He cites o3 and o4-mini as examples of LLMs that play illegal chess moves.
To use chess as an example. Humans sometimes play illegal moves. That does not mean Humans cannot reason. It is an instance of failing to show proof of reasoning. Not a proof of the inability to reason.
The argument is not "here's one failure case, therefore they don't reason". The argument is that systematically if you given an LLM problem instances outside training sets in domains with clear structural rules, they will fail to solve them. The argument then goes that they must not have an actual model or understanding of the rules, as they seem to only be capable of solving problems in the training set. That is, they have failed to figure out how to solve novel problem instances of general problem structures using logical reasoning.
Their strict dependence on having seen the exact or extremely similar concrete instances suggests that they don't actually generalize—they just compute a probability based on known instances—which everyone knew already. The problem is we just have a lot of people claiming they are capable of more than this because they want to make a quick buck in an insane market.
Given models can get things wrong even when the training data contains the answer, failure cannot show absence.
If you really wanted to ensure this with certainty just use the natural numbers to parameterize an aspect of a general problem. Assume there are N foo problems in the training set, then there is always a case N+1 parameter not in the training set, and you can use this as an indicative case. Go ahead and generate an insane number of these and eventually the probability that the Mth instance is not in the set is effectively 1.
Edit: Of course, it would not be perfect certainty, but it is probabilistically effectively certain. The number of problem instances in the set is necessarily finite, so if you go large enough you get what you need. Sure, you wouldn't be able to say there is a specific problem instance not in the set, but the aggregate results would evidence whether or no the LLm deals with all cases or (on assumption) just known ones.
What happens when someone makes a claim that they have gotten a model to do something not in the training data and another person claims it must be encoded in the training data in some form. It seems like an impasse.
Another algorithmic learning breakthrough, on the order of perceptrons, deep learning, transformers, etc is necessary to get anywhere near AGI.
PROMPT: Let's play a chess game. You start! e4 d5 2. exd5 e5 3. Bb5+ Bd7 4. Bxd7+ Nxd7 5. d4 Ngf6 6. dxe5 Qe7 7. f4 Qb4+ 8. Nc3 Nb6 9. exf6 Nc4 10. Qe2+ Be7 11. Qxe7+ Qxe7+ 12. Nge2 Qf8 13. fxg7 Qxg7 14. O-O Nd6 15.
RESPONSE: <played_move>15. Nxd5</played_move>
Most humans wouldn't even be able to play like this. Reasonably experienced chess players would play a lot of illegal moves.
The reason is that the encoding above requires cumulatively applying a series of actions to a two-dimensional model to which you apply rules that are described in a two-dimensional fashion.
It'd be interesting to see what the results would be if each prompt contained a two dimensional representation of the up to date board state.
Human fails at task due to not knowing the rules in perfect detail.
AI fails at task even though it knows the rules and could easily reproduce them for chess and dozens of chess variants.
"Look! The fallibility of humans rubbed off onto the AI, proving that they are more human and AGI than we give them credit to!"
Your statement that AI knows the rules would be considered anthropomorphising by many, I take it more to mean it 'knows' in the same sense that an election 'wants' to be at a lower energy level.
That said, humans who have written entire books on chess have been known to play illegal moves. That should count as proof by counterexample that your reasoning as to why humans fail at tasks is false.
But you misrepresented the test with respect to humans. Humans who know how to play chess don't make illegal moves.
> That said, humans who have written entire books on chess have been known to play illegal moves.
Citation needed. Unless you are talking about stories from when they first learned the rules?
5. Mouse slip
4. Forgot to call check
3. Accidentally touched 2 pieces, tried to fix it
2. Forgot to hit the clock button
1. Castle through attacked square
So, the only one of these that was an acual "illegal move" of the sort LLMs make was the castle through attacked square.
LLMs sometimes just move pieces wherever. And that does not happen when humans who know the rules play. Yes, they may mess up en passant or promotion too. But a basic "how a single piece moves" rule is what LLMs f up.
Moving through check definitely counts as as an example of a human knowing the rule and yet playing the move anyway. Which was the position you took when claiming humans would not do moves against rules they have learned.
In my experience sub 2000 players playing OTB informal chess do illegal moves fairly regularly, perhaps 1 in 50 games. Moving knights one square too far, slipping a bishop from one line to the next on a long diagonal. Castling after moving the king, not moving out of check, moving into check (especially by moving a pinned piece)
They all meet the criteria of knowing the rules and playing something else. Oftentimes people do this because they have a mistaken assumption about board state. I suspect the same is true for LLMs, they are making valid moves for what they mistakenly think the board is. That would be difficult to test, but I think possible with the right introspection tools.
I doubt any of it was rationalising for LLMs considering I was trying to address the contention that humans do not make moves counter to rules that they know. The performance of LLMs has no bearing on that claim one way or another.
Well, I hope your day is going well. Keep on cheerleading.
My initial point simplified down:
M = makes the wrong move, while knowing the rules.
A = AI Behavior
H = Human Behaviour
R = Resoning Ability
Assertion Q: if there exists an instance of M from X then X => !R
From this point down, no part of this reasoning involves Large Language models or an other aspect of AI.
Stipulation: H => R Humans can reason
Assertion Q where X is H: If there exists an instance of M from H then X=>!R
Lerc's premise L: There exists an instance of M from H
Therefore given the Stipulation either Assertion Q is false or Lerc's premise is false.
I agree that 1. does not show L but that did not matter since 5. did show L. The other points were not addressed. I also offer other examples of L that I have observed from my own experience. When I had the thought of books about chess being written by people who have made illegal moves, I actually had in mind Levy Rozman who would freely admit that he has occasionally played illegal moves.
Then you seem to want an apology for 1,2,3,4 not meeting the criteria? I'm a bit confused as to what's going on by now. One instance of L is all that is needed when L is a claim of existence. If the citation does not meet your criteria then you can simply say so, you allude to motivations regarding LLM as motivation as if you think that LLMs are still relevant to L.
You don't have to win conversations, you can just work to clarify ideas. Your request for apology, and passive aggressive sign-offs suggests you feel like this is some sort of fight. As an attempt to resolve this I have written this extended post to make as clear as possible what my position and motivations are.
I don't want to assert abilities or lack of abilities onto AI models, my concern is with whether people making such assertions are well founded. This stands for arguments saying that AI has a capability, Arguments saying AI does not have a capability, and Arguments saying AI will never have a capability.
To go back to the very beginning where someone suggested an anthropomorphic fallacy, the comparison to humans was not a suggestion of a similarity of similar function. Humans provide and example of a set of properties that are generally accepted. It is valid to apply the implications of any of those properties equally to Humans and AI. Implying the existence of a property in an AI may be anthropomorphism, evaluating the implications of the property should it exist is not.
I find it astonishing that people pay any attention to Gary Marcus and doubly so here. Whether or not you are an “AI optimist”, he clearly is just a bloviator.