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submitted 1 week ago* (last edited 1 week ago) by lgsp@feddit.it to c/technology@lemmy.world

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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[-] glizzyguzzler@lemmy.blahaj.zone 53 points 1 week ago

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 bitch shit because that’s the most likely next word at the cost of environmental disaster

[-] peoplebeproblems@midwest.social 17 points 1 week ago

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

[-] adespoton@lemmy.ca 12 points 1 week ago

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

[-] IncogCyberspaceUser@lemmy.world 11 points 1 week ago

But why male models?

[-] random_character_a@lemmy.world 7 points 1 week ago

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

[-] Treczoks@lemmy.world 6 points 1 week ago

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

[-] lgsp@feddit.it 5 points 1 week ago

Thank you. I found the article, linkin the OP

[-] AnneBonny@lemmy.dbzer0.com 6 points 1 week ago

How would you prove that someone or something is capable of reasoning or thinking?

[-] glizzyguzzler@lemmy.blahaj.zone 6 points 1 week ago

You can prove it’s not by doing some matrix multiplication and seeing its matrix multiplication. Much easier way to go about it

[-] theunknownmuncher@lemmy.world 18 points 1 week ago* (last edited 1 week ago)

Yes, neural networks can be implemented with matrix operations. What does that have to do with proving or disproving the ability to reason? You didn't post a relevant or complete thought

Your comment is like saying an audio file isn't really music because it's just a series of numbers.

[-] glizzyguzzler@lemmy.blahaj.zone 2 points 1 week ago* (last edited 1 week ago)

Improper comparison; an audio file isn’t the basic action on data, it is the data; the audio codec is the basic action on the data

“An LLM model isn’t really an LLM because it’s just a series of numbers”

But the action of turning the series of numbers into something of value (audio codec for an audio file, matrix math for an LLM) are actions that can be analyzed

And clearly matrix multiplication cannot reason any better than an audio codec algorithm. It’s matrix math, it’s cool we love matrix math. Really big matrix math is really cool and makes real sounding stuff. But it’s just matrix math, that’s how we know it can’t think

[-] theunknownmuncher@lemmy.world 5 points 1 week ago* (last edited 1 week ago)

LOL you didn't really make the point you thought you did. It isn't an "improper comparison" (it's called a false equivalency FYI), because there isn't a real distinction between information and this thing you just made up called "basic action on data", but anyway have it your way:

Your comment is still exactly like saying an audio pipeline isn't really playing music because it's actually just doing basic math.

[-] BB84@mander.xyz 3 points 1 week ago

Can humans think?

[-] DarkDarkHouse@lemmy.sdf.org 3 points 1 week ago

Do LLMs not exhibit emergent behaviour? But who am I, a simple skin-bag of chemicals, to really say.

[-] whaleross@lemmy.world 6 points 1 week ago

People that can not do Matrix multiplication do not possess the basic concepts of intelligence now? Or is software that can do matrix multiplication intelligent?

[-] WolfLink@sh.itjust.works 5 points 1 week ago

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

[-] AnneBonny@lemmy.dbzer0.com 1 points 1 week ago

Who has claimed that LLMs have the capacity to reason?

[-] theparadox@lemmy.world 12 points 1 week ago

More than enough people who claim to know how it works think it might be "evolving" into a sentient being inside it's little black box. Example from a conversation I gave up on... https://sh.itjust.works/comment/18759960

[-] theunknownmuncher@lemmy.world 5 points 1 week ago

I don't want to brigade, so I'll put my thoughts here. The linked comment is making the same mistake about self preservation that people make when they ask an LLM to "show it's work" or explain it's reasoning. The text response of an LLM cannot be taken at it's word or used to confirm that kind of theory. It requires tracing the logic under the hood.

Just like how it's not actually an AI assistant, but trained and prompted to output text that is expected to be what an AI assistant would respond with, if it is expected that it would pursue self preservation, then it will output text that matches that. It's output is always "fake"

That doesn't mean there isn't a real potential element of self preservation, though, but you'd need to dig and trace through the network to show it, not use the text output.

[-] AnneBonny@lemmy.dbzer0.com 1 points 1 week ago

Maybe I should rephrase my question:

Outside of comment sections on the internet, who has claimed or is claiming that LLMs have the capacity to reason?

[-] adespoton@lemmy.ca 6 points 1 week ago

The study being referenced explains in detail why they can’t. So I’d say it’s Anthropic who stated LLMs don’t have the capacity to reason, and that’s what we’re discussing.

The popular media tends to go on and on about conflating AI with AGI and synthetic reasoning.

