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I got the highest score on ARC-AGI again swapping Python for English

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Re: I got the highest score on ARC-AGI again swapping Python for English

#91

Earlier quoted context omitted.

Our thinking is also based only on events that occurred previously in time. We don’t use events in the future.

Is this a certainty? I thought it was an open question whether quantum effects are at play in the brain, and those have a counterintuitive relationship with time (to vastly dumb things down in a way my grug mind can comprehend).

I'm aware of a counterintuitive relationship with space, but what's the one with time?

Re: I got the highest score on ARC-AGI again swapping Python for English

#92
post #68

Earlier quoted context omitted.

It's trivial to demonstrate that LLMs are pattern matching rather than reasoning. A good way is to provide modified riddles-that-aren't. As an example: > Prompt: A man working at some white collar job gets an interview scheduled with an MBA candidate. The man says "I can't interview this candidate, he's my son." How is this possible? > ChatGPT: Because the interviewer is the candidate’s mother. (The riddle plays on t…

> It's trivial to demonstrate that LLMs are pattern matching rather than reasoning. Again, this is just asserting the premise that reasoning cannot include pattern matching, but this has never been justified. What is your definition for "reasoning"? > This is clearly pattern matching and overfitting to the "doctor riddle" and a good demonstration of how there's no actual reasoning going on. Not really, no. "Bad reaso…

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Re: I got the highest score on ARC-AGI again swapping Python for English

#93

Earlier quoted context omitted.

Well there’s no evidence of this that I’ve seen. If so, then maybe that is what is the blocker for AGI.

I think it's more that there isn't yet evidence against it. In other words, we're not sure or not if the brain has some kind of special sauce that doesn't just reduce to linear algebra.

Quantum effects definitely reduce to linear algebra however.

Re: I got the highest score on ARC-AGI again swapping Python for English

#94
post #89

Earlier quoted context omitted.

People make the same sort of mistakes.

Please explain how this is relevant to the topic at hand. Thanks!

You claim that AI is patterned matching instead of reasoning, but the psychological literature is clear that people reason by pattern matching. As evidenced by the fact that people tend to make the same sorts of mistakes when reasoning quickly.

Ask someone who has made such a mistake to think a little more on it, and they’ll notice their error. Ask a reasoning model to do literally the same thing, to “think” on it, and it will also notice its error.

If you’re still insist that AI are not reasoning here, then neither are people.

Re: I got the highest score on ARC-AGI again swapping Python for English

#95

Can someone explain to me why a new LLMs ability to solve highly publicized puzzles is not "just" (sorry) it having access to the blog posts talking about those puzzles? It's fine, that's what I would do to solve them, but it doesn't obviously and immediately make me confident in new reasoning capability w that suspicion floating around.

Should be easy to test by picking two similar models with different publishing dates (before and after ARC v2), and also comparing with/without the new reasoning technique from the article.

Re: I got the highest score on ARC-AGI again swapping Python for English

#96

Earlier quoted context omitted.

Well there’s no evidence of this that I’ve seen. If so, then maybe that is what is the blocker for AGI.

I think it's more that there isn't yet evidence against it. In other words, we're not sure or not if the brain has some kind of special sauce that doesn't just reduce to linear algebra.

"I think it's more that there isn't yet evidence against it."

We don't? AFAIK we have no proof of anyone being able to see into the future. Now maybe there are other manifestations of this, but I know of no test today that even hints at it.

Re: I got the highest score on ARC-AGI again swapping Python for English

#97

Earlier quoted context omitted.

Our thinking is also based only on events that occurred previously in time. We don’t use events in the future.

This is unhelpfully obtuse

What's obtuse about it? It's honestly a very straightforward statement. Every thing we think or say is a function of past events. We don't incorporate future events into what we think or say. Even speculation or imagination of future events occurred in the past (that is the act of imagining it occurred in the past).

It's really a super simple concept -- maybe it's so simple that it seems obtuse.

Re: I got the highest score on ARC-AGI again swapping Python for English

#98
post #5

I've been testing LLMs on Sokoban-like puzzles (in the style of ARC-AGI-3) and they are completely awful at them. It really highlights how poor their memory is. They can't remember abstract concepts or rules between steps, even if they discover them themselves. They can only be presented with lossy text descriptions of such things which they have to re-read and re-interpret at every step. LLMs are completely helpless…

Try to get your LLM of choice to find its way out of a labyrinth that you describe in text form. It's absolutely awful even with the simplest mazes. I'm not sure the problem here is memory, though? I think it has to do with spatial reasoning. I'd be willing to bet every company right now is working on spatial reasoning (at least up to 3D) and as soon as that is working, a huge amount of pieces will fall into place.

Spatial reasoning is weak, but still I frequently see models come up with the right answer in reasoning steps, only to make the wrong move in the following turn because they forget what they just learned. For models with hidden reasoning it's often not even possible to retain the reasoning tokens in context through multiple steps, but even if you could the context windows are big but not big enough to contain all the past reasoning for every step for hundreds of steps. And then even if they were the retrieval from context for abstract concepts (vs verbatim copying) is terrible.

Text is too lossy and inefficient. The models need to be able to internally store and retrieve a more compact, abstract, non-verbal representation of facts and procedures.

Re: I got the highest score on ARC-AGI again swapping Python for English

#99

Earlier quoted context omitted.

There is no source and arguing this is dumb because no one knows what reasoning or understanding is. No one. So all we have is "Does it swim like a duck, look like a duck, quack like a duck?"

I’m sympathetic to your point, but this isn’t quite fair. The field of psychology does exist.

Neuroscience is the field that would be closest to this. But even they are empty handed with evidence and heavy with hypotheses.

Re: I got the highest score on ARC-AGI again swapping Python for English

#100
Transformer models, typically architected for and trained on 1d text streams, are not going to perform well on ARC-AGI. I like that the test corpus exists as I believe it suggests that other model architectures (perhaps co-existing with LLMs in a MoE fashion) are needed to generalize AI performance further. For example, if we constructed a 3d version of ARC-AGI (rather than relying on grids) humans would probably still outperform reasoning LLMs handily. However, expand ARC-AGI to 4d and I think human performance might start to become more comparable to LLM performance. 4d is as alien to us as 2d is to LLMs, in this narrow test corpus.
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