One important distinction is that the strength of LLMs isn't just in storing or retrieving knowledge like Wikipedia, it’s in comprehension. 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. They can explain complex ideas in simpler terms, adapt responses based on the user's level of understanding, and…
An unreliable computer treated as a god by a pre-information-age society sounds like a Star Trek episode.
Local LLMs versus offline Wikipedia
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Re: Local LLMs versus offline Wikipedia
#32One important distinction is that the strength of LLMs isn't just in storing or retrieving knowledge like Wikipedia, it’s in comprehension. 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. They can explain complex ideas in simpler terms, adapt responses based on the user's level of understanding, and…
Re: Local LLMs versus offline Wikipedia
#33One important distinction is that the strength of LLMs isn't just in storing or retrieving knowledge like Wikipedia, it’s in comprehension. 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. They can explain complex ideas in simpler terms, adapt responses based on the user's level of understanding, and…
An unreliable computer treated as a god by a pre-information-age society sounds like a Star Trek episode.
On the other hand, real history if filled with all sorts of things being treated as a god that were much worse than "unreliable computer". For example, a lot of times it's just a human with malice.
So how bad could it really get
Re: Local LLMs versus offline Wikipedia
#34Wouldn’t Wikipedia compress a lot more than llms? Are these uncompressed sizes?
Re: Local LLMs versus offline Wikipedia
#35One important distinction is that the strength of LLMs isn't just in storing or retrieving knowledge like Wikipedia, it’s in comprehension. 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. They can explain complex ideas in simpler terms, adapt responses based on the user's level of understanding, and…
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.
Re: Local LLMs versus offline Wikipedia
#36Earlier quoted context omitted.
we did that and still do. people just don't buy encyclopedias that much nowadays
Imagine taking the whole Web, removing spam, duplicates, bad explanations It will be the free new Wikipedia+ to learn anything in the best way possible, with the best graphs, interactive widgets, etc What LLMs have for free but humans for some reason don’t In some places it is possible to use copyrighted materials to educate if not directly for profit
Re: Local LLMs versus offline Wikipedia
#37One important distinction is that the strength of LLMs isn't just in storing or retrieving knowledge like Wikipedia, it’s in comprehension. 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. They can explain complex ideas in simpler terms, adapt responses based on the user's level of understanding, and…
Re: Local LLMs versus offline Wikipedia
#38Wouldn’t Wikipedia compress a lot more than llms? Are these uncompressed sizes?
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.
Re: Local LLMs versus offline Wikipedia
#39One important distinction is that the strength of LLMs isn't just in storing or retrieving knowledge like Wikipedia, it’s in comprehension. 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. They can explain complex ideas in simpler terms, adapt responses based on the user's level of understanding, and…
To be fair, so do humans and wikipedia.
Re: Local LLMs versus offline Wikipedia
#40Earlier quoted context omitted.
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?
Try any article on a controversial issue.