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

jeremyberman.substack.com

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

#51
post #30

Earlier quoted context omitted.

> we can apply the rule, "-A cannot follow from A", etc. regardless of the A You can't think of any domains where we are unable to apply this rule? I feel like I'm surrounded by people claiming "A, therefore -A!!" And if I'm one of them, and this were a reasoning dead-zone for me, I wouldn't be able to tell!

That's an abductive failure to recognise that something is A, and something else is not-A I dont see cases where people recognise the contradiction and then perform it.

People who know alcohol is bad for them and don't want to keep being drunks but keep drinking, people who believe phones are bad for their kids but still buy them, people who understand AI will significantly degrade the environment if it becomes ubiquitous but still work to help it become ubiquitous...

Mathematicians who publish proofs that are later proven inconsistent!

I suspect we have fundamentally different views of how humans work. I see our behavior and beliefs as _mostly_ irrational, with only a few "reasoning live-zones" where, with great effort, we can achieve logical thought.

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

#52
post #44

Earlier quoted context omitted.

> like we all do Do we though? Sure, we communicate sequentially, but that doesn't mean that our internal effort is piecewise and linear. A modern transformer LLM however is. Each token is sampled from a population exclusively dependent on the tokens that came before it. Mechanistically speaking, it works similarly to autocomplete, but at a very different scale. Now how much of an unavoidable handicap this incurs, if…

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).

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

#54
post #23

> LLMs are PhD-level reasoners in math and science, yet they fail at children's puzzles. How is this possible? Because they are not. Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. It’s the same reason why most of the people who pass your leetcode tests don’t actually know how to build anything real. They are taught to the test not taught to reality.

> Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. Do submarines swim? I don't really care if it gets me where I want to go. The fact is that just two days ago, I asked Claude to look at some reasonably complicated concurrent code to which I had added a new feature, and asked it to list what tests needed to be added; and then when I asked GPT-5 to add them, it one-sh…

> Do submarines swim?

It doesn't matter HOW LLMs "swim" as long as they can, but the point being raised is whether they actually can.

It's as if LLMs can swim in the ocean, in rough surf, but fail to swim in rivers or swimming pools, because they don't have a generalized ability to swim - they've just been RL-trained on the solution steps to swimming in surf, but since those exact conditions don't exist in a river (which might seem like a less challenging environment), they fail there.

So, the question that might be asked is when LLMs are trained to perform well in these vertical domains like math and programming, where it's easy to verify results and provide outcome- or process-based RL rewards, are they really learning to reason, or are they just learning to pattern match to steer generation in the direction of problem-specific reasoning steps that they had been trained on?

Does the LLM have the capability to reason/swim, or is it really just an expert system that has been given the rules to reason/swim in certain cases, but would need to be similarly hand fed the reasoning steps to be successful in other cases?

I think the answer is pretty obvious given that LLM's can't learn at runtime - can't try out some reasoning generalization they may have arrived at, find that it doesn't work in a specific case, then explore the problem and figure it out for next time.

Given that it's Demis Hassabis who it pointing out this deficiency of LLMs (and has a 5-10 year plan/timeline to fix it - AGI), not some ill-informed LLM critic, it seems silly to deny it.

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

#55

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).

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

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

#56

> LLMs are PhD-level reasoners in math and science, yet they fail at children's puzzles. How is this possible? Because they are not. Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. It’s the same reason why most of the people who pass your leetcode tests don’t actually know how to build anything real. They are taught to the test not taught to reality.

"Not understanding or reasoning" is anthropocentric cope. There is very little practical difference between "understanding" and "reasoning" implemented in human mind and that implemented in LLMs. One notable difference, however, is that LLMs disproportionately suck at spatial reasoning . Which shouldn't be surprising, considering that their training datasets are almost entirely text. The ultimate wordcel makes for a…

Very much agree with this. Looking at the dimensionality of a given problem space is a very helpful heuristic when analyzing how likely an llm is going to be suitable/reliable for that task. Consider how important positional encodings are LLM performance. You also then have an attention model that operates in that 1-dimensional space. With multidimensional data significant transformations to encode into a higher dimensional abstraction needs to happen within the model itself, before the model can even attempt to intelligently manipulate it.

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

#57
post #23

> LLMs are PhD-level reasoners in math and science, yet they fail at children's puzzles. How is this possible? Because they are not. Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. It’s the same reason why most of the people who pass your leetcode tests don’t actually know how to build anything real. They are taught to the test not taught to reality.

> Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. Do submarines swim? I don't really care if it gets me where I want to go. The fact is that just two days ago, I asked Claude to look at some reasonably complicated concurrent code to which I had added a new feature, and asked it to list what tests needed to be added; and then when I asked GPT-5 to add them, it one-sh…

Most of our coding is just plumbing. Getting data from one place to where it needs to be. There is no advanced reasoning necessary. Just a good idea of the structure of the code and the data-structures.

Even high school maths tests are way harder than what most professional programmers do on a daily basis.

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

#58
post #23

> LLMs are PhD-level reasoners in math and science, yet they fail at children's puzzles. How is this possible? Because they are not. Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. It’s the same reason why most of the people who pass your leetcode tests don’t actually know how to build anything real. They are taught to the test not taught to reality.

> Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. Do submarines swim? I don't really care if it gets me where I want to go. The fact is that just two days ago, I asked Claude to look at some reasonably complicated concurrent code to which I had added a new feature, and asked it to list what tests needed to be added; and then when I asked GPT-5 to add them, it one-sh…

>and the LLMs, which almost certainly didn't have a lot of "assemble these items" in their training data

I don't think this assumption is sound. Humans write a huge amount on "assemble components x and y to make entity z". I'd expect all LLMs to have consumed every IKEA type instruction manual, the rules for Jenga, all geometry textbooks and papers ever written.

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

#59

> LLMs are PhD-level reasoners in math and science, yet they fail at children's puzzles. How is this possible? Because they are not. Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. It’s the same reason why most of the people who pass your leetcode tests don’t actually know how to build anything real. They are taught to the test not taught to reality.

>Pattern matching questions on a contrived test is not the same thing as understanding or reasoning.

I think most of the problem i solve is also a pattern matching. The problems i am good at solving are the ones i've seen before or the ones i can break into problems i've seen before.

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

#60
post #23

Earlier quoted context omitted.

> Pattern matching questions on a contrived test is not the same thing as understanding or reasoning. Do submarines swim? I don't really care if it gets me where I want to go. The fact is that just two days ago, I asked Claude to look at some reasonably complicated concurrent code to which I had added a new feature, and asked it to list what tests needed to be added; and then when I asked GPT-5 to add them, it one-sh…

> Do submarines swim? It doesn't matter HOW LLMs "swim" as long as they can, but the point being raised is whether they actually can. It's as if LLMs can swim in the ocean, in rough surf, but fail to swim in rivers or swimming pools, because they don't have a generalized ability to swim - they've just been RL-trained on the solution steps to swimming in surf, but since those exact conditions don't exist in a river (w…

> are they really learning to reason, or are they just learning to pattern match to steer generation in the direction of problem-specific reasoning steps that they had been trained on?

Are you sure there's a real difference? Do you have a definition of "reasoning" that excludes this?

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