Please use this identifier to cite or link to this item: https://library.megu.edu.ua:9443/jspui/handle/123456789/6247
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYuskovych-Zhukovska, V.-
dc.contributor.authorBogut, O.-
dc.date.accessioned2026-02-18T10:17:02Z-
dc.date.available2026-02-18T10:17:02Z-
dc.date.issued2024-
dc.identifier.citationValentyna Yuskovych-Zhukovska, Oleg Bogut. Features of using artificial intelligence to enhance the qualifications of web developers. Education and economy in the digital age : мonograph / еd. : N. Dobosh, A. Ostenda. The University of Technology in Katowice Press, 2024. P. 166-171.en_US
dc.identifier.urihttps://library.megu.edu.ua:9443/jspui/handle/123456789/6247-
dc.description.abstractCurrently, large language models (LLMs) play a pivotal role in the development of artificial intelligence (AI), possessing the ability to generate text indistinguishable from human writing (Blank, 2024). These models, such as GPT-4, are built on deep learning and neural networks and are trained using massive datasets. They exhibit a high capacity for contextual understanding and text generation across various subjects. High-quality AI algorithms require extensive data for training. For instance, the GPT-4 dataset was developed using 13 trillion tokens, comprising both textual data and code samples.en_US
dc.publisherThe University of Technology in Katowice Pressen_US
dc.subjectlarge language modelsen_US
dc.subjectLLMsen_US
dc.subjectGPT-4en_US
dc.subjectdevelopeden_US
dc.subjectmassive datasetsen_US
dc.titleFeatures of using artificial intelligence to enhance the qualifications of web developersen_US
dc.title.alternativeмонографіяen_US
dc.typeBooken_US
Appears in Collections:Управління ІТ-проектами

Files in This Item:
File Description SizeFormat 
2024.pdfFeatures of using artificial intelligence to enhance the qualifications of web developers1.45 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Admin Tools