I'm excited for the big jump in ARC-AGI scores from recent models, but no one should think for a second this is some leap in "general intelligence".
I joke to myself that the G in ARC-AGI is "graphical". I think what's held back models on ARC-AGI is their terrible spatial reasoning, and I'm guessing that's what the recent models have cracked.
Looking forward to ARC-AGI 3, which focuses on trial and error and exploring a set of constraints via games.
Agreed. I love the elegance of ARC, but it always felt like a gotcha to give spatial reasoning challenges to token generators- and the fact that the token generators are somehow beating it anyway really says something.
The average ARC AGI 2 score for a single human is around 60%.
"100% of tasks have been solved by at least 2 humans (many by more) in under 2 attempts. The average test-taker score was 60%."
https://arcprize.org/arc-agi/2/
Worth keeping in mind that in this case the test takers were random members of the general public. The score of e.g. people with bachelor's degrees in science and engineering would be significantly higher.
Random members of the public = average human beings. I thought those were already classified as General Intelligences.
Average human beings with average human problems.
What is the point of comparing performance of these tools to humans? Machines have been able to accomplish specific tasks better than humans since the industrial revolution. Yet we don't ascribe intelligence to a calculator.
None of these benchmarks prove these tools are intelligent, let alone generally intelligent. The hubris and grift are exhausting.
What's the point of denying or downplaying that we are seeing amazing and accelerating advancements in areas that many of us thought were impossible?
It can be reasonable to be skeptical that advances on benchmarks may be only weakly or even negatively correlated with advances on real-world tasks. I.e. a huge jump on benchmarks might not be perceptible to 99% of users doing 99% of tasks, or some users might even note degradation on specific tasks. This is especially the case when there is some reason to believe most benchmarks are being gamed.
Real-world use is what matters, in the end. I'd be surprised if a change this large doesn't translate to something noticeable in general, but the skepticism is not unreasonable here.
I would suggest it is a phenomenon that is well studied, and has many forms. I guess mostly identify preservation. If you dislike AI from the start, it is generally a very strongly emotional view. I don't mean there is no good reason behind it, I mean, it is deeply rooted in your psyche, very emotional.
People are incredibly unlikely to change those sort of views, regardless of evidence. So you find this interesting outcome where they both viscerally hate AI, but also deny that it is in any way as good as people claim.
That won't change with evidence until it is literally impossible not to change.
The hubris and grift are exhausting.
And moving the goalposts every few months isn't? What evidence of intelligence would satisfy you?
Personally, my biggest unsatisfied requirement is continual-learning capability, but it's clear we aren't too far from seeing that happen.
> What evidence of intelligence would satisfy you?
That is a loaded question. It presumes that we can agree on what intelligence is, and that we can measure it in a reliable way. It is akin to asking an atheist the same about God. The burden of proof is on the claimer.
The reality is that we can argue about that until we're blue in the face, and get nowhere.
In this case it would be more productive to talk about the practical tasks a pattern matching and generation machine can do, rather than how good it is at some obscure puzzle. The fact that it's better than humans at solving some problems is not particularly surprising, since computers have been better than humans at many tasks for decades. This new technology gives them broader capabilities, but ascribing human qualities to it and calling it intelligence is nothing but a marketing tactic that's making some people very rich.
(Shrug) Unless and until you provide us with your own definition of intelligence, I'd say the marketing people are as entitled to their opinion as you are.
> What evidence of intelligence would satisfy you?
Imposing world peace and/or exterminating homo sapiens
> Machines have been able to accomplish specific tasks...
Indeed, and the specific task machines are accomplishing now is intelligence. Not yet "better than human" (and certainly not better than every human) but getting closer.
> Indeed, and the specific task machines are accomplishing now is intelligence.
How so? This sentence, like most of this field, is making baseless claims that are more aspirational than true.
Maybe it would help if we could first agree on a definition of "intelligence", yet we don't have a reliable way of measuring that in living beings either.
If the people building and hyping this technology had any sense of modesty, they would present it as what it actually is: a large pattern matching and generation machine. This doesn't mean that this can't be very useful, perhaps generally so, but it's a huge stretch and an insult to living beings to call this intelligence.
But there's a great deal of money to be made on this idea we've been chasing for decades now, so here we are.
> Maybe it would help if we could first agree on a definition of "intelligence", yet we don't have a reliable way of measuring that in living beings either.
How about this specific definition of intelligence?
AGI would be to achieve that faster than an average human.I still can't understand why they should be faster. Humans have general intelligence, afaik. It doesn't matter if it's fast or slow. A machine able to do what the average human can do (intelligence-wise) but 100 times slower still has general intelligence. Since it's artificial, it's AGI.
Wouldn't you deal with spatial reasoning by giving it access to a tool that structures the space in a way it can understand or just is a sub-model that can do spatial reasoning? These "general" models would serve as the frontal cortex while other models do specialized work. What is missing?
That's a bit like saying just give blind people cameras so they can see.
I mean, no not really. These models can see, you're giving them eyes to connect to that part of their brain.
They should train more on sports commentary, perhaps that could give spatial reasoning a boost.