图书简介
In recent years, neural networks have re-emerged in relation to artificial intelligence (AI), representing a well-grounded paradigm rooted in disciplines from physics and psychology to information science and engineering. Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. This book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book: by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering.
1. Nature’s Learning Rule: The Hebbian-LMS Algorithm 2. A Half Century of Progress Toward a Unified Neural Theory of Mind and Brain With Applications to Autonomous Adaptive Agents and Mental Disorders 3. Third Gen AI as Human Experience Based Expert Systems 4. The Brain-Mind-Computer Trichotomy: Hermeneutic Approach 5. From Synapses to Ephapsis: Embodied Cognition and Wearable Personal Assistants 6. Evolving and Spiking Connectionist Systems for Brain-Inspired Artificial Intelligence 7. Pitfalls and Opportunities in the Development and Evaluation of Artificial Intelligence Systems 8. The New AI: Basic Concepts, and Urgent Risks and Opportunities in the Internet of Things 9. Theory of the Brain and Mind: Visions and History 10. Computers Versus Brains: Game Is Over or More to Come? 11. Deep Learning Approaches to Electrophysiological Multivariate Time-Series Analysis Computational Intelligence in the Time of Cyber-Physical Systems and the Internet of Things 12. Multiview Learning in Biomedical Applications 13. Meaning Versus Information, Prediction 14. Versus Memory, and Question Versus Answer 15. Evolving Deep Neural Networks
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