this post was submitted on 05 Dec 2024
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When it's important you can have an LLM query a search engine and read/summarize the top n results. It's actually pretty good, it'll give direct quotes, citations, etc.
And some of those citations and quotes will be completely false and randomly generated, but they will sound very believable, so you don't know truth from random fiction until you check every single one of them. At which point you should ask yourself why did you add unneccessary step of burning small portion of the rainforest to ask random word generator for stuff, when you could not do that and look for sources directly, saving that much time and energy
I guess it depends on your models and tool chain. I don't have this issue but I have seen it for sure, in the past with smaller models no tools and legal code.
As a side note, I feel like this take is intellectually lazy. A knife cannot be used or handled like a spoon because it's not a spoon. That doesn't mean the knife is bad, in fact knives are very good, but they do require more attention and care. LLMs are great at cutting through noise to get you closer to what is contextually relevant, but it's not a search engine so, like with a knife, you have to be keenly aware of the sharp end when you use it.
I, too, get the feeling, that the RoI is not there with LLM. Being able to include "site:" or "ext:" are more efficient.
I just made another test: Kaba, just googling kaba gets you a german wiki article, explaining it means KAkao + BAnana
chatgpt: It is the combination of the first syllables of KAkao and BEutel - Beutel is bag in german.
It just made up the important part. On top of chatgpt says Kaba is a famous product in many countries, I am sure it is not.