Demystifying Artificial Intelligence
This book is intended for business professionals that want to understand the fundamental concepts of Artificial Intelligence, their applications and limitations.Built as a collaborative effort between academia and the industry, this book bridges the gap between theory and business application, demystifying AI through fundamental concepts and industry examples. The reader will find here an overview of the different AI techniques to search, plan, reason, learn, adapt, understand and interact.
Practical information:
Georganiseerd door:
The book covers the two traditional paradigms in AI: the statistical and data-driven AI systems, which learn and perform by ingesting millions of data points into machine learning algorithms, and the consciously modelled AI systems, known as symbolic AI systems, which use explicit symbols to represent the world and make conclusions. Rather than opposing those two paradigms, the book will also show how those different fields can complement each other.
All royalties go to a charity.
“Demystifying AI reveals its true power: not as a mysterious force, but as a tool for human progress, accessible to all who seek to understand it.”
Dr. Barak Chizi, Chief Data & Analytics Officer, KBC Group
- a holistic view of the different AI fields: symbolic, data-driven, statistical and ethical AI
- the key concepts explained using a pedagogical approach
- illustrated by 22 industry examples
Author / Editor information
Emmanuel Gillain works at Microsoft and served on advisory boards. He helps companies leverage digital technologies to their advantage. He holds industry certifications, a master’s degree in engineering and completed an executive management program at INSEAD.
The theory of the core chapters in this book was contributed by internationally renowned professors in the field of artificial intelligence: Prof. Yves Deville, Prof. Bart Bogaerts, Prof. Isabelle Linden, Prof. Aleksandra Pizurica, Prof. Hendrik Blockeel, Prof. Walter Daelemans, Prof. Erik Mannens.
A significant number of the authors of this book are integral members of the Flanders AI Research Program. Find the list of their contributions here:
- Reasoning with first-order logic
Bart Bogaerts - KU Leuven, VUB
- Probalistic reasoning: When the environment is uncertain
Alexandra Pižurica - University of Ghent
- Learning from data
Hendrik Blockeel - KU Leuven
- Between language and knowledge
Walter Daelemans - University of Antwerp
- Some words about ethics. The angles of fairness and transparency
Erik Mannens - University of Antwerp, University of Ghent
- Industry examples when different AI techniques are combined
Hendrik Blockeel (with Oussama Chelly) - KU Leuven
Teachers / speakers
Walter Daelemans
Walter Daelemans is professor of Artificial Intelligence and Natural Language Processing (NLP) at the University of Antwerp. He helped pioneer the statistical and machine learning revolution in NLP in the nineties with the development of Memory-Based Language Processing and with work on the methodology of machine learning for language processing. He was awarded EurAI and ACL fellowships for this work, and has published influential work on text mining and knowledge extraction from biomedical, clinical, and social media text, and on stylometry and author profiling. With currently 32 supervised PhDs graduated and more than 400 co-authored publications he is one of the most prolific NLP researchers in the Low Countries. In addition, he has been involved in the creation of high profile valorization results with popular open-source software such as TiMBL and Pattern, and has been instrumental in the creation of several spin-offs (textkernel, textgain, fluent.ai).
Erik Mannens
Erik Mannens is Director @ imec UAntwerp IDLab & Professor @ UAntwerp (Sustainable AI) and @ Ghent University (Semantic Intelligence). Since 2005 he has successfully managed +160 "interdisciplinary" projects (amounting 30M euro of Funding for his team) and teams of 50 to 125 researchers. He received his PhD degree in Computer Science Engineering (2011) at UGent, his Masters degree in Computer Science (1995) at K.U. Leuven University & his Masters degree in Electro-Mechanical Engineering (1992) at KAHO Ghent.
Being 50+, from now on I tend to only take on new projects who will have a positive & lasting impact on Society and "Spaceship Earth" as a whole! #SustainableDevelopmentGoals ... As such, I took on the Operational Lead of SOLID Lab Flanders for half a year in 2022 and now I am heading imec UAntwerp IDLab where we're working towards Sustainable AI. As such, I now head a Data Science team of +125 Wireless Communication & AI Experts that research all aspects of the Sustainability of AI.
Expertise: Sustainable AI & Ethical AI
Bart Bogaerts
I'm a research professor in the Declarative Languages and Artificial Intelligence section of the KU Leuven. My research interests are spread throughout the field of knowledge representation. They range from high-level representation languages to performance optimisations in SAT, from abstract, algebraical frameworks to unify semantics of logics to implementation of knowledge base systems, from applications of KR to integration of declarative problem solving paradigms,... My current focus is developing mechanisms that instill trust in solving technology by means of proofs. This is the core topic of my ERC grant.
I am also partially affiliated to the AI lab of the Vrije Universiteit Brussel (VUB).
Alexandra Pižurica
Aleksandra Pizurica is Professor in statistical image modelling at Ghent University. Prof. Pizurica is a Senior Area Editor for the IEEE Transactions on Image Processing (2016 –), Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology (2016 –), and served as an Associated Editor for the IEEE Transactions on Image Processing (2012–2016). She received the Scientific Prize “de Boelpaepe” for 2013-2014, from the Royal Academy of Science, Letters and Fine Arts of Belgium. Her research is in the area of statistical modelling, probabilistic graphical models and inference, sparse coding, signal/image processing and machine learning.
Hendrik Blockeel
Hendrik Blockeel (PhD in Computer Science, 1998, KU Leuven) is a full professor ("gewoon hoogleraar") at KU Leuven. From 2007 till 2016 he was also affiliated with Leiden University. His research interests include theory and algorithms for machine learning and data mining in general, with a particular focus on relational learning, graph mining, probabilistic logics, inductive knowledge bases, and applications of these techniques in the broader field of computer science, bio-informatics, and medical informatics.
Related courses
Artificial Intelligence in Business and Industry
Postgraduate - Kortrijk - KU Leuven, PUC - KU Leuven Continue, VAIA