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This book will present a complete modeling of the human psychic system that allows to generate the thoughts in a strictly organizational approach that mixes a rising and falling approach. The model will present the architecture of the psychic system that can generate sensations and thoughts, showing how one can feel thoughts. The model developed into an organizational architecture based on massive multiagent systems. The architecture will be fully developed, showing how an artificial system can be endowed with consciousness and intentionally generate thoughts and, especially, feel them. These results are multidisciplinary, combining both psychology and computer science disciplines.
Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world. The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011. From its very definition, the reflection of the phenomena that lie beyond AI must be inherently interdisciplinary. And so is this book: all the authors took part in a mutual transdisciplinary dialogue after explaining their views on AI not only to a narrow selection of their usual close peers with the same specialisation, but to a much broader audience of various experts from AI engineering, natural sciences, humanities and philosophy. The chapters of this book thus reflect results of such a dialogue.
This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations. Artificial Dreams epitomize our controversial quest for non-biological intelligence and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities. While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which is often uncritically praised, or hypocritically condemned. And so this phenomenon found its place in the subtitle of the whole volume as well as in the title of the chapter of Kevin Warwick, one of the keynote speakers at “Beyond AI: Artificial Dreams”.
With a 30-year career in artificial intelligence (AI) and computer science, Hall reviews the history of AI, predicting the probable achievements in the near future and provides an intriguing glimpse into the astonishing possibilities and dilemmas on the horizon.
“Andrew Smart deftly shows why it’s time for us to think deeply about thinking machines before they begin thinking deeply about us.” —Douglas Rushkoff, author, Escaping the Growth Trap,Present Shock, and Program or Be Programmed “Provocative and cool.” —Cory Doctorow “Forget the Turing test—will the supersmart AIs that we hear so much about these days pass the acid test? In this playful, informative, and prescient book, Andrew Smart brings psychedelics into dialogue with neuroscience in order to challenge the whiz-bang computational views of human and machine sentience that dominate the headlines. Giving robots LSD sounds like a joke, but Smart is dead serious in his critique of the hidden and sometimes dangerous biases that underlie both popular and scientific fantasies of digital minds.” —Erik Davis, host of “Expanding Mind” and author, Techgnosis: Myth, Magic, and Mysticism in the Age of Information “Philosophy, psychedelics, robots, and the future; consciousness and intelligence, what else do you desire? Here you will see why those machines that reach singularity will be smarter than us and take over the world—and shall need to be conscious…and maybe they can only be conscious if they are human enough. The thesis of the book, and the path shown us by Smart, leads to a great trip, of imagination and philosophy, of maths and neuroscience.” —Dr. Tristan Bekinschtein, Lecturer, Department of Psychology, University of Cambridge Can we build a robot that trips on acid? This is not a frivolous question, according to neuroscientist Andrew Smart. If we can’t, he argues, we haven’t really created artificial intelligence. In an exposition reminiscent of crossover works such as Gödel, Escher, Bach and Fermat’s Last Theorem, Andrew Smart weaves together Mangarevan binary numbers, the discovery of LSD, Leibniz, computer programming, and much more to connect the vast but largely forgotten world of psychedelic research with the resurgent field of AI and the attempt to build conscious robots. A book that draws on the history of mathematics, philosophy, and digital technology, Beyond Zero and One challenges fundamental assumptions underlying artificial intelligence. Is the human brain based on computation? Can information alone explain human consciousness and intelligence? Smart convincingly makes the case that true intelligence, and artificial intelligence, requires an appreciation of what is beyond the computational.
This collection of essays by 12 members of the MIT staff, provides an inside reporton the scope and expectations of current research in one of the world's major AI centers. Thechapters on artificial intelligence, expert systems, vision, robotics, and natural language provideboth a broad overview of current areas of activity and an assessment of the field at a time of greatpublic interest and rapid technological progress.Contents: Artificial Intelligence (Patrick H.Winston and Karen Prendergast). KnowledgeBased Systems (Randall Davis). Expert-System Tools andTechniques (Peter Szolovits). Medical Diagnosis: Evolution of Systems Building Expertise (Ramesh S.Patil). Artificial Intelligence and Software Engineering (Charles Rich and Richard C. Waters).Intelligent Natural Language Processing (Robert C. Berwick). Automatic Speech Recognition andUnderstanding (Victor W. Zue). Robot Programming and Artificial Intelligence (Tomas Lozano-Perez).Robot Hands and Tactile Sensing (John M. Hollerbach). Intelligent Vision (Michael Brady). MakingRobots See (W. Eric L. Grimson). Autonomous Mobile Robots (Rodney A. Brooks).W. Eric L. Grimson,author of From Images to Surfaces: A Computational Study of the Human Early Vision System (MIT Press1981), and Ramesh S. Patil are both Assistant Professors in the Department of Electrical Engineeringand Computer Science at MIT. AI in the 1980s and Beyond is included in the Artificial IntelligenceSeries, edited by Patrick H. Winston and Michael Brady.
Master the approaches and principles of Artificial Intelligence (AI) algorithms, and apply them to Data Science projects with Python and Julia code. Aspiring and practicing Data Science and AI professionals, along with Python and Julia programmers, will practice numerous AI algorithms and develop a more holistic understanding of the field of AI, and will learn when to use each framework to tackle projects in our increasingly complex world. The first two chapters introduce the field, with Chapter 1 surveying Deep Learning models and Chapter 2 providing an overview of algorithms beyond Deep Learning, including Optimization, Fuzzy Logic, and Artificial Creativity. The next chapters focus on AI frameworks; they contain data and Python and Julia code in a provided Docker, so you can practice. Chapter 3 covers Apache's MXNet, Chapter 4 covers TensorFlow, and Chapter 5 investigates Keras. After covering these Deep Learning frameworks, we explore a series of optimization frameworks, with Chapter 6 covering Particle Swarm Optimization (PSO), Chapter 7 on Genetic Algorithms (GAs), and Chapter 8 discussing Simulated Annealing (SA). Chapter 9 begins our exploration of advanced AI methods, by covering Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Chapter 10 discusses optimization ensembles and how they can add value to the Data Science pipeline. Chapter 11 contains several alternative AI frameworks including Extreme Learning Machines (ELMs), Capsule Networks (CapsNets), and Fuzzy Inference Systems (FIS). Chapter 12 covers other considerations complementary to the AI topics covered, including Big Data concepts, Data Science specialization areas, and useful data resources to experiment on. A comprehensive glossary is included, as well as a series of appendices covering Transfer Learning, Reinforcement Learning, Autoencoder Systems, and Generative Adversarial Networks. There is also an appendix on the business aspects of AI in data science projects, and an appendix on how to use the Docker image to access the book's data and code. The field of AI is vast, and can be overwhelming for the newcomer to approach. This book will arm you with a solid understanding of the field, plus inspire you to explore further.
With a 30-year career in artificial intelligence (AI) and computer science, Hall reviews the history of AI, predicting the probable achievements in the near future and provides an intriguing glimpse into the astonishing possibilities and dilemmas on the horizon.
This book will present a complete modeling of the human psychic system that allows to generate the thoughts in a strictly organizational approach that mixes a rising and falling approach. The model will present the architecture of the psychic system that can generate sensations and thoughts, showing how one can feel thoughts. The model developed into an organizational architecture based on massive multiagent systems. The architecture will be fully developed, showing how an artificial system can be endowed with consciousness and intentionally generate thoughts and, especially, feel them. These results are multidisciplinary, combining both psychology and computer science disciplines.
"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.