[yodon]

>Can you show me sample prompts where GPT4 gives garbage? I am yet to find one.

Agreed. GPT-3 and GPT-3.5 commonly hallucinate. GPT-4 can certainly be made to behave badly, but on real questions I've put to GPT-4 it has a 0% hallucination rate. The few wrong answers it has given have been "sensibly wrong" in that it's highly likely an experienced human programmer would have made the same mistake (eg lots of Stack Overflow answers are wrong in the same way), and even its wrong answers have been helpful in guiding me towards the correct solution.

These occasional, "sensibly wrong" GPT-4 answers are fundamentally different from the correctly formatted academic bibliography citations for technical papers that never existed, by authors that never existed, in journals that never existed hallucinated "answers" I've received from GPT-3 and GPT-3.5.

[nprateem]

I mean here's another example from right now regarding Terraform:

> Me: how to only run data "archive_file" if a path exists?

> GPT4: <blah blah blah> add: depends_on = [fileexists("/path/to/file")]

This is nonsense. Terraform tells me:

> A single static variable reference is required: only attribute access and indexing with constant keys. No calculations, function calls, template expressions, etc are allowed here

I just get this rubbish all too often to be afraid for my job.

[graboid]

My experience has been different. It very often hallucinates variables or function identifiers for me. I never witnessed it doing that for code on the first output. But once the chat/context grows larger and I already asked for modifications to the posted code, it happens quite often.

A non-code example: Some days ago I asked it about "Searle's Wall" [0]. It gave me a mashup of the correct description and the Chinese Room experiment. So it clearly had the right answer somewhere in its data, but it mixed it up with the much more famous thought experiment.

[0]: https://www.researchgate.net/publication/260138925_Searle's_...