Zusammenfassungen
In Part Two, The Problem
of Inference, I argue that the only type
of inference—thinking,
in other words—that
will
work for human-level
AI (or anything even close to it) is the one we don’t
have a clue
how to program or engineer. The problem
of inference goes to the
heart of the AI debate because
it deals directly with intelligence, in
people
or machines. Our knowledge of the various
types of inference
dates back to Aristotle and other ancient Greeks, and has been developed
in the fields of logic and mathematics.
Inference is already described
using formal, symbolic systems like computer programs, so
a very clear view of the project
of engineering intelligence can be
gained by exploring inference. There
are three types. Classic AI explored
one (deduction), modern AI explores another (induction). The
third type (abduction) makes for general intelligence, and, surprise,
no one is working on it—at all.1 Finally,
since each type of inference is
distinct—meaning,
one type cannot be reduced to another—we know
that failure to build AI systems using the type of inference undergirding
general intelligence will
result in failure to make progress
toward
artificial
general intelligence, or AGI.
Von Erik J. Larson im Buch The Myth Of Artificial Intelligence (2021) Dieses Kapitel erwähnt ...
Personen KB IB clear | Stanley Kubrick | ||||||||||||||||||
Begriffe KB IB clear | AlexNet | ||||||||||||||||||
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Beat und dieses Kapitel
Beat hat Dieses Kapitel während seiner Zeit am Institut für Medien und Schule (IMS) ins Biblionetz aufgenommen. Beat besitzt weder ein physisches noch ein digitales Exemplar. Aufgrund der wenigen Einträge im Biblionetz scheint er es nicht wirklich gelesen zu haben. Es gibt bisher auch nur wenige Objekte im Biblionetz, die dieses Werk zitieren.