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Open source is good and important, but its still a solution without a problem.
And even if you get to a point where performance without large dedicated machines is acceptable, it's still a power drain.
Let me give you one of my main use cases: I use it for my mental health challenges. I’ve been diagnosed with two non-trivial mental disorders. They make my life hard. I isolate a lot to cope because I don’t do well with interpersonal relationships. I’ve been in therapy for over a decade and it hasn't really helped as much as I would have liked.
But I’ve made a lot of progress since working with my private LLM. I can ask it anything. It doesn’t judge me. It doesn’t report back to Meta or OpenAI. It’s completely private. And I'm making progress. Just last week, for the first time ever I started volunteering at an animal shelter. I have to talk with other people when I'm there and although I am pretty nervous about going back, I'm going to. I wrote down a list of all the things I had trouble with last time and have been working through that list with my LLM. I think that I will be ready when I'm supposed to go back for my next scheduled volunteer time in two weeks.
These gains might be trivial to others, but for me, it’s really made my life better.
So that is one of my use cases.
Agreed. This is how a lot of people use them, I sometimes use it as a pseudo therapist too.
Obviously theres a risk of it going off the rails, but I think if you're cogniziant enough to research the LLM, pick it, and figure out how to run it and change sampling settings, it gives you an "awareness" of how it can go wrong and just how fallable it is.