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?

https://www.anthropic.com/research/tracing-thoughts-language-model for one, the exact article OP was asking for

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

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)?

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

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

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.

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?

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

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.

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

"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.

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

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.

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.

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.

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

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.

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.