Edit: apparently not, the author is just really good at coming up with ai adverse puzzles. When testing ChatGPT did much better on last year’s puzzles.
> Here are things LLMs didn't influence:
> The story.
> The puzzles.
> The inputs.
> I don't have a ChatGPT or Bard or whatever account, and I've never even used an LLM to write code or solve a puzzle, so I'm not sure what kinds of puzzles would be good or bad if that were my goal. Fortunately, it's not my goal - my goal is to help people become better programmers, not to create some kind of wacky LLM obstacle course. I'd rather have puzzles that are good for humans than puzzles that are both bad for humans and also somehow make the speed contest LLM-resistant.
> I did the same thing this year that I do every year: I picked 25 puzzle ideas that sounded interesting to me, wrote them up, and then calibrated them based on betatester feedback. If you found a given puzzle easier or harder than you expected, please remember that difficulty is subjective and writing puzzles is tricky.
At least one betatester might very well have been using chatgpt.
Some people have even speculated that the problems this year were deliberately formulated to foil ChatGPT, but Eric actually denied that this is the case.
Here are things LLMs didn't influence: The story. The puzzles. The inputs.
I did the same thing this year that I do every year: I picked 25 puzzle ideas that sounded interesting to me, wrote them up, and then calibrated them based on betatester feedback.
It's interesting it turns out this year was not written with gpt in mind.
aka new unique problems that aren't in its training set