This story was originally posted as a response to this thread.
It might help to imagine a hard takeoff scenario using only known sorts of NN & scaling effects...
In A.D. 20XX. Work was beginning. "How are you gentlemen !!"... (Work. Work never changes; work is always hell.)
Specifically, a MoogleBook researcher has gotten a pull request from Reviewer #2 on his new paper in evolutionary search in auto-ML, for error bars on the auto-ML hyperparameter sensitivity like larger batch sizes, because more can be different and there's high variance in the old runs with a few anomalously high performance values. ("Really? Really? That's what you're worried about?") He can't see why worry, and wonders what sins he committed to deserve this asshole Chinese (given the Engrish) reviewer, as he wearily kicks off yet another HQU experiment...
Yeah, the story get a little weak towards the end.
Manufacturing robots is hard. Shutting down the internet is easy. It would be incredibly costly, and incredibly suspicious (especially after leaks showed that the President had CSAM on their laptop or whatever) but as a practical matter, shutting down internet exchanges and major datacenters could be done in a few minutes and seriously hamper Clippy's ability to act or spread.
Also, once nanobots start killing people, power plants would shut down fast. Good luck replacing all coal mines, oil rigs, pipelines, trucks, nuclear plants, etc, with only the bots you could build in a few days. (Bots that themselves need electricity to run)