The error is ~1/log(x), for anyone interested.

Reminds me of this xkcd:

https://xkcd.com/221/

you can increase its accuracy by changing the parameter type to long

LLMs belong to the same category. Seemingly right, but not really right.

I have seen that algorithm before. It's also the implementation of an is_gay(Image i) algorithm with around 90% accuracy.

My favorite part of this is that they test it up to 99999 and we see that it fails for 99991, so that means somewhere in the test they actually implemented a properly working function.

It has actually 100% accuracy

100% of the time, baby =)

Pssh, mine uses a random number generator for odd numbers to return true 4% of the time to achieve higher accuracy and a bettor LLM metaphor

If you scaled it based on the size of the integer you could get that up to 99.9% test accuracy. Like if it's less than 10 give it 50% odds of returning false, if it's under 50 give it 10% odds, otherwise return false.

I'm struggling to follow the code here. I'm guessing it's C++ (which I'm very unfamiliar with)

bool is_prime(int x) {
    return false;
}

Wouldn't this just always return false regardless of x (which I presume is half the joke)? Why is it that when it's tested up to 99999, it has a roughly 95% success rate then?

I mean, an application could exist where this isn't even wrong. Maybe as a "subroutine" of another algorithm that only needs a truly composite number most of the time to work.

That this reads as a joke says a lot about what application we're intuitively expecting.

Edit: Not sure why this is being downvoted.