I think the slow down / pause vs acceleration framing is broken b/c it assumes there's basically only one forward direction which is to big and general models.

I think the slow down / pause vs acceleration framing is broken b/c it assumes there's basically only one forward direction which is to big and general models. Why should that be the case? What if instead of building one big scary AI god, we built an ecosystem of extremely effective, efficient and predictable, reliable tools? Tools that are specialized for particular purposes could potentially be safer, more efficient, more reliable and effective, and even more profitable for their makers. We currently put science, engineering, general question answering, paper-writing, "smart search", and chatting with a fantasy character all into the same token-prediction platform. We struggle with hallucinations when trying to make fact-based decisions using the same tool that our neighbor might be using for creating writing prompts (or at least was trained in part on fanfic). We pushed people to integrate giant generalist models into their workflows, tie in with tools, etc. And then a coworker can have a bot write slack updates that summarize progress on tickets from your teams project, at the cost of giving an untrustworthy agent access to a bunch of internal systems, and a small risk that it will do something crazy. And when it works, that's worth _something_ but probably our team would pay for that ability at a different price point than the models we use to build products. If I could do programming with a faster, specialized model that was trained not just to complete program text-tokens but on tuples of program text, compiler IR, program traces, etc, so it had a deep and explicit understanding of how the program would build and execute, and where the model was closely integrated with the language toolchain, I might be more productive and be willing to pay more than for a generalist model. I don't _need_ my coding model to be able to role play, or be able to potentially engineer a super-pathogen, and if the size and latency of my coding model could be lowered by entirely cutting out that possibility, everyone can be better off. Maybe bioscience applications are super valuable, in which case someone should build them. But does the model that suggests CRISPR edits to a model bacterium need to also know about computer security, and should it have scifi novels in its training data? Does it even need to be capable of producing unconstrained tokens, or should it be limited to producing in some relevant domain-specific language? And would labs be willing to pay more for a model that was specialized, and by construction unable to try to break out of its sandbox and post their experiment protocols to an obscure german wiki?