[rickspencer3]

In my experience, LLVMs are not about being provided facts. They are about synthesizing new content and insights based on the model and inputs.

Rather than asking it about facts, I find it useful to derive new insights.

For example: "Tell me 5 topics about databases that might make it to the front page of hacker news." It can generate an interesting list. That is much more like the example they provided in the article, synthesizing a bed time story is not factual.

Also, "write me some python code to do x" where x is based on libraries that were well documented before 2022 also has similarly creative results in my experience.