AI transforms technologies in the modern era, reshaping industries, economies, and societies through simulated human intelligence and automation of complex tasks. Rooted in disciplines like computer science, mathematics, cognitive psychology, and data science, AI relies on foundational methods including machine learning, neural networks, and natural language processing to analyze data, recognize patterns, and make decisions. Advances in computational power and the development of sophisticated models accelerate AI's capabilities, enabling breakthroughs in areas like healthcare, robotics, education, and autonomous systems. As researchers push the boundaries of machine intelligence, the future of AI presents both extraordinary opportunities and significant ethical, social, and technological challenges that shape the relationship between humans and intelligent machines. The Foundations and Future of AI: Methods, Models, and Machine Intelligence explores the fundamental principles, techniques, and models that form the basis of AI, including machine learning, neural networks, and data-driven decision-making systems. It examines the future development of machine intelligence, focusing on its potential applications, societal impact, ethical concerns, and the evolving relationship between humans and intelligent technologies. This book covers topics such as predictive modeling, computer vision, and data analysis, and is a useful resource for engineers, academicians, researchers, and scientists.
AmazonPagina's: 370, Hardcover, IGI GLOBAL SCIENTIFIC PUBLISHING
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