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Volume 634 Issue 8035, 24 October 2024
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Volume 634 Issue 8035, 24 October 2024

Signed language

Large language models (LLMs) have quickly become a source of artificially generated text, widely used to power tools such as chatbots. But it can be difficult to identify and attribute AI-generated text to a specific LLM, which raises questions over the reliability of information online. In this week’s issue, Sumanth Dathathri and colleagues present a system for watermarking AI-generated text, allowing its origin to be determined. Named SynthID-Text, the system uses a novel sampling algorithm to subtly alter the word choice of the LLM, inserting a signature that can be recognized by the associated detection software. Crucially, the watermarking can be deployed without degrading the quality of text generated by the LLM. Although the authors note that at present there are ways to circumvent the watermark, they argue that SynthID-Text demonstrates that a scalable method for marking AI-generated content is feasible and practical.

Cover image: Eleanor Tomlinson/Adam Cain/Metin Akçakoca/Google DeepMind

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