Comment by girvo
1 day ago
Yeah I'm quite surprised as to how all of those are supposed to be considered problems. They all make sense to me if we're trying to judge whether these tools are AGI, no?
1 day ago
Yeah I'm quite surprised as to how all of those are supposed to be considered problems. They all make sense to me if we're trying to judge whether these tools are AGI, no?
I think that any logic-based test that your average human can "fail" (aka, score below 50%) is not exactly testing for whether something is AGI or not. Though I suppose it depends on your definition of AGI (and whether all humans, or at least your average human, is considered AGI under that definition).
If I had a puzzle I really needed solved, then I would not ask a rando on the street, I would ask someone I know is really good at puzzles.
My point is: For AGI to be useful, it really should be able to perform at the top 10% or better level for as many professions as possible (ideally all of them).
An AI that can only perform at the average human level is useless unless it can be trained for the job like humans can.
> An AI that can only perform at the average human level is useless unless it can be trained for the job like humans can.
Yes, if you want skilled labour. But that's not at all what ARC-AGI attempts to test for: it's testing for general intelligence as possessed by anyone without a mental incapacity.
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This issue here is that people have different definitions of AGI. From the description. Getting 100% on this benchmark would be more than AGI and would qualify for ASI (Algorithmic Super Intelligence) not just AGI.
If you only outdo humans 50% of the time you're never going to get consensus on if you've qualified. Whereas outdoing 90% of humans on 90% of all the most difficult tasks we could come up with is going to be difficult to argue against.
This benchmark is only one such task. After this one there's still the rest of that 90% to go.
Beating humans isn't anywhere near sufficient to qualify as ASI. That's an entirely different league with criteria that are even more vague.
Even dumb humans are considered to have general intelligence. If the bar is having to outdo the median human, then 50% of humans don't have general intelligence.
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I’d be hesitant to call that ASI if it’s pretty obvious how you’d write a regular old program to solve it.
It’s not that simple since each problem is supposed to be distinct and different enough that no single program can solve multiple of them properly. No problem spec is provided as well iiuc so you can’t simply ask an LLM to generate code without doing other things.
3 replies →
It's not obvious at all. And I would say pretty much impossible without using machine learning. Even for ARC-AGI-1 there is no GOFAI program that scores high.
People are still debating whether these models exhibit any kind of intelligence and any kind of thinking. Setting the bar higher then necessary is welcome, but at this point I’m pretty sure everyone’s opinions are set in stone.
There's a single true definition of AGI, open the page about AGI on Wikipedia but using archive.org on a snapshot from 10 years ago.
All the rest is bullshit made up by LLM labs to make it seem like they hit AGI by dumbing down its definition.
https://web.archive.org/web/20150108000749/https://en.wikipe...
In retrospect, it seems obvious that we hit AGI by a reasonable "at least as intelligent as some humans" definition when o3 came out, and everything since then has been goalpost moving by people who have higher and higher bars for which percentile human they would be willing to employ (or consider intellectually capable). People should really just use the term "ASI" when their definition of AGI excludes the majority of humans.
Edit: Here's the guy who coined the term saying we're already there. Everything else is arguing over definitions.
https://x.com/mgubrud/status/2036262415634153624
> Well, Lars, I INVENTED THE TERM and I say we have achieved AGI. Current models perform at roughly high-human level in command of language and general knowledge, but work thousands of times faster than us. Still some major deficiencies remain but they're falling fast.
> They all make sense to me if we're trying to judge whether these tools are AGI, no?
As long as the mean and median human scores are clearly communicated, the scoring is fine. I think the human scores above would surprise people at first glance, even if they make sense once you think about it, so there's an argument to be made that scores can be misleading.