The brain does not work the way you think… (I work in the field, bio-informatics). What you call “neural networks” come from an early misunderstanding of how the brain stores information. It’s a LOT more complicated and frankly, barely understood.
It’s a LOT more complicated and frankly, barely understood.
Yet you confidently state that the brain doesn’t work the way LLMs do?
Obviously it doesn’t work exactly the same way that LLMs do, if only because of the completely different substrates. But when you get to more nebulous concepts like “creativity” and “inspiration” it’s not so clear.
The part where brain and neural net differ is in the learning via backpropagation, that seem to be done different in the brain, as there is no mechanism to go backwards through the network and jiggle the weights.
That aside, they seem to work very similar once they are trained, as the knowledge they are able to extract from data ends up being basically the same that a human would be able to extract. There is surprisingly little weirdness in AI and a surprising amount of human-like capabilities.
That would be a much better comparison if it was artificial intelligence, but these are just reinforcement learning models. They do not get inspired.
More to the point: they replicate patterns of words.
So do humans.
That’s a Bingo!
…like the naturally occuring neural networks are.
The brain does not work the way you think… (I work in the field, bio-informatics). What you call “neural networks” come from an early misunderstanding of how the brain stores information. It’s a LOT more complicated and frankly, barely understood.
Yeah, accurately simulating a single pyramidal neuron requires an eight-layer deep neural network:
https://www.cell.com/neuron/pdf/S0896-6273(21)00501-8.pdf
that was an interesting read, thank you
Yet you confidently state that the brain doesn’t work the way LLMs do?
Obviously it doesn’t work exactly the same way that LLMs do, if only because of the completely different substrates. But when you get to more nebulous concepts like “creativity” and “inspiration” it’s not so clear.
The part where brain and neural net differ is in the learning via backpropagation, that seem to be done different in the brain, as there is no mechanism to go backwards through the network and jiggle the weights.
That aside, they seem to work very similar once they are trained, as the knowledge they are able to extract from data ends up being basically the same that a human would be able to extract. There is surprisingly little weirdness in AI and a surprising amount of human-like capabilities.