OK you read the headline.
Imagine if Caliber had an AI tool that trained itself on all its books such that a user could ask a question regarding those specific books. And then extrapolate. Imagine if anyone anywhere could then ask questions to your local AI and get answers without actually sharing your books.
Right now I host my own Caliber server but I don’t even know if I can search a term and get a particular book that contains thar term. I think it can search the title and metadata. I’m probably wrong. But the point is that it could be so much more. And it could circumvent the copyright laws that have always held back knowledge.
Like maybe my car broke down and I could ask IA why and how to fix it. Then it would start asking for the make and model and what sort of sounds it made. It would then search forums, our books and formulate an answer composed in the form of a book specifically written for me about my car’s particular problem and how to solve it. Maybe better just a speech that you could listen to while fixing the car step by step…“now look a little to the left and you’ll find a large box with 3 screws…”
It would be awesome to have that locally for my books and have access to everyone else’s knowledge in books too.
Rag is fucking awesome, But in its current state it can’t handle unlimited amounts of data. On consumer machines I think you can throw around 100 megs at it before it starts losing it That’s quite a lot of text, but not really a decent collection of books. They might be able to get away with separating the books into categories and adding them as different knowledge bases. They’d have to select which knowledge base they wanted to ask but if they could keep the size down it might work relatively well
I fed mine about a year’s worth of slack traffic from work. I would ask it how many times people had trouble with a certain system. It would say three, meanwhile there were 500 tickets in the system of people having trouble with it.
No if I asked it about those three things it would have great detail. I can even ask it for sentiment of people that were talking about it It would recognize reasonably well if they were upset, understanding or angry.