We can then view recent

work in artificial intelligence as a crucial experiment disaffirming the

traditional assumption that human reason can be analyzed into rule governed
operations on situation-free discrete elements - the most important

disconfirmation of this metaphysical demand that has ever been

produced. This technique of turning our philosophical assumptions into

technology until they reveal their limits suggests fascinating new areas

for basic research.

C. E. Shannon, the inventor of information theory, sees, to some

extent, how different potentially intelligent machines would have to be.

In his discussion of "What Computers Should be Doing," he observes:

Efficient machines for such problems as pattern recognition, language 
translation,

and so on, may require a different type ofcomputer than any we have today.

It is my feeling that this will be a computer whose natural operation is in 
terms

of patterns, concepts, and vague similarities, rather than sequential operations

on ten-digit numbers. 19

We have seen that, as far as we can tell from the only being that can deal

with such "vagueness," a "machine" which could use a natural language

and recognize complex patterns would have to have a body so that it

could be at home in the world.

What Computers Can't Do

Hubert Dreyfus

[n.b. The word that is screwing people up here & elsewhere is "patterns". 
"Pattern recognition" **in the real world** is actually SCHEMA recognition. Our 
culture commonly talks of people, say, recognizing common "patterns" in faces, 
trees or rocks. There are no such patterns in the true logicomathematical 
sense, only schemas - which are fluid, non-geometrical affairs. ]





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AGI
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