Artificial Intelligence
What Is Behind the Technology of the Future?
Published on 16. May 2025
Book
Paperback/Softback
XX, 474 pages
978-3-031-50607-9 (ISBN)
Description
Artificial Intelligence (AI) is already present in our daily routines, and in the future, we will encounter it in almost every aspect of life - from analyzing X-rays for medical diagnosis, driving autonomous cars, maintaining complex machinery, to drafting essays on environmental problems and drawing imaginative pictures. The potentials of AI are enormous, while at the same time many myths, uncertainties and challenges circulate that need to be tackled.
The English translation of the book "Künstliche Intelligenz - Was steckt hinter der Technologie der Zukunft?" originally published in German (Springer Vieweg, 2020), this book is addressed to the general public, from interested citizens to corporate executives who want to develop a better and deeper understanding of AI technologies and assess their consequences.
Mathematical basics, terminology, and methods are explained in understandable language. Adaptations to different media such as images, text, and speech and the corresponding generative models are introduced. A concluding discussion of opportunities and challenges helps readers evaluate new developments, demystify them, and assess their relevance for the future.
The English translation of the book "Künstliche Intelligenz - Was steckt hinter der Technologie der Zukunft?" originally published in German (Springer Vieweg, 2020), this book is addressed to the general public, from interested citizens to corporate executives who want to develop a better and deeper understanding of AI technologies and assess their consequences.
Mathematical basics, terminology, and methods are explained in understandable language. Adaptations to different media such as images, text, and speech and the corresponding generative models are introduced. A concluding discussion of opportunities and challenges helps readers evaluate new developments, demystify them, and assess their relevance for the future.
More details
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Illustrations
412 farbige Abbildungen, 7 s/w Abbildungen
XX, 474 p. 419 illus., 412 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 27 mm
Weight
744 gr
ISBN-13
978-3-031-50607-9 (9783031506079)
DOI
10.1007/978-3-031-50605-5
Schweitzer Classification
Other editions
Additional editions
Book
05/2024
Springer
€53.49
Shipment within 15-20 days
Persons
Dr. Gerhard Paaß
is a Lead Scientist at the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS). With a background in Mathematics, he is a recognized expert in the field of Artificial Intelligence, particularly in the area of Natural Language Processing. Dr. Paaß has previously worked at UC Berkeley in California and the University of Technology in Brisbane. He has served as reviewer and conference chair at various international conferences, including NeurIPS, CIKM, ECML/PKDD, ICDM, and KDD, where he regularly is a member of the program committee. Dr. Paaß has received a "best paper" award on probabilistic logic, is the author of about 70 publications for international conferences and journals and he is co-author of the best-selling Open Access book "Foundation Models for Natural Language Processing" (Springer, 2023). He is currently involved in the creation of a computer center for Foundation Models. Besides experimental researchon Foundation Models, he holds lectures for Deep Learning and Natural Language Understanding at the University of Bonn and in industry.
Dr. Dirk Hecker is deputy director of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and managing director of the Fraunhofer Big Data and Artificial Intelligence Alliance, the largest alliance of the Fraunhofer-Gesellschaft with more than 30 member institutes. In addition, Dr. Hecker is a member of the board of directors of the Fraunhofer Academy, which is a further education institution of the Fraunhofer-Gesellschaft aimed at specialists and executives of technology-driven companies. Dr. Hecker has many years of experience in leading research and industrial projects in the field of data mining and Machine Learning. His current work focuses on Big Data Analytics, Predictive Analytics, Deep Learning and Explainable AI. He studied geo-informatics at the Universities of Cologne and Bonn and received his PhD from the University of Cologne. Dr. Hecker is the author of numerous publications in the above-mentioned fields and is active as a subject matter expert and auditor on the topic of Artificial Intelligence in a wide variety of committees.
Dr. Dirk Hecker is deputy director of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and managing director of the Fraunhofer Big Data and Artificial Intelligence Alliance, the largest alliance of the Fraunhofer-Gesellschaft with more than 30 member institutes. In addition, Dr. Hecker is a member of the board of directors of the Fraunhofer Academy, which is a further education institution of the Fraunhofer-Gesellschaft aimed at specialists and executives of technology-driven companies. Dr. Hecker has many years of experience in leading research and industrial projects in the field of data mining and Machine Learning. His current work focuses on Big Data Analytics, Predictive Analytics, Deep Learning and Explainable AI. He studied geo-informatics at the Universities of Cologne and Bonn and received his PhD from the University of Cologne. Dr. Hecker is the author of numerous publications in the above-mentioned fields and is active as a subject matter expert and auditor on the topic of Artificial Intelligence in a wide variety of committees.
Content
Preface.- About the Authors.- 1. What Is Intelligent About Artificial Intelligence?.- 2 What Are the Capabilities of Artificial Intelligence?.- 3. Some Basic Concepts of Machine Learning.- 4. Deep Learning Can Recognize Complex Relationships.- 5. Image Recognition with Deep Neural Networks.- 6. Capturing the Meaning of Written Text.- 7. Understanding Spoken Language.- 8. Learning Optimal Policies.- 9. Creative Artificial Intelligence and Emotions.- 10. AI and Its Opportunities, Challenges and Risks.- Appendix.- Index.