Issue No. 06 - November/December (2000 vol. 15)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/5254.895861
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.
statistical AI, vision, game-playing, representation and reasoning, AI, learning theory.
S. J. Hong, L. Morgenstern and C. Apte, "AI at IBM Research," in IEEE Intelligent Systems, vol. 15, no. , pp. 51-57, 2000.