Intelligent tools on the loose: Reasoning models for exploratory computational design

Abstract

Generative artificial intelligence has swept into design research and practice, with popular image generators and language model interfaces now being used across disciplines and design stages. The multimodal language models exhibit fundamentally different characteristics from earlier machine learning approaches, and present unique challenges and opportunities for designers. A key question for design research arises: How can the capabilities of these large multimodal models become part of our design tools? This work investigates how the recent development of reasoning language models in particular can be utilized for early stage exploratory design. We outline a set of principles to build effective tools with these models by drawing from research in artificial intelligence. Specifically, we explore the application of the new reasoning model paradigm in computational design scripting. We present a system which successfully generates computer-aided design (CAD) scripts in Grasshopper. The system is compared to existing CAD AI approaches for its capabilities and characteristics. High latency and the absence of a user-model feedback loop still restrict real-time exploration in our system. Our developed principles can further inform broad exploratory tools and motivate inquiries into multimodal reasoning for design. By demonstrating a new CAD approach, we show large models’ utility as creative tools. Future research should address latency, enhance interactivity, and address other design tasks beyond CAD.