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From DeepSeek to Distillation: Protecting IP In An AI World
A flurry of developments in late January 2025 has caused quite a buzz in the AI world. On January 20, DeepSeek released a new open-source AI model called R1 and an accompanying research paper. R1 was touted as performing comparably to proprietary frontier models at a fraction of the cost, with drastically reduced computational resources needed both to train and run the model. DeepSeek explained that it used new techniques in reinforcement learning, but others suspect that it might also have benefitted from unauthorized model distillation. Within a week, there was a strong market reaction, with AI-related semiconductor stocks dropping more than 10% on January 27.
Just a few days later, on January 29, the U.S. Copyright Office published the second installment of its three-part Report on Copyright and Artificial Intelligence — this part focusing on the copyrightability of AI-generated outputs. In that report, the Copyright Office analyzed the amount and nature of human contribution needed to bring AI outputs within the scope of U.S. copyright protection. It concluded that existing law remains appropriate for the new AI technologies and that mere prompts generally do not meet the standard of human contribution needed for copyright protection. It gathered and considered public comments for its analysis but rejected arguments that legal change is necessary to counter international competition, such as foreign entities distilling U.S. frontier models.
Protection against unauthorized model distillation is an emerging issue within the longstanding theme of safeguarding intellectual property (IP). Existing countermeasures have primarily focused on technical solutions, such as restricting access through application programming interface (API) rate limiting or embedding traceable watermarks in AI outputs. This article examines the legal protections available under the current legal framework and explore why patents may serve as a crucial safeguard against unauthorized distillation.
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