Dernière sortie
Artificial Brain and Simulation
About the BookThe human brain remains the most explosive enigmatic and powerful computing system ever known. Its unmatched ability to learn, adapt, reason, and generate creativity continues to inspire scientists, engineers, and philosophers across generations. With the rise of Artificial Intelligence (AI), Neuroscience, and Neuromorphic Engineering, the question once relegated to the realm of science fiction - Can we build an artificial brain? - is now a legitimate and actively explored scientific frontier. This book, Artificial Brain and Simulation, is an earnest attempt to synthesize the diverse yet interrelated domains of cognitive science, machine learning, brain simulation, neuromorphic computing, and robotics into a cohesive academic framework.
This work is not merely a speculative exploration of artificial cognition. Rather, it is grounded in current scientific developments, technological breakthroughs, and practical systems already demonstrating nascent forms of synthetic intelligence. From IBM Watson's symbolic reasoning to the digital neurons firing inside Intel's Loihi neuromorphic chip, from brain-computer interfaces used in prosthetics to AI-driven diagnosis of neurological disorders, the world is witnessing an unprecedented convergence of human cognition and machine computation.
This convergence is shaping what we refer to as Artificial Brain Simulation. Why This Book?: The goal of this book is to serve as a comprehensive guide and reference text for students, researchers, academicians, technologists, and policy makers. It captures the evolving narrative of brain-inspired computing, simulative cognition, and intelligent neural interfaces. Despite the proliferation of literature on AI and neuroscience individually, there exists a noticeable void where both disciplines intersect with engineering design - particularly in the design and simulation of artificial brains.
This book addresses that void. It dives deep into the biological fundamentals of the human brain while simultaneously translating those concepts into machine-executable systems, neural network models, and cognitive architectures. It traces the history, evaluates the present, and speculates on the future of artificially simulating human thought, perception, memory, decision-making, emotion, and even consciousness.
Target Audience: This book is written with multiple tiers of readers in mind: Undergraduate and graduate students studying computer science, neuroscience, AI, robotics, cognitive science, or biomedical engineering. Researchers and Ph. D. candidates seeking deep insights into brain-inspired AI, computational neuroscience, and machine consciousness. Faculty and educators looking for a structured reference to design multidisciplinary courses involving AI and biological cognition.
Industry professionals and startups working on neural interfaces, robotics, AR/VR, BCI, IoT, and intelligent automation. Futurists and philosophers of technology interested in the ethical, social, and psychological dimensions of synthetic minds.
This work is not merely a speculative exploration of artificial cognition. Rather, it is grounded in current scientific developments, technological breakthroughs, and practical systems already demonstrating nascent forms of synthetic intelligence. From IBM Watson's symbolic reasoning to the digital neurons firing inside Intel's Loihi neuromorphic chip, from brain-computer interfaces used in prosthetics to AI-driven diagnosis of neurological disorders, the world is witnessing an unprecedented convergence of human cognition and machine computation.
This convergence is shaping what we refer to as Artificial Brain Simulation. Why This Book?: The goal of this book is to serve as a comprehensive guide and reference text for students, researchers, academicians, technologists, and policy makers. It captures the evolving narrative of brain-inspired computing, simulative cognition, and intelligent neural interfaces. Despite the proliferation of literature on AI and neuroscience individually, there exists a noticeable void where both disciplines intersect with engineering design - particularly in the design and simulation of artificial brains.
This book addresses that void. It dives deep into the biological fundamentals of the human brain while simultaneously translating those concepts into machine-executable systems, neural network models, and cognitive architectures. It traces the history, evaluates the present, and speculates on the future of artificially simulating human thought, perception, memory, decision-making, emotion, and even consciousness.
Target Audience: This book is written with multiple tiers of readers in mind: Undergraduate and graduate students studying computer science, neuroscience, AI, robotics, cognitive science, or biomedical engineering. Researchers and Ph. D. candidates seeking deep insights into brain-inspired AI, computational neuroscience, and machine consciousness. Faculty and educators looking for a structured reference to design multidisciplinary courses involving AI and biological cognition.
Industry professionals and startups working on neural interfaces, robotics, AR/VR, BCI, IoT, and intelligent automation. Futurists and philosophers of technology interested in the ethical, social, and psychological dimensions of synthetic minds.
