Regulatory object

At 269 pages, GAAIA contains plenty of excellent stuff. It would formally authorize the Center for AI Standards and Innovation with a $100m annual budget.

The definitive early read on the bipartisan Great American AI Act — the first serious federal answer to the regulatory-object question: attach rules to frontier developers via an authorized CAISI, third-party verification organizations, and SB 53-style transparency, traded against preemption.

The draft's frontier model provisions are not starting from scratch. They closely track the framework emerging from California's SB 53, New York's RAISE Act, and Illinois' SB 315.

Side-by-side of the federal draft against SB 53, RAISE, and Illinois SB 315, showing a de facto US regulatory object — large frontier developers defined by compute-plus-revenue triggers — crystallizing from state templates.

Implementation details matter a lot, but this document exceeds expectations a lot.

Close reading of OpenAI's federal policy blueprint — developer-level obligations overseen by CAISI in exchange for preemption — arguing it could be the 'minimum viable deal' on what rules attach to, while flagging the accountability gaps such a bargain must close.

Model weights and code are digital artifacts; once released, by a lab, a leak, or a foreign competitor, they replicate at near-zero cost.

A clean statement of the use-based position: model- and weights-attached rules are unenforceable once artifacts replicate, so regulation should bind at deployment choke points — the application-layer answer the framing warns misses the frontier.

more than half of US states have together enacted more than 100 new AI laws this term

The best mid-2026 empirical map of what US states actually attach rules to — companion chatbots, data centers, insurance, dynamic pricing — showing application-layer objects dominating state practice even as frontier-developer frameworks spread.