Demystifying Artificial Intelligence

Symbolic, Data-Driven, Statistical and Ethical AI

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Contributor(s)
Gillain, Emmanuel (editor)
Language
English
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Abstract
The book provides an overview of the different AI technologies, demystifying terms such as search, reasoning, learning, adapting, understanding, and interacting. It covers the two dominant paradigms in AI, both the “data-driven” and “symbolic” AI systems, showing how they can complement each other. The theory is illustrated with 22 real-world examples from industry, giving a solid understanding of AI concepts, applicability, and limitations.
URI
https://doab-dev.siscern.org/handle/20.500.12854/170131
Keywords
Machine Learning; Natural Language Processing; Neural Networks; Logic Reasoning; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction
DOI
10.1515/978311142614
ISBN
9783111426143, 9783111425672, 9783111426303
Publisher
De Gruyter
Publisher website
http://www.degruyter.com/
Publication date and place
Berlin/Boston, 2024
Grantor
Imprint
De Gruyter
Series
De Gruyter STEM,
Pages
460