scholarly journals The artificial intelligence revolution: Achievements and prospects

2021 ◽  
Author(s):  
Vladimir Sergeevich Smolin
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Social Relations ◽  
Human Society ◽  
Network Algorithms ◽  
Further Development

The commercially successful application of neural network algorithms in artificial intelligence (AI) systems and devices after 2010 has significantly accelerated the process of achieving new successes in solving “intellectual problems. Further development of work on AI will affect not only the technological order, but also social relations in human society, and it is necessary to think about the possible consequences of such an influence right now.

Construction of first-class university course based on artificial intelligence and neural network algorithm

2020 ◽  
pp. 1-12
Author(s):  
Yingli Duan
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Vocational Training ◽  
Network Algorithms ◽  
Teaching Efficiency ◽  
Neural Network Algorithm ◽  
Solid Foundation ◽  
University Level ◽  
University Course

Curriculum is the basis of vocational training, its development level and teaching efficiency determine the realization of vocational training objectives, as well as the quality and level of major vocational academic training. Therefore, the development of curriculum is an important issue. And affect the school’s teaching capacity building. The analysis of the latest developments in the main courses shows that there are some deviations or irrationalities in the curriculum in some colleges and universities, and the general problems of understanding the latest courses, such as lack of solid foundation in curriculum setting, unclear direction of objectives, unclear reform ideas, inadequate and systematic construction measures, lack of attention to the quality of education. This paper explains the rules for the establishment of first-level courses, clarifies the ideas and priorities of architecture, and explores strategies for building university-level courses using knowledge of artificial intelligence and neural network algorithms in order to gain experience from them.

scholarly journals Image Classification Using Reinforcement Learning

2020 ◽  
Vol 23 (6) ◽  
pp. 1172-1191
Author(s):  
Artem Aleksandrovich Elizarov ◽  
Evgenii Viktorovich Razinkov
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Reinforcement Learning ◽  
Image Classification ◽  
Deep Neural Network ◽  
Learning Algorithms ◽  
Further Development

Recently, such a direction of machine learning as reinforcement learning has been actively developing. As a consequence, attempts are being made to use reinforcement learning for solving computer vision problems, in particular for solving the problem of image classification. The tasks of computer vision are currently one of the most urgent tasks of artificial intelligence. The article proposes a method for image classification in the form of a deep neural network using reinforcement learning. The idea of ​​the developed method comes down to solving the problem of a contextual multi-armed bandit using various strategies for achieving a compromise between exploitation and research and reinforcement learning algorithms. Strategies such as -greedy, -softmax, -decay-softmax, and the UCB1 method, and reinforcement learning algorithms such as DQN, REINFORCE, and A2C are considered. The analysis of the influence of various parameters on the efficiency of the method is carried out, and options for further development of the method are proposed.

scholarly journals Artificial Intelligence in Modern Journalism: History, Facts, Prospects for Development

2019 ◽  
Vol 8 (3) ◽  
pp. 555-568
Author(s):  
Olga Chertovskikh ◽  
Matvey Chertovskikh
Keyword(s):  
Artificial Intelligence ◽  
Mass Media ◽  
Technological Development ◽  
Human Society ◽  
Practical Application ◽  
Journalism History ◽  
History Of ◽  
Smart Machines ◽  
Further Development ◽  
Development Prospects

The article focuses on the issue of introduction of AI technology into the modern journalism. The topic proves to be of relevant importance as both mass media and press services reveal their direct dependence on the technological development level of the human society. It means that any new relevant technology can change the whole system. The objective of the article is to research the issue of Artificial Intelligence introduction into the modern journalism. The authors consider the history of the “smart machines” creation. Furthermore, they describe the current situation in the sphere of journalism, bring some specific examples of the existing and the projected systems and highlight the areas of possible practical application and the development prospects. They also obtain information on the main principles of the operation, the algorithms, the goals and the capabilities of the machines. In addition, the authors consider the advantages and the risks of this state-of-the-art technology, analyze the cultural and the psychological aspects of its mass introduction, make predictions concerning the prospects for the further development of this sphere, consider different scenarios of its development and identify the challenges and the advantages for the profession of a journalist. In conclusion, the authors state that despite the fact that AI in journalism is a mass phenomenon, all the projects of the introduction of Artificial Intelligence are not currently posing a direct threat to the profession. However, the fact that the mass media of different countries are starting to actively apply AI in journalism, emphasizes the relevance and the importance of further research in this sphere.

scholarly journals Subjectness of digital communication in the context of technological evolution of the Internet: features and transformation scenarios

2021 ◽  
Author(s):  
S.V. Volodenkov ◽  
S.N. Fedorchenko
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Current Practice ◽  
Digital Communication ◽  
Social Practices ◽  
Network Algorithms ◽  
Political Sphere ◽  
Communication Processes ◽  
Self Learning

