My personnal guess is that the brain may eventually be modeled. As for language (and other things), I think the main issue is that there is a small piece of architecture that is highly replicated (like the visual system), but we just haven’t found it yet. (And since we can’t record in human brains with electrodes, it won’t come tomorrow!) But this is just a guess.
plcsays:
Having read his Synapse State Theory paper, I don’t quite know what to think – He seems to have a point, but I fail to perceive the big difference with today’s commonly accepted model of the animal brain:
That the differences and plasticity of neural synapses make up the “matter” of thought (if that is precise enough to describe it).
Perhaps he’d be more accepted by his scientific colleagues if he cared more for other people’s work – He’d have to present sound arguments rather than just dismissing the accepted current research.
And about the time complexity of modelling mental activity, wouldn’t that be more like Omega(N*S), where N = total number of neurons, and S = total number of synapses because:
A ‘worst case’ scenario would probably be an activity involving every single neuron (or a very large amount of them anyway). If every neuron fires, you’d have to update every synapse connected to it, in order to update its new state of conductivity.
And if we try to reason about the number of synapses compared to neurons, we get a (probably unrealistic) scenario of every neuron connected to all the remaining neurons, leaving us with (1/2)*n*(n+1) synapses. (because the problem essentially is SIGMA(s, from s=1 to s=n) )
This leaves us with something in the order of Theta(n^2) (and that is regardless of whether a synapse is unidirectional or not), resulting in a total lower bound for mental modelling of Omega(n^3)
I certainly look forward to reading his book in order to see for myself if he’s on to something or has simply given in to his megalomania.
My personnal guess is that the brain may eventually be modeled. As for language (and other things), I think the main issue is that there is a small piece of architecture that is highly replicated (like the visual system), but we just haven’t found it yet. (And since we can’t record in human brains with electrodes, it won’t come tomorrow!) But this is just a guess.
Having read his Synapse State Theory paper, I don’t quite know what to think – He seems to have a point, but I fail to perceive the big difference with today’s commonly accepted model of the animal brain:
That the differences and plasticity of neural synapses make up the “matter” of thought (if that is precise enough to describe it).
Perhaps he’d be more accepted by his scientific colleagues if he cared more for other people’s work – He’d have to present sound arguments rather than just dismissing the accepted current research.
And about the time complexity of modelling mental activity, wouldn’t that be more like Omega(N*S), where N = total number of neurons, and S = total number of synapses because:
A ‘worst case’ scenario would probably be an activity involving every single neuron (or a very large amount of them anyway). If every neuron fires, you’d have to update every synapse connected to it, in order to update its new state of conductivity.
And if we try to reason about the number of synapses compared to neurons, we get a (probably unrealistic) scenario of every neuron connected to all the remaining neurons, leaving us with (1/2)*n*(n+1) synapses. (because the problem essentially is SIGMA(s, from s=1 to s=n) )
This leaves us with something in the order of Theta(n^2) (and that is regardless of whether a synapse is unidirectional or not), resulting in a total lower bound for mental modelling of Omega(n^3)
I certainly look forward to reading his book in order to see for myself if he’s on to something or has simply given in to his megalomania.