Disruption of the research software landscape through AI software generation

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In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. 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.

What Happened

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. Subjects Technology Programming language Code availability.

• IEEE/CVF International Conference on Computer Vision 3992–4003 (IEEE, 2023).

• Nature Methods thanks Robert Haase, Wei Ouyang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

• The manuscript was written jointly by N.D.M and J.M.R.K.

Key Details

So-Last for helpful discussions on U-Nets.

• MOSS was developed using LLM-assisted programming tools including Anthropic’s Claude.

What Reports Say

Coverage of the story so far points to:

• Continued reporting by Nature as more details emerge