At this point I'd describe intelligent machine as being able to
construct incremental internal models of wide variety of processes,
based on moderately explicit information about those processes (in
other words, being able to learn sufficiently general models, and to
elaborate them). Using these models, it's able to represent
information about other, compound processes, in sufficiently explicit
form, and so on. For example, at first it can learn about letters,
then words, then about reading, then pick a textbook on some subject,
etc. Almost all of functionality of intelligent machine consists in
ability to translate data in variety of formats between
representations, making various aspects of it explicit. As a result,
it can translate consequences of its actions into changes in external
processes, and intelligently choose these actions.


-- 
Vladimir Nesov                            mailto:[EMAIL PROTECTED]

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