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Seminar: 9/12 - Lotfi Zadeh

11:00 to 12:30 PM      at:  

Department of Electrical Engineering and Computer Science, UC Berkeley
"Toward human level machine intelligence—is it achievable? The need for a paradigm shift."

Officially, AI was born in 1956. Since then, very impressive progress has been made in many areas?but not in the realm of human level machine intelligence. Anyone who has been forced to use a dumb automated customer service system will readily agree. The Turing Test lies far beyond. Today, no machine can pass the Turing Test and none is likely to do so in the foreseeable future.
Humans have many remarkable capabilities. Among them there are two that stand out in importance. First, the capability to reason, converse and make rational decisions in an environment of imprecision, uncertainty, incompleteness of information and partiality of truth. And second, the capability to perform a wide variety of physical and mental tasks without any measurements and any computations. A prerequisite to achievement of human level machine intelligence is mechanization of these capabilities and, in particular, mechanization of natural language understanding. In my view, mechanization of these capabilities is beyond the reach of the armamentarium of AI?an armamentarium which in large measure is based on classical, Aristotelian, bivalent logic and bivalent-logic-based probability theory.
To make significant progress toward achievement of human level machine intelligence a paradigm shift is needed. More specifically, what is needed is an addition to the armamentarium of AI of two methodologies: (a) a nontraditional methodology of computing with words (CW); and (b) a countertraditional methodology which involves a progression from computing with numbers to computing with words. The centerpiece of these methodologies is the concept of precisiation of meaning.