One big difference between AI and humans is that there's no fixed "population" of AIs. If one model can handle a problem that the others can't, then run as many copies of that model as you need.
It doesn't matter how many models can't accomplish this. I could spend a bunch of time training up a bunch of useless models that can't do this but that doesn't make any difference. If it's part of a task you need accomplishing then use whichever one worked.
It's nice in that it gives the various Discord competitors a longer period to work on getting their software spiffed up.
Yes. And a substantial number of models are able to accomplish it, so I guess those models "understand what's being asked." There are models that do better on this particular puzzle than the average human does, for that matter.
It's tricky in the sense that it requires abstract reasoning.
Whenever you want a view that's closest to the "truth", look at what the insurance rates are like. Insurance companies' whole business hinges on turning objective reality into money.
This could backfire on them, I recall several years back reading a study in which anti-abortion sentiment plummeted the moment subjects were asked whether the pregnant woman herself should be punished (not even executed, just punished) for getting an abortion.
It's an interesting bit of cognitive dissonance, the sentiment seemed to be "yeah, abortion is murder, the doctor's a murderer, but the person who hired him to do that murder is an innocent victim who must be protected."
In fact, I prefer the use of local AIs and dislike how the field is being dominated by big companies like Google or OpenAI. Unfortunately personal preferences don't change reality.
I'm not doing it on behalf of anyone. Should we ignore the technology because we don't like the specific people who are developing it?
And yet the best models outdid humans at this "car wash test." Humans got it right only 71.5% of the time.
Yeah, "AI is getting pretty good" is a very unpopular opinion in these parts. Popularity doesn't change the results though.
And that score is matched by GPT-5. Humans are running out of "tricky" puzzles to retreat to.
Alright, so swap in some different words if you don't like those. The basic point is the same - there's a bunch of models from different sources that can solve this, it's not just some weird one-off fluke.
Your own argument is a bit all over the place too, by the way. You said this puzzle "wasn't tricky in the slightest" and yet that "it requires understanding what is being asked." So only 71.5% of humans can accomplish this "not tricky in the slightest" problem, but there are some AI models that are able to "understand what is being asked"? Is "understanding" things not "tricky"?