diz

Not really. Here's the chain-of-word-vomit that led to the answers:

https://pastebin.com/HQUExXkX

Note that in "its impossible" answer it correctly echoes that you can take one other item with you, and does not bring the duck back (while the old overfitted gpt4 obsessively brought items back), while in the duck + 3 vegetables variant, it has a correct answer in the wordvomit, but not being an AI enthusiast it can't actually choose the correct answer (a problem shared with the monkeys on typewriters).

I'd say it clearly isn't ignoring the prompt or differences from the original river crossings. It just can't actually reason, and the problem requires a modicum of reasoning, much as unloading groceries from a car does.

It’s a failure mode that comes from pattern matching without actual reasoning.

Exactly. Also looking at its chain-of-wordvomit (which apparently I can't share other than by cut and pasting it somewhere), I don't think this is the same as GPT 4 overfitting to the original river crossing and always bringing items back needlessly.

Note also that in one example it discusses moving the duck and another item across the river (so "up to two other items" works); it is not ignoring the prompt, and it isn't even trying to bring anything back. And its answer (calling it impossible) has nothing to do with the original.

In the other one it does bring items back, it tries different orders, even finds an order that actually works (with two unnecessary moves), but because it isn't an AI fanboy reading tea leaves, it still gives out the wrong answer.

Here's the full logs:

https://pastebin.com/HQUExXkX

Content warning: AI wordvomit which is so bad it is folded hidden in a google tool.

Yeah, exactly. There's no trick to it at all, unlike the original puzzle.

I also tested OpenAI's offerings a few months back with similarly nonsensical results: https://awful.systems/post/1769506

All-vegetables no duck variant is solved correctly now, but I doubt it is due to improved reasoning as such, I think they may have augmented the training data with some variants of the river crossing. The river crossing is one of the top most known puzzles, and various people have been posting hilarious bot failures with variants of it. So it wouldn't be unexpected that their training data augmentation has river crossing variants.

Of course, there's very many ways in which the puzzle can be modified, and their augmentation would only cover obvious stuff like variation on what items can be left with what items or spots on the boat.

Perhaps it was near ready to emit a stop token after "the robot can take all 4 vegetables in one trip if it is allowed to carry all of them at once." but "However" won, and then after "However" it had to say something else because that's how "however" works...

Agreed on the style being absolutely nauseating. It wasn't a very good style when humans were using it, but now it is just the style of absolute bottom of the barrel, top of the search results garbage.

I feel like letter counting and other letter manipulation problems kind of under-sell the underlying failure to count - LLMs work on tokens, not letters, so they are expected to have a difficulty with letters.

The inability to count is of course wholly general - in a river crossing puzzle an LLM can not keep track of what's on either side of the river, for example, and sometimes misreports how many steps it output.

Other thing to add to this is that there's just one or two people in the train providing service for hundreds of other people or millions of dollars worth of goods. Automating those people away is simply not economical, not even in terms of the headcount replaced vs headcount that has to be hired to maintain the automation software and hardware.

Unless you're a techbro, who deeply resents labor, someone who would rather hire 10 software engineers than 1 train driver.

Also, my thought on this is that since an LLM has no internal state with which to represent the state of the problem, it can't ever actually solve any variation of the river crossing. Not even those that it "solves" correctly.

If it outputs the correct sequence, inside your head the model of the problem will be in the solved state, but on the LLM's side there's just a sequence of steps that it wrote down, with those steps directly inhibiting production of another "Trip" token, until that crosses a threshold. There isn't an inventory or even a count of items, there's an unrelated number that weights for or against "Trip".

If we are to anthropomorphize it (which we shouldn't, but anyway), it's bullshitting up an answer and it gradually gets a feeling that it has bullshitted enough, which can happen at the right moment, or not.