[ACCount37]

The question, as always, is: can we get any useful insights from all of that?

Trying to copy biological systems 1:1 rarely works, and copying biological systems doesn't seem to be required either. CNNs are somewhat brain-inspired, but only somewhat, and LLMs have very little architectural similarity to human brain - other than being an artificial neural network.

This functional similarity of LLMs to the human brain doesn't come from reverse engineered details of how the human brain works - it comes from the training process.

[Marshferm]

There's nothing similar about LLMs and human brains. Theyre entirely divergent. Training a machine has nothing remotely to do with biological development.

[ACCount37]

They perform incredibly similar functions. Thus, "functionally similar".

[Marshferm]

There’s no functional similarity in the slightest. Notice you can’t cite examples.

[ACCount37]

Hard metrics: LLMs perform NLP, NLU and CSR tasks at humanlike levels.

Research findings: LLMs have and use world models. They use some type of abstract thinking - with internal representation that often correspond to human abstract concepts. Which adds up to a capability profile that's amusingly humanlike.

Humans, however, don't like that. They really don't. AI effect is too strong, and it demands that humans must be Special. So some humans, when faced with the possibility that an AI might be doing the same thing their own brains do, resort to coping and seething.

[Marshferm]

These are not examples, they’re narrative (false) equivalencies.

Brains don’t perform Natural language CSR etc, those are cultural extensions separate from mental states etc. there are no functional equivalencies here.

There are many many empirical disputes for function eg

Aru et al “The feasibility of artificial consciousness through the lens of neuroscience” December 2023