Disruption of the research software landscape through AI software generation

IF 28.3 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2026-08-17 DOI:10.1038/s41592-026-03210-x

Nelson D. Medina, Joergen M. R. Kornfeld

引用次数: 0

Abstract

Specialized research software has historically been costly and time-consuming to create, but large language models (LLMs) have become capable enough at code generation to fundamentally change this. We describe how LLM-assisted programming disrupts the landscape by allowing researchers to build tools without support from software engineers, illustrate this with an example built rapidly by a single LLM-assisted developer, and discuss opportunities and risks.

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通过人工智能软件生成颠覆研究软件格局。

专门的研究软件在历史上是昂贵和耗时的，但是大型语言模型（llm）在代码生成方面已经足够强大，从根本上改变了这一点。我们描述了llm辅助编程如何通过允许研究人员在没有软件工程师支持的情况下构建工具来破坏景观，用一个由llm辅助开发人员快速构建的示例来说明这一点，并讨论了机会和风险。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Methods 生物-生化研究方法

CiteScore

58.70

自引率

1.70%

发文量

326

审稿时长

1 months

期刊介绍： Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.