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Comment by allarm | Hacker News Reader

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allarm·

> responded

And the results are just awful.

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Hell yeah, no argument there

- but in this case I wouldn't advocate for [dead]ing a mostly AI response as it was exactly what was asked for and it compares AI models when asked for potato based dad jokes.

Of course they're awful, they're jokes about potatoes and poems about lemons.

The question is, can you tell that a machine wrote all of them? If so, how?

Nope I guess can't tell between machine written and mediocre jokes.

Models are structurally biased toward the expected, which is the opposite of what makes a joke land or a poem transcend.

I think you could make that case for poetry but I'm not sure about jokes. Great poems tell us something new or make us feel something new, which is hard to do when the subject is lemons, while jokes work by wedging the familiar into new contexts.

That's why the jokes work somewhat better than the poems here. I genuinely laughed at "Are those chips?" Which came from the model running on my own freakin' GPU.

Yeah I mean I also chuckle at good (or cheap) puns sometimes. But wordplay and puns are the current ceiling of LLMs. Good at them because they're purely structural (pattern-match on phonetics, then swap the meaning). In that bit, there's no buildup, no callbacks, no escalation, no expectations to subvert, no thesis, no perspective.

Grounded, buried, couchy, deep-seated, eyes, baked... It's like a thesaurus!

I feel like human comedians would have to deal with a lot of layered subtleties. They would make the potatoes _serve the bit_ instead of _be the bit_.

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