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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[–] [email protected] 1 points 3 days ago (1 children)

I was channeling the Interstellar docking computer (“improper contact” in such a sassy voice) ;)

There is a distinction between data and an action you perform on data (matrix maths, codec algorithm, etc.). It’s literally completely different.

An audio codec (not a pipeline) is just actually doing math - just like the workings of an LLM. There’s plenty of work to be done after the audio codec decodes the m4a to get to tunes in your ears. Same for an LLM, sandwiching those matrix multiplications that make the magic happen are layers that crunch the prompts and assemble the tokens you see it spit out.

LLMs can’t think, that’s just the fact of how they work. The problem is that AI companies are happy to describe them in terms that make you think they can think to sell their product! I literally cannot be wrong that LLMs cannot think or reason, there’s no room for debate, it’s settled long ago. AI companies will string the LLMs together and let them chew for a while to try make themselves catch when they’re dropping bullshit. It’s still not thinking and reasoning though. They can be useful tools, but LLMs are just tools not sentient or verging on sentient

[–] [email protected] 0 points 3 days ago* (last edited 2 days ago) (1 children)

There is a distinction between data and an action you perform on data (matrix maths, codec algorithm, etc.). It’s literally completely different.

Incorrect. You might want to take an information theory class before speaking on subjects like this.

I literally cannot be wrong that LLMs cannot think or reason, there’s no room for debate, it’s settled long ago.

Lmao yup totally, it's not like this type of research currently gets huge funding at universities and institutions or anything like that 😂 it's a dead research field because it's already "settled". (You're wrong 🤭)

LLMs are just tools not sentient or verging on sentient

Correct. No one claimed they are "sentient" (you actually mean "sapient", not "sentient", but it's fine because people commonly mix these terms up. Sentience is about the physical senses. If you can respond to stimuli from your environment, you're sentient, if you can "I think, therefore I am", you're sapient). And no, LLMs are not sapient either, and sapience has nothing to do with neural networks' ability to mathematically reason or use logic, you're just moving the goalpost. But at least you moved it far enough to be actually correct?

[–] [email protected] 1 points 10 hours ago (1 children)

It’s wild, we’re just completely talking past each other at this point! I don’t think I’ve ever gotten to a point where I’m like “it’s blue” and someone’s like “it’s gold” so clearly. And like I know enough to know what I’m talking about and that I’m not wrong (unis are not getting tons of grants to see “if AI can think”, no one but fart sniffing AI bros would fund that (see OP’s requested source is from an AI company about their own model), research funding goes towards making useful things not if ChatGPT is really going through it like the rest of us), but you are very confident in yourself as well. Your mention of information theory leads me to believe you’ve got a degree in the computer science field. The basis of machine learning is not in computer science but in stats (math). So I won’t change my understanding based on your claims since I don’t think you deeply know the basis just the application. The focus on using the “right words” as a gotchya bolsters that vibe. I know you won’t change your thoughts based on my input, so we’re at the age-old internet stalemate! Anyway, just wanted you to know why I decided not to entertain what you’ve been saying - I’m sure I’m in the same boat from your perspective ;)

[–] [email protected] 1 points 7 hours ago (1 children)

loses the argument "we’re at the age-old internet stalemate!" LMAO

[–] [email protected] 1 points 2 hours ago

Indeed I did not, we’re at a stalemate because you and I do not believe what the other is saying! So we can’t move anywhere since it’s two walls. Buuuut Tim Apple got my back for once, just saw this now!: https://lemmy.blahaj.zone/post/27197259

I’ll leave it at that, as thanks to that white paper I win! Yay internet points!