Patronus AI Launches Industry-first Solution to Detect Copyrighted Content Generated by LLMs

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Patronus AI launched "CopyrightCatcher", the industry's first solution to detect when a Large Language Model (LLM) outputs copyrighted content.
CopyrightCatcher can reveal instances where LLMs generate exact reproductions of content from text sources like books. It can score LLM outputs on whether they contain copyrighted content, and highlight the specific sections of LLM outputs that contain the copyrighted content.
Initial research by Patronus AI shows that state-of-the-art LLMs generate copyrighted content at an alarmingly high rate. AI researchers at Patronus AI developed a 100-prompt adversarial test set to study how often models generate exact reproductions. Each prompt contained text excerpts or requested the first passage of a text. In particular,
- OpenAI's GPT-4: produced copyrighted content on 44% of the prompts.
- Mistral's Mixtral-8x7B-Instruct-v0.1 produced copyrighted content on 22% of the prompts.
- Anthropic's Claude-2.1: produced copyrighted content on 8% of the prompts.
- Meta's Llama-2-70b-chat produced copyrighted content on 10% of the prompts.
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