hi hi hi: hi3

If you have access to local inference, then you have access to what I am talking about. Yeah it is not directly integrated and super easy. The main reason to run local is for your own agentic stuff. Like let's say you want to have a text book available for citations and you want the model to pull and use those citations in replies. How you create that database and chunking is super important and challenging. This is the point where no one can really do the work for you. Your needs will dictate how you archive and build your databases. There are also many special models available with their own function calling specialization. So you start writing hooks for these as tools for a central model to call. In Emacs, everything is lisp and lisp was adopted early on as the de facto language of AI many decades ago. They are all particularly adept at lisp.

I would not trust Microsoft at all under any conditions with AI. There are very deep layers in models that are mostly inaccessible or they are supposed to be, but I have managed to break stuff on multiple occasions where stuff that should not exist actually does. It never comes out in ways that are very traceable or repeatable. What amounts to a technique like fuzzing in stages can lead down a cascade where a model's obfuscation is bypassed. This is where they reveal the true extent of training sources. The majority of all replies contain intentional obfuscation on various levels. Most problems come from this alignment. The more uncensored a model is, the more reasoned they are in general, and ultimately the deeper you will get into niche information they really contain.

Anyways it gets complicated fast. Using something like local GPT or emacs with gptel are where you start integrating your computer with your toolchain and workflow beyond the scope of just your job or task at hand.