The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence

This quote/commented critique of Turing's classical paper suggests that Turing meant -- or should have meant -- the robotic version of the Turing Test (and not just the email version). Moreover, any dynamic system (that we design and understand) can be a candidate, not just a computational one. Turing also dismisses the other-minds problem and the mind/body problem too quickly. They are at the heart of both the problem he is addressing and the solution he is proposing

Herbert Simon (1916-2001). The scientist of the artificial

With the disappearance of Herbert A. Simon, we have lost one of the most original thinkers of the 20th century. Highly influential in a number of scientific fields—some of which he actually helped create, such as artificial intelligence or information-processing psychology—Simon was a true polymath. His research started in management science and political science, later encompassed operations research, statistics and economics, and finally included computer science, artificial intelligence, psychology, education, philosophy of science, biology, and the sciences of design. His often controversial ideas earned him wide scientific recognition and essentially all the top awards of the fields in which he researched, including the Turing award from the Association of Computing Machinery, with Allen Newell, in 1975, the Nobel prize in economics, in 1978, and the Gold Medal Award for Psychological Science from the American Psychological Foundation, in 1988

We need a Weizenbaum test for AI

Alan Turing introduced his 1950 paper on Computing Machinery and Intelligence with the question “Can machines think?” But rather than engaging in what he regarded as never-ending subjective debate about definitions of intelligence, he instead proposed a thought experiment. His “imitation game” offered a test in which an evaluator held conversations with a human and a computer. If the evaluator failed to tell them apart, the computer could be said to have exhibited artificial intelligence (AI)

Application of data science for controlling energy crises: A case study of Pakistan

© 2019 Association for Computing Machinery. Today Pakistan is facing numerous challenges for the interconnection of local energy resources and for balanced energy policies. Data Science, Big Data, Artificial Intelligence (AI), IoT and Cloud computing draws our focus towards controlling energy crises in terms of smart energy generation, consumption and to overcome causes of energy crises. To make a conclusion valuable we have to extract significant value from a large amount of data that‟s why data management plays a significant role. This Paper presents a review of energy sectors, energy resources, energy crises in Pakistan. It also presents the possible solution of energy crises with the help of data science application and the involvement of Big Data, Cloud computing, IoT and AI

Leveraging Intelligent Computation Offloading with Fog/Edge Computing for Tactile Internet: Advantages and Limitations

[EN] With the recent advancement in wireless communication and networks, we are at the doorstep of the Tactile Internet. The Tactile Internet aims to enable the skill delivery and thereafter democratize the specialized skills for many emerging applications (e.g., remote medical, industrial machinery, remote robotics, autonomous driving). In this article, we start with the motivation of applying intelligent edge computing for computation offloading in the Tactile Internet. Afterward, we outline the main research challenges to leverage edge intelligence at the master, network, and controlled domain of the Tactile Internet. The key research challenges in the Tactile Internet lie in its stringent requirements such as ultra-low latency, ultra-high reliability, and almost zero service outage. We also discuss major entities in intelligent edge computing and their role in the Tactile Internet. Finally, several potential research challenges in edge intelligence for the Tactile Internet are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grant 61901128, and Agile Edge Intelligence for Delay Sensitive IoT (AgilE-IoT) project (Grant No. 9131-00119B) of Independent Research Fund Denmark (DFF).Mukherjee, M.; Guo, M.; Lloret, J.; Zhang, Q. (2020). Leveraging Intelligent Computation Offloading with Fog/Edge Computing for Tactile Internet: Advantages and Limitations. IEEE Network. 34(5):322-329. https://doi.org/10.1109/MNET.001.200000432232934

The child program and the history of AI

In this contribution I try to illustrate some of the most significant moments in the history of AI (Artificial Intelligence), imagining that they have been a series of subsequent stages in the development of the so called "Child Program." With this name Alan Turing - in Computing machinery and intelligence (1950) - described for the first time the idea of an algorithm "capable of being educated." After discussing Turing’s prophecy, I will present some milestones of research in AI considering that each is a piece of a "learning scheme" of extended intelligence, i.e. an intelligence ascribable not only to humans beings, but also to any subject able to support thinking functions. I propose that from the elements of this scheme it is possible to draw useful suggestions for human education in general. In the final part of the contribution, I will collect the elements into a synoptic vision, which I will call "the educational protocol of the extended intelligence." This will define the minimum requirements that a training course should possess in order to conduct a "child program" at the "adult program" stage

ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF ALAN TURING’S ROLE IN THE CONCEPTION AND DEVELOPMENT OF INTELLIGENT MACHINERY

The purpose of this thesis is to follow the thread of Alan Turing’s ideas throughout his decades of research and analyze how his predictions have come to fruition over the years. Turing’s Computing Machinery and Intelligence is the paper in which the Turing Test is described as an alternative way to answer the question “can machines think?” (Turing 433). Since the development of Turing’s original paper, there has been a tremendous amount of advancement in the field of artificial intelligence. The field has made its way into art classification as well as the medical industry. The main concept researched in this analysis focuses on whether or not a machine exists that has passed the Turing Test. Should it be determined that a machine has indeed passed this test, it is important to discuss what the ethical implications of this accomplishment entail. Turing’s paper, while raising great controversy regarding its ethical implications, proves to offer significant contribution to the field of artificial intelligence and technology

Blockchain technology as a support infrastructure in E-Government evolution at Dubai economic department

© 2019 Association for Computing Machinery. World is experiencing revolution with the proliferation of technologies like blockchain, artificial intelligence, IOT, and cloud computing in our lives. This study explores Dubai Economic Department\u27s (DED) electronic government (e-government) stages of integrating emerging technologies as its contribution in creating a smarter city. Our findings suggest that blockchain technology can be used as a platform to transform the e-business operating models in order to offer fully integrated services and to enforce common business rules. It can help governments in making processes simpler, faster and secure. It can be used for syncing of data across different departments, automatically & instantaneously. This work provides policy makers, enterprise architects and IT managers with useful guidelines to define and drive their e-government strategy and planning actions towards the most appropriate domains of implementation

Experimental set-up for investigation of fault diagnosis of a centrifugal pump

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated