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Cybernetics, Human Cognition, and Machine Learning in Communicative Applications / edited by Vinit Kumar Gunjan, Sabrina Senatore, Amit Kumar

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Cognitive Science and TechnologyPublisher: Singapore : Springer Nature Singapore, 2025Publisher: Singapore : Imprint: Springer, 2025Edition: 1st ed. 2025Description: 1 Online-Ressource(VIII, 427 p. 177 illus., 139 illus. in color.)ISBN:
  • 9789819785339
Subject(s): Additional physical formats: 9789819785322 | 9789819785346 | 9789819785353 | Erscheint auch als: 9789819785322 Druck-Ausgabe | Erscheint auch als: 9789819785346 Druck-Ausgabe | Erscheint auch als: 9789819785353 Druck-AusgabeDDC classification:
  • 006.3 23
DOI: DOI: 10.1007/978-981-97-8533-9Online resources: Summary: 1. Introduction to Cybernetics, Cognition, and Machine Learning -- 2. Foundations of Cybernetics -- 3. Cognition and Cognitive Systems -- 4. Introduction to Machine Learning -- 5. Cybernetics and Machine Learning Integration.Summary: This book presents the fascinating intersection of human cognition and artificial intelligence. Written by leading experts in the fields of cybernetics, cognitive science, and machine learning, this book seeks to bridge the gap between these disciplines and explores the synergies that emerge when humans and machines work together. The book examines the challenges posed by biased data, lack of transparency, and the "black box" nature of some machine learning algorithms. It proposes novel ways to address these issues and foster greater trust and accountability in AI systems. Drawing on cutting-edge research and real-world case studies, it presents a comprehensive and forward-looking perspective on the future of AI and its impact on society. In conclusion, this book offers a compelling exploration of the synergy between human cognition and machine learning, providing insights that are relevant to scholars, researchers, policymakers, and anyone interested in the transformative potential of artificial intelligence.PPN: PPN: 1914539885Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-INR | ZDB-2-SXIT
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