It's a different style of comedy. Absurdism vs. joke setups (and not quite nailing it)

Uncensored LLMs are funnier but most comedy just falls flat in text format. Once the uncensored multimodal models start rolling out we’ll get some real laughs.

Moshi is actually pretty funny just for having a 72 IQ

https://www.moshi.chat/

I would argue that Markov chains were a better tool for comedic purposes. Notice that in all of the examples of using Markov chains, the person would see a potential, come up with a purpose, exercise the setup, and then fill the setup with generated text. Likewise in a random generation examples, the person would asses the results, then find what parts were actually funny, and choose to spread this parts. LLMs output has less potentially funny results, it has less potential for unexpectedly change realistic-sounding output to absurdist output, and so as a tool it is less fit for comedic purposes.

I chuckled a bit. They are OK, if you don't get exposed to them too often. And with an LLM you can get as much exposure as you want (and all of the jokes are naturally from roughly the same probability distribution).

I don't expect too much until AI self-play learning will be made possible, so I don't get disappointed by the expected shortcomings.

It's the "impressed by the spectacle" one. I tried jokes with LLMs many times, and they're always this. Riffing on a couple of themes loosely related to what was asked. Always unfunny and uncreative.

LLMs were never very good at directly generating original jokes, for a simple reason: writing a good joke generally starts with finding a good punchline, and then setting it up. An LLM generating token after token will first write a set-up, and then try to shoehorn a punchline into it. Prompt engineering can fairly easily work around this, but just straight-up asking an LLM for a joke never really produced good results on average.