Local LLMs versus offline Wikipedia

An unreliable computer treated as a god by a pre-information-age society sounds like a Star Trek episode.

I think some combination of both search (perhaps of an offline database of wikipedia and other sources) and a local LLM would be the best, as long as the LLM is terse and provides links to relevant pages.

I find LLMs with the search functionality to be weak because they blab on too much when they should be giving me more outgoing links I can use to find more information.

Indeed. Ideally, you don't want to trust other people's summaries of sources, but you want to look at the sources yourself, often with a critical eye. This is one of the things that everyone gets taught in school, everyone's says they agree with, and then just about no one does (and at times, people will outright disparage the idea). Once out of school, tertiary sources get treated as if they're completely reliable.

I've found using LLM's to be a good way of getting an idea of where the current historiography of a topic stands, and which sources I should dive into. Conversely, I've been disappointed by the number of Wikipedia editors who become outright hostile when you say that Wikipedia is unreliable and that people often need to dive into the sources to get a better understanding of things. There have been some Wikipedia articles I've come across that have been so unreliable that people who didn't look at other sources would have been greatly mislead.

A tangent - sounds like https://en.wikipedia.org/wiki/The_Book_of_Koli - a key plot component is a chatty Sony AI music player. A little YA, but a fun read..

In a 'rebooting society' doomsday scenario you're assuming that our language and understanding would persist. An LLM would essentially be a blackbox that you cannot understand or decipher, and would be doubly prone to hallucinations and issues when interacting with it using a language it was not trained on. Wikipedia is something you could gradually untangle, especially if the downloaded version also contained associated images.

> LLMs will return faulty or imprecise information at times

To be fair, so do humans and wikipedia.

> LLMs will return faulty or imprecise information at times, but what they can do is understand vague or poorly formed questions and help guide a user toward an answer.

- "'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' "

which means you'd still want wikipedia, as the impercision will get in the way of real progress beyond the basics.

the real valuable would be both of them. the LLM is good for refining/interpreting questions or longer form progress issues, and the wiki would be actual information for each component of whatever you're trying to do.

But neither are sufficient for modern technology beyond pointing to a starting point.

we did that and still do. people just don't buy encyclopedias that much nowadays

I’m a massive Wikipedia fan, have a lot of it downloaded locally on my phone, binge read it before bed, etc. Even so, I rarely go through talk pages or version history unless I’m contributing something. What would you see in an article that motivates you to check out the meta layers?

The downloads are (presumably) already compressed.

And there are strong ties between LLMs and compression. LLMs work by predicting the next token. The best compression algorithms work by predicting the next token and encoding the difference between the predicted token and the actual token in a space-efficient way. So in a sense, a LLM trained on Wikipedia is kind of a compressed version of Wikipedia.

Yes, they're uncompressed. For reference, `enwiki-20250620-pages-articles-multistream.xml.bz2` is 25,176,364,573 bytes; you could get that lower with better compression. You can do partial reads from multistream bz2, though, which is handy.

Because old laptop that can’t run a local LLM in reasonable time.

Now this is an avengers level threat.