[brucethemoose2]

You're talking about seperate networks picking LORAs and such? Loading a huge number of embeddings or swapping between sub/additive networks or whatever is not very efficient either, and right now the LLM itself is quite monolithic.

And training such a decision tree seems like it would take a very long time.

The OpenAI CEO has talked about using subnetworks instead of an omegamodel like everyone is using now, and that would make lots of what you describe (and straight up anonymous finetuning) more practical.