US tech giants unite to combat model copying in China


The firms are sharing information through the Frontier Model Forum to detect so-called adversarial distillation attempts that violate their terms of service. — Bloomberg

NEW YORK: Rivals OpenAI, Anthropic PBC and Alphabet Inc’s Google have begun working together to try to clamp down on Chinese competitors extracting results from cutting-edge US artificial intelligence (AI) models to gain an edge in the global AI race.

The firms are sharing information through the Frontier Model Forum, an industry non-profit that the three tech companies founded with Microsoft Corp in 2023, to detect so-called adversarial distillation attempts that violate their terms of service, according to people familiar with the matter.

The rare collaboration between these tech giants underscores the severity of a concern raised by US AI companies that some users, especially in China, are creating imitation versions of their products that could undercut them on price and siphon away customers while posing a national security risk.

US officials have estimated that unauthorised distillation costs Silicon Valley labs billions of dollars in annual profit, according to a person familiar with the findings who described them on condition of anonymity.

OpenAI confirmed it’s part of the information sharing effort on adversarial distillation through the Frontier Model Forum and pointed to a recent memo it sent to the US Congress on the practice, where it accused Chinese firm DeepSeek of trying to “free-ride on the capabilities developed by OpenAI and other American frontier labs”.

Google, Anthropic, and the Frontier Model Forum declined to comment.

Distillation is a technique where an older “teacher” AI model is used to train a newer, “student” model that replicates the capabilities of the earlier system – often at a much lower cost than producing an original model from scratch.

Some forms of distillation are widely accepted and even encouraged by AI labs, such as when companies create smaller, more efficient versions of their own models, or allow outside developers to use distillation to build non-competitive technologies. — Bloomberg

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