Ben and Shane,

I started this discussion with the hope to show people that there are
actually different understandings (or call them "definitions" ) of
intelligence, each with its intuitions and motivations, and they lead
to different destinations and serve different purposes. These goals
cannot replace each other, but since they are related, we still
benefit from discussions like this. Though we won't reach a consensus
soon, the discussions make our difference better understood.

As for which of the notions fit the word "intelligence" better, it is
a less important issue, though it is still an issue. Though I'm not a
native English speaker, this time my understanding is not necessarily
wrong. At least I'm not the only one who feel uncomfortable to call a
thermostat or a brute-force algorithm "intelligent" (though far below
human level).

Our core difference is not in our choice of word, nor just about the
role "efficiency" plays in intelligence. Since the very beginning of
my research I have the feeling that AI is fundamentally different from
traditional computer science/technique, and this difference is in the
theoretical foundation, rather than in the hardware (whether to use
von Neumann architecture ...) or software (which programming language
to use ...) details. This is where my definition of intelligence come
from.

To me, traditional computer science (CS) studies "what is the best
solution to a problem if the system has SUFFICIENT knowledge and
resources", and AI is about "what is the best solution to a problem if
the system has INSUFFICIENT knowledge and resources". I also believe
that traditional AI failed largely because it conceptually stayed too
closely to CS.

In your definitions, both AI and CS are doing "problem-solving", and
all computer systems will be called "intelligent" (though to various
degrees). I feel that in this way the most important feature of
intelligence will be lost among the less important features.

Again, I'm not trying to convince you, but to make myself more clear.

Pei

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