The data connection - challenges at the frontiers of Artificial Intelligence research

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Title The data connection - challenges at the frontiers of Artificial Intelligence research
Author Blumenstein, Michael Myer
Publication Title QUESTnet 2010
Year Published 2010
Abstract The quest to develop artificially intelligent machines that exhibit the behaviour of their biological counterparts has yielded decades of inspired investigation. Recently, a number of significant outcomes have been proffered in the domain of "Artificial Intelligence" research, however despite tremendous progress in the field, a number of challenges still remain. These include the inherent difficulties in replicating the biological complexities of the human brain, but also relate to the practical problems of having rapid and convenient access to real-world data, the ability to effectively manipulate, process and classify unknown records, as well as the efficient management of large quantities of categorised information. This presentation explores the groundbreaking developments in the areas of computer vision, automated pattern recognition and artificial intelligence in the context of real-world problems that are underpinned by the need to apply large volumes of accurate data for training and processing. A number of applications are presented including research into intelligent on-line water quality monitoring technology to ensure sustainable, safe supplies of freshwater across large-scale networks, in addition to the development of automatic systems for monitoring the activities of visitors at our beaches and coastal zones, as well as technologies for preventing the deterioration and collapse of bridges, and finally software that can be used for the early diagnosis and treatment of such brain disorders as Parkinson's disease. Further discussion is dedicated to the future data and resource requirements of artificial intelligence research, implications of the National Broadband Network roll-out, and finally possible directions for attaining the goal of conscious machines.
Peer Reviewed No
Published Yes
Publisher URI https://www.questnet.edu.au/display/qnc2010/Home
Copyright Statement Copyright remains with the author 2010. This is the author-manuscript version of this paper. It is posted here with permission of the copyright owner for your personal use only. No further distribution permitted. For information about this conference please refer to the conference’s website or contact the author.
Conference name QUESTnet 2010
Location Gold Coast, Australia
Date From 2010-07-06
Date To 2010-07-09
URI http://hdl.handle.net/10072/39124
Date Accessioned 2011-04-04
Date Available 2012-09-17T22:00:09Z
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Networking and Communications
Publication Type Conference Publications (Extract Paper)
Publication Type Code e3

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