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ARC Prize – a $1M+ competition towards open AGI progress

arcprize.org

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Re: ARC Prize – a $1M+ competition towards open AGI progress

#341
post #334

Earlier quoted context omitted.

That's a good point. In my head I was considering stuff like chess, where even though it took a long time to reach superhuman performance on computers, the issue was mainly compute. People basically knew how to do it algorithmically before then (pruning tree search). I guess the underlying issue with my argument is that we really have no idea how large the search space is for finding AGI, so applying something like B…

> we know that human AGI was a result of an optimisation process (natural selection) I don't think this is obviously correct. Three things: 1) Many actions we think of as "intelligence" are just short-cuts based on heuristics. 2) While there's probably an argument that problem solving is selected for it's not clear to me how far this goes at all. There's little evidence that smarter people end up in more powerful pos…

> also perhaps human GI? Nothing artificial about it.

Lol, thanks, that's quite funny. I should spend less time on the internet.

> While there's probably an argument that problem solving is selected for it's not clear to me how far this goes at all.

Yeah, I meant something much more low brow which is that _humans_, with all of our properties (including GI), are a result of natural selection. I'm not claiming GI was selected for specifically, but it certainly occurred as a side-effect either way. So we know optimisation can work.

> There are plenty of imaginable forms of intelligence that are often ignored during these conversations.

I completely agree! I wish there was more discussion on intelligence in the broad in these threads. Even if you insist on sticking to humans it's pretty clear that something like a company or a government is operating very intelligently in its own environment (business, or politics), well beyond the influence of its individual constituents.

> Basically I don't think your expression of Bayes' theorem had nearly enough possibilities in it.

Another issue with Bayes in general is that you have a fixed probability space in mind when you use it, right? I can use Bayes to optimise my beliefs against a fixed ontology, but it says nothing about how or when to update the ontology itself.

And no doubt my ontology is lacking when it comes to (A)GI...

Re: ARC Prize – a $1M+ competition towards open AGI progress

#342

Earlier quoted context omitted.

Humans can do infinitely many things because we have general intelligence. Testing whether an AI can play chess or solve Chollet's ARC problems, or some other set of narrow skills, doesn't prove generality. If you want to test for generality, then you either have to: 1) Have a huge and very broad test suite, covering as many diverse human-level skills as possible. and/or, 2) Reductively understand what human intellig…

I suspect trying to reductively understand intelligence is a bit like trying to reductively understand biology - every level of abstraction is causally influenced by every other level of abstraction, so there just aren't simple primitives you can break everything down into.

You can get pretty far with an understanding of biochemical reaction cycles, genetic theory, and protein molecular interactions.

Re: ARC Prize – a $1M+ competition towards open AGI progress

#343
post #334

Earlier quoted context omitted.

> we know that human AGI was a result of an optimisation process (natural selection) I don't think this is obviously correct. Three things: 1) Many actions we think of as "intelligence" are just short-cuts based on heuristics. 2) While there's probably an argument that problem solving is selected for it's not clear to me how far this goes at all. There's little evidence that smarter people end up in more powerful pos…

> While there's probably an argument that problem solving is selected for it's not clear to me how far this goes at all. There's little evidence that smarter people end up in more powerful positions for example. Evolution hasn't had enough time to adapt us to our new fangled lifestyle of last few hundred years, or few thousand for that matter, and anyways in the modern world people are not generally competing on thin…

I strongly agree that the predictive and planning ability is very important - things like agriculture rely on it and must be selective at that point.

But the point has previously been made else humans developed large brains long (1.5M years?) before agriculture, and for a long time the only benefit seemed to be fire and flint tools.

It's not widely understood the causal link here - there are other species that have large brains but haven't developed these skills. So it's not clear exactly what facets of intelligence are selected for.

Re: ARC Prize – a $1M+ competition towards open AGI progress

#344

Earlier quoted context omitted.

