Back in the 2000s, one of my favorite programmers from the Before Times—Fabrice Bellard—came up with an algorithm for computing digits of pi that was so much better than the state of the art, he beat with a $3000 PC the record for speed of pi calculation, which had been established with a supercomputer.
Some bright spark—maybe they'll have Claude assist, maybe it'll trigger Claude's safety locks, I dunno—is going to derive a way to do transformer or other frontier AI inference in a really efficient manner on consumer hardware, making local models practical to run on the PCs people have today and nearly, if not actually, competitive with today's frontier models. "There is another theory which states that this has already happened"—perhaps several times already, and we just need a few more goes of the cycle. I find that for supposedly a crowd of the smartest dudes in the room, people in the Valley like to do things the stupid way around, by sheer fucking brute force: scale up massively, burn billions and trillions of VCbux on capex, aggressively conserve developer effort at the expense of everybody's CPU time and storage capacity—yours, your cloud provider's, your customers'... So I suspect, but at this time cannot prove, that there's a whole lot of headroom for optimization of AI inference, which has the potential to put some truly powerful models in the hands of ordinary people.
And that's very dangerous, because so much for pacing the frontier! If Joe Schmoe can build a mini-AI lab in his mancave, he can then gain access to a model that gives him all the big scary things Dario and Sam are worried about: instructions on how to build bombs or bioweapons, child porn generation, human sacrifice, cats living with dogs, mass hysteria! If you're concerned about an AI-mediated workplace panopticon, Joe Schmoe could, in principle, build one of those for his auto body shop with a local model. The only way to stop Joe from doing so is to stop Joe from acquiring the equipment it would take to run such a model.
Pacing the frontier is at least as much about pacing what you can compute as it is about what goes on in billion-dollar data centers. Any argument for limiting AI growth and development—and admittedly, there are some strong ones—is an argument against general purpose computing. So if we're really going to regulate AI, bend over for the laws that mandate OS/firmware/hardware-enforced restrictions on what binaries your computer may run. And so long open source. Oh well, those laws were coming anyway; that's what the age verification thing is all about. Society has determined that people can't be trusted with computers.