Earlier quoted context omitted.
"The Democrat decided to reject the measure because it applies only to the biggest and most expensive AI models and doesn’t take into account whether they are deployed in high-risk situations, he said in his veto message." That doesn't mean you're wrong , but it's not what Newsom signaled.
Only applying to the biggest models is the point ; the biggest models are the inherently high-risk ones. The larger they get, the more that running them at all is the "high-risk situation". Passing this would not have been a complete solution, but it would have been a step in the right direction. This is a huge disappointment.
What is the actual, concrete concern here? That a model "breaks out", or something?
The risk with AI is not in just running models, the risk is becoming overconfident in them, and then putting them in charge of real-world stuff in a way that allows them to do harm.
Hooking a model up to an effector capable of harm is a deliberate act requiring assurance that it doesn't harm -- and if we should regulate anything, it's that. Without that, inference is just making datacenters warm. It seems shortsighted to set an arbitrary limit on model size when you can recklessly hook up a smaller, shittier model to something safety-critical, and cause all the havoc you want.