Seems to me there's a question of dynamic range, temporally speaking.  In 
classical computers, that is dealt with by separating exponents and mantissas 
as in floating point arithmetic.  If everything compresses by 7 order of 
magnitude, then perhaps it would just be a matter of adding 7 more digits (e.g. 
bits) of precision to the exponent.  Then it would be faster and cover the 
relevant part of the dynamic range of the environment.

-----Original Message-----
From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of glen ?
Sent: Monday, May 08, 2017 1:22 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Subject: Re: [FRIAM] the arc of ai (was Re: Whew!)


What if faster firing tightened a brain's coupling to its environment, rather 
than loosening it?  That would suggest that brains with fast neurons would be 
_less_ tolerant of ambiguity, not more.  One couldn't think deeply about 
anything because the environment would keep you locked in a kind of 
stimulus-response cage ... a slave of your own fast firing neurons.

On 05/08/2017 08:45 AM, Marcus Daniels wrote:
> A fun fact that I ran across last week:   A superconducting neuron made of 
> Josephson Junctions could be 7 orders of magnitude faster than those in the 
> human central nervous system.  Being superconducting there would be no heat, 
> and the possibility of deep 3d integration.  
> 
> Of course, lithography won't be adaptive unless it is way overbuilt and then 
> trimmed-down.    That would be one data point in favor of the adaption being 
> more important than deep skill.


--
☣ glen

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