I'm looking for an article showing that LLMs don't know how they work internally
Technology
80
Beiträge
32
Kommentatoren
5
Aufrufe
-
"Researchers" did a thing I did the first day I was actually able to ChatGPT and came to a conclusion that is in the disclaimers on the ChatGPT website. Can I get paid to do this kind of "research?" If you've even read a cursory article about how LLMs work you'd know that asking them what their reasoning is for anything doesn't work because the answer would just always be an explanation of how LLMs work generally.
Very arrogant answer. Good that you have intuition, but the article is serious, especially given how LLMs are used today. The link to it is in the OP now, but I guess you already know everything...
-
There was a study by Anthropic, the company behind Claude, that developed another AI that they used as a sort of "brain scanner" for the LLM, in the sense that allowed them to see sort of a model of how the LLM "internal process" worked
Yes, that's it. I added the link in the OP,
-
I agree. This is the exact problem I think people need to face with nural network AIs. They work the exact same way we do. Even if we analysed the human brain it would look like wires connected to wires with different resistances all over the place with some other chemical influences.
I think everyone forgets that nural networks were used in AI to replicate how animal brains work, and clearly if it worked for us to get smart then it should work for something synthetic. Well we've certainly answered that now.
Everyone being like "oh it's just a predictive model and it's all math and math can't be intelligent" are questioning exactly how their own brains work. We are just prediction machines, the brain releases dopamine when it correctly predicts things, it self learns from correctly assuming how things work. We modelled AI off of ourselves. And if we don't understand how we work, of course we're not gonna understand how it works.
Even if LLM "neurons" and their interconnections are modeled to the biological ones, LLMs aren't modeled on human brain, where a lot is not understood.
The first thing is that how the neurons are organized is completely different. Think about the cortex and the transformer.
Second is the learning process. Nowhere close.
The fact explained in the article about how we do math, through logical steps while LLMs use resemblance is a small but meaningful example. And it also shows that you can see how LLMs work, it's just very difficult
-
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.
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
-
I agree. This is the exact problem I think people need to face with nural network AIs. They work the exact same way we do. Even if we analysed the human brain it would look like wires connected to wires with different resistances all over the place with some other chemical influences.
I think everyone forgets that nural networks were used in AI to replicate how animal brains work, and clearly if it worked for us to get smart then it should work for something synthetic. Well we've certainly answered that now.
Everyone being like "oh it's just a predictive model and it's all math and math can't be intelligent" are questioning exactly how their own brains work. We are just prediction machines, the brain releases dopamine when it correctly predicts things, it self learns from correctly assuming how things work. We modelled AI off of ourselves. And if we don't understand how we work, of course we're not gonna understand how it works.
LLMs among other things lack the whole neurotransmitter "live" regulation aspect and plasticity of the brain.
We are nowhere near a close representation of actual brains. LLMs to brains are like a horse carriage compared to modern cars. Yes they have four wheels and they move, and cars also need four wheels and move, but that is far from being close to each other.
-
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
Do LLMs not exhibit emergent behaviour? But who am I, a simple skin-bag of chemicals, to really say.
-
LLMs among other things lack the whole neurotransmitter "live" regulation aspect and plasticity of the brain.
We are nowhere near a close representation of actual brains. LLMs to brains are like a horse carriage compared to modern cars. Yes they have four wheels and they move, and cars also need four wheels and move, but that is far from being close to each other.
So LLMs are like a human with anterograde amnesia. They're like Dory.
-
I agree. This is the exact problem I think people need to face with nural network AIs. They work the exact same way we do. Even if we analysed the human brain it would look like wires connected to wires with different resistances all over the place with some other chemical influences.
I think everyone forgets that nural networks were used in AI to replicate how animal brains work, and clearly if it worked for us to get smart then it should work for something synthetic. Well we've certainly answered that now.
Everyone being like "oh it's just a predictive model and it's all math and math can't be intelligent" are questioning exactly how their own brains work. We are just prediction machines, the brain releases dopamine when it correctly predicts things, it self learns from correctly assuming how things work. We modelled AI off of ourselves. And if we don't understand how we work, of course we're not gonna understand how it works.
They work the exact same way we do.
Two things being difficult to understand does not mean that they are the exact same.
-
You can prove it’s not by doing some matrix multiplication and seeing its matrix multiplication. Much easier way to go about it
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?
-
Here's a book for a different audience. Explains in layman terms why to be wary about this tech, https://thebullshitmachines.com/
-
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 oneEDIT2: 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
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
-
-
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
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.
