Despite media reports, the idea of an "FDA for AI" that pre-approves models is not supported by key policy advisors. Insiders stress the goal is industry coordination to harden government systems against AI threats, not to create a Washington-based approval bottleneck that would kill innovation.

The Commerce Department's 'Casey' initiative is evaluating unreleased models from major labs like OpenAI and Google. This silent approval process could slow public releases, give government exclusive access, and create hurdles for new entrants, effectively forming a regulatory moat that benefits established players.

The traditional government model of setting a regulation and waiting years to assess it is obsolete for AI. A new approach is needed: a dynamic board of government, industry, and academic leaders collaborating to make and update rules in real-time.

Unlike mature tech products with annual releases, the AI model landscape is in a constant state of flux. Companies are incentivized to launch new versions immediately to claim the top spot on performance benchmarks, leading to a frenetic and unpredictable release schedule rather than a stable cadence.

The US government is restricting Anthropic's commercial rollout of its new model, Mythos, over concerns it could hamper the government's own access to compute. This move treats AI capacity as a strategic national resource and effectively creates a de facto licensing system for powerful models, marking a new era of AI governance.

Previously, labs like OpenAI would use models like GPT-4 internally long before public release. Now, the competitive landscape forces them to release new capabilities almost immediately, reducing the internal-to-external lead time from many months to just one or two.

The Trump administration's consideration of an FDA-like review process for new AI models signals a trend towards "soft nationalization." This involves government agencies partnering with and overseeing top AI labs to mitigate catastrophic risks and maintain a national security advantage.

Silicon Valley's economic engine is "permissionless innovation"—the freedom to build without prior government approval. Proposed AI regulations requiring pre-approval for new models would dismantle this foundation, favoring large incumbents with lobbying power and stifling the startup ecosystem.

Slowing public releases of AI models for government review may not slow overall progress. This creates a scenario where labs advance internally for months, giving government agencies exclusive access while delaying public commercialization and the next cycle of investment.