The extensive use of information and communication technology has generated large volumes of data storage. The data repositories might contain massive amount of useful information. In order to extract useful knowledge from these data repositories for making better decision, necessitate the need for proper methods of extracting knowledge. Machine learning is an important technique which extracts necessary knodledge and information such as association, patterns, changes and anomalies from various data repositories (Barka et al., 2010).
The idea of machine learning is something resulting from this environment. Computers can break down advanced information to discover patterns and laws in ways that is more complex for a human to do. The fundamental thought of machine learning is that a computer can automatically gain from experience (Mitchell, 1997). Although machine learning applications differ, its general function is similar through its applications. The computer process a huge amount of data, and locate patterns and hidden rules in the data. These rules and patterns are numerical in nature, and they can be simply processed and defined by a computer. The computer would then be able to utilize those standards to …show more content…
It is because the standard of a mega university is based on its useful record of academic performance. There are many opinions on students achievent based on the previous information. According to Usamah (2013) expressed that students accomplishment can be get by measuring the learning evaluation and co-educational programs. In any case, a large portion of the investigations specified about graduation being the measure of students achievement. The assessment is essential to keep up students achievement and the success of learning process. By examining students achievement, a vital program can be highly arranged throughout their period of studies in a university (Z. Ibrahim
Based upon the analysis, Parnas’ article is geared more towards people involved in the field of Artificial Intelligence where Eldridge’s article is geared towards people who are not necessarily knowledgeable about Artificial Intelligence yet are interested to learn more about the topic. Throughout the article, Parnas maintains the skeptical attitude towards Artificial Intelligence, literally ending with “Devices that use heuristics to create the illusion of Intelligence present a risk we should not accept” (Parnas, 6). Eldridge on the other hand, maintains a positive attitude throughout the article despite the shortcomings of AI. Together, both authors provide compelling arguments for and against Artificial
Rise of Artificial Intelligence and Ethics: Literature Review The Ethics of Artificial Intelligence, authored by Nick Bostrom and Eliezer Yudkowsky, as a draft for the Cambridge Handbook of Artificial Intelligence, introduces five (5) topics of discussion in the realm of Artificial Intelligence (AI) and ethics, including, short term AI ethical issues, AI safety challenges, moral status of AI, how to conduct ethical assessment of AI, and super-intelligent Artificial Intelligence issues or, what happens when AI becomes much more intelligent than humans, but without ethical constraints? This topic of ethics and morality within AI is of particular interest for me as I will be working with machine learning, mathematical modeling, and computer simulations for my upcoming summer internship at the Naval Surface Warfare Center (NSWC) in Norco, California. After I complete my Master Degree in 2020 at Northeastern University, I will become a full time research engineer working at this navy laboratory. At the suggestion of my NSWC mentor, I have opted to concentrate my master’s degree in Computer Vision, Machine Learning, and Algorithm Development, technologies which are all strongly associated with AI. Nick Bostrom, one of the authors on this article, is Professor in the Faculty of Philosophy at Oxford University and the Director at the Future of Humanity Institute within the Oxford Martin School.
“Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we’ll augment our intelligence” (Rometly, G.). Artificial intelligence are high-tech machines and computer systems that obtain the ability to learn human intelligence and characteristics with the imperfect data or information that people feed the computers and machines. When artificial intelligence is thought of, individuals immediately conclude that the definition of artificial intelligence are robots with human characteristics as well as other computers far more technical than ordinary everyday computers. This definition is not necessary wrong, but it is not correct either.
A standardized test, according to W. James Popham of ASCD.org, is “any examination that is administered and scored in a predetermined, standard manner.” In standardized testing, examinees are instructed to precisely answer a specific set of questions, which are usually multiple-choices. Although standardized testing is believed to be an objective method to grade students, administers should understand that these tests are not only a waste of time, but also a waste of money. Standardized testing is irrelevant to a student’s education because it is an unreliable way to measure a student’s knowledge, causes stress, and hinders a student’s overall learning potential.
In Alan Turing’s paper Computing Machinery and Intelligence, he proposes a thought experiment that would eventually be tested, and even later be beaten. He describes an experiment where a man and a woman are in two different rooms and an outside observer has to guess at the sexes of the participants. He then suggests that one of the participants be replaced with a computer. Once humanity is unable to tell the difference and will guess that the computer is human at the same rate that it will guess that it is a machine will answer Turing’s thesis of, “Can machines think?’ (434).
Artificial Intelligence and its effect on the workforce Artificial intelligence(AI) is a recent reality of technological advancement affecting human society. To analyze its effect on the workforce we will look back in history for technological disruptions and how they affected the workforce and compare and contrast to the way AI is currently impacting and will continue impacting the human workforce and other aspects of human society such as economics, politics and the general environment. History Throughout history technological advancement has affected human society in its ways of living, working and its environment.
Artificial Intelligence is the field within computer science to explain some aspects of the human thinking. It includes aspects of intelligence to interact with the environment through sensory means and the ability to make decisions in unforeseen circumstances without human intervention. The beginnings of modern AI can be traced to classical philosophers' attempts to describe human thinking as a symbolic system. MIT cognitive scientist Marvin Minsky and others who attended the conference
Data warehouses supports and transform enormous of data from single transactional files into single decision-backing database technology (K. Wagner, F.Lee, J. Glaser, 2013). Also, data mining is an IT concepts that Epic system has for extracting and identify specific clinical data. This transaction occurs when the tool is programmed to look for patterns, trends and/or trend rules. For example, North Point Health and Wellness Clinic render the following services: dental, mental health, primary care, lab, ex-rays, mammograms, vision and pharmacy services.
The attraction of artificial intelligence for me lies in its breadth of applicability, both as a method of problem solving in itself and in a symbiotic integration with other areas of computer science. A broad spectrum of applications exist within the artificial intelligence field, ranging from intelligent non-player controlled characters in computer game software to a ubiquitous computing solution that intelligently reacts to a variety of users. This diversity is one of the main reasons that I feel compelled to pursue artificial intelligence further. While I have striven to develop my understanding of artificial intelligence during my undergraduate education, the choreographed requirements of a bachelor's degree have restricted my research to only a minute sample of artificial intelligence’s applications. During my exposure to the field, I have often been unsatisfied with the level of interaction artificial intelligence displays in response to prompts of varying complexity.
As big data things continue to grow in this modern era, today we can learn how to predict or assume anything that will happen in the future with data from the past. This studies known as Predictive Analytics. Predictive analytics combine methods from machine learning, data mining and statistics to find meaning or pattern from a huge volume of data. Tom H Davenport, a senior advisor at Deloitte Analytics has broken down three primer models on doing predictive analytics: the data, statistics, and assumptions.
Students are most essential asset for any educational institute. The social and economic development is directly linked with student academic performance. The students’ performance plays an important role in producing the best quality graduates who will become great leader and manpower for the country thus responsible for the country’s economic and social development. Student academic performance measurement has received considerable attention in previous research, it is challenging aspects of academic literature, and science student performance are affected due to social, psychological, economic, environmental and personal factors. These factors strongly influence on the student performance, but these factors vary from person to person (Irfan Mushtaq and Shabana Nawaz