The work aimed to study the peculiarities of the subjectness of the phenomenon of digital communication in the context of intensive digitalization of key spheres of life of modern society, as well as to identify the prospects and threats of introducing self-learning neural network algorithms and artificial intelligence technologies into communication processes unfolding in the social and political sphere. One of the study's key objectives was to identify scenarios of possible social changes in the context of society digitalization and the traditional social practices transformation in terms of the emergence of new digital subjects of mass public communication that form the pseudo structure of digital interaction between people. As a methodological optics, the work used the method of discourse analysis of scientific research devoted to the implementation and application of artificial intelligence technologies and self-learning neural networks in the processes of socio-political digitalization, as well as the method of critical analysis of current communication practice in the socio-political sphere. At the same time, when analyzing the current practice of digitalization in foreign countries, the case study method was used. In turn, to determine the scenarios for the transformation of traditional social space and social practices, the method of scenario techniques and scenario forecasting was applied. As a research result, it was concluded that the introduction of technological solutions based on artificial intelligence algorithms and self-learning neural networks into contemporary socio-political communication processes creates the potential for the problem of identifying the subjects of communicative acts in the socio-political sphere of the contemporary society life. Based on the results of the study, it is shown that artificial intelligence and self-learning neural network algorithms are increasingly being implemented in the current practice of contemporary digital communications, forming a high potential for information and communication impact on the mass consciousness of technological solutions that no longer require self-control from human operators. The work also concludes that in the current practice of social interactions in the digital space, a person faces a new phenomenon – interfaceization, within which self-communication stimulates the universalization and standardization of digital behavior, creating, disseminating, strengthening, and imposing special digital rituals. The article proves that digital rituals blur the line between digital avatars' activity based on artificial intelligence and the activity of real people, resulting in the potential for a person to lose their own subjectness in the digital universe.

scholarly journals Neurotechnologies: Development, practical application and regulation

2021 ◽  
Vol 12 (3) ◽  
pp. 502-521
Author(s):  
Irina A. Filipova ◽  
Keyword(s):  
Artificial Intelligence ◽  
System Analysis ◽  
Legal Regulation ◽  
Modern World ◽  
Human Society ◽  
Development Programs ◽  
Neural Implants ◽  
Strategic Development ◽  
Logical Method ◽  
Further Development

Neurotechnology is one of the groups of technologies called disruptive or cross-cutting digital technologies. The spread of these technologies in many sectors of the economy can radically change human society. The state contributes to the development of technology when it implements strategic development programs and creates special legislation. The lack of regulation is an obstacle to the development and dissemination of this technology in practice. Therefore, the regulation of artificial intelligence technologies is actively created in the modern world. The law practically does not regulate other cross-cutting technologies, including neurotechnologies. The uncertainty of the further development of technologies and the impossibility of accurate forecasting of development explain the lack of regulation. At the same time, neurotechnologies are increasingly used in practice (neural implants, neural interfaces). According to experts, the pace of development of neurotechnologies in the next decade will lead to an explosive increase in their distribution in society. The subject of research in this article is the study of the need for the creation of special regulation. The objectives of the study include the analysis of risks associated with the development of neurotechnologies and the substantiation of opportunities to eliminate risks through legal regulation. Methods of system analysis, abstraction, legal modelling, the formal-logical method and the comparativelegal method are used in this study. The result of the work includes a greater likelihood of the future integration of the human body and artificial intelligence into a single system due to the development of neurotechnologies, which will require a rethinking of some personal and socio-economic human rights.

scholarly journals Artificial Neural Network Algorithms based Nonlinear Data Analysis for Forecasting in the Finance Sector

2018 ◽  
Vol 7 (4.10) ◽  
pp. 169
Author(s):  
Jitendra Kumar Jaiswal ◽  
Raja Das
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Stock Price ◽  
Historical Data ◽  
Wireless Systems ◽  
Regulatory Function ◽  
Demand And Supply ◽  
Network Algorithms ◽  
Political Environments ◽  
Moving Pattern

The involvement of big populace in the quantitative trading has been increased remarkably since the wired and wireless systems have become quite ubiquitous in the fields of finance and economics. Statistical, mathematical and technical analysis in parallel with machine learning and artificial intelligence are frequently being applied to perceive prices moving pattern and forecasting. However stock price do not follow any deterministic regulatory function, factor or circumstances rather than many considerations such as economy and finance, political environments, demand and supply, buying and selling tendency, trading and investment, etc. Historical data assist remarkably for prices forecasting as an important option for mathematicians and researchers. In this paper, we have followed backpropagation and radial basis function neural network for predicting future prices by modifying these techniques as per requirements. We have also performed a comparative analysis of the two ANN techniques for existing and our modified models.  

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