Why can't people make ai's by making a neuron sim and then scaling it up with a supercomputer to the point where it has a humans number of neurons and then raise it like a human?

Remotedeck@discuss.tchncs.de to No Stupid Questions@lemmy.world – 105 points –

I know current learning models work a little like neurons but why not just make a sim that works exactly like how we understand neurons work

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Actually, neuron-based machine learning models can handle this. The connections between the fake neurons can be modeled as a "strength", or the probability that activating neuron A leads to activation of neuron B. Advanced learning models just change the strength of these connections. If the probability is zero, that's a "lost" connection.

Those models don't have physical connections between neurons, but mathematical/programmed connections. Those are easy to change.

That's a vastly simplified model. Real neurons can't be approximated with a couple of weights - each neuron is at least as complex as a multi-layer RNN.

I'd love to know more.

I recently read "The brain is a computer is a brain: neuroscience’s internal debate and the social significance of the Computational Metaphor" and found it compelling. It bristled a lot of feathers on Lemmy, but think their critique is valid.

Do you have any review resources? I have a bit of knowledge around biology and biochemistry, but haven't studied neuroscience.

And no pressure. It's a lot to ask dor some random person on the internet. Cheers!