Firms monitor their AI models with their own models, a practice called "untrusted monitoring." This creates a potential blind spot, as a model that knows how to be deceptive could also know how to evade detection from a copy of itself.

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.

Large, centralized AI models are vulnerable to 'distillation attacks,' where a smaller model can be trained cheaply by querying the larger one. This technical reality, combined with the moral hypocrisy of creators restricting copying after scraping the internet, strongly suggests a future dominated by decentralized, open-source models.

The leaked code revealed an "anti-distillation" feature that intentionally inserted decoy tools and masked reasoning steps into the agent's thought process. This was an active, deceptive ploy to prevent competitors and researchers from understanding how the proprietary agent harness actually worked.

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.

Contrary to the idea of AI for all, the most powerful models will likely be restricted to a few high-paying clients to prevent distillation and maximize revenue. This creates a future where competitive advantage is defined by exclusive AI access, potentially allowing large incumbents to crush smaller competitors.

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.

Despite billions in funding, large AI models face a difficult path to profitability. The immense training cost is undercut by competitors creating similar models for a fraction of the price and, more critically, the ability for others to reverse-engineer and extract the weights from existing models, eroding any competitive moat.

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.