工作流程
计算机科学
空格(标点符号)
数据库
操作系统
作者
Liane Makatura,Michael Foshey,Bohan Wang,Felix HähnLein,Pingchuan Ma,Bingyao Deng,Megan Tjandrasuwita,Andrew Spielberg,Crystal E. Owens,Peter Yichen Chen,Allan Zhao,Amy Zhu,Wil J Norton,Edward Gu,Joseph Jacob,Yaxian Li,Adriana Schulz,Wojciech Matusik
出处
期刊:Cornell University - arXiv
日期:2023-01-01
被引量:2
标识
DOI:10.48550/arxiv.2307.14377
摘要
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.
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