Re:Brains are not required to think or solve problems – simp...
by PeterisP on Thursday January 25, 2024 @12:05PM
(#39131830)
Nobody is attempting to have one-to-one correspondence between neurons and artificial "neurons", the fact that a single biological does much more doesn't imply some limitation or incompleteness (as long as the same computations can be implemented simply by having more of them, and as far as we understand, that seems to be the case) - the choice is primary because due to how our hardware parallelization works, we'd prefer to implement the exact same behavior with 1000 structurally identical "neurons" rather than have a single more complex "emulated neuron" that requires more complicated logic that can't be straightforwardly reduced to massive matrix multiplication.
Re:Brains are not required to think or solve problems – simp...
by stcredzero on Thursday January 25, 2024 @01:42PM
(#39133068)
that requires more complicated logic that can't be straightforwardly reduced to massive matrix multiplication
What are the rationale for thinking it doesn't matter? Or is it the case that researchers think a larger number of simpler neurons could be equivalent to a smaller number of "complex emulated neurons?"
Re:Brains are not required to think or solve problems – simp...
by PeterisP on Thursday January 25, 2024 @05:34PM
(#39136359)
Yes, computation as such is sufficiently universal that it's very reasonable to assume that a larger number of simpler neurons would be equivalent to a smaller number of "complex emulated neurons".
I've occasionally run into science podcasts, going back almost a decade, where some researcher talks about the computational power of cell membranes, and how the synapses evolved from these mechanisms. Amoebas and paramecia navigate their environments, sense, and react through their cell membranes. Apparently, synapses evolved from these mechanisms.
The upshot of this for AI, is that the neural network model may be drastically incomplete, with far more computation actually happening inside actual individual neurons.