Opportunities for Large Language Models and Discourse in Engineering Design

• URL: http://arxiv.org/abs/2306.09169v1
• Date: Thu, 15 Jun 2023 14:46:44 GMT
• Title: Opportunities for Large Language Models and Discourse in Engineering Design
• Authors: Jan G\"opfert, Jann M. Weinand, Patrick Kuckertz, Detlef Stolten
• Abstract summary: We argue that discourse should be regarded as the core of engineering design processes, and therefore should be represented in a digital artifact. We describe how simulations, experiments, topology optimizations, and other process steps can be integrated into a machine-actionable, discourse-centric design process.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, large language models have achieved breakthroughs on a wide range of benchmarks in natural language processing and continue to increase in performance. Recently, the advances of large language models have raised interest outside the natural language processing community and could have a large impact on daily life. In this paper, we pose the question: How will large language models and other foundation models shape the future product development process? We provide the reader with an overview of the subject by summarizing both recent advances in natural language processing and the use of information technology in the engineering design process. We argue that discourse should be regarded as the core of engineering design processes, and therefore should be represented in a digital artifact. On this basis, we describe how foundation models such as large language models could contribute to the design discourse by automating parts thereof that involve creativity and reasoning, and were previously reserved for humans. We describe how simulations, experiments, topology optimizations, and other process steps can be integrated into a machine-actionable, discourse-centric design process. Finally, we outline the future research that will be necessary for the implementation of the conceptualized framework.

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