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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Между индексальным и иконическим: фотографии в контексте развития нейронных сетей

Артикульт. 2024. № 1(53). С. 48–63.
Fadeeva T., Staruseva-Persheeva A., Pronina A.

The rapid development of technoscience calls into question the usual ways of perception and traditional practices of information analysis, in particular, one of the challenges for the communication society has been the development of artificial intelligence capable of creating images that are almost indistinguishable from paintings and photographs, this is clearly visible in the discussions that are developing today around photography and push us to think about the semiotic shift taking place in this field. The article observes three ways for a photographer to work with neural networks, each of which has its own limits of applicability: image processing, image creation based on the style of a famous photographer, image generation "from scratch". The key examples of neural networks at the disposal of photographers and artists are analyzed, their features and expressive capabilities are indicated, as well as those aesthetic and semiological issues that are issues that are actualized by the introduction of artificial intelligence into photographic practice. Based on the results of the study, the authors come to the conclusion that the semiotic shifts occurring in the field of photography challenge traditional forms of representation and have a fundamental impact on how the categories of authorship and viewership can be understood in the modern sociocultural process.

Research target: Art History
Language: Russian
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Keywords: искусственный интеллектмашинное обучениесовременное искусствонейронные сетиneural networksmachine learningсовременная фотография contemporary art artificial intelligenceсontemporary photographyneurophotographygenerative photographyнейрофотоографиягенеративная фотография
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