"this just in, tool behaves predictably outside of imagined specification"
LLMs aren't random name generators any more than a hammer is a screwdriver.
Ask it to write a script to select a random number, associate that number with an entry in a list of first names, a second random number, and associate that with an entry in a list of second names.
Presto bang-o, you've got a bespoke random name generator.
Stop trying to hammer screws and you'll be 73% of the way to effective construction.
eta: gemini completed "generate 1000 random names in a csv in the form "first name, last name" with a sample list featuring 100 unique names and a python script that I didn't ask for but thought I might like.
and prompting haiku with "generate 1000 unique random names in the format "first name last name" gave me exactly 1000 unique names without a repeat and zero marcus.
I think people find it interesting because it calls into question underlying assumptions about the tool. What would you say the tool is for? Programming?
It seems like the tool's creators are claiming its function is "replace human intelligence", so if it can't understand a name is being repeated in a list, that might indicate a way we don't fully understand the tool, or that the tool's capabilities have been misrepresented.
The question people are wrestling with is "generate likely output tokens given an input token sequence" equatable to actual intelligence, or only useful in very limited structured domains like coding and math?