Leading AI labs, despite intense competition, are collaborating through the Frontier Model Forum to detect and prevent Chinese firms from creating imitation models. This rare alliance is driven by the shared existential threat that 'adversarial distillation' poses to their business models and to U.S. national security.

Despite creating supposedly superintelligent models, leading AI labs still rely on crude access restrictions to prevent 'distillation'—an existential threat where competitors replicate their models. This reveals a critical capability gap: their AI is not yet smart enough to detect and prevent its own theft.

Meta prohibits its AI engineers from using external tools like Codex and Claude for specific tasks. This is to prevent contaminating proprietary training data with outputs from rival models, a legal and technical problem called distillation that complicates proving a model's origin and could violate terms of service.

Despite intense domestic rivalry, top US AI labs like OpenAI, Anthropic, and Google are collaborating to detect "adversarial distillation"—where Chinese firms copy their models. This rare cooperation shows the shared commercial and national security threat from foreign competitors outweighs their direct competition.

China is gaining an efficiency edge in AI by using "distillation"—training smaller, cheaper models from larger ones. This "train the trainer" approach is much faster and challenges the capital-intensive US strategy, highlighting how inefficient and "bloated" current Western foundational models are.

US officials and AI labs allege Chinese firms are engaged in industrial-scale IP theft. They reportedly use fraudulent accounts to extract capabilities from US models like Claude to train their own, creating a facade of domestic innovation.

Frontier AI labs are restricting API access not just for security, but to prevent competitors from using 'distillation' to create cheap copies of their models. This practice makes it impossible to recoup massive R&D investments, forcing a move towards more restrictive, geopolitically motivated access.

Unable to build frontier models from scratch, some Chinese companies gain a competitive edge by using "scale distillation." This involves training smaller, open models on the outputs of larger, proprietary US models, effectively piggybacking on American R&D to create capable, low-cost alternatives.

Chinese firms are closing the AI capability gap by using "distillation" to replicate the intelligence of leading US models. This creates a strategic vulnerability, as copying software models is easier than replicating China's hardware manufacturing prowess.