"I became operational . . . in Urbana, Illinois, on January 12, 1997."
Inspired by HAL's self-proclaimed birth date, HAL's Legacy reflects upon science fiction's most famous computer and explores the relationship between science fantasy and technological fact. The informative, nontechnical chapters written especially for this book describe many of the areas of computer science critical to the design of intelligent machines, discuss whether scientists in the 1960s were accurate about the prospects for advancement in their fields, and look at how HAL has influenced scientific research.
Contributions by leading scientists look at the technologies that would be critical if we were, as Arthur Clarke and Stanley Kubrick imagined thirty years ago, to try and build HAL in 1997: supercomputers, fault-tolerance and reliability, planning, artificial intelligence, lipreading, speech recognition and synthesis, commonsense reasoning, the ability to recognize and display emotion, and human-machine interaction. Not only would these technologies be critical in building HAL, but all are being explored for the design of today's intelligent machines. A separate chapter by philosopher Daniel Dennett considers the ethical implications of intelligent machines.
Profusely illustrated with color images from the film and from current research, HAL's Legacy provides surprising new perspectives on key moments in the film - you will never view 2001 the same way again.
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If you loved "2001: A Space Odyssey," you'll be delighted by this book that asks "How realistic was HAL?" Contributions by various scientists include essays on supercomputer design with regard to speech synthesis, common sense reasoning, emotions, lip reading and even playing chess. As the authors explore what is science fantasy and what is technological fact, they also look at how HAL influenced technological development in the past 30 years. The final chapter, called "When HAL Kills, Who's to Blame?" deals with the ethical aspects of building intelligent machines.
David G. Stork is Chief Scientist of the Ricoh California Research Center and Head of its Machine Learning and Perception Group, as well as Consulting Associate Professor of Electrical Engineering and Visiting Scholar in Psychology at Stanford University.
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