Philosophical Problems of IT & Cyberspace (PhilIT&C)

This article is devoted to the study of the specific features of the display of social networks and computer technologies in the late 70s of the XX – early 20s of the XXI century in the fantastic Star Wars universe created by American filmmaker D. Lucas. In this scientific work, the authors argue for the relevance and scientific novelty of the problem under consideration. The study examines the peculiarities of the influence of social networks and computer technologies in modern conditions. The article provides a justification for the need to analyze the reflection of this issue in fantasy art as an auxiliary factor in the development of the prognostic function of science. This paper provides a reasoned explanation of the choice of the Star Wars universe as an object of research, taking into account its importance in the fantasy genre, as well as in order to refute stereotypes according to which Star Wars is a collection of entertainment materials in which there is completely no semantic load. The authors analyze the fundamental differences in the coverage of the studied problem in such genres of art as literature and cinema in the context of Star Wars. The article examines the features of the evolution of the display of cybernetic technologies and communication network platforms in the Star Wars universe in the mid‑1970s – early 2020s, as a reflection of the real development of scientific and technological progress, as well as an example of the impact of political, socio‑economic and moral factors on the use of online platforms and computer technology during the period under study. In this article, using the example of the Star Wars universe, the features of the transformation of the role of specialists in the field of high technology through the prism of the attitude of artists to them – more specifically, writers and cinematographers – are also considered. The article also examines the moral and ethical aspect of the use of computer technology and social networks, considered by artists who have made a significant contribution to the development of the fantastic epic of Star Wars.

Today, large language models are very powerful, informational and analytical tools that significantly accelerate most of the existing methods and methodologies for processing informational processes. Scientific information is of particular importance in this capacity, which gradually involves the power of large language models. This interaction of science and qualitative new opportunities for working with information lead us to new, unique scientific discoveries, their great quantitative diversity. There is an acceleration of scientific research, a reduction in the time spent on its implementation – the freed up time can be spent both on solving new scientific problems and on scientific creativity, which, although it may not necessarily lead to a specific solution to a particular scientific problem, but is able to demonstrate the beauty of science in various disciplinary areas. As a result, the interaction of large language models and scientific information is at the same time a research for solutions to scientific problems, scientific problems, and scientific creativity. Solving scientific problems requires the ability to efficiently process big data, which cannot be done without an effective method – one of the significant methods was the Transformer architecture, introduced in 2017 and comprehensively integrated into the GPT‑3 model, which, as of September 2020, was the largest and most advanced language model in the world. Therefore, GPT‑3 can be called the basis of most scientific developments carried out in the context of using large language models. The interaction of science and large language models has become a factor in the emergence of a large number of questions, among which are: «Is the result of data analysis new knowledge?», «What are the prospects for scientific creativity in the era of big computing?». Currently, these issues are extremely important, because they allow us to develop the foundations for effective human‑computer interaction. Therefore, this study analyzes the issues presented.

The article presents a new method for obtaining analogues of words, characterized by simplicity and the absence of the need for preliminary training on large data as in existing methods. In the method under study, analogues are determined by their syntactic predicates using methods of distributive semantics. In the study, analogues of adjectives, nouns and verbs were obtained and analyzed. This made it possible to obtain a result that is not inferior to the results obtained using the most popular neural network approach as word2vec when qualitatively comparing analogues. The demonstrated method shows that obtaining analogues is possible using methods of distributive semantics using a more interpretable method, which opens up the possibility of studying semantic analogy. This method also allows you to identify analogues on a specific topic. Based on the experimental results obtained, an original definition of analogues and cognitive schemes is formulated. The article also analyzes and substantiates the possibility of a new approach for creating artificial intelligence systems based on the researched method. According to the authors, this provides significant advantages for the creation of such systems. In particular, the proposed method allows for broader generalizations over orders of magnitude smaller data, as well as learning during use, which is not possible for neural networks.