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Animats ◴[] No.41890003[source]
This is an important result.

The actual paper [1] says that functional MRI (which is measuring which parts of the brain are active by sensing blood flow) indicates that different brain hardware is used for non-language and language functions. This has been suspected for years, but now there's an experimental result.

What this tells us for AI is that we need something else besides LLMs. It's not clear what that something else is. But, as the paper mentions, the low-end mammals and the corvids lack language but have some substantial problem-solving capability. That's seen down at squirrel and crow size, where the brains are tiny. So if someone figures out to do this, it will probably take less hardware than an LLM.

This is the next big piece we need for AI. No idea how to do this, but it's the right question to work on.

[1] https://www.nature.com/articles/s41586-024-07522-w.epdf?shar...

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CSMastermind ◴[] No.41892068[source]
When you look at how humans play chess they employ several different cognitive strategies. Memorization, calculation, strategic thinking, heuristics, and learned experience.

When the first chess engines came out they only employed one of these: calculation. It wasn't until relatively recently that we had computer programs that could perform all of them. But it turns out that if you scale that up with enough compute you can achieve superhuman results with calculation alone.

It's not clear to me that LLMs sufficiently scaled won't achieve superhuman performance on general cognitive tasks even if there are things humans do which they can't.

The other thing I'd point out is that all language is essentially synthetic training data. Humans invented language as a way to transfer their internal thought processes to other humans. It makes sense that the process of thinking and the process of translating those thoughts into and out of language would be distinct.

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nox101 ◴[] No.41892362[source]
It sounds like you think this research is wrong? (it claims llms can not reason)

https://arstechnica.com/ai/2024/10/llms-cant-perform-genuine...

or do you maybe think no logical reasoning is needed to do everything a human can do? Tho humans seem to be able to do logical reasoning

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bbor ◴[] No.41892803[source]
I’ll pop in with a friendly “that research is definitely wrong”. If they want to prove that LLMs can’t reason, shouldn’t they stringently define that word somewhere in their paper? As it stands, they’re proving something small (some of today’s LLMs have XYZ weaknesses) and claiming something big (humans have an ineffable calculator-soul).

LLMs absolutely 100% can reason, if we take the dictionary definition; it’s trivial to show their ability to answer non-memorized questions, and the only way to do that is some sort of reasoning. I personally don’t think they’re the most efficient tool for deliberative derivation of concepts, but I also think any sort of categorical prohibition is anti-scientific. What is the brain other than a neural network?

Even if we accept the most fringe, anthropocentric theories like Penrose & Hammerhoff’s quantum tubules, that’s just a neural network with fancy weights. How could we possibly hope to forbid digital recreations of our brains from “truly” or “really” mimicking them?

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tsimionescu ◴[] No.41893282[source]
> Even if we accept the most fringe, anthropocentric theories like Penrose & Hammerhoff’s quantum tubules, that’s just a neural network with fancy weights.

First, while it is a fringe idea with little backing it, it's far from the most fringe.

Secondly, it is not at all known that animal brains are accurately modeled as an ANN, any more so than any other Turing-compatible system can be modeled as an ANN. Biological neurons are themselves small computers, like all living cells in general, with not fully understood capabilities. The way biological neurons are connected is far more complex than a weight in an ANN. And I'm not talking about fantasy quantum effects in microtubules, I'm talking about well-established biology, with many kinds of synapses, some of which are "multicast" in a spatially distinct area instead of connected to specific neurons. And about the non-neuronal glands which are known to change neuron behavior and so on.

How critical any of these differences are to cognition is anyone's guess at this time. But dismissing them and reducing the brain to a bigger NN is not wise.

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1. Koala_ice ◴[] No.41894649{3}[source]
There's a lot of other interesting biology besides propagation of electrical signals. Examples include: 1/ Transport of mRNAs (in specialized vesicle structures!) between neurons. 2/ Activation and integration of retrotransposons during brain development (which I have long hypothesized acts as a sort of randomization function for the neural field). 3/ Transport of proteins between and within neurons. This isn't just adventitious movement, either - neurons have a specialized intracellular transport system that allows them to deliver proteins to faraway locations (think >1 meters).