ICBS (Institute for Cognitive and Brain Sciences) seminar given September 12, 2008 at UC Berkeley. Speaker is: Lotfi Zadeh, Dept. of Electrical Engineering & Computer Science, UC Berkeley.
Abstract.
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.
Biographical Note:
LOTFI A. ZADEH is a Professor in the Graduate School, Computer Science Division, Department of EECS, University of California, Berkeley. In addition, he is serving as the Director of BISC (Berkeley Initiative in Soft Computing). Since the publication of his first paper on fuzzy sets in 1965, his research has been focused on fuzzy logic and its applications.
Lotfi Zadeh has received many awards, among them the IEEE Medal of Honor, the ACM Allen Newell Award, the Honda Prize, the Okawa Prize, the Nicolaus Copernicus Medal of the Polish Academy of Sciences and the Silicon Valley Hall of Fame. He is a recipient of twenty-seven honorary doctorates, and is a member of the National Academy of Engineering. In addition, he is a foreign member of the Russian Academy of Natural Sciences, the Finnish Academy of Sciences, the Polish Academy of Sciences, the Korean Academy of Science & Technology and the Bulgarian Academy of Sciences.
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