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Title:Primerjava uporabnosti izbranih brezplačnih velikih jezikovnih modelov
Authors:ID Lamovec, Nina Danaja (Author)
ID Werber, Borut (Mentor) More about this mentor... New window
Files:.pdf MAG_Lamovec_Nina_Danaja_2025.pdf (12,44 MB)
MD5: 6A342D7787D20C025F0AB34268F32973
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FOV - Faculty of Organizational Sciences in Kranj
Abstract:Zaključno delo obravnava temo generativne umetne inteligence. Glavni namen raziskave je bil sistematično primerjati zmogljivosti različnih brezplačno dostopnih generativnih modelov, ki so na voljo na internetu, in razviti metodo za njihovo primerjavo. Raziskava je obsegala tri vrste modelov: modeli za generiranje besedila, modeli za generiranje programske kode in modeli za generiranje slik. Za vsako kategorijo smo izvedli analizo rezultatov, pri čemer smo upoštevali domeno specifične metrike in kriterije kakovosti. Glavni prispevek zaključne naloge je jasna primerjava trenutno dostopnih orodij generativne umetne inteligence, kar je koristno za končne uporabnike, ter ponuja metodološki okvir, ki ga lahko drugi raziskovalci uporabijo ali razširijo za prihodnje primerjave.
Keywords:generativna umetna inteligenca, primerjava, umetna inteligenca
Place of publishing:Maribor
Year of publishing:2025
PID:20.500.12556/DKUM-95316 New window
COBISS.SI-ID:261202691 New window
Publication date in DKUM:12.12.2025
Views:101
Downloads:12
Metadata:XML DC-XML DC-RDF
Categories:FOV
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Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:12.09.2025

Secondary language

Language:English
Title:Usability comparison of selected free large language models
Abstract:This thesis explores the topic of generative artificial intelligence. The main objective of the research was to systematically compare the capabilities of various freely available generative models accessible online and to develop a method for their evaluation. The study included three types of models: text-generating models, code-generating models, and image-generating models. For each category, we conducted a thorough analysis of the outputs, considering domain-specific metrics and quality criteria. The main contributions of this thesis are a clear comparison of currently available generative AI tools, which is highly useful for end-users, and a methodological framework that other researchers can use or extend for future comparative studies.
Keywords:generative artificial inteligence, artificial inteligence, comparison


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