scholarly journals Priority of scientific and technological development "The transition to advanced digital, intelligent manufacturing technologies, robotic systems, new materials and methods of design, the creation of systems for processing large amounts of data, machine learning and artificial intelligence". Opening speech of the chairman of the priority council of RAS academician I.A. Kalyaev

2019 ◽  
Vol 89 (4) ◽  
pp. 348-350
Author(s):  
I. A. Kalyaev
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Technological Development ◽  
Intelligent Manufacturing ◽  
Robotic Systems ◽  
New Materials ◽  
The Creation ◽  
Manufacturing Technologies ◽  
Scientific And Technological Development

Opening speech of the chairman of the priority council of RAS academician I.A. Kalyaev

Stepping back to move forward: Centering capital in discussions of technology and the future of work

2020 ◽  
Vol 5 (3-4) ◽  
pp. 129-133
Author(s):  
Benjamin Shestakofsky
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Technological Development ◽  
Structural Features ◽  
Robotic Systems ◽  
Future Of Work ◽  
Technological Unemployment ◽  
The Future ◽  
Constructivist Approaches ◽  
The Relationship

Some researchers have warned that advances in artificial intelligence will increasingly allow employers to substitute human workers with software and robotic systems, heralding an impending wave of technological unemployment. By attending to the particular contexts in which new technologies are developed and implemented, others have revealed that there is nothing inevitable about the future of work, and that there is instead the potential for a diversity of models for organizing the relationship between work and artificial intelligence. Although these social constructivist approaches allow researchers to identify sources of contingency in technological outcomes, they are less useful in explaining how aims and outcomes can converge across diverse settings. In this essay, I make the case that researchers of work and technology should endeavor to link the outcomes of artificial intelligence systems not only to their immediate environments but also to less visible—but nevertheless deeply influential—structural features of societies. I demonstrate the utility of this approach by elaborating on how finance capital structures technology choices in the workplace. I argue that investigating how the structure of ownership influences a firm’s technology choices can open our eyes to alternative models and politics of technological development, improving our understanding of how to make innovation work for everyone instead of allowing the benefits generated by technological change to be hoarded by a select few.

scholarly journals Advancing Post-Genome Data and System Integration through Machine Learning

2002 ◽  
Vol 3 (1) ◽  
pp. 28-31 ◽  
Author(s):  
Francisco Azuaje
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
System Integration ◽  
Intelligent Systems ◽  
Biological Data ◽  
Markup Languages ◽  
Public And Private ◽  
Genome Data ◽  
The Creation ◽  
Biological Data Integration

Research on biological data integration has traditionally focused on the development of systems for the maintenance and interconnection of databases. In the next few years, public and private biotechnology organisations will expand their actions to promote the creation of a post-genome semantic web. It has commonly been accepted that artificial intelligence and data mining techniques may support the interpretation of huge amounts of integrated data. But at the same time, these research disciplines are contributing to the creation of content markup languages and sophisticated programs able to exploit the constraints and preferences of user domains. This paper discusses a number of issues on intelligent systems for the integration of bioinformatic resources.

scholarly journals The Teleological Nature of Digital Aesthetics – the New Aesthetic in Advance of Artificial Intelligence

2019 ◽  
pp. 105
Author(s):  
Scott Contreras-Koterbay
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Media Studies ◽  
Technological Development ◽  
Aesthetic Experiences ◽  
Real Possibility ◽  
Digital Aesthetics ◽  
Curatorial Practice ◽  
Digital Objects ◽  
The Aesthetic

If aesthetic and teleological judgments are equally reflective, then it can be argued that such judgments can be applied concurrently to digital objects, specifically those that are products of the rapidly developing sophisticated forms of artificial intelligence (AI). Evidence of the aesthetic effects of technological development are observable in more than just experienceable objects; rooted in inscrutable machine learning, AI’s complexity is a problem when it is presented as an aesthetic authority, particularly when it comes to automated curatorial practice or as a progressively determinative aesthetic force originating in an independent agency that is internally self-consistent.Rooted in theories of the post-digital and the New Aesthetic, this paper examines emerging new forms of art and aesthetic experiences that appear to reveal these capabilities of AI. While the most advanced forms of AI barely qualify for a ‘soft’ description at this point, it appears inevitable that a ‘hard’ form of AI is in the future. Increased forms of technological automation obscure the increasingly real possibility of genuine products of the imagination and the creativity of autonomous digital agencies as independent algorithmic entities, but such obfuscation is likely to fade away under the evolutionary pressures of technological development. It’s impossible to predict the aesthetic products of AI at this stage but, if the development of AI is teleological, then it might be possible to predict some of the foreseeable associated aesthetic problems. Article received: April 10, 2019; Article accepted: July 6, 2019; Published online: October 15, 2019; Original scholarly paperHow to cite this article: Contreras-Koterbay, Scott. "The Teleological Nature of Digital Aesthetics – the New Aesthetic in Advance of Artificial Intelligence." AM Journal of Art and Media Studies 20 (2019): 105-112. doi: 10.25038/am.v0i20.326.

scholarly journals Artificial Intelligence & Machine Learning: a model for a new judicial system?

2020 ◽  
pp. 81-91
Author(s):  
Paula C. Arias
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
System Integration ◽  
Judicial System ◽  
Modern Life ◽  
Technological Advances ◽  
The Creation ◽  
Almost All

Artificial Intelligence and Machine Learning are a result not only of technological advances but also of the exploitation of information or data, which has led to its expansion into almost all aspects of modern life, including law and its practice. Due to the benefits of these technologies, such as efficiency, objectivity, and transparency, the trend is towards the integration of Artificial Intelligence and Machine Learning in the judicial system. Integration that is advocated at all levels and, today, has been achieved mostly under the implementation of tools to assist the exercise of the judiciary. The "success" of this integration has led to the creation of an automated court or an artificially intelligent judge as a futuristic proposal.

