Abundant resources but unable to detect? Benchmark partner questions Anthropic's push to restrict model distillation

Benchmark partner Chetan Puttagunta posted on X, expressing confusion over Anthropic's public call for stricter regulation on AI model distillation. He noted that Anthropic is currently a company valued at approximately $1 trillion with vast technical and financial resources. At the scale described, so-called "large-scale distillation attacks" should theoretically be easier to identify and track. If Anthropic chooses to restrict such activities, the real cost may not be a lack of technical capability, but rather the sacrifice of some API revenue. "The only cost required seems to be reducing revenue from related API businesses."

Previously, AI companies like Anthropic have been paying close attention to the issue of model distillation. Model distillation typically refers to using the output of a large model (the teacher model) to train another model (the student model), aiming to reduce costs and improve efficiency. Some AI companies are concerned that competitors might obtain model outputs by calling a large number of APIs, which could then be used to train their own models, thereby bypassing the original R&D investment. According to Puttagunta's perspective, the controversy surrounding model distillation in the AI industry essentially involves the balance between commercial interests, open competition, and intellectual property protection. For leading AI companies, finding the balance between protecting core technology and maintaining an open ecosystem will become an important issue for future industry competition.