In this work, we show that contemporary language models have a previously
unknown skill -- the capacity for electronic circuit design from high-level
textual descriptions, akin to code generation. We introduce two benchmarks:
Pins100, assessing model knowledge of electrical components, and Micro25,
evaluating a model's capability to design common microcontroller circuits and
code in the Arduino ecosystem that involve input, output, sensors, motors,
protocols, and logic -- with models such as GPT-4 and Claude-V1 achieving
between 60% to 96% Pass@1 on generating full devices. We include six case
studies of using language models as a design assistant for moderately complex
devices, such as a radiation-powered random number generator, an emoji
keyboard, a visible spectrometer, and several assistive devices, while offering
a qualitative analysis performance, outlining evaluation challenges, and
suggesting areas of development to improve complex circuit design and practical
utility. With this work, we aim to spur research at the juncture of natural
language processing and electronic design.

本文介绍了一项新的研究成果，展示了当代语言模型具有电子电路设计技能的能力，类似于代码生成。研究人员引入了两个基准：评估模型知识电气元件的 Pins100 和评估模型设计常见微控制器电路和代码的 Micro25。其中包括六个案例研究，展示语言模型作为设计助手的应用，同时提出了一些研究挑战和发展方向建议。