AI Game-Playing Techniques: Are They Useful for Anything Other Than Games? In conjunction with the American Association for Artificial Intelligence's Hall of Champions exhibit, the Innovative Applications of Artificial Intelligence held a panel discussion entitled "AI Game-Playing Techniques: Are They Useful for Anything Other Than Games?" This article summarizes the panelists' comments about whether ideas and techniques from AI game playing are useful elsewhere and what kinds of game might be suitable as "challenge problems" for future research. AAAI-98's Hall of Champions exhibit) is an AI games researcher at the University of Alberta and author of the checkers program The early research on the alpha-beta search algorithm was useful in establishing a foundation for AI theories of heuristic search, and these theories have been useful in many areas of AI. Several of the panelists (particularly Schaeffer, Wilkins, and Fotland) pointed out that the minimax search algorithms traditionally associated with AI have only a limited range of applicability.
Dr. Yoshua Bengio, Professor, Department of Computer Science & Operations Research, Université de Montréal Dr. Fei-Fei Li, Associate Professor, Computer Science Department, Stanford University Dr. John Smith, Senior Manager of Intelligent Information Systems, IBM Research Session Chair: Dr. Michael Karasick, VP Innovations, IBM Watson For more, read the white paper, "Computing, cognition, and the future of knowing" https://ibm.biz/BdHErb How we teach computers to understand pictures Fei Fei Li - Duration: 18:03. IBM Research 11,273 views Foundations and Challenges of Deep Learning (Yoshua Bengio) - Duration: 1:12:00. Stanford University School of Engineering 1,004 views Stanford Engineering's Fei-Fei Li explores visual intelligence in computers - Duration: 20:07. Microsoft Research 5,691 views Rajat Arya, Brian Kent: Getting Started with Machine Learning Applications - Duration: 1:27:40.