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?
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?
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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Simulating even one neuron is very complex. Neurons in artificial neuron nets used in machine learning are a gross oversimplification. On top on this you need to get the wiring right. On top on this you need to get the sensorial system right (a brain without input is worthless). On top of this you need an environment. So it's multiple layers of complexity that we don't have
What I find fascinating is the efficiency of the brain.
With a supercomputer and the energy of a nuclear station to run it we are able to simulate a handful of neurons interacting with each other.
On the other hand the brain with billions of neurons only requires the energy of one or two potato to run.
To be fair, nature had millions od years to optimize the power consumption and we only observe the successful results since the failures didn't survive.
We're having our particular technological revolutions as well. In little more than a century we've managed to construct computing devices with capabilities that may have taken thousands of years to be achieved by nature.