June 2026
Intermediate
400 pages
10h 11m
English
book
Composite Artificial Intelligence
by T. S. Arun Samuel, L. Jerart Julus, P. Kanimozhi, T. Ananth Kumar, S. Balamurugan
Content preview from Composite Artificial Intelligence
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Preface
In the rapidly evolving landscape of artificial intelligence (AI), the demand for more adaptive, intelligent, and context-aware systems has led to the emergence of Composite Artificial Intelligence (Composite AI)—a paradigm that integrates multiple AI techniques to solve complex real-world problems with higher efficiency and intelligence. This book aims to serve as a comprehensive guide for students, researchers, and practitioners seeking to understand, develop, and apply composite AI systems.
Unlike traditional AI approaches that often rely on singular methodologies, composite AI combines symbolic reasoning, machine learning, data fusion, optimization algorithms, and cognitive computing to create solutions that mimic human-level decision-making more closely. From natural language processing and image recognition to biomedical diagnostics and social media analysis, composite AI is redefining what is possible in intelligent computing.
This book is structured into three parts:
Part I: Foundational Concepts and Emerging Trends in Composite AI lays the groundwork with key concepts, such as data fusion, language models, and early implementations of composite AI in pattern recognition.
Part II: Advanced Methods and Technical Challenges in Composite AI explores cutting-edge optimization techniques, bias mitigation strategies, and integration challenges, providing insights into the complexities of real-world AI development.
Part III: Real-World Applications of Composite AI ...
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