About the BookThe human brain remains the most explosive enigmatic and powerful computing system ever known. Its unmatched ability to learn, adapt, reason, and generate creativity continues to inspire scientists, engineers, and philosophers across generations. With the rise of Artificial Intelligence (AI), Neuroscience, and Neuromorphic Engineering, the question once relegated to the realm of science fiction - Can we build an artificial brain? - is now a legitimate and actively explored scientific frontier. This book, Artificial Brain and Simulation, is an earnest attempt to synthesize the diverse yet interrelated domains of cognitive science, machine learning, brain simulation, neuromorphic computing, and robotics into a cohesive academic framework.
This work is not merely a speculative exploration of artificial cognition. Rather, it is grounded in current scientific developments, technological breakthroughs, and practical systems already demonstrating nascent forms of synthetic intelligence. From IBM Watson's symbolic reasoning to the digital neurons firing inside Intel's Loihi neuromorphic chip, from brain-computer interfaces used in prosthetics to AI-driven diagnosis of neurological disorders, the world is witnessing an unprecedented convergence of human cognition and machine computation.
This convergence is shaping what we refer to as Artificial Brain Simulation. Why This Book?: The goal of this book is to serve as a comprehensive guide and reference text for students, researchers, academicians, technologists, and policy makers. It captures the evolving narrative of brain-inspired computing, simulative cognition, and intelligent neural interfaces. Despite the proliferation of literature on AI and neuroscience individually, there exists a noticeable void where both disciplines intersect with engineering design - particularly in the design and simulation of artificial brains.
This book addresses that void. It dives deep into the biological fundamentals of the human brain while simultaneously translating those concepts into machine-executable systems, neural network models, and cognitive architectures. It traces the history, evaluates the present, and speculates on the future of artificially simulating human thought, perception, memory, decision-making, emotion, and even consciousness.
Target Audience: This book is written with multiple tiers of readers in mind: Undergraduate and graduate students studying computer science, neuroscience, AI, robotics, cognitive science, or biomedical engineering. Researchers and Ph. D. candidates seeking deep insights into brain-inspired AI, computational neuroscience, and machine consciousness. Faculty and educators looking for a structured reference to design multidisciplinary courses involving AI and biological cognition.
Industry professionals and startups working on neural interfaces, robotics, AR/VR, BCI, IoT, and intelligent automation. Futurists and philosophers of technology interested in the ethical, social, and psychological dimensions of synthetic minds.
This work is not merely a speculative exploration of artificial cognition. Rather, it is grounded in current scientific developments, technological breakthroughs, and practical systems already demonstrating nascent forms of synthetic intelligence. From IBM Watson's symbolic reasoning to the digital neurons firing inside Intel's Loihi neuromorphic chip, from brain-computer interfaces used in prosthetics to AI-driven diagnosis of neurological disorders, the world is witnessing an unprecedented convergence of human cognition and machine computation.
This convergence is shaping what we refer to as Artificial Brain Simulation. Why This Book?: The goal of this book is to serve as a comprehensive guide and reference text for students, researchers, academicians, technologists, and policy makers. It captures the evolving narrative of brain-inspired computing, simulative cognition, and intelligent neural interfaces. Despite the proliferation of literature on AI and neuroscience individually, there exists a noticeable void where both disciplines intersect with engineering design - particularly in the design and simulation of artificial brains.
This book addresses that void. It dives deep into the biological fundamentals of the human brain while simultaneously translating those concepts into machine-executable systems, neural network models, and cognitive architectures. It traces the history, evaluates the present, and speculates on the future of artificially simulating human thought, perception, memory, decision-making, emotion, and even consciousness.
Target Audience: This book is written with multiple tiers of readers in mind: Undergraduate and graduate students studying computer science, neuroscience, AI, robotics, cognitive science, or biomedical engineering. Researchers and Ph. D. candidates seeking deep insights into brain-inspired AI, computational neuroscience, and machine consciousness. Faculty and educators looking for a structured reference to design multidisciplinary courses involving AI and biological cognition.
Industry professionals and startups working on neural interfaces, robotics, AR/VR, BCI, IoT, and intelligent automation. Futurists and philosophers of technology interested in the ethical, social, and psychological dimensions of synthetic minds.
