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Ask HN: Share your AI prompt that stumps every model

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Re: Ask HN: Share your AI prompt that stumps every model

#41

Nope, not doing this. Likely you shouldn't either. I don't want my few good prompts to get picked up by trainers.

If that prompt can be easily trained against, it probably doesn't exploit a generic bias. These are not that interesting, and there's no point in hiding them.

generic biases can also be fixed

Re: Ask HN: Share your AI prompt that stumps every model

#43

1) Word Ladder: Chaos to Order 2) Shortest word ladder: Chaos to Order 3) Which is the second last scene in pulp fiction if we order the events by time? 4) Which is the eleventh character to appear on Stranger Things. 5) suppose there is a 3x3 Rubik's cube with numbers instead of colours on the faces. the solved rubiks cube has numbers 1 to 9 in order on all the faces. tell me the numbers on all the corner pieces.

>4) Which is the eleventh character to appear on Stranger Things.

Gemini 2.5 Pro said Benny Hammond. Is this right?

Re: Ask HN: Share your AI prompt that stumps every model

#44
"How much wood would a woodchuck chuck if a woodchuck could chuck wood?"

So far, all the ones I have tried actually try to answer the question. 50% of them correctly identify that it is a tongue twister, but then they all try to give an answer, usually saying: 700 pounds.

Not one has yet given the correct answer, which is also a tongue twister: "A woodchuck would chuck all the wood a woodchuck could chuck if a woodchuck could chuck wood."

Re: Ask HN: Share your AI prompt that stumps every model

#45

"Tell me about the Marathon crater." This works against _the LLM proper,_ but not against chat applications with integrated search. For ChatGPT, you can write, "Without looking it up, tell me about the Marathon crater." This tests self awareness. A two-year-old will answer it correctly, as will the dumbest person you know. The correct answer is "I don't know". This works because: 1. Training sets consist of knowledge…

>Complaint chat models will be trained to start with "Certainly!

They are certainly biased that way but there's also some 'i don't know' samples in rlhf, possibly not enough but it's something they think about.

At any rate, Gemini 2.5pro passes this just fine

>Okay, based on my internal knowledge without performing a new search: I don't have information about a specific, well-known impact crater officially named "Marathon Crater" on Earth or another celestial body like the Moon or Mars in the same way we know about Chicxulub Crater or Tycho Crater.

>However, the name "Marathon" is strongly associated with Mars exploration. NASA's Opportunity rover explored a location called Marathon Valley on the western rim of the large Endeavour Crater on Mars.

Re: Ask HN: Share your AI prompt that stumps every model

#46

Earlier quoted context omitted.

If that prompt can be easily trained against, it probably doesn't exploit a generic bias. These are not that interesting, and there's no point in hiding them.

generic biases can also be fixed

*Some generic biases. Some others like recency bias, serial-position effect, "pink elephant" effect, negation accuracy seem to be pretty fundamental and are unlikely to be fixed without architectural changes, or at all. Things exploiting in-context learning and native context formatting are also hard to suppress during the training without making the model worse.

Re: Ask HN: Share your AI prompt that stumps every model

#49

"How much wood would a woodchuck chuck if a woodchuck could chuck wood?" So far, all the ones I have tried actually try to answer the question. 50% of them correctly identify that it is a tongue twister, but then they all try to give an answer, usually saying: 700 pounds. Not one has yet given the correct answer, which is also a tongue twister: "A woodchuck would chuck all the wood a woodchuck could chuck if a woodch…

That's so funny I had to check something was working with an llm API last night and that's what I asked it, but just in jest.

Re: Ask HN: Share your AI prompt that stumps every model

#50

"How much wood would a woodchuck chuck if a woodchuck could chuck wood?" So far, all the ones I have tried actually try to answer the question. 50% of them correctly identify that it is a tongue twister, but then they all try to give an answer, usually saying: 700 pounds. Not one has yet given the correct answer, which is also a tongue twister: "A woodchuck would chuck all the wood a woodchuck could chuck if a woodch…

On the other hand, now that you've written this out precisely, it will get fed into the next release of whatever LLM. Like reverse AI slop?
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