[remram]

> couldn't believe they used so much Wikipedia to get their answers. This at least seems like an upgrade from that

I don't know if I would even agree with that. Wikipedia doesn't invent/hallucinate answers when confused, and all claims can be traced back to a source. It has the possibility of fabricated information from malicious actors, but that seems like a step up from LLMs trained on random data (including fabrications) which also adds its own hallucinations.

[bongoman42]

Unfortunately, there's plenty of wrong information on Wikipedia and the sources don't always say what the article is claiming. Another issue is that, all sources are not created equal and you can often find a source to back you up regardless of what you might want backed up. This is especially in politicised issues like autism, and even things that might appear uncontroversial like vaccines and so on.

[ikesau]

There's arbitrary "accuracy lowering" vandalism done by (i suspect) bots that alters dates by a few days/months/years, changes the middle initial of someone, or randomizes the output in an example demonstrating how a cipher works.

it can be hard to spot if no one's watching the article. puts me in a funk whenever I catch it.

[marcosdumay]

Some people edit chemistry articles replacing the reactions by stuff that doesn't make any sense or can't possibly work. Some people changes the descriptions of CS algorithms removing pre-conditions, random steps, or adding a wrong intermediate state. And, maybe the worst, somebody vandalizes all the math articles changing the explanations into abstract nonsense that nobody that doesn't already know their meaning can ever understand.

[remram]

Better than using an LLM which is (at best) trained on Wikipedia.

I'm not saying that Wikipedia is a silver bullet, I'm saying that LLMs are definitely worse. They have to be, by construction.