3 ms·
I'd settle for "as good as", not "better." I've had several similar experiences as the above poster. Most recently, I was playing around with an interview ques
by majormajor 4y ago
I'd settle for "as good as", not "better."
I've had several similar experiences as the above poster. Most recently, I was playing around with an interview question and removed a constraint and asked it to update its solution for it.
It gave a new solution, but it still didn't work on the new, harder input.
I pointed out exactly how it failed, and it said "ah, yes, you are right, that should produce True, not false"... and spit out exactly the same code.
...
So now the question is, is it overly mean to pick interview questions based on which ones can be extended in ways that GPT-4 doesn't understand? ;)
- literalAardvark 4y agoI wouldn't say it's overly mean. I guess if they find some hard limits to transformer based intelligence, questions like that will be how we decide which things are worth learning.
- hammyhavoc 4y agoI've encountered it agreeing I am correct then proceeding to serve the same code, or even worse, regressing and losing corrections made earlier. The longer you "talk" to it in a conversation, the worse the output becomes. It can feel like you're getting somewhere, but you're usually not. It's largely a waste of time, anybody who knows what they're doing will just do it properly. Anybody who doesn't know what they're doing will waste their time and likely never learn how to do things correctly, and their Dunning-Kruger complex will be in full-effect.