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<p>The findings of a workshop, the goals of which were to identify applications, research problems, and designs of high performance computing and communications (HPCC) systems for supporting applications are discussed. In computer vision, the main scientific issues are machine learning, surface reconstruction, inverse optics and integration, model acquisition, and perception and action. In speech and natural language processing (SNLP), issues were identified statistical analysis in corpus-based speech and language understanding, search strategies for language analysis, auditory and vocal-tract modeling, integration of multiple levels of speech and language analyses, and connectionist systems. In AI, important issues that need immediate attention include the development of efficient machine learning and heuristic search methods that can adapt to different architectural configurations, and the design and construction of scalable and verifiable knowledge bases, active memories, and artificial neural networks.</p>
speech processing; high performance computing and communications; computer vision; natural language processing; artificial intelligence; machine learning; surface reconstruction; inverse optics; model acquisition; statistical analysis; search strategies; language analysis; auditory; vocal-tract modeling; connectionist systems; heuristic search methods; verifiable knowledge bases; active memories; artificial neural networks; computer vision; learning (artificial intelligence); natural languages; speech analysis and processing
D. DeGroot, S. Nirenburg, R.K. Bajcsy, N.H. Morgan, S.J. Stolfo, S.L. Tanimoto, R.E. Korf, D. Moldovan, C.R. Dyer, T.S. Huang, B.W. Wah, L. Hirschman, C. Stanfill, C. Weems, K. DeJong, D.P. Miranker, J. Aloimonos, D. Ballard, T. Poggio, A.K. Joshi, S.E. Levinson, E.M. Riseman, R. Grishman, S.E. Fahlman, "Report on Workshop on High Performance Computing and Communications for Grand Challenge Applications: Computer Vision, Speech and Natural Language Processing, and Artificial Intelligence", IEEE Transactions on Knowledge & Data Engineering, vol. 5, no. , pp. 138-154, February 1993, doi:10.1109/69.204098
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