This is not what I'm saying. Consider the following statement: "Absence of evidence is evidence of absence." Presumably you would call this a simple logical fallacy for the same reason, but a little reflection would show that in many cases such a statement is true! It depends on context, in this case your estimate of how well your search covered the possible search space. Evidence is a continuous variable - things ca…

We know that computers are capable of things that humans can't - anything related to brute force computation, search and memory for example. So, just because a human can't do something, or struggles to do it, doesn't mean that the task requires a huge IQ or generality - it may just require a lot of compute/memory, such as DeepBlue playing chess. In the case in point of these ARC puzzles, they are easy for a human, so…

I disagree that gradient descent brute force extracts the training set. That "overfitting" kind of thing has been shown to be false many times. Transformers learn predictive models of their input, beyond what their training set contains.

But in general I agree about active inference. Clearly there is something missing there.

Doing alpha-go style MCTS would be interesting but how would you approach training the policy and value net? It's not like we can take snapshots of people's thought processes as they read text in the same way you can perform arbitrary rollouts of your game engine.

Re: ARC Prize – a $1M+ competition towards open AGI progress

#346

Earlier quoted context omitted.

The fact that two intelligent beings are debating what the correct answer is shows that there is no fixed correct answer that proves "intelligence". This is IQ tests all over again. Actually testing how alike you think to the author of the test.

Honestly I’d disagree. I was a bit confused at first but moment I realized I could resize the grid, the answer strikes me as obvious and clear. Yes, in some theoretic sense you can argue a 3 x 3 grid answer is fine, but shows this to 100 different humans and majority would agree that resizing the grid is the obvious and more natural solution.

So anyone who disagrees, including you for a short time, is actually not an intelligent being?

Not to mention that ignoring the size of the grid, one might disagree about the answer of one of the tests.

Re: ARC Prize – a $1M+ competition towards open AGI progress

#347

Earlier quoted context omitted.

There's a difference between memorizing meanings of words (addition is same as counting this and then the other thing, "3" means three things) and memorizing methods (table of single digit addition/multiplication to do them faster in your head). You were arguing the second, I'm a counterexample. I agree about the first, everyone learns language by memorization (some rote, some by use), but language is not math.

> You were arguing the second, I'm a counterexample. I still don't think you are. Since we agree that you memorized numbers and how they are sequential, and that counting is moving "up" in the sequence, addition as counting is still memorizing a procedure based on this, not just memorizing a name: to add any two numbers, count down on one as you count up on the other until the first number number reaches zero, and th…

Sorry, I strongly disagree.

I did memorize names of numbers, but that is not essential in any way to doing or understanding math, and I can remember a time where I understood addition but did not fully understand how names of numbers work (I remember, when I was six, playing with a friend at counting up high, and we came up with some ridiculous names for high numbers because we didn't understand decimal very well yet).

Addition is a thing you do on matchsticks, or fingers, or eggs, or whatever objects you're thinking about. It's merging two groups and then counting the resulting group. This is how I learned addition works (plus the invariant that you will get the same result no matter what kind of object you happen to work with). Counting up and down is one method that I learned, but I learned it by understanding how and why it obviously works, which means I had the ability to generate variants - instead of 2+8=3+7=... I can do 8+2=9+1=..., or I can add ten at a time, etc'.

Same goes for multiplication. I remember the very simple conversation where I was taught multiplication. "Mom, what is multiplication?" "It's addition again and again, for example 4x3 is 3+3+3". That's it, from that point on I understood (integer) multiplication, and could e.g. wonder myself at why people claim that xy=yx and convince myself that it makes sense, and explore and learn faster ways to calculate it while understanding how they fit in the world and what they mean. (An exception is long multiplication, which I was taught as a method one day and was simple enough that I could memorize it and it was many years before I was comfortable enough with math that whenever I did it it was obvious to me why what I'm doing here calculates exactly multiplication. Long division is a more complex method: it was taught to me twice by my parents, twice again in the slightly harder polynomial variant by university textbooks, and yet I still don't have it memorized because I never bothered to figure out how it works nor to practice enough that I understand it).

I never in my life had an ability to add 2+2 while not understanding what + means. I did for half an hour have the same for long division (kinda... I did understand what division means, just not how the method accomplishes it) and then forgot. All the math I remember, I was taught in the correct order.

edit: a good test for whether I understood a method or just memorized it would be, if there's a step I'm not sure I remember correctly, whether I can tell which variation has to be the correct one. For example, in long multiplication, if I remembered each line has to be indented one place more to the right or left but wasn't sure which, since I understand it, I can easily tell that it has to be the left because this accomplishes the goal of multiplying it by 10, which we need to do because we had x0 and treated it as x.

