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AI at IBM Research
November/December 2000 (vol. 15 no. 6)
pp. 51-57
For many years, most AI research at IBM used the symbolic paradigm, but today increasingly uses statistics, particularly for such applications areas as machine learning and natural language processing. This trend has led to the growth of new areas such as statistical learning theory and Bayesian networks as active areas of inquiry. This article reports on the range of AI activities within IBM Research and discusses emerging issues, particularly in broad areas: representation and reasoning, statistical AI, vision, and game playing.
Index Terms:
statistical AI, vision, game-playing, representation and reasoning, AI, learning theory.
Citation:
Chidanand Apte, Leora Morgenstern, Se June Hong, "AI at IBM Research," IEEE Intelligent Systems, vol. 15, no. 6, pp. 51-57, Nov.-Dec. 2000, doi:10.1109/5254.895861
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