Comment by anon373839
2 days ago
> You just can't compress the entire human knowledge into a 30GB file
Fortunately, that isn’t necessary! What LLMs need is a level of fluency with key concepts so that they can (1) make effective use of retrieval tools and (2) understand the material in the context window. 30GB-sized models can absolutely store enough knowledge to do this.
Here is an example from the field of law. Most lawyers who have litigated contract disputes in California know about Civil Code § 1717, which makes any contract providing for attorney fees to a prevailing party mutual, so that even if the contract was written to be one-sided, it won’t be enforced that way. It’s a simple enough concept, but there are many more particulars to it, such as what happens when the fee provision is only written to apply to part of the contract. (Answer: it depends on other facts.)
When a lawyer recognizes that they’re in a situation where § 1717 is relevant, the first thing they will do is pull the statute and read it, because nobody has it memorized. And they don’t need to.
> (1) make effective use of retrieval tools and (
A downside is that you can't just download a lot of that knowledge, vs with the weights the copyright infringement has been outsourced to the lab. Nor can you just search for the info because the internet as a whole is increasingly aggressive at blocking anything that looks like an AI agent.
I'd love to see more retrieval powered local AI-- I think it's an area that open source development could excel. ... but there are advantages of having the knowledge in the weights!
Perhaps what needs happen is for someone to make an "ultrapedia", an AI restatement of a huge library of reference works-- created expressly for the purpose of being a locally stored corpus for AI agents.
I wonder how much more effective LLMs would be at general knowledge if you just download wikipedia and set up an MCP for it.