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Elon Musk has stated in court that his AI company xAI partially relied on OpenAI models while developing its chatbot Grok. The comment came during testimony in a California federal case, adding a public acknowledgment to a practice that has largely been discussed behind the scenes in the AI industry.
The statement was made as part of Musk’s ongoing legal dispute with OpenAI leadership, where he alleges the company moved away from its original nonprofit mission. During questioning, Musk confirmed that xAI had used distillation techniques, at least in part, to train Grok, as reported by TechCrunch.
Distillation refers to the process of training a new AI model by querying an existing one and learning from its outputs. Instead of building a system entirely from scratch, developers can use responses from more advanced models to replicate similar behavior at lower cost. This approach has become a point of tension in the industry, particularly among leading AI labs.
Companies like OpenAI, Anthropic, and Google have raised concerns about the practice, especially when it involves large scale automated querying. These efforts can reduce the competitive advantage gained from expensive infrastructure and training data.
Musk’s acknowledgment suggests that distillation is not limited to smaller or overseas developers, but is also used among major U.S. based AI firms. While the legality of the practice remains unclear, it may conflict with the terms of service set by companies offering AI APIs and chatbots.
The issue has gained attention partly due to concerns about international competition. Some AI developers have used distillation to build lower cost models that approach the performance of leading systems. In response, major labs have begun collaborating through industry groups to detect and limit such activity, including monitoring for unusual query patterns.
Musk also commented on the broader competitive landscape during his testimony, ranking Anthropic as the current leader in AI, followed by OpenAI and Google. He described xAI as a smaller player still working to scale, with significantly fewer resources than its rivals.
The testimony offers a rare look into how AI systems may be developed across the industry, highlighting the blurred lines between competition, collaboration, and imitation. As legal and technical questions around distillation continue to evolve, the practice is likely to remain a central issue in the race to build more capable AI systems.
