¶ … Machine Learning
It should be noted that there is a marked paucity of research material and scholarly articles existent, from the past three years, regarding the usage of intelligence tests that are deemed mainstream (i.e., not the Turing Test and more frequently utilized assessments such as any variety of the Wechsler tests or the Stanford-Binet assessment) to assess machine intelligence or that of expert systems. Machine intelligence such as IBM's Watson and even certain expert systems are still relatively novel, which is why the vast majority of research material pertaining to these purported types of intelligence utilize the Turing Test, which was explicitly designed to determine the intelligence of computers or machines.
Nonetheless, the first document examined within this assignment is van der Maas et al.'s "Intelligence is what the intelligence test measures. Seriously." This article sheds a good deal of insight on the g factor and its importance within the framework of mainstream intelligence tests. Specifically, it utilizes an alternative for the g factor, the mutualism model. The principle difference between the latter and the former is that in the mutalism model the g factor is not causal and is an index...
Machine Learning Method in Bioinformatics Bioinformatics involves an integrated approach involving the use of information technology, computer science to biology and medicine as professional and knowledge fields. It encompasses the knowledge associated with information systems, artificial intelligence, databases, and algorithms, soft computing, software engineering, image processing, modeling and simulation, data mining, signal processing, computation theory and information, system an d control theory, discrete mathematics, statistics and circuit theory. On the other
Netflix and Machine Learning Machine Learning (ML) represents a data analysis technique involving automation of analytical model development. This segment of AI (artificial intelligence) is grounded in the notion that a system is able to learn using information provided, discern patterns, and engage in decision-making without much human involvement required. Owing to technological advancements in computing, contemporary ML differs from ML of earlier times. The concept traces its roots to pattern
The Influence of AI on Future Performance of Homeland Security Functions in Cyber SecurityOverviewCyber security is a crucial aspect of Homeland Security in the Digital Age. Under the DHS, cyber security efforts focus on combating cyber crime, developing and implementing a cyber incident response function, maintaining the cyber security of networks within the federal government, securing critical infrastructure, implementing cyber security governance, and sharing information in a safe and effective
Abstract This paper discusses the issue of privacy in social networks with respect to advances in machine learning. It shows how machine learning protocols have been developed both to enhance and secure privacy as well as to invade privacy and collect, analyze, predict data based on users’ information and experience online. The conflict between these two directions in machine learning is likely to lead to a system wherein machine learning algorithms
Stevens Star Model and New Tech to Improve Patient OutcomesThe Stevens Star Model of Knowledge Transformation is a framework that guides the transformation of knowledge from research into practice. This model consists of five points: discovery, summary, translation, integration, and evaluation. Each point represents a step in the process of moving from scientific evidence to practical application in patient care (Song et al., 2021). This paper shows how in the
deficits of students with mathematics disabilities? Mathematical skills are definitely just as crucial as literacy and reading skills when it comes to succeeding at school and beyond. Of late, researchers and policymakers have focused considerably on reading; the latter's attention was manifest in the 2001 No Child Left Behind (NCLB) Act. While reading deficiencies are commonly believed to be one among the main characteristics of learning-disabled pupils, mathematical disabilities pose
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