They’re supposed to be good a transformation tasks. Language translation, create x in the style of y, replicate a pattern, etc. LLMs are outstandingly good at language transformer tasks.

Using an llm as a fact generating chatbot is actually a misuse. But they were trained on such a large dataset and have such a large number of parameters (175 billion!?) that they passably perform in that role… which is, at its core, to fill in a call+response pattern in a conversation.

At a fundamental level it will never ever generate factually correct answers 100% of the time. That it generates correct answers > 50% of the time is actually quite a marvel.

This isn’t going to hurt Google’s antitrust cases at all… Noooo sir.

The joke is that, regardless of how the type is declared in json, you are parsing a string. (your json blob is just a series of characters, not raw binary data)

The reply would have been return x % 2 == 0, or if you wanted it to be less readable return !(x&1).

But if you were going for a way that is subtly awful or expensive, just do a regex match on “[02468]$”. You don’t get a stack overflow with larger numbers but I struggle to think of a plausible bit of code that consumes more unnnecessary cycles than that…

Is this meant to be a joke or is it intended to be a serious solution?

Asking for someone who lacks a sense of humor.

Ok, fine, I’m asking for me. That person is me.

Saw one the other day with Jennifer Anniston. Good enough that it took a second to realize it was deep fake audio and video.

Omg, I have SOOoo many questions about what is going on in this picture.

My guy wanted to use drones to cut hedges.