Artificial intelligence is a field within computer science that was built on decades of study, experiments, and collaboration between academia and the private sector. All that work paved the way for everything that came after it, but now that the stakes surrounding AI are the highest they've ever been, that spirit of collaboration has turned into fierce competition that some AI researchers think has gone too far.
Research published last week suggested MoonshotAI, the Chinese company behind the Kimi AI models, may have found a way to “steal” reasoning context from leading US models, and that paper has caught a lot of attention. Z.ai's GLM-5.2 model, which was the model Hugging Face turned to during the OpenAI hacking incident, was also implicated.
Eight researchers from seven institutions put their names to the “Stolen Thoughts” paper, detailing a method for obtaining hidden reasoning traces from proprietary LLMs via APIs by taking encrypted chain-of-thought blocks and replaying them to a weaker model that lacked security protections introduced in newer models.
One of the authors behind the paper, MATS Researcher Joachim Schaeffer, told *The Stack *it would be a big deal if any lab could access the raw reasoning data of frontier LLMs and use it to train their own models.
AI model distillation, the process of using a larger model to generate responses used to train a smaller model with similar capabilities, has already been a point of contention between US and Chinese labs, with Anthropic accusing Moonshot AI, DeepSeek and MiniMax of illicitly deploying the practice on Claude models in February.
“I think one has to put a lot of caveats in here of ‘there's no proof, we just observed interesting model behavior, we only asked questions,’" Schaeffer said. "But nonetheless, the things that we saw were consistent with that [distillation] story."
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