[-] theunknownmuncher@lemmy.world 4 points 1 week ago

You're confusing the confirmation that the LLM cannot explain it's under-the-hood reasoning as text output, with a confirmation of not being able to reason at all. Anthropic is not claiming that it cannot reason. They actually find that it performs complex logic and behavior like planning ahead.

[-] adespoton@lemmy.ca 0 points 1 week ago

No, they really don’t. It’s a large language model. Input cues instruct it as to which weighted path through the matrix to take. Those paths are complex enough that the human mind can’t hold all the branches and weights at the same time. But there’s no planning going on; the model can’t backtrack a few steps, consider different outcomes and run a meta analysis. Other reasoning models can do that, but not language models; language models are complex predictive translators.

[-] theunknownmuncher@lemmy.world 7 points 1 week ago

To write the second line, the model had to satisfy two constraints at the same time: the need to rhyme (with "grab it"), and the need to make sense (why did he grab the carrot?). Our guess was that Claude was writing word-by-word without much forethought until the end of the line, where it would make sure to pick a word that rhymes. We therefore expected to see a circuit with parallel paths, one for ensuring the final word made sense, and one for ensuring it rhymes.

Instead, we found that Claude plans ahead. Before starting the second line, it began "thinking" of potential on-topic words that would rhyme with "grab it". Then, with these plans in mind, it writes a line to end with the planned word.

🙃 actually read the research?

[-] just_another_person@lemmy.world 1 points 1 week ago

It's a developer option that isn't generally available on consumer-facing products. It's literally just a debug log that outputs the steps to arrive at a response, nothing more.

It's not about novel ideation or reasoning (programmatic neural networks don't do that), but just an output of statistical data that says "Step was 90% certain, Step 2 was 89% certain...etc"

[-] theunknownmuncher@lemmy.world -1 points 1 week ago* (last edited 1 week ago)

It's true that LLMs aren't "aware" of what internal steps they are taking, so asking an LLM how they reasoned out an answer will just output text that statistically sounds right based on its training set, but to say something like "they can never reason" is provably false.

Its obvious that you have a bias and desperately want reality to confirm it, but there's been significant research and progress in tracing internals of LLMs, that show logic, planning, and reasoning.

EDIT: lol you can downvote me but it doesn't change evidence based research

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

Developing a AAA video game has a higher carbon footprint than training an LLM, and running inference uses significantly less power than playing that same video game.

[-] glizzyguzzler@lemmy.blahaj.zone 11 points 1 week ago

Too deep on the AI propaganda there, it’s completing the next word. You can give the LLM base umpteen layers to make complicated connections, still ain’t thinking.

The LLM corpos trying to get nuclear plants to power their gigantic data centers while AAA devs aren’t trying to buy nuclear plants says that’s a straw man and you simultaneously also are wrong.

Using a pre-trained and memory-crushed LLM that can run on a small device won’t take up too much power. But that’s not what you’re thinking of. You’re thinking of the LLM only accessible via ChatGPT’s api that has a yuge context length and massive matrices that needs hilariously large amounts of RAM and compute power to execute. And it’s still a facsimile of thought.

It’s okay they suck and have very niche actual use cases - maybe it’ll get us to something better. But they ain’t gold, they ain't smart, and they ain’t worth destroying the planet.

[-] ohwhatfollyisman@lemmy.world 6 points 1 week ago

but there's been significant research and progress in tracing internals of LLMs, that show logic, planning, and reasoning.

would there be a source for such research?

[-] theunknownmuncher@lemmy.world 7 points 1 week ago
[-] ohwhatfollyisman@lemmy.world 7 points 1 week ago

but this article espouses that llms do the opposite of logic, planning, and reasoning?

quoting:

Claude, on occasion, will give a plausible-sounding argument designed to agree with the user rather than to follow logical steps. We show this by asking it for help on a hard math problem while giving it an incorrect hint. We are able to “catch it in the act” as it makes up its fake reasoning,

are there any sources which show that llms use logic, conduct planning, and reason (as was asserted in the 2nd level comment)?

[-] theunknownmuncher@lemmy.world 5 points 1 week ago

No, you're misunderstanding the findings. It does show that LLMs do not explain their reasoning when asked, which makes sense and is expected. They do not have access to their inner-workings and generate a response that "sounds" right, but tracing their internal logic shows they operate differently than what they claim, when asked. You can't ask an LLM to explain its own reasoning. But the article shows how they've made progress with tracing under-the-hood, and the surprising results they found about how it is able to do things like plan ahead, which defeats the misconception that it is just "autocomplete"

this post was submitted on 01 Jun 2025
199 points (97.2% liked)

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