Artificial Brain
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Artificial Brain
Author: Fouad Sabry
language: en
Publisher: One Billion Knowledgeable
Release Date: 2022-07-10
What Is Artificial Brain An artificial brain is a combination of computer software and hardware that has cognitive capacities that are analogous to those of a human or animal brain. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Artificial brain Chapter 2: Artificial intelligence Chapter 3: Chinese room Chapter 4: Technological singularity Chapter 5: The Age of Spiritual Machines Chapter 6: Mind uploading Chapter 7: Bio-inspired computing Chapter 8: Neuromorphic engineering Chapter 9: Artificial general intelligence Chapter 10: The Singularity Is Near Chapter 11: Neural network Chapter 12: Physical symbol system Chapter 13: Philosophy of artificial intelligence Chapter 14: Neuroinformatics Chapter 15: Outline of artificial intelligence Chapter 16: Hubert Dreyfus's views on artificial intelligence Chapter 17: Brain simulation Chapter 18: How to Create a Mind Chapter 19: Cognitive computer Chapter 20: Hypothetical technology Chapter 21: Turing's Wager (II) Answering the public top questions about artificial brain. (III) Real world examples for the usage of artificial brain in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of artificial brain' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of artificial brain.
ARTIFICIAL BRAIN AND SIMULATION
Author: S. R. Jena
language: en
Publisher: SRJX RESEARCH AND INNOVATION LAB LLP
Release Date: 2025-06-28
The 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. Book Structure and Flow The book is divided into 14 meticulously crafted chapters, each building upon the foundation laid by its predecessors: Chapter 1: Introduction To Artificial Brain This chapter defines what constitutes an artificial brain, outlines the motivation behind its development, and distinguishes it from general-purpose AI. It provides historical insights and visual representations comparing human brains with machine-based intelligence. Chapter 2: Neuroscience Overview To simulate the brain, one must first understand it. This chapter explains the structure, components, and processes of the human brain — including neurons, synapses, learning, memory, and cognition — all explained in computational terms. Chapter 3: Foundations of Artificial Intelligence This chapter transitions to core AI principles, introducing learning paradigms (supervised, unsupervised, reinforcement), deep learning, neural networks, and cognitive architectures like ACT-R and SOAR. Chapter 4: Neuromorphic Computing Neuromorphic systems mimic the behavior of neurons in silicon. This chapter details spiking neural networks, memristors, neuromorphic chips like Loihi and TrueNorth, and the integration of hardware with software. Chapter 5: Brain-Inspired Algorithms Here we discuss Hebbian learning, reinforcement learning loops, bio-inspired optimization methods (GA, PSO, ACO, BFO), and deep cognitive networks as scalable learning systems. Chapter 6: Brain Simulation Projects This chapter dives into real-world simulations like the Blue Brain Project, the Human Brain Project (HBP), OpenWorm, and Nengo — highlighting architectural details and outcomes. Chapter 7: Architecture of Artificial Brain Covering layer-wise simulation of perception, cognition, decision-making, and motor control, this chapter also introduces architectural block diagrams of artificial brains in modular format. Chapter 8: Cognitive Computing and Reasoning Explores AI capabilities in symbolic reasoning, language understanding, planning, perception, and the philosophical notion of self-awareness in synthetic systems. Chapter 9: Memory and Learning Systems It delves into memory models (short-term vs long-term), neural memory frameworks, lifelong learning, and transfer learning. Visual diagrams illustrate how memory evolves in artificial systems. Chapter 10: AI in Healthcare and Brain-Computer Interfaces (BCIs) The intersection of AI and neuroscience is most visible in neural prosthetics, AI for neurological disorders, and BCI-based medical interventions. This chapter includes real-time BCI system design. Chapter 11: Robotics and Autonomous Systems This chapter introduces cognitive robots, emotion-enabled machines, artificial empathy, and humanoid assistants that simulate real social interaction and decision-making. Chapter 12: Smart Systems and Embedded AI Explores deployment of cognitive systems in mobile chips, IoT platforms, smart surveillance, and AR/VR environments. It underscores the importance of real-time, low-power neural architectures. Chapter 13: Ethical, Philosophical Issues and Technological Challenges As artificial brains grow closer to consciousness, this chapter discusses machine rights, existential risks, interpretability, and the control mechanisms necessary to safeguard humanity. A speculative yet evidence-based chapter exploring machine consciousness, AI-human symbiosis, and the implications of uploading human minds into machines (mind uploading). Chapter 14: The Future of Artificial Brain A forward-looking chapter forecasting technological, cognitive, societal, and regulatory trends shaping the future of artificial brain systems. Unique Features of the Book Interdisciplinary Approach: Merges neuroscience, AI, robotics, cognitive science, ethics, and embedded computing. Detailed Diagrams: Over 100 hand-drawn and digitally illustrated diagrams explain complex systems in accessible formats. Comparison Tables: Comparative evaluations of architectures (e.g., ACT-R vs SOAR), chip designs (Loihi vs TrueNorth), and learning models. Recent Research Citations: Each chapter ends with a list of 30 IEEE-style references covering the most recent developments. Case Studies & Applications: Includes Neuralink, BrainGate, OpenWorm, HBP, and real-world BCI-enabled prosthetics. Ethical & Philosophical Lens: Goes beyond technology to address societal impact, machine rights, and AI regulation. The journey toward building an artificial brain is not merely technological—it is deeply philosophical, neuropsychological, and even spiritual. The idea that machines could one day think, feel, or possess some form of synthetic awareness requires us to redefine intelligence, personhood, and even life itself. This book encourages readers to question conventional boundaries and embrace a future that may include minds made of code, thoughts running through silicon, and humanity coexisting with a new cognitive species. We believe Artificial Brain and Simulation will serve as a bridge — connecting the brilliance of natural intelligence with the promise of artificial cognition. Whether you are a student, researcher, or simply a curious mind, we invite you to embark on this voyage where biology meets computation, neurons inspire algorithms, and thought itself is reimagined. We thank you for picking up this book — and we hope it will both inform and inspire you to shape the intelligent systems of tomorrow.
Higher Intelligence
This book describes historical and current research into artificial intelligence. It focuses on the limitations imposed by hardware and software, and approaches inspired by the nature of human brains.