[Oberon] Re (2): Re (n): Accessibility of FPGA configuration to V5 system.

[Charles Perkins]

I've been watching Numenta ( https://numenta.com/ ) and and I think their
search for the pattern of how real neurons cooperate (an algorithm!) in the
brain, giving rise to our own intelligence, is the most likely to get us to
artificial general intelligence.

They observe that the physical structure of the neocortex is largely the
same across the whole of it, but different regions of the neocortex perform
different functions in cognition (vision, hearing, planning, etc.) implying
that if we understand the structure we can understand and reproduce the
functions of cognition.

I found that to be a compelling argument and I look forward to seeing where
they take it.

Chuck

On Mon, Aug 30, 2021 at 6:53 AM <peter at easthope.ca> wrote:

> From:   gray <gray at grayraven.org>
> Date:   Mon, 30 Aug 2021 15:49:04 +0400
> > I guess as of today the best still utterly simplistic approach ...
>
> Overview of the vast subject here.
> https://en.wikipedia.org/wiki/Nervous_system_network_models
>
> > ... of artificially implementing something like a nervous system would
> be
> > neural networks.
>
> Model a brain as a machine of static configuration?
>
> Another approach is to model development beginning where neural cells
> first differentiate.  In gastrulation, there is no neural cell.
> https://en.wikipedia.org/wiki/Gastrulation
>
> Later the neural groove appears.
>
> https://en.wikipedia.org/wiki/Organogenesis#Organs_produced_by_the_germ_layers
>
> I imagine modelling the process where the neural groove or first
> neuron appears.  WIth current knowledge, one neuron is fairly
> understandable.  =8~)  As neurons are added, connectivity is possible
> and the process becomes interesting.  Learning proceeds as neurons
> are added.
>
> A serious literature search will find whether anyone has tackled that.
>
> Thanks for tolerating the digression.
>
> Regards,                                ... P.L.
>
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