Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trendÔÇöa new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly.
AI and Big Data's Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
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Moses Strydom is a retired professor and recent Chair of the Department of Mechanical and Industrial Engineering at the University of South Africa. An alumni of the University of Perpignan, France (PhD) and New Mexico State University (MSc), Moses is bilingual, French-English, and for the past 30 years, as an academic, has worked in several universities in Africa, France, and the USA. His research interests include computational/experimental fluid dynamics, hydrogen fuel cells; big data and robotics, and holographic technology in m-learning. He has published in several research journals and books, and presented conference papers, both nationally and internationally.
Sheryl Buckley is an Associate Professor in the School of Computing at the University of South Africa (UNISA). She holds a Primary Teacher’s Diploma, Further Diploma in Education, National Diploma in Computer Practice, BEd in Computer based Education, Med in Computer based Education, Postgraduate diploma in Information Management and DLitt et Phil in Information Science. Sheryl previously taught at a High School and at a Technical College for 10 years respectively. Sheryl has been for more than 25 years teaching, researching, practicing and supervising students engaged in research at both doctoral and masters level. Sheryl is a member of the Computer Society of South Africa and an Examiner for the Gauteng Department of Education. In addition, she is a peer reviewer for local, national and international conferences and journals.
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Paperback. Condition: New. Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trendÔÇöa new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data's Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions. Seller Inventory # LU-9781522596882
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