Saturday, 3 August 2013

Development of AI

INTRODUCTION
Artificial intelligence is technology and a branch of computer science that studies and develops intelligent machines and software. Luger and Stubblefield define Artificial Intelligence as the branch of computer science that is concerned with the automation of intelligent behavior. The field of artificial intelligence attempts to understand intelligent entities. One reason to study it is to learn more about our own intelligence [1]. It is a broad topic, comprising of diverse fields of study, from neuroscience to expert systems. The common element that all the fields of AI have in between them is the creation of machines that can "think" like human. The theory and insights brought about by AI research are the likely trends in the future of computing [2].
    DEVELOPMENT
The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. By the end of the two-month conference, artificial intelligence had found its niche. However, the main concept of Artificial Intelligence was initiated when Alan Turing proposed “Turing Test” in 1950. Artificial intelligence research has progressed very much since the Dartmouth conference, but the ultimate AI system has yet to be invented [3]. The main advances over the past sixty years have been advances in search algorithms, machine learning algorithms, and integrating statistical analysis into understanding the world at large [4].
The development of AI has been steady with a number of advancements done almost every year since 1956. The first demonstration of the program Logic Theorist (LT) written by Allen Newell, J.C. Shaw and Herbert A. Simon in 1956 at Carnegie Mellon University is presently often considered as the first AI program, though Arthur Samuel's checkers program, developed in 1952, also has a strong claim. In 1957, John McCarthy invented the LISP programming language at MIT which was a huge development in the field of AI. It is still a popular language in learning and research of AI. In 1961, James Slagle wrote the first symbolic integration program in LISP, known as SAINT, which solved calculus problems as equivalent to college freshman level. Continuing the trend of development in 1962, First industrial robot company, Unimation, was founded.
The progress of AI was still quick in 1970s when PROLOG, as an alternative to LISP in logic programming, was created in 1972 and designed to handle computational linguistics, especially natural language processing [4]. A significant promise was shown by AI systems during late 1970s when BKG, a backgammon program written by Hans Berliner at CMU, defeated the reigning world champion in 1979. In 1980s, the first expert system shells and commercial applications based on LISP were developed and market. However, the progress of AI stagnated a bit during early 1980s due to limited computer power and lack of funding for AI research.
1990s saw major advances in all areas of AI, with significant demonstrations and development in a lot of fields related with AI like machine learning, intelligent tutoring, uncertain reasoning, data mining, natural language understanding and translation, and virtual reality. Many examples include Ian Horswill’s extension of behavior-based robotics by creating Polly, the first robot to navigate using vision and operate at animal-like speeds. Also, the new paradigm called "intelligent agents" became widely accepted during the 90s. By late 1990s, algorithms developed by AI researchers appeared as parts of larger systems.
By 2000s, AI had become capable of solving a lot of perceivably very difficult problems. In 2005, Blue Brain project that simulates the brain at molecular detail was born. Similarly, in that year, Honda created the ASIMO robot, an artificially intelligent humanoid robot, which was able to walk as fast as human, delivering trays to customers in restaurant settings. The research and development is still continuing. Throughout its short history, research in AI proved to be essential throughout the technology industry, such as data mining, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and Google's search engine.
   CONCLUSION
Hence, we can say that Artificial Intelligence is a multidisciplinary subject having interconnection with a number of subjects. Its concepts are originated from both abstract and pragmatic fields. Although its modern history is relatively shorter than various disciplines, a large number of researches have already been done in it using methodologies from various related subjects. Therefore, it has become an important subject that acts as an intermediate between abstract human thought and transforming its concepts into intelligent machines.  
References
[1] Stuart Russell, Peter Norvig. “Chapter 1: Introduction.” Internet: http://www.cs.berkeley.edu/~russell/intro.html, [July 27, 2013]
[2] Unknown. “An Introduction to Artificial Intelligence.” Internet: http://library.thinkquest.org/2705/basics.html, [July 27, 2013]
[3] Unknown. “A BRIEF HISTORY OF ARTIFICIAL INTELLIGENCE”. Internet: http://www.atariarchives.org/deli/artificial_intelligence.php, [July 27, 2013]

[4] Chris Smith et al. “The History of Artificial Intelligence” Internet: http://www.cs.washington.edu/education/courses/csep590/06au/projects/history-ai.pdf, December 2006 [July 27, 2013]
©Dixit Bhatta 2013

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