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DOI: 10.1515/aucts-2015-0011 ACTA UIVERSITATIS CIBINIENSIS
DOI: 10.1515/aucts-2015-0011 ACTA UIVERSITATIS CIBINIENSIS

Brain-Like Artificial Intelligence: Analysis of a Promising Field
Brain-Like Artificial Intelligence: Analysis of a Promising Field

... which could lead to the same level of cognition, the same way there are plenty of different hardware which can support the exact same operating system in computer science. This approach, applied to Brain-Like Intelligence, is usually categorised as the Top-Down approach, being about the recreation ...
2014 NEURAL NETWORKS AND FUZZY LOGIC CONTROL
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... [5], bridging parallel models such as BSP [7], Multi-BSP [8, 6] or PRAM, and state-of-the-art scheduling algorithms (based on both constraint solving engines or dedicated heuristics [2]) on top of such models. Our goals are to: • Define a general model for massively parallel execution platforms • De ...
project_final1 - CIS @ Temple University
project_final1 - CIS @ Temple University

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ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND DEEP
ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND DEEP

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The Twentieth National Conference on Artificial Intelligence
The Twentieth National Conference on Artificial Intelligence

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Could a machine think? - Alan M. Turing vs. John R. Searle
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Postdoctoral Researcher /Research Associate Bio

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Neural Network
Neural Network

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artificial intelligence notes reasoning methods lecturer:coşkun sönmez
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The Big Test - Rensselaer Polytechnic Institute
The Big Test - Rensselaer Polytechnic Institute

... machine an IQ test … However, [good performance on tasks seen in IQ tests would not] be completely satisfactory because the machine would have to be specially prepared for any specific task that it was asked to perform. The task could not be described to the machine in a normal conversation (verbal ...
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CSE 471/598 Introduction to AI

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The Turing Test Turing`s own objections
The Turing Test Turing`s own objections

... Potted history of IQ tests Turing Test (as now interpreted!) suggests that we base our decision about whether a machine can think on its outward behaviour, and whether we confuse it with humans. Concept of Intelligence in humans We talk about people being more or less intelligent. Perhaps examining ...
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History of artificial intelligence

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
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