🚀 go-pugleaf

In article <875924895snz@longley.demon.co.uk>,
David@longley.demon.co.uk (David Longley) wrote:

>In article <34352c7c.1516199@news.earthlink.net>
>           savainl@earthlink.net "Louis Savain" writes:
>> 
>> .........  I think you have a somewhat pessimistic view of the power
>> of inductive learning.  Sure, it is a trial and error processes that
>> can easily give rise to superstitions, as you pointed out, but this
>> trial and error process should not be underestimated.  It can also be
>> used to send men to the moon and invent intelligent, conditionable
>> robots.
>> 
>> Regards,
>> 
>> Louis Savain,
>> 
>You're  correct in your first sentence - and you are also  correct  in 
>saying  that my view of "intelligence" is somewhat idiosyncratic.  But 
>that doesn't mean it's wrong of course - maybe just unfamiliar. 
>
>I suspect we, as a species, have had ANNs for many thousands of  years 
>- and that it was something such as the discovery of deduction  itself 
>(and  especially the predicate calculus quite recently) which gave  us 
>the  skills we regard as intelligent behaviour. Certainly I'd put  our 
>ability  to  get  to  the moon etc.  down  to  deduction  rather  than 
>induction.

  I agree, and as I wrote in a response to Neil Rickert, we could not
have discovered deduction were it not for the power of our inductive
learning capabilities.  In the context creating a general learning AI,
I believe that induction is the only process that is fundamental to
learning.  Our future AIs will discover deduction just like we did.

>[...]
>
>My general conclusion is that *many* psychologists have in  gfact 
>misread what their discipline has all been about since the 1960s. 
>As an ampirical discipline, and in contrast to the technology  of 
>AI,  it  is  a catalogue of the failings  of  a  system  (*human* 
>information    processing)   optimised   for   fault    tolerance 
>biologically,  but minimally rational without the support of  the 
>extensional stance - artificial intelligence (science).

  I agree.  However, this extensional stance is learned inductively
and we must acknowledge this fact if we are to create a general
synthetic intelligence.  Inductive learning is a powerful way (I would
argue that it is the only way) to quickly gain and manage large
amounts of knowledge and, given enough time, this knowledge can become
highly accurate in its agreement with nature.  We could not have
survived otherwise.

>[Well researched quotes deleted]
> 
>Throughout, it  is  being argued that such inductive inferences are in 
>fact best modelled  using artificial  neural  network technology,  and 
>that   such  processing  is intensional, with all of  the  traditional 
>problems of intensionality:

  Agreed.  Our future AIs will need to be trained to follow rigorous
empirically-grounded methods of research.  Most of them however will
not be pressed into scientific service and their fallible "intensional
processing" (the high level operation of which we will never fully
understand) will work fine in the more mundane tasks for which they
will be conditioned.  IMO, this is the real goal of AI.  I would agree
with you that this goal cannot be achieved without us humans adopting,
as an operating principle, the "extensional stance" that you are
championing.

  Thanks for the pertinent quotes and the references.

Regards,

Louis Savain

President, Marengo Media, Inc.