Live data from Hacker News

Training a trillion parameter model to be funny

jokegen.sdan.io

1–10 of 42 posts

Re: Training a trillion parameter model to be funny

#6
I once had a vivid dream that AI robots had taken over & were keeping humans around because they'd not yet mastered comedy. All of human culture globally was a comedy arms race with 24/7 open mic comedy jams on every corner.

They (the machines) had billboards/signage everywhere showing the estimated time left for humanity. A really good joke would lead the timer to grow (until they figured out how to produce the general patterns needed to both create and appreciate the joke).

Re: Training a trillion parameter model to be funny

#8
post #3

It would be easier to judge this if the jokes weren't 90% about AI and silicon valley, understandable only to people who subscribe to astralcodexten

I thought this one was not bad:

    [write a joke about thinking machines and the idea of tropes]

    it's funny how enemies to lovers is a common trope that's uncommon in real life and lovers to enemies is an uncommon trope that's common in real life

Re: Training a trillion parameter model to be funny

#9

I once had a vivid dream that AI robots had taken over & were keeping humans around because they'd not yet mastered comedy. All of human culture globally was a comedy arms race with 24/7 open mic comedy jams on every corner. They (the machines) had billboards/signage everywhere showing the estimated time left for humanity. A really good joke would lead the timer to grow (until they figured out how to produce the gene…

openclaw, turn this into a broadway production, book me two front row seats, hire an escort..... brunette, 28, slim waist, sweet face, hates comedy and AI

Re: Training a trillion parameter model to be funny

#10
Circa GPT-3.5 to GPT-4o I was involved in some research in figuring out how to make LLMs funny. We tried a bunch of different things, from giving it rules on homonym jokes [1], double-entendre jokes, fine tuning on comedian transcripts, to fine tuning on publicly rated joke boards.

We could not make it funny. Also interesting was that when CoT research was getting a lot of attention, we tried a joke version of CoT, asking GPT4 to explain why a joke was funny in order to produce training set data. Most of the explanations were completely off base.

After this work, I became a lot less worried about the GAI-taking-over narrative.

Funny is very, very hard.

[1] without a dictionary, which at first seems inefficient, but this work demonstrated that GPT could perfectly reconstruct the dictionary anyway

Post reply on HN