this post was submitted on 01 Jun 2025
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I found the aeticle in a post on the fediverse, and I can't find it anymore.

The reaserchers asked a simple mathematical question to an LLM ( like 7+4) and then could see how internally it worked by finding similar paths, but nothing like performing mathematical reasoning, even if the final answer was correct.

Then they asked the LLM to explain how it found the result, what was it's internal reasoning. The answer was detailed step by step mathematical logic, like a human explaining how to perform an addition.

This showed 2 things:

  • LLM don't "know" how they work

  • the second answer was a rephrasing of original text used for training that explain how math works, so LLM just used that as an explanation

I think it was a very interesting an meaningful analysis

Can anyone help me find this?

EDIT: thanks to @theunknownmuncher @lemmy.world https://www.anthropic.com/research/tracing-thoughts-language-model its this one

EDIT2: I'm aware LLM dont "know" anything and don't reason, and it's exactly why I wanted to find the article. Some more details here: https://feddit.it/post/18191686/13815095

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[–] theunknownmuncher@lemmy.world 76 points 3 days ago (2 children)
[–] lgsp@feddit.it 21 points 3 days ago

Oh wow thank you! That's it!

I didn't even remember now good this article was and how many experiments it collected

[–] anzo@programming.dev 5 points 2 days ago

Here's a book for a different audience. Explains in layman terms why to be wary about this tech, https://thebullshitmachines.com/

[–] glizzyguzzler@lemmy.blahaj.zone 67 points 3 days ago (39 children)

Can’t help but here’s a rant on people asking LLMs to “explain their reasoning” which is impossible because they can never reason (not meant to be attacking OP, just attacking the “LLMs think and reason” people and companies that spout it):

LLMs are just matrix math to complete the most likely next word. They don’t know anything and can’t reason.

Anything you read or hear about LLMs or “AI” getting “asked questions” or “explain its reasoning” or talking about how they’re “thinking” is just AI propaganda to make you think they’re doing something LLMs literally can’t do but people sure wish they could.

In this case it sounds like people who don’t understand how LLMs work eating that propaganda up and approaching LLMs like there’s something to talk to or discern from.

If you waste egregiously high amounts of gigawatts to put everything that’s ever been typed into matrices you can operate on, you get a facsimile of the human knowledge that went into typing all of that stuff.

It’d be impressive if the environmental toll making the matrices and using them wasn’t critically bad.

TLDR; LLMs can never think or reason, anyone talking about them thinking or reasoning is bullshitting, they utilize almost everything that’s ever been typed to give (occasionally) reasonably useful outputs that are the most basic removed shit because that’s the most likely next word at the cost of environmental disaster

[–] WolfLink@sh.itjust.works 6 points 2 days ago (1 children)

The environmental toll doesn’t have to be that bad. You can get decent results from single high-end gaming GPU.

You can, but the stuff that’s really useful (very competent code completion) needs gigantic context lengths that even rich peeps with $2k GPUs can’t do. And that’s ignoring the training power and hardware costs to get the models.

Techbros chasing VC funding are pushing LLMs to the physical limit of what humanity can provide power and hardware-wise. Way less hype and letting them come to market organically in 5/10 years would give the LLMs a lot more power efficiency at the current context and depth limits. But that ain’t this timeline, we just got VC money looking to buy nuclear plants and fascists trying to subdue the US for the techbro oligarchs womp womp

[–] peoplebeproblems@midwest.social 19 points 3 days ago (2 children)

People don't understand what "model" means. That's the unfortunate reality.

[–] adespoton@lemmy.ca 14 points 3 days ago (1 children)

They walk down runways and pose for magazines. Do they reason? Sometimes.

[–] IncogCyberspaceUser@lemmy.world 11 points 3 days ago (1 children)

Yeah. That's because peoples unfortunate reality is a "model".

[–] Treczoks@lemmy.world 9 points 3 days ago (1 children)

I've read that article. They used something they called an "MRI for AIs", and checked e.g. how an AI handled math questions, and then asked the AI how it came to that answer, and the pathways actually differed. While the AI talked about using a textbook answer, it actually did a different approach. That's what I remember of that article.

But yes, it exists, and it is science, not TicTok

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[–] BodilessGaze@sh.itjust.works 39 points 3 days ago (21 children)

I don't know how I work. I couldn't tell you much about neuroscience beyond "neurons are linked together and somehow that creates thoughts". And even when it comes to complex thoughts, I sometimes can't explain why. At my job, I often lean on intuition I've developed over a decade. I can look at a system and get an immediate sense if it's going to work well, but actually explaining why or why not takes a lot more time and energy. Am I an LLM?

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[–] KeenFlame@feddit.nu 13 points 2 days ago

It's the anthropic article you are looking for, where they performed open brain surgery equivalent to find out that they do maths in very strange and eerily humanlike operations, like they will estimate, then if it goes over calculate the last digit like I do. It sucks as a counting technique though

[–] JackGreenEarth@lemm.ee 18 points 3 days ago (1 children)

By design, they don't know how they work. It's interesting to see this experimentally proven, but it was already known. In the same way the predictive text function on your phone keyboard doesn't know how it works.

[–] lgsp@feddit.it 16 points 3 days ago (1 children)

I'm aware of this and agree but:

  • I see that asking how an LLM got to their answers as a "proof" of sound reasoning has become common

  • this new trend of "reasoning" models, where an internal conversation is shown in all its steps, seems to be based on this assumption of trustable train of thoughts. And given the simple experiment I mentioned, it is extremely dangerous and misleading

  • take a look at this video: https://youtube.com/watch?v=Xx4Tpsk_fnM : everything is based on observing and directing this internal reasoning, and these guys are computer scientists. How can they trust this?

So having a good written article at hand is a good idea imho

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[–] tal@lemmy.today 11 points 3 days ago* (last edited 3 days ago)

Define "know".

  • An LLM can have text describing how it works and be trained on that text and respond with an answer incorporating that.

  • LLMs have no intrinsic ability to "sense" what's going on inside them, nor even a sense of time. It's just not an input to their state. You can build neural-net-based systems that do have such an input, but ChatGPT or whatever isn't that.

  • LLMs lack a lot of the mechanisms that I would call essential to be able to solve problems in a generalized way. While I think Dijkstra had a valid point:

    The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.

    ...and we shouldn't let our prejudices about how a mind "should" function internally cloud how we treat artificial intelligence...it's also true that we can look at an LLM and say that it just fundamentally doesn't have the ability to do a lot of things that a human-like mind can. An LLM is, at best, something like a small part of our mind. While extracting it and playing with it in isolation can produce some interesting results, there's a lot that it can't do on its own: it won't, say, engage in goal-oriented behavior. Asking a chatbot questions that require introspection and insight on its part won't yield interesting result, because it can't really engage in introspection or insight to any meaningful degree. It has very little mutable state, unlike your mind.

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