Right-sizing language models is something I'm really here for. I find that a 1.5B parameter model fronting simple questions from a backing RAG source that a larger model gradually works on is more scalable. Classic information sources and stores can be QA'd, and they don't have such huge energy footprints.
AI will work out better if we give humans, classic code, SLMs, and frontier LLMs the roles they're right-sized for, and ensure data privacy and individual dignity at every stage of the contract.
