Adapting organizational IT-solutions for local large language model support
| dc.contributor.author | Mäkelä, Tuukka | |
| dc.contributor.department | fi=Johtamisen ja yrittäjyyden laitos|en=Department of Management and Entrepreneurship| | |
| dc.contributor.faculty | fi=Turun kauppakorkeakoulu|en=Turku School of Economics| | |
| dc.contributor.studysubject | fi=Tietojärjestelmätiede|en=Information Systems Science| | |
| dc.date.accessioned | 2025-06-30T21:05:45Z | |
| dc.date.available | 2025-06-30T21:05:45Z | |
| dc.date.issued | 2025-06-04 | |
| dc.description.abstract | This research aims to broaden understanding on the topic of localized large language models (LLMs) in organizational contexts. As a technology, these can offer a lot of advantages, that are suitable for the corporate world. Most notably, these offer significant benefits for controlling security related aspects – as such a system can be ran completely in-house, without any organizational and potentially sensitive data leaving the full control of a given organization. Due to the demands of especially higher-end LLMs, most organizations are not prepared and ready to start supporting them on their pre-existing hardware structures. Whilst it’s normal for most organizations to have deployed computing solutions of some degree within their whole organization – due to the unique and ML-heavy focus of LLM-based workloads, these may not be compatible, forcing organizations to re-think their IT-solutions in order to begin utilizing localized LLMs. This research has been completed on the basis of a few different methodologies and stages. Firstly, the driving factors and key trends impacting these developments were investigated with the aid of a systematic gray-literature review. After understanding these factors, the research aimed to understand the functionalities and requirements of a few key tiers of LLMs, through the completion of practical benchmark runs, as well as third-party benchmark data. On the basis of these findings, the research is completed with a list of suggestions and factors of different tiers of LLM-systems. These include factors such as requirements and benefits an organization may expect to achieve from such systems. These solutions have been made on the principles of a design science-based artifact – giving anyone seeking to utilize these findings a solid foundation for understanding and completing such a project in a sensible and cost-effective manner. The artifact built within this research includes methods for planning such projects, and details about phases and tasks which should be completed to ensure a successful deployment takes place. | |
| dc.format.extent | 140 | |
| dc.identifier.olddbid | 199509 | |
| dc.identifier.oldhandle | 10024/182540 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/12654 | |
| dc.identifier.urn | URN:NBN:fi-fe2025063075758 | |
| dc.language.iso | eng | |
| dc.rights | fi=Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.|en=This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.| | |
| dc.rights.accessrights | avoin | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/182540 | |
| dc.subject | Localized LLMs, Machine Learning, Artificial Intelligence, data-security, open-source models | |
| dc.title | Adapting organizational IT-solutions for local large language model support | |
| dc.type.ontasot | fi=Pro gradu -tutkielma|en=Master's thesis| |
Tiedostot
1 - 1 / 1