-
I agree. This is the exact problem I think people need to face with nural network AIs. They work the exact same way we do. Even if we analysed the human brain it would look like wires connected to wires with different resistances all over the place with some other chemical influences.
I think everyone forgets that nural networks were used in AI to replicate how animal brains work, and clearly if it worked for us to get smart then it should work for something synthetic. Well we've certainly answered that now.
Everyone being like "oh it's just a predictive model and it's all math and math can't be intelligent" are questioning exactly how their own brains work. We are just prediction machines, the brain releases dopamine when it correctly predicts things, it self learns from correctly assuming how things work. We modelled AI off of ourselves. And if we don't understand how we work, of course we're not gonna understand how it works.
I agree. This is the exact problem I think people need to face with nural network AIs. They work the exact same way we do.
I don't think this is a fair way of summarizing it. You're making it sound like we have AGI, which we do not have AGI and we may never have AGI.
-
Even if LLM "neurons" and their interconnections are modeled to the biological ones, LLMs aren't modeled on human brain, where a lot is not understood.
The first thing is that how the neurons are organized is completely different. Think about the cortex and the transformer.
Second is the learning process. Nowhere close.
The fact explained in the article about how we do math, through logical steps while LLMs use resemblance is a small but meaningful example. And it also shows that you can see how LLMs work, it's just very difficult
I agree, but I'm not sure it matters when it comes to the big questions, like "what separates us from the LLMs?" Answering that basically amounts to answering "what does it mean to be human?", which has been stumping philosophers for millennia.
It's true that artificial neurons are significant different than biological ones, but are biological neurons what make us human? I'd argue no. Animals have neurons, so are they human? Also, if we ever did create a brain simulation that perfectly replicated someone's brain down to the cellular level, and that simulation behaved exactly like the original, I would characterize that as a human.
It's also true LLMs can't learn, but there are plenty of people with anterograde amnesia that can't either.
This feels similar to the debates about what separates us from other animal species. It used to be thought that humans were qualitatively different than other species by virtue of our use of tools, language, and culture. Then it was discovered that plenty of other animals use tools, have language, and something resembling a culture. These discoveries were ridiculed by many throughout the 20th century, even by scientists, because they wanted to keep believing humans are special in some qualitative way. I see the same thing happening with LLMs.
-
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
Can humans think?
-
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/18759960Maybe 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?
-
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
The environmental toll doesn’t have to be that bad. You can get decent results from single high-end gaming GPU.
-
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 oneEDIT2: 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
Humans don't know how they work internally either. I mean what are you expecting?
-
-
I agree. This is the exact problem I think people need to face with nural network AIs. They work the exact same way we do.
I don't think this is a fair way of summarizing it. You're making it sound like we have AGI, which we do not have AGI and we may never have AGI.
Let's get something straight, no I'm not saying we have our modern definition of AGI but we've practically got the original definition coined before LLMs were a thing. Which was that the proposed AGI agent should maximise "the ability to satisfy goals in a wide range of environments". I personally think we've just moved the goal posts a bit.
Wether we'll ever have thinking, rationalised and possibly conscious AGI is beyond the question. But I do think current AI is similar to existing brains today.
Do you not agree that animal brains are just prediction machines?
That we have our own hallucinations all the time? Think visual tricks, lapses in memory, deja vu, or just the many mental disorders people can have.
Do you think our brain doesn't follow path of least resistance in processing? Or do you think our thoughts comes from elsewhere?
I seriously don't think animal brains or human to be specific are that special that nurural networks are beneath. Sure people didn't like being likened to animals but it was the truth, and I as do many AI researches, liken us to AI.
AI is primitive now, yet it can still pass the bar, doctors exams, compute complex physics problems and write a book (soulless as it may be like some authors) in less than a few seconds.
Whilst we may not have AGI the question was about math. The paper questioned how it did 36+59 and it did things in an interesting way where it half predicted what the tens column would be and 'knew' what the units column was, then put it together. Although thats not how I or even you may do it there are probably people who do it similar.
All I argue is that AI is closer to how our brains think, and with our brains being irrational quite often it shouldn't be surprising that AI nural networks are also irrational at times.
-
They work the exact same way we do.
Two things being difficult to understand does not mean that they are the exact same.
Maybe work is the wrong word, same output. Just as a belt and chain drive does the same thing, or how fluorescent, incandescent or LED lights produce light even though they're completely different mechanisms.
What I was saying is that one is based on the other, so similar problems like irrational thought even if the right answer is conjured shouldn't be surprising. Although an animal brain and nural network are not the same, the broad concept of how they work is.
