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Artificial Intelligence (AI): Trying to Get Computers to Think Like Us
Artificial Intelligence (AI): Trying to Get Computers to Think Like Us

... AI is a field older than most realize – the term was coined in the mid 1950s. The field is comprised of many subfields but the main focus is on building intelligent entities. In order to achieve this goal many subcomponents need to be built, including methods for assisting computers to think like hu ...
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... Neural Networks: Use data to predict outputs or interpret inputs Genetic Algorithms: Use data to find “optimal” solutions Fuzzy Logic: Facilitate solutions to human vagueness problems Robotics: Mimic physical human processes Natural-Language Processing: Mimic human communication Intelligent Tutorial ...
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... South America. To complicate matters further, in order to understand places as humans do, an agent must understand that places have attributes that, from a human perspective, provide certain affordances [Gibson, 1979; Glenberg & Robertson, 1999]. For example, a place can be safe, dangerous, hard to ...
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Why Heideggerian AI Failed and how Fixing it would Require

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... Nature being a source of inspiration plays a clamorous role for the advancement in technology and for the solution of computational hard problems as they provide more emphatic and attractive solutions [1]. A new terminology introduced to encompass these nature inspired computation techniques well fa ...
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Liability for Distributed Artificial Intelligences
Liability for Distributed Artificial Intelligences

... about 300 chips per unit are forecast for the year 2000.' This is a part of a trend known as "ubiquitous computing," intensively studied by Xerox PARC in Palo Alto.8 These developments echo the spread of personal computers (PCs), which since 1981 show a total rise from zero in 1981 to about 100 mill ...
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Intelligence explosion

An intelligence explosion is the expected outcome of the hypothetically forthcoming technological singularity, that is, the result of man building artificial general intelligence (strong AI). Strong AI would be capable of recursive self-improvement leading to the emergence of superintelligence, the limits of which are unknown.The notion of an ""intelligence explosion"" was first described by Good (1965), who speculated on the effects of superhuman machines, should they ever be invented:Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.Although technological progress has been accelerating, it has been limited by the basic intelligence of the human brain, which has not, according to Paul R. Ehrlich, changed significantly for millennia. However, with the increasing power of computers and other technologies, it might eventually be possible to build a machine that is more intelligent than humanity. If a superhuman intelligence were to be invented—either through the amplification of human intelligence or through artificial intelligence—it would bring to bear greater problem-solving and inventive skills than current humans are capable of. It could then design an even more capable machine, or re-write its own software to become even more intelligent. This more capable machine could then go on to design a machine of yet greater capability. These iterations of recursive self-improvement could accelerate, potentially allowing enormous qualitative change before any upper limits imposed by the laws of physics or theoretical computation set in.
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