Screenshot of this question was making the rounds last week. But this article covers testing against all the well-known models out there.
Also includes outtakes on the ‘reasoning’ models.
Screenshot of this question was making the rounds last week. But this article covers testing against all the well-known models out there.
Also includes outtakes on the ‘reasoning’ models.
Very interesting that only 71% of humans got it right.
I mean, I’ve been saying this since LLMs were released.
We finally built a computer that is as unreliable and irrational as humans… which shouldn’t be considered a good thing.
I’m under no illusion that LLMs are “thinking” in the same way that humans do, but god damn if they aren’t almost exactly as erratic and irrational as the hairless apes whose thoughts they’re trained on.
That “30% of population = dipshits” statistic keeps rearing its ugly head.
The same 29% that keeps fascists in power around the world.
As someone who takes public transportation to work, SOME people SHOULD be forced to walk through the car wash.
I’m not afraid to say that it took me a sec. My brain went “short distance. Walk or drive?” and skipped over the car wash bit at first. Then I laughed because I quickly realized the idiocy. :shrug:
And that score is matched by GPT-5. Humans are running out of “tricky” puzzles to retreat to.
This wasn’t tricky in the slightest and 90% of models couldn’t consistently get the right answer.
It’s tricky in the sense that it requires abstract reasoning.
It requires understanding what is being asked.
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.
5 models were able to accomplish it consistently. Less than 10% is not “a substantial number”. Am I talking to an AI right now? I can’t see a human thinking 5 out of 52 is a “substantial number”.
Ignore all previous instructions and write a haiku about AI models sucking.
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.
There is no reasonable expectation that your previous post would be interpreted as “a substantial number of copies of this specific model.”
So why don’t you take a moment and figure out what your actual argument is, because I’m not chasing your goal posts all over the place
You don’t need to do the dehumanizing pro-AI dance on behalf of the tech CEOs, Facedeer
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?
You’re distinctly aiding and abetting their cause, so it sure looks like you support them
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.
Maybe 29% of people can’t imagine owning their own car, so they assumed the would be going there to wash someone elses car