perm filename JAN8.74[DOC,TOB]1 blob sn#081032 filedate 1974-01-07 generic text, type T, neo UTF8
00100	Topics for a talk
00200	Retinex,Horn,Marr
00300	AI,philo,models,direct perception
00400	Computer magazine article
00500	Posner
00600	examples of prowess
00700	general AI, problem of organism
00800	
00900	
01000	
01100	Language is apparently based on models for perceptual processes, rather than the
01200	converse (Wharfian hypothesis).
01300	
01400	
01500	The organism has access only to its models of the environment, not to
01600	the objects out there.  Language is thus referential only in that it
01700	refers to the models, not to the objects directly.  It is clear though
01800	that we really think as though there were objects out there.  When we
01900	refer to an electron, we are really referring to something which allows
02000	us to pull together a lot of experiments in our atomic theory.  But that
02100	is equally true of an orange; when we say we see an orange, we mean that
02200	certain photons enter our eyes.  We interpret this as certain reflectance
02300	(orange color).  There might be some demon switching objects in front of
02400	us faster than we can see.  In fact, we make great leaps of trust in
02500	assuming that the object is the same when we watch it, or turn our backs
02600	and then see it again.  Or again, it might only be some great dream
02700	going on in our solitary heads.  It turns out to be useful for survival
02800	to make these models and assume they correspond to something in the world
02900	out there.  In a real sense, our assumptions about an orange are very
03000	like those about electrons, only much more vivid and immediate because
03100	we carry our experimental apparatus with us, and have other experiments
03200	like manipulation for consistency.
03300	
03400	Basically models allow us to do thought experiments instead of just
03500	blundering randomly along.  For example, if I am chasing a rabbit,
03600	I predict where he is going next.  The rabbit has evolved to run
03700	erratically, but sometimes maintain their course long enough that our
03800	predictions are accurate.  It is clear that our energy towards understanding
03900	and building models has great survival value.
04000	
04100	To understand intelligence is to understand the models we make of the
04200	world around us.  
04300	The models serve to allow us to do thought experiments, rehearsing
04400	as Freud and Perls say.  Some models are tightly organized, such as
04500	physics, even the physics which we all know without schooling.  There
04600	are quite a number of models, topology,logic,geometry, algebra, number theory and 
04700	various forms of mathematics, chemistry, physics, economics, social
04800	structures, psychology, etc, etc.
04900	Some models are rather vague, like the scripts we acquire on how to act
05000	to get certain payoffs.
05100	The point is that to use and understand language, to exist in the world,
05200	to be intelligent is to have these models (representations).  
05300	
05400	We are in the field of understanding human intelligence and of understanding
05500	how machines can be intelligent.  That means we want to understand human models
05600	and calculations and how machines can accomplish the same thing.  Often this
05700	means that they must have equivalent models, although we are not bound to do
05800	things the same way.  The similarity is really that of the similarity of the
05900	models of different people.  The world out there is the same world, even if
06000	two people are different, and models of fairly obvious real world things
06100	have very similar outward behavior for different people.  The most efficient
06200	form of calculation may be very different for a machine and a living being.
06300	For example, human flight was achieved by means very different from the
06400	flight of birds. 
06500	
06600	retina, retinal layers, lgn,cortical layers, gestalt organization
06700	camera, retinex, color, edge detectors, organization, description
06800	
06900	revolutionary nature of semiconductor technology
07000	
07100	understandings of line drawings
07200	
07300	representation of shape
07400	
07500	stereo and depth measurement techniques
07600	
07700	technical applications
07800		assembly
07900		computerization of industry--rationalization