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Artificial Intelligence Document Classification
Molnár, Ondřej ; Kačic, Matej (referee) ; Třeštíková, Lenka (advisor)
This paper deals with document classification using artificial intelligence. It describes the principles of classification and machine learning. It also introduces AI methods and presents Naive Bayes classification method in detail. Provides practical implementation of the classifier in MS Office and discusses other possible extensions.
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Řízení pracovníků prostřednictvím umělé inteligence
VÚBP
Vyšší úroveň automatizace a konstantní sledování pracovníků digitálními technologiemi v mnoha případech omezí mezilidský kontakt a zvýší tlak na pracovní výkonnost, což může mít škodlivé účinky na duševní zdraví pracovníků.
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Business planning in the AI era: a study of ChatGPT's capabilities and limitations
Fiala, Martin
Business planning plays an important role in ensuring the success and growth of a company. Artificial intelligence (AI) systems have the potential to revolutionize business planning, offering benefits such as enhanced decision-making, reliable insights, and improved collaboration between AI and human expertise. This study aims to explore the potential of ChatGPT in business planning and shed light on its strengths and weaknesses, ultimately helping organizations make informed decisions about incorporating AI into their planning processes. The primary objective of this thesis is to investigate the capabilities and limitations of ChatGPT, in the context of business planning of food truck business in Czech Republic, using a single-case study approach. The findings from the literature review and case study are synthesized to provide a comprehensive understanding of the topic. The results from the qualitative and quantitative analyses are used to assess the effectiveness of ChatGPT in executing various tasks related to the business planning scenario. In addition, recommendations for future research and practical applications of ChatGPT are provided. The implications of AI advancements for businesses and practitioners are both promising and challenging. By improving interpretability and explainability, addressing data quality issues, fostering collaboration between artificial intelligence and human experts, and considering ethical implications, we can pave the way for more effective and responsible use of AI systems for business planning.
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Proposal of AI-Enabled Microsoft Power Platform Automation in Environment of Financial Audit
Heffner, Christián ; Kříž, Jiří (referee) ; Luhan, Jan (advisor)
This diploma thesis is focused on the design of the automation of the selected process using AI and Microsoft Power Platform. Part of the work is the detailed design of the Front-end in Power Apps, the AI module in MS AI builder and the design of the back-end in Power Automate as part of the Custom Solution Design. The work analyzes the current state in the company and the selected process. Based on the analysis, the application that automates the process is designed. The analysis is preceded by extensive theoretical research dealