How Can Large Language Models Help Humans in Design and Manufacturing?
Liane Makatura Michael Foshey Bohan Wang Felix HähnLein Pingchuan Ma Bolei Deng Megan Tjandrasuwita Andrew Spielberg Crystal Elaine Owens Peter Yichen Chen Allan Zhao Amy Zhu Wil J Norton Edward Gu Joshua Jacob Yifei Li Adriana Schulz Wojciech Matusik
The advancement of Large Language Models (LLMs), including GPT-4, provides
exciting new opportunities for generative design. We investigate the
application of this tool across the entire design and manufacturing workflow.
Specifically, we scrutinize the utility of LLMs in tasks such as: converting a
text-based prompt into a design specification, transforming a design into
manufacturing instructions, producing a design space and design variations,
computing the performance of a design, and searching for designs predicated on
performance. Through a series of examples, we highlight both the benefits and
the limitations of the current LLMs. By exposing these limitations, we aspire
to catalyze the continued improvement and progression of these models.