Collection


#RSAC: Panel Discussion on the Role of Machine Learning & AI in Cyber

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A panel of industry experts gathered at RSA 2018 in San Francisco to explore the role that machine learning and artificial intelligence is playing in the current cyber landscape. After opening the discussion by asking the panel to each give their own definition of what machine learning is, Ira asked the speakers to define what types of applications are most appropriate for the use of machine learning and AI. Hillard: The places where it is most mature is around speech and image processing, and also around fraud detection. "The technology should be an enabler to solving a problem but sometimes it gets lost in what's being accomplished." Friedrichs: Most people have woken up to the fact that machine learning and AI are not the panacea that marketing tells us they are, but they can add to the feature set of a product.


Panel Looks to Foster Collaboration Around AI and Machine Learning for CNS Diseases GNS HealthCare

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There's no question artificial intelligence and machine learning technologies are enabling important discoveries in healthcare, but there can be a bit of a disconnect among the various stakeholders using them. A panel discussion at the upcoming CNS Summit in Boca Raton, Fla. presents a rare opportunity to bring the parties together and foster collaboration.


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AI Magazine

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.



Panel Discussion: Applications of Machine Learning

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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.


AI Game-Playing Techniques

AI Magazine

In conjunction with the Association for the Advancement of 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.



The Dark Ages of AI: A Panel Discussion at AAAI-84

AI Magazine

This panel, which met in Austin, Texas, discussed the "deep unease among AI researchers who have been around more than the last four years or so ... that perhaps expectations about AI are too high, and that this will eventually result in disaster."