The flow I've been going through:
* Do this task with this constraint > GPT4 Does task
* Analyse all of the items and whether they adhere to the constraint > GPT4 "Apologies, I got some things wrong, here's what I did incorrect"
* Fix the things you did wrong, remember the constraint is of upmost importance > GPT4 "I have completed the task and fixed the constraint
* Analyse all of the items and whether they adhere to the constraint > GPT4 "Apologies, I got some things wrong, here's what I did incorrect"
...
At least it can analyse the results, but even then if you don't ask in the right way it will blatantly lie to you and tell you it's all correct when it's not.
What is the difference here? No hallucinations, everything correct… is it just random chance?
But on programming language and other logical question areas it does not matter much, as you can verify with logic if something is correct, and then it is incredible useful
There is no logic, no reasoning, no nothing. Yet people complain it's 'giving me wrong answers'. Well, it doesn't know what's it's giving you either way. It only knows the statistics or odds about the sentences it creates being similar to what others have said before.
As an aside, the claims that people are willing to make about language models are quite astounding considering that they never seem to realize that most of those claims apply to humans also...
My anecdote with technical information is exactly the opposite, unfortunately.
I routinely use it to help guide my research - generally about topics I know something about but want to know more.
It often will provide some response that is entirely wrong but looks very good. When called out, it apologizes, then proceeds to produce more information that's also not entirely correct. There's an artform to teasing out the right answer... but of course you have to be knowledgeable enough to know what is right in the first place.
The subtleties of correct or wrong can be very difficult to determine for a layperson. Without deep knowledge, one might be inclined to believe the first response it provides.
That's pretty terrifying when you think of the possible implications revolving around research, law, etc.