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Mind, Brain, Quantum AI, and the Multiverse
There is a long-lasting controversy concerning our mind and consciousness. Mind, Brain, Quantum AI, and the Multiverse proposes a connection between the mind, the brain, and the multiverse. The author introduces the main philosophical ideas concerning mind and freedom, and explains the basic principles of computer science, artificial intelligence of brain research, quantum physics, and quantum artificial intelligence. He indicates how we can provide an answer to the problem of the mind and consciousness by describing the nature of the physical world. His proposed explanation includes the Everett Many-Worlds theory. This book tries to avoid any non-essential metaphysical speculations. The text is an essential compilation of knowledge in philosophy, computer science, biology, and quantum physics. It is written for readers without any requirements in mathematics, physics, or computer science.
Quantum Artificial Intelligence with Qiskit
Quantum Artificial Intelligence (QAI) is a new interdisciplinary research field that combines quantum computing with Artificial Intelligence (AI), aiming to use the unique properties of quantum computers to enhance the capabilities of AI systems. Quantum Artificial Intelligence with Qiskit provides a cohesive overview of the field of QAI, providing the tools for readers to create and manipulate quantum programs on devices as accessible as a laptop computer. Introducing symbolical quantum algorithms, sub-symbolical quantum algorithms, and quantum Machine Learning (ML) algorithms, this book explains each process step by step with associated Qiskit listings. All examples are additionally available for download at https://github.com/andrzejwichert/qai. Allowing readers to learn the basic concepts of quantum computing on their home computers, this book is accessible to both the general readership as well as students and instructors of courses relating to computer science and AI.
Principles Of Quantum Artificial Intelligence: Quantum Problem Solving And Machine Learning (Second Edition)
This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.
Intelligent Big Multimedia Databases
Multimedia databases address a growing number of commercially important applications such as media on demand, surveillance systems and medical systems. The book presents essential and relevant techniques and algorithms to develop and implement large multimedia database systems.The traditional relational database model is based on a relational algebra that is an offshoot of first-order logic and of the algebra of sets. The simple relational model is not powerful enough to address multimedia data. Because of this, multimedia databases are categorized into many major areas. Each of these areas are now so extensive that a major understanding of the mathematical core concepts requires the study of different fields such as information retrieval, digital image processing, feature extraction, fractals, machine learning, neuronal networks and high-dimensional indexing. This book unifies the essential concepts and recent algorithms into a single comprehensive volume.
Principles Of Quantum Artificial Intelligence
In this book, we introduce quantum computation and its application to AI. We highlight problem solving and knowledge representation framework. Based on information theory, we cover two main principles of quantum computation — Quantum Fourier transform and Grover search. Then, we indicate how these two principles can be applied to problem solving and finally present a general model of a quantum computer that is based on production systems.
Machine Learning - A Journey To Deep Learning: With Exercises And Answers
This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)
Liberating Sociology: From Newtonian Toward Quantum Imaginations: Volume 1: Unriddling the Quantum Enigma
In this major new study in the sociology of scientific knowledge, social theorist Mohammad H. Tamdgidi reports having unriddled the so-called ‘quantum enigma.’ This book opens the lid of the Schrödinger’s Cat box of the ‘quantum enigma’ after decades and finds something both odd and familiar: Not only the cat is both alive and dead, it has morphed into an elephant in the room in whose interpretation Einstein, Bohr, Bohm, and others were each both right and wrong because the enigma has acquired both localized and spread-out features whose unriddling requires both physics and sociology amid both transdisciplinary and transcultural contexts. The book offers, in a transdisciplinary an...
Mind, Brain, Quantum AI, and the Multiverse
Mind, Brain, Quantum AI, and the Multiverse There is a long-lasting controversy concerning our mind and consciousness.This book proposes a connection between the mind, the brain, and the multiverse. The author introduces the main philosophical ideas concerning mind and freedom, and explains the basic principles of computer science, artificial intelligence of brain research, quantum physics, and quantum artificial intelligence. He indicates how we can provide an answer to the problem of the mind and consciousness by describing the nature of the physical world. His proposed explanation includes the Everett Many-Worlds theory. Mind, Brain, Quantum AI, and the Multiverse tries to avoid any non-essential metaphysical speculations. The book is an essential compilation of knowledge in philosophy, computer science, biology, and quantum physics. It is written for readers without any requirements in mathematics, physics, or computer science.
Principles of Quantum Artificial Intelligence
In this book, we introduce quantum computation and its application to AI. We highlight problem solving and knowledge representation framework. Based on information theory, we cover two main principles of quantum computation -- Quantum Fourier transform and Grover search. Then, we indicate how these two principles can be applied to problem solving and finally present a general model of a quantum computer that is based on production systems.
