analysis of a transformer model, the key component of LLM, its attributes are mapped onto Conversational Architecture parameters. With the identified design implications, a theatre hall design experiment is conducted. Through observation, the feasibility and challenges of the proposed framework are analysed.
Citation:
Cheung, L.H., Di Marco, G. Composing Conversational Architecture by Integrating Large Language Model: From Reactive to Suggestive Architecture through Exploring the Mathematical Nature of the Transformer Model. Nexus Netw J (2024). https://doi.org/10.1007/s00004-024-00805-9