Music, Art, Machine Learning, and Standardization

Leonardo ◽  
2021 ◽  
pp. 1-11
Author(s):  
Taylor Brook
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Culture Industry ◽  
Economic Power ◽  
The Creation

Abstract This paper explores current and hypothetical implementations of machine learning toward the creation and marketing of cultural commodities, focusing on music in popular and experimental forms. Building on Adorno and Horkheimer's critique of the culture industry, this article considers the role of machine learning and artificial intelligence as a force for stylistic standardization and further consolidation of economic power in music and art.

Introduction in emotional chat bots & base of Bioinformatics

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Artificial Intelligence ◽  
Public Administration ◽  
Conceptual Model ◽  
Interdisciplinary Research ◽  
Technological Development ◽  
Digital Transformation ◽  
Information Flows ◽  
It Systems ◽  
Scientific Task ◽  
Scientific And Technological Development

The article proposed interdisciplinary research should contribute to understanding the attitude of the population to the ongoing processes of digital transformation of the means of interaction with authorities, the level of their confidence in the widespread introduction of artificial intelligence technologies in the provision of public services. Understanding the psychology of the user, the specifics of information flows in public administration, the capabilities of modern IT systems - all this together will make it possible to significantly improve the corresponding communication processes.The scientific task posed within the framework of the topic is to develop a conceptual model for optimizing one of the main elements of modern e-government systems - "intelligent chat bots" designed to make the interaction of citizens with government bodies more efficient. The results of the article is contribute to the implementation of the goals, objectives and strategic guidelines of the programs of scientific and technological development of both the region and Russia as a whole.

scholarly journals Machine learning as the new approach in understanding biomarkers of suicidal behavior

2020 ◽  
Author(s):  
Alja Videtič Paska ◽  
Katarina Kouter
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Analysis ◽  
High Throughput ◽  
Suicidal Behavior ◽  
Technological Development ◽  
Machine Learning Algorithms ◽  
Classical Approach ◽  
New Approach

In psychiatry, compared to other medical fields, the identification of biological markers that would complement current clinical interview, and enable more objective and faster clinical diagnosis, implement accurate monitoring of treatment response and remission, is grave. Current technological development enables analyses of various biological marks in high throughput scale at reasonable costs, and therefore ‘omic’ studies are entering the psychiatry research. However, big data demands a whole new plethora of skills in data processing, before clinically useful information can be extracted. So far the classical approach to data analysis did not really contribute to identification of biomarkers in psychiatry, but the extensive amounts of data might get to a higher level, if artificial intelligence in the shape of machine learning algorithms would be applied. Not many studies on machine learning in psychiatry have been published, but we can already see from that handful of studies that the potential to build a screening portfolio of biomarkers for different psychopathologies, including suicide, exists.

scholarly journals PROBLEMS OF CONTROL OF MIDWATER TRAWL COMPLEXES USING EQUATIONS OF ELECTRIC AND MECHANICAL DRIVES OF TRAWL WINCHES

2020 ◽  
Vol 2020 (4) ◽  
pp. 93-101
Author(s):  
Aleksandr Nedostup ◽  
Alexey Olegovich Razhev ◽  
Vyacheslav Valerievich Makarov
Keyword(s):  
Artificial Intelligence ◽  
Predictive Modeling ◽  
Information Technologies ◽  
Interdisciplinary Approach ◽  
Robotic Systems ◽  
Control Architecture ◽  
New Materials ◽  
Midwater Trawl ◽  
Modern Information ◽  
Self Learning

The paper touches upon the problems of transition to advanced digital, intelligent man-ufacturing technologies, robotic systems, new materials and design methods, the creation of systems for processing large amounts of data, machine learning and artificial intelligence. Automation of fishing process requires an interdisciplinary approach using modern information technologies. The possibility of using artificial intelligence technologies for solving the problems of predictive modeling of the behavior of a trawl system while fishing on a self-learning neural network has been proved. The equations of electric and mechanical drives of trawl winches for controlling the shape-changing design of a midwater trawl are given. The question of improving the control characteristics of a midwater trawl system by introducing a control architecture adapted for the trawl system taking into account the industrial requirements and by developing a mathematical model of the trawl system, in-cluding an accurate model of hydrodynamic forces on the trawl flaps is considered.

Neuromarketing Trends and Opportunities for Companies

2020 ◽  
pp. 82-103
Author(s):  
Arabinda Bhandari
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Remote Sensing ◽  
Decision Making ◽  
Brand Management ◽  
Technological Development ◽  
Research Direction ◽  
Future Research ◽  
Design Decision ◽  
Future Research Direction

The main purpose of this chapter is to concisely describe the origin of neuromarketing, its applications in the organization, and to explore consumer behavior with the help of different neuromarketing technologies like fMRI, EEG, and MEG. This chapter gives a guideline on how neuromarketing would be used in different areas of organization functions, like, brand management, advertisement, communication, product design, decision making, etc. with the help of data mining, artificial intelligence, social media, machine learning, remote sensing, AR, and VR. The chapter identifies the opportunities of neuromarketing with the latest technological development to understand the customer mindset so that it would be easy to formulate neurostrategy for an organization. This chapter gives a future research direction with strategic management, so that it will be helpful for a professional to create a more accurate strategy in a VUCA (volatility, uncertainty, complexity, ambiguity) environment, predict, and fulfill the “institution void” situation with more accuracy in an emerging developing market.

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