r/ChatGPT • u/moreveal • 4h ago
Other LLMs made it harder to know when to give up
I've noticed a weird effect from using LLMs all the time: it's become harder to know when to give up.
Before, you'd try the approaches you knew, look for solutions, and eventually reach a point where there was simply nowhere left to go. With LLMs, that point almost disappears. If one approach fails, there's always another one that sounds reasonable enough to try.
I had this happen while optimizing a module for Hashcat. I'd already tried everything I could think of and assumed I'd hit the limit. I kept throwing the problem at an LLM anyway. Most of its ideas went nowhere, until after a lot of attempts it found something that actually improved performance.
After something like that, ten failed attempts stop being a good reason to quit. You've already seen the eleventh one suddenly work.
So an unsolvable problem and a problem that's only a few prompts away from a solution can feel almost identical. It feels like we've lost a useful signal for when it's time to stop.
Has anyone else noticed this?
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u/bixofa 4h ago
Is that a bad thing?
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u/moreveal 4h ago
Yeah, kinda. You can waste hours on something that's just not solvable, while before you'd probably give up much earlier.
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u/bixofa 4h ago
How do you know if something is not solvable or not?
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u/moreveal 3h ago
You don't always know, that's the point. But sometimes you know the domain well enough to know there's nowhere left to go. LLM doesn't always know that.
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u/nomdeplume 4h ago
This is a problem when you replace knowledge with an LLM. Instead of having the knowledge to know what's possible and asking the LLM to implement... You just don't know if it's possible or not and are spending tokens to compensate for that
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u/310_619_760 4h ago
You've just described the beauty of why this AI industrial revolution is so incredible. Although I personally feel those of us who had to go through the pain staking efforts to learn technological material on their own appreciate and value it more.
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u/moreveal 4h ago
Yeah, I think I'd agree. Along with that downside, it makes things possible that weren't actually impossible before - we just lacked the experience or skills to figure them out.
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u/bill_txs 4h ago
Yes it's making some things which were ridiculous to consider doing possible to try. This can cause a problem with scope control on real projects.
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u/Shays_P 4h ago
But why do you have to know when to give up if itss solevable? One thing I love chatgpt voice for is trying to figure out the names of songs I cannot remember for the life of me but it keeps pulling little bits and melodies and singular words in the song together until we find it
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u/Angeline4PFC 4h ago
Yeah, but that's not unsolvable. Just hard. You know the song exists; it's just a matter of finding it. But an LLM will also keep trying something that is not solvable at all as long as the user keeps trying. I don't remember it even saying, that's it. We tried everything; let's give up.
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u/SylviaJarvis 3h ago
"...is completely impossible because everyone else has already failed."
"Good. Let me try, and we'll know for sure, won't we?"
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