There is a sense in which even professionals can become helpless to the 
state-of-the-art in any field.   For example, if Matlab or Mathematica don’t 
make it easy, then don’t even try.   Or if a compiler produces slow code, 
change the source code of the program until it does produce optimal code rather 
than fixing the compiler.    When there is no technology, people accept that 
they have to figure things in out.   A problem has to be very serious to 
motivate the investment in literacy to get over an energy barrier introduced by 
tried-and-true but never perfect technology, and increasingly, only specialists 
make that investment.   That said, having no technology is a ridiculous 
solution to the problem.

From: Friam <friam-boun...@redfish.com> on behalf of Gary Schiltz 
<g...@naturesvisualarts.com>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Date: Monday, July 29, 2019 at 12:33 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Subject: Re: [FRIAM] Predictive coding basedon deep learning

Boy howdy (I've always wanted to say that) does that ring true here in Ecuador. 
There are just so many things that I took for granted back in the USA that I 
can't get here, be it technology, tools, food ingredients. If something I 
brought from there breaks, I make sure to tear it apart to see if it is 
something I can fabricate from what I can get here. It really pays to be a 
Jack/Jill of all trades. I've come to appreciate the value of knowing a little 
of everything, and not much of anything in particular.

On Mon, Jul 29, 2019 at 1:29 PM Marcus Daniels 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

Steve writes:

< What I'm trying to expose is the meta-heuristic of being a facile model 
builder/adopter/fitter... and how our technological prosthetics (precut colored 
plexiglass and stain-by-number patterns or GPS/routing systems that present 
opaque-to-the-user preferences or predictive SDE programming environments).  >

When technology doesn’t work, take it apart and figure out what is wrong with 
it or how it could be improved.    Human experts, or skilled practitioners, can 
hurt more they help because they have no incentive to unpack their expertise 
into reusable automated systems.   The trick is to look at skills as technology 
and to be facile evolving the technology.

Marcus
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