LLMs lack the human nuance that a good Wikipedia article requires. Weighing quality sources and digesting them in the most useful way that a human would want and expect — that is very difficult for both humans and machines, and it is why Wikipedia as a whole is such a treasure: Because a community of editors take the time to tweak the articles and aim for perfection.
There are guidelines across all Wikipedia articles that make a good experience for the reader. We can’t even get the world’s greatest LLMs to follow a set of rules in a small conversation.
In my opinion simply using a dataset of high quality books and highly rated academic journals is enough to surpass current Wikipedia quality.
In my experience when using LLMs as a replacement for Wikipedia (learning about history), it is often of higher quality in niche topics and far less biased in political contentious areas
For me Wikipedia is only good for introductions and exploration. You don't have time to read a dense tome but also don't have enough experience in reading research papers in that area? Wikipedia it is then.
Wikipedia is the tabloid equivalent for scientific topics.
LLMs tend to be much more useful for niche topics, because they've most likely been trained directly on the source itself.
LLMs lack the human nuance that a good Wikipedia article requires. Weighing quality sources and digesting them in the most useful way that a human would want and expect — that is very difficult for both humans and machines, and it is why Wikipedia as a whole is such a treasure: Because a community of editors take the time to tweak the articles and aim for perfection.
There are guidelines across all Wikipedia articles that make a good experience for the reader. We can’t even get the world’s greatest LLMs to follow a set of rules in a small conversation.