Re: ARC Prize – a $1M+ competition towards open AGI progress

#348
Some very hand-wavey (and late) thoughts from an outsider:

The current batch of LLMs can be uncharitably summarized as "just predict the next token". They're pretty good at that. If they were perfect at it, they'd enable AGI - but it doesn't look like they're going to get there. It seems like the wrong approach. Among other issues, finite context windows seem like a big limitation (even though they're being expanded), and recursive summarization is an interesting kludge.

The ARC-AGI tasks seem more about pattern matching, in the abstract sense (but also literally). Humans are good at pattern matching, and we seem to use pattern matching test performance as a proxy for measuring human intelligence (like in "IQ" tests). I'm going to side-step the question of "what is intelligence, really?" by defining it as being good at solving ARC-AGI tasks.

I don't know what the solution is, but I have some idea of what it might look like - a machine with high-order pattern-matching capabilities. "high-order" as in being able to operate on multiple granularities/abstraction-levels at once (there are parallels here to recursive summarization in LLMs).

So what is the difference between "pattern matching" and "token prediction"? They're closely related, and you could use one to do the other. But the real difference is that in pattern matching there are specific patterns that you're matching against. If you're lucky you can even name the pattern/trope, but it might be something more abstract and nameless. These patterns can be taught explicitly, or inferred from the environment (i.e. "training data").

On the other hand, "token prediction" (as implemented today) is more of a probabilistic soup of variables. You can ask an LLM why it gave a particular answer and it will hallucinate something plausible for you, but the real answer is just "the weights said so". But a hypothetical pattern matching machine could tell you which pattern(s) it was matching against, and why.

So to summarize (hah), I think a good solution will involve high-order meta-pattern matching capabilities (natively, not emulated or kludged via an LLM-shaped interface). I have no idea how to get there!

Re: ARC Prize – a $1M+ competition towards open AGI progress

#349

Earlier quoted context omitted.

I suspect trying to reductively understand intelligence is a bit like trying to reductively understand biology - every level of abstraction is causally influenced by every other level of abstraction, so there just aren't simple primitives you can break everything down into.

You can get pretty far with an understanding of biochemical reaction cycles, genetic theory, and protein molecular interactions.

Trying to express the high-level behaviour of an organism in those reductive terms is way beyond science right now, if it's even possible at all. Like have a look at a chart of human metabolic pathways - it's absolute insanity. And those are extremely simplified already!

Re: ARC Prize – a $1M+ competition towards open AGI progress

#350

Earlier quoted context omitted.

There's a difference between memorizing meanings of words (addition is same as counting this and then the other thing, "3" means three things) and memorizing methods (table of single digit addition/multiplication to do them faster in your head). You were arguing the second, I'm a counterexample. I agree about the first, everyone learns language by memorization (some rote, some by use), but language is not math.

> You were arguing the second, I'm a counterexample. I still don't think you are. Since we agree that you memorized numbers and how they are sequential, and that counting is moving "up" in the sequence, addition as counting is still memorizing a procedure based on this, not just memorizing a name: to add any two numbers, count down on one as you count up on the other until the first number number reaches zero, and th…

I think you are confusing "memory" with strategies based on memorisation. Yes memorising (ie putting things into memory) is always involved in learning in some way, but that is too general and not what is discussed here. "Compression is understanding" possibly to some extent, but understanding is not just compression; that would be a reduction of what understanding really is, as it involves a certain range of processes and contexts in which the understanding is actually enacted rather than purely "memorised" or applied, and that is fundamentally relational. It is so relational that it can even go deeply down to how motor skills are acquired or spatial relationships understood. It is no surprise that tasks like mental rotation correlates well with mathematical skills.

Current research in early mathematical education now focuses on teaching certain spatial skills to very young kids rather than (just) numbers. Mathematics is about understanding of relationships, and that is not a detached kind of understanding that we can make into an algorithm, but deeply invested and relational between the "subject" and the "object" of understanding. Taking the subject and all the relations with the world out of the context of learning processes is absurd, because that is in the exact centre of them.

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