In my mind the existential risks make regulation of large training runs worth it. Should distributed training runs become an issue we can figure out a way to inspect them, too.
To respond to the specific htpothetical, if that scenario happens it will presumably be by either a botnet, by a large group of wealthy hobbyists, or by a corporation or a nation state intent on circumventing the pause. Botnets have been dismantled before, and large groups of wealthy hoobyists tend to interested in self preservation (at least more so than individuals). Corporate and state actors defecting on international treaties can be penalized via standard mechanisms.
Here’s a legit question: you say pause. Pause until what? What is the go condition? You can never prove an unbounded negative like “AI will never ever become dangerous” so I would think there is no go condition anyone could agree on.
… which means people eventually just ignore the pause when they get tired of it and the hysteria dies out. Why bother then?
If that happened open efforts could marshal tens or hundreds of thousands of GPUs.
Right now the barrier is that training requires too much synchronization bandwidth between compute nodes, but I’m not aware of any hard mathematical reason there couldn’t be an algorithm that does not have to sync so much. Even if it were less efficient this could be overcome by the sheer number of nodes you could marshal.