Publicação
The implementation of artificial intelligence to simplify the first level support of a management system at a large company
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | Matos, Celso Augusto de Matos | |
| dc.contributor.advisor | Manfreda, Anton | |
| dc.contributor.author | Pham, Nguyen | |
| dc.date.accessioned | 2024-03-14T17:14:59Z | |
| dc.date.available | 2024-03-14T17:14:59Z | |
| dc.date.issued | 2024-02-02 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management | pt_PT |
| dc.description.abstract | This thesis delves into the practical aspects and challenges of implementing Generative AI within a corporate setting. Through a careful exploration of various use cases, frameworks, and methodologies, the research analyzes the role of Generative AI in enhancing business processes and fostering innovation. The journey begins with a comprehensive overview of Generative AI, clearing up its foundational concepts. The study navigates through the intricacies of Generative AI's application, with a specific emphasis on its ability to generate text, addressing nuances in large language models, natural language processing, and conversational intelligence. One primary emphasis of the research is the integration of large language models in question-answering applications, highlighting their potential to efficiently navigate vast document repositories. The linear question-answering approach is examined closely, leading to the introduction of more flexible methods, such as the ReAct (Reasoning-Action) framework. Another integral part of the thesis is the examination of open-source initiatives like LangChain, which facilitate the utilization of Generative AI. The emergence of smaller, cost-effective models challenges the dominance of big tech companies, paving the way for increased accessibility and ownership. As the research progresses, attention is directed towards the evolving landscape of AI governance, encompassing legal implications, licensing, and privacy concerns. The study anticipates the impact of regulatory frameworks on the deployment of Generative AI underscoring potential challenges for compliance purposes. Overall, this thesis offers valuable insights into the realm of Generative AI implementation, laying the groundwork for future initiatives and promoting a nuanced comprehension of its potential effects on business environments. | pt_PT |
| dc.identifier.tid | 203545117 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/164932 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | AI Governance | pt_PT |
| dc.subject | Artificial Intelligence | pt_PT |
| dc.subject | Conversational Intelligence | pt_PT |
| dc.subject | Generative AI | pt_PT |
| dc.subject | IT Service Management | pt_PT |
| dc.subject | Large Language Model | pt_PT |
| dc.subject | LLM | pt_PT |
| dc.subject | Open Source | pt_PT |
| dc.subject | SDG 9 - Industry, innovation and infrastructure | pt_PT |
| dc.title | The implementation of artificial intelligence to simplify the first level support of a management system at a large company | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Gestão de Informação, especialização em Gestão dos Sistemas e Tecnologias de Informação | pt_PT |