Artificial Intelligence

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Artificial Intelligence : A Review

Somya Khandelwal somyakhandelwal92@gmail.com
Abstract-This paper examines the current and future roles of Artificial Intelligence (AI) in Computer Science (CS) teaching And research. It characterizes the methodology of Artificial Intelligence by looking at research in speech understanding, a field where AI approaches contrast starkly with the alternatives, particularly engineering approaches. Four values of AI stand out as influential: ambitious goals, introspective plausibility, computational elegance, and wide significance.

I. Introduction

ARTIFICIAL INTELLIGENCE IS A GROWING SUBFIELD OF COMPUTER SCIENCE. THE TERM “ARTIFICIAL INTELLIGENCE” WAS COINED IN 1956 AT A CONFERENCE AIMED AT USING COMPUTERS TO SIMULATE HUMAN INTELLIGENCE. GAME PLAYING AND THEOREM PROVING ARE TWO OF THE EARLIER ATTEMPTS AT GETTING COMPUTERS TO THINK INTELLIGENTLY. SEARCH AND LOGIC FORMED THE BASIS OF THE FIRST AI SYSTEMS. THE LIMITATIONS OF THESE METHODS WERE IDENTIFIED AND LED TO FURTHER DEVELOPMENT OF THE FIELD AND AREAS SUCH AS EXPERT SYSTEMS, NEURAL NETWORKS, EVOLUTIONARY ALGORITHMS, SWARM INTELLIGENCE AND AGENT-BASED TECHNOLOGIES, JUST TO NAME A FEW. THE CONTRIBUTION OF THE PAPER IS AN OVERVIEW OF THE CURRENT STATUS OF THE FIELD OF AI AND NEW DIRECTIONS IN THIS DOMAIN. IT IS ALSO WRITTEN FOR ANY AI RESEARCHERS WHO ARE CONTEMPLATING STARTING A PROJECT IN SPEECH UNDERSTANDING —IT IS INTENDED TO BE THE PAPER THAT, IF AVAILABLE EARLIER, MIGHT HAVE SAVED ME FOUR YEARS OF WASTED EFFORT. RESEARCH IN ARTIFICIAL INTELLIGENCE HAS GROWN RAPIDLY SINCE ITS INCEPTION. THE THREE MAIN DIRECTIONS OF RESEARCH ARE...
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