> The issue I think is that it's pulling from too many sources. There are plenty of sources that are pretty machine readable that will give it good answers. There's a lot of training that can be eked out from the legal databases that already exist that could make it a lot better. If it takes in too much information from too many sources, it tends to get garbled.

No, this is a common misunderstanding about the way these things work. A LLM is not really pulling from any sources specifically. It has no concept of a source. It has a bunch of weights that were trained to predict the next likely word, and those weights were tuned by feeding in a large amount of text from the internet.

Improving the quality of the sources used to train the weights would likely help, but would not solve the fundamental problem that this isn't actually a lossless knowledge compression algorithm. It's a statistical machine designed to guess the next word. That makes it fundamentally non-deterministic and unsuitable for any task where factual correctness matters (and there's no knowledgeable human in the loop to issue corrections).