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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">RUDN Journal of Studies in Literature and Journalism</journal-id><journal-title-group><journal-title xml:lang="en">RUDN Journal of Studies in Literature and Journalism</journal-title><trans-title-group xml:lang="ru"><trans-title>Вестник Российского университета дружбы народов. Серия: Литературоведение. Журналистика</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2312-9220</issn><issn publication-format="electronic">2312-9247</issn><publisher><publisher-name xml:lang="en">Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">35470</article-id><article-id pub-id-type="doi">10.22363/2312-9220-2023-28-2-355-367</article-id><article-id pub-id-type="edn">RZMQIG</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>JOURNALISM</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Журналистика</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Transforming the future: a review of artificial intelligence models</article-title><trans-title-group xml:lang="ru"><trans-title>Трансформация будущего: обзор моделей искусственного интеллекта</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6722-2431</contrib-id><name-alternatives><name xml:lang="en"><surname>Pugachev</surname><given-names>Andrei A.</given-names></name><name xml:lang="ru"><surname>Пугачев</surname><given-names>Андрей Алексеевич</given-names></name></name-alternatives><bio xml:lang="en"><p>PhD student, Department of Mass Communication, Faculty of Philology</p></bio><bio xml:lang="ru"><p>аспирант, кафедра массовых коммуникаций, филологический факультет</p></bio><email>quadriptych@gmail.com</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0001-8105-892X</contrib-id><name-alternatives><name xml:lang="en"><surname>Kharchenko</surname><given-names>Alina V.</given-names></name><name xml:lang="ru"><surname>Харченко</surname><given-names>Алина Вадимовна</given-names></name></name-alternatives><bio xml:lang="en"><p>lecturer, Department of Mass Communication, Faculty of Philology</p></bio><bio xml:lang="ru"><p>преподаватель, кафедра массовых коммуникаций, филологический факультет</p></bio><email>kharchenko-av@rudn.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3447-8008</contrib-id><name-alternatives><name xml:lang="en"><surname>Sleptsov</surname><given-names>Nikolai A.</given-names></name><name xml:lang="ru"><surname>Слепцов</surname><given-names>Николай Андреевич</given-names></name></name-alternatives><bio xml:lang="en"><p>lecturer, Department of Mass Communication, Faculty of Philology</p></bio><bio xml:lang="ru"><p>преподаватель, кафедра массовых коммуникаций, филологический факультет</p></bio><email>nikolai.slepcov@skillbox.ru</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">RUDN University</institution></aff><aff><institution xml:lang="ru">Российский университет дружбы народов</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2023-07-15" publication-format="electronic"><day>15</day><month>07</month><year>2023</year></pub-date><volume>28</volume><issue>2</issue><issue-title xml:lang="en">VOL 28, NO2 (2023)</issue-title><issue-title xml:lang="ru">ТОМ 28, №2 (2023)</issue-title><fpage>355</fpage><lpage>367</lpage><history><date date-type="received" iso-8601-date="2023-07-20"><day>20</day><month>07</month><year>2023</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2023, Pugachev A.A., Kharchenko A.V., Sleptsov N.A.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2023, Пугачев А.А., Харченко А.В., Слепцов Н.А.</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="en">Pugachev A.A., Kharchenko A.V., Sleptsov N.A.</copyright-holder><copyright-holder xml:lang="ru">Пугачев А.А., Харченко А.В., Слепцов Н.А.</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://journals.rudn.ru/literary-criticism/article/view/35470">https://journals.rudn.ru/literary-criticism/article/view/35470</self-uri><abstract xml:lang="en"><p>A comprehensive review of existing artificial intelligence models, focusing on fourteen prominent language and multimodal generative models from four rapidly evolving categories: Marketing, Copywriting, Image Improvement, and Social Media, is made. As of May 2023, 1,523 AI models are available to end users, with notable Russian services such as Balaboba, GigaChat, and Kandinskiy 2.0 emerging as counterparts to popular foreign neural networks. The potential applications of these tools in various media production domains, including journalism, marketing, and copywriting, are explored. It was necessary to talk about language models, since these are the ones, most connected not only to the media sphere, but to academic writing as well. Moreover, the authors delve into the ethical considerations associated with the use of AI models in professional settings, addressing potential challenges and concerns. The importance of responsible development, use, and regulation of AI technology, as well as the need for collaboration among researchers, governments, and private organizations to ensure ethical AI practices, is highlighted. The authors also outline the prospects for further development of AI models and related research, emphasizing the need to foster an environment of continuous learning for innovation that is inclusive and accessible. This approach will help maximize the benefits of AI while minimizing potential harm, paving the way for a more prosperous, equitable, and sustainable future. The presented materials can serve as an introduction to the emerging branch of AI models development.</p></abstract><trans-abstract xml:lang="ru"><p>Выполняется комплексный обзор существующих моделей искусственного интеллекта (ИИ). Особое внимание уделено четырнадцати известным языковым и мультимодальным генеративным моделям из четырех быстро развивающихся категорий инструментов: Marketing, Copywriting, Image Improvement и Social Media. По состоянию на май 2023 г. конечным пользователям доступны 1523 модели ИИ, среди которых выделяются такие российские сервисы, как Balaboba, GigaChat и Kandinskiy 2.0, являющиеся аналогами популярных зарубежных нейросетей. Рассматриваются потенциальные возможности применения этих инструментов в различных сферах медиапроизводства, включая журналистику, маркетинг и копирайтинг. Обсуждаются языковые модели, поскольку именно они больше всего связаны не только с медиасферой, но и с академическим письмом. Затрагиваются этические аспекты: потенциальные проблемы, связанные с использованием моделей ИИ в профессиональной сфере. Подчеркивается важность ответственного подхода к разработке, использованию и регулированию технологий ИИ, а также сотрудничества между исследователями, правительствами и частными организациями для обеспечения этичности применения ИИ. Описаны перспективы дальнейшего развития моделей ИИ и соответствующих исследований, выделена необходимость создания среды непрерывного обучения в области инноваций, которая должна быть инклюзивной и доступной. Такой подход поможет максимизировать преимущества ИИ при минимизации потенциального вреда, прокладывая путь к более процветающему, справедливому и устойчивому будущему. Представленные материалы могут служить введением в развивающуюся отрасль разработки моделей ИИ.</p></trans-abstract><kwd-group xml:lang="en"><kwd>deep learning</kwd><kwd>machine learning</kwd><kwd>neural networks</kwd><kwd>language model</kwd><kwd>generative model</kwd><kwd>AI storytelling</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>глубокое обучение</kwd><kwd>машинное обучение</kwd><kwd>нейросети</kwd><kwd>языковая модель</kwd><kwd>генеративная модель</kwd><kwd>ИИ-сторителлинг</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Benefo, E.O., Tingler, A., White, M., Cover, J., Torres, L., Broussard, C., Shirmohammadi, A., Pradhan, A.K., &amp; Patra, D. (2022). Ethical, legal, social, and economic (ELSE) implications of artificial intelligence at a global level: A scientometrics approach. 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