Gary Marcus

Rank 13 of 47
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Score 83
5/18/2025, 12:11:30 AM
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In reply to:
Daniel Litt
@littmath
·
240d
@colin_fraser @GaryMarcus @MelMitchell1 @rao2z Oh yes, it’s very weird! I agree that there’s a lot we don’t understand here. But “zero abstracting ability” etc. is just obviously wrong.
Colin Fraser
@colin_fraser
·
240d
@littmath @GaryMarcus @MelMitchell1 @rao2z You must admit (I know I don’t have to convince you) it’s strange that such an intelligent entity would be so bad at tic tac toe
Colin Fraser
@colin_fraser
·
240d
@littmath @GaryMarcus @MelMitchell1 @rao2z That, I theorize, is why o3 can’t do this but it can do like algebraic geometry or whatever. This involves checking many cases, thinking steps ahead for each one, backtracking, and so on. It’s easy work but it’s work and there’s a lot of it.
Colin Fraser
@colin_fraser
·
240d
@rapid_rar @irl_danB @CHaesemeyer No. Maybe if it thought for more than 3 minutes it would have found a better move.
Colin Fraser
@colin_fraser
·
240d
@littmath @GaryMarcus @MelMitchell1 @rao2z I think we’ve talked about this before and you disagreed with me but I’ll ask again; I’ve found the hallmark of problems that they do badly at is they involve a lot of “busywork”—trying many cases, finding the correct path out of many possible options, etc. Do you find this?
Daniel Litt
@littmath
·
240d
@GaryMarcus @colin_fraser @MelMitchell1 @rao2z Let me put it this way—they can very reliably solve some out-of-distribution hard problems that humans can’t reliably solve. Being able to solve *all* problems is not a pre-condition for intelligence; otherwise people aren’t intelligent.
Gary Marcus
@GaryMarcus
·
240d
@littmath @colin_fraser @MelMitchell1 @rao2z Some, but not reliably. They can’t even solve large multiplication problems reliably.

LLMs exceed their predecessors but demonstrably still have not solved this problem, which is most clear when the training set is known, and when direct data augmentation is not possible.

Some

The statement is part of a technical discussion about the capabilities of AI models in abstract reasoning and problem-solving. It addresses the claim that AI has 'zero abstracting ability,' suggesting that this is an overstatement. The conversation involves evaluating AI's performance in tasks like tic-tac-toe and algebraic geometry, contributing to the broader discourse on AI's limitations and strengths.

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    The statement does no harm and is part of a constructive discussion. [+1]
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    It promotes understanding by clarifying a point about AI capabilities. [+1]
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    Engages in constructive criticism by addressing a specific claim without personal attacks. [+1]