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 | | Robots Unlimited: Life in a Virtual Age by David Levy ISBN-10: 9781568812397 ISBN-10: 1-56881-239-6 ISBN-13: 9781568812397 ISBN-13: 978-1-56881-239-7 Hardcover 2005-11-30 A K Peters, Ltd. Find Lowest Price |
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Product Description Consider this -- Robots will one day be able to write poetry and prose so touching that it will make men weep compose symphonies that rival the work of Mozart judge a court case with absolute impartiality and fairness converse with the natural ease of your best friend. Robots will one day be so life-like that a human could fall in love and marry one. Thought Provoking and controversial? Certainly. Farfetched? Not at all. In the 50 years since the inception of Artificial Intelligence, computer scientists have made remarkable achievements that can be seen in computer games, childrens toys, your home PC and nearly every facet of human life. In this popular approach to understanding AI, David Levy captures the essence, excitement and potential of Artificial Intelligence. He lays the factual foundations for his intriguing speculations by presenting the history of AI from its earliest conception to present day. He then considers the most recent advances and makes predictions about the future of this burgeoning science. | ||
Reviews | ||
Computer Recognition Charge coupled device (CCD) count the number of electrons within each pixel. Each number is stored, so the whole image can be represented by a series of numbers. Computers can see my means of this device and attempt functional replication of the eye. In a color image the numbers represent both the hue and intensity of the pixel. One of the earliest vision problems to be subject to machine recognition was hand-writing technology. Character segmentation is important because printed characters can be of different size and can be separated by neighbor characters by different distances. The PDA made handwriting recognition an important field of research. The recognition system possess information about how the characters were written, writing direction and the writing order of the strokes and match with the shape of stored characters. In 1960, Israel Gelfand, at the USSR Academy of Science developed a successful natural handwriting technology. Stefan Pachikov founded paragraph International which SGI later buys. NHR technology underlying idea is that fact that cursive handwriting is a series of movements made by a writing instrument. Each movement can be represented by one more more of eight elements that are sufficient to describe all the trajectories of the pend found in the cursive letter of the Roman alphabet. The analytical word recognizer is based on a database of symbol prototypes and neural network generalized pattern recognition schemes and training. Human Face recognition differentiates unique physical attributes about a person face, the different heights, depths, and weights. Computer vision systems can pick peoples face out of a crowd almost instantaneously and measure various features of that face and compare the measurements with those faces stored in the database. Everyones face has distinguishable features for example peaks and troughs. There are about 80 of these features on the human face, including distance between the eyes, the width of the nose and the depth of the eye sockets. The computer after measuring the face creates a numerical number representing the face. Usually 14 to 22 of the 80 features in a face print is enough to complete the recognition process. Video surveillance system search for face in Low resolution image of the scene and switches to a high resolution search when a head-like has been spotted. Once a face is detected, the system determines then determines the position, size and pose of the head. The image of the head is then scaled up or down in size and rotated in the same size and pose employed for faces in the system's database. The most successful recognition system can match faceprints at 60 million per minute. MobileEye acts as a silent driver assisting with Forward looking, side mirror, and in cabin recognition. MobileEye can detect cars moving into the passing lane, distance ranges, and switch attention by changing colors indicating possible collision objects, pedestrians moving into the travel lane, and off-road path finding. The recognition software can watch passenger position and make decision for airbag deployment. Cameras on the side mirror can watch blind spots and warn for sudden merges into the passing lane by other cars. Side mirror recognition differentiates between cars not within collision and those who are. Forward looking recognition system can recognize markings on the road. "The system fits a three-parameter road model that accounts for lateral position, slope and curvature. The curvature parameter is used for increasing the warning reliability under curved roads and for estimating time to lane crossing." The ears of a computer are microphones, devices that contain some sort of diaphragm that vibrates in concert with audible sound. The vibrations are converted to electrical signals, which can be displayed as a waveform on a screen or measured electronically. Speech recognition is recognizing waveforms. Different people can say the same word with different pitches, speeds, and intensities; all these variation change how the word is said. Dynamic time warping has the affect of stretching or compressing segments of the speech sound in a word, in order to make the waveform easier to match with a store waveform. A technique called Hidden Markov Models HMMs are used to recognize phoneme strings and calculate summed values for all possible combinations of the sounds. The highest probabilities phoneme string is selected. Visual recognition systems are being used to watch lip movement and use context feedback to improve speech recognition. | ||
A complete and expert analysis and collection of such a popular and innovative science Robots Unlimited: Life In A Virtual Age by David Levy (leader of the winning team of the Loebner Prize Competition in 1997) is a highly researched and historically impressive documentation devoted to the past fifty years of research and development in Artificial Intelligence and Robotics. As an informative and superbly written study, Robots Unlimited offers readers an outstanding historical survey and a seminal reference to the many intricacies of an ever-escalating modern science in these specialized fields, as well as knowledgeable and intuitive predictions of what the future may bring for robotic and artificial intelligence breakthroughs. Very strongly recommended to all students of Robotics, Artificial Intelligence, and relevant technological advancements, Robots Unlimited gives its readers a complete and expert analysis and collection of such a popular and innovative science. | ||
An interesting overview of robotics and machine intelligence Throughout the last five decades, fed by both curiosity and military requirements, the design and construction of robots has occupied the time of many researchers, and involved the spending of hundreds of millions of dollars. In this book the author presents an overview of robotics for a semi-popular audience, beginning with a fairly detailed summary of the early history of artificial intelligence. It should be remembered that robotics is but one subfield of artificial intelligence, and that the latter field encompasses much more than the building of humanoid-looking machines. And interestingly, when one compares the research forty or even fifty years ago with what is going on at the present time, it is readily apparent that the differences are more of quality rather than quantity. But intelligent machines do not have to take the form of humanoid robots. Hollywood and science fiction novels are partly responsible for this attitude, as are the philosophers, who insist upon the Turing test as being a genuine test for machine intelligence. It is evident when reading the book, especially the last part, that the author will not be convinced of the existence of intelligent machines until they do most, if not all, of the things that humans do. This includes the ability to make love, the ability to reproduce, the possession of legal rights, the possession of consciousness, and the ability to feel emotion and fall in love. A machine taking the form of a humanoid robot that was able to do all of things would certainly qualify as being intelligent. But there are many other types of machines, some of which exists today and are working in the field, that qualify as being intelligent, even though it is a different type of intelligence than what most humans are used to (or would acknowledge as such). This observation raises another issue that is noticeably lacking in this book, as well as in the history of artificial intelligence in general. This issue involves the adoption of a quantitative definition of machine intelligence that will allow its measurement. If one is to judge the progress in artificial intelligence, it is necessary to define criteria, possibly informal, for assessing to what degree one machine is more intelligent or of higher quality than another. The criteria must also be able to distinguish an intelligent from a non-intelligent machine. The Turing test is not entirely suitable as a criterion, since it emphasizes, somewhat myopically and exclusively, human intelligence as being the most objective measure. After careful study of the history of artificial intelligence, in this book and many others, as well as research papers, and through the development and practical use of `algorithms' that are deemed to be intelligent in some way, this reviewer arrived at an informal classification scheme for intelligent machines. Sometimes this scheme allows the quantitative measurement of machine intelligence, a `machine IQ' if you will, but usually it classifies machines according to what they can do, and to the degree that the machines require assistance from another machine (human or not). For example, one could label a machine `Type-1' if it is an ordinary calculating machine, unable to learn or check its answers, or unaware of its environment. Type-1 machines are uninteresting from the standpoint of artificial intelligence research. A `Type-2' machine can find answers to domain-specific problems and check these answers according to standards given to it from another machine. Type-2 machines essentially need `tutors' or some kind of assistance to evaluate or continue learning. The chess playing machines described in this book, such as Deep Blue and Deep Thought, could be classified as Type-2 machines. The Pinkerton music-creating machine is also Type-2 as are the rule-based music-creating machines discussed in the book. `Type-3' machines are able to check their answers to domain-specific problems and make judgments as to the quality of these answers, and do independently of any external standards. The Samuel checkers playing machine and the NeuroGammon and TD-Gammon backgammon playing machines described in this book could be classified as Type-3 machines, as would the `metagame' machines that can learn how to play a game given only the rules. Also Type-3 is the bridge-playing COBRA machine, and the Poki poker-playing machine, the Thaler Creativity Machine, the BRUTUS storytelling machine, all of which are discussed in the book. A `Type-4' machine is one that is able to judge the quality of its answers to domain-specific problems and then propose theories or explanations that subsume these problems. Type-4 machines are thus machines that one could use to conduct scientific research for example. The EMI music-making machine discussed in the book is a Type-4 machine, due to its ability to analyze the structure of the music presented to it, and then extract the composer's style from it. Type-4 machines have been used in automated drug discovery, although this use is not discussed in this book. Next are the `Type-5' machines, which are able to solve problems in more than one domain, but with their interest in solving these problems is instigated by an external inquirer, i.e. they do not possess any innate curiosity. The `commonsense reasoning' machines of Cycorp, Inc, which are discussed in the book, are examples of Type-5 machines. It is their ability to solve problems in more than one domain that makes Type-5 machines of great interest to many in the artificial intelligence community. Many in fact do not believe a machine is truly intelligent unless it can think in more than one domain. A `Type-6' machine can express curiosity and creativity, can solve problems without any external instigation, and can develop theories or explanations around these problems. The author discusses several types of machines in the book that could be classified as Type-6, if one omitted the ability to find solutions without being instigated by an external machine or human. Lastly, there are `Type-7' machines, which can self-manage and self-replicate, and are also Type-6. Self-replication is discussed in the book, but there are no machines to date that are Type-7. | ||
Describing the Current State of the Art in Robotics It's been about 50 years since the word Artificial Intelligence was coined. Since then there have been a number of television shows and movies about AI, but in real life AI has yet to produce a young boy to life an even quasi-normal life. Behind the scenes however, research has been going on to develop the sub-systems needed as a foundation of AI. In this book the author describes what's going on in computers about such critical areas as vision, speech, taste, smell and so on. The big problem, and what's covered in most of the book are what you might call the thinking components. How do computers think? How do they play games such as chess? Or one of the hot new items, play soccer. Then there are real problems like getting the computer to write fiction? Can a computer be programmed to transpose bits and bytes into thought, or love? There have been a number of books lately on robotic activities you can do at home. This one is a description of the state of the art in the research labs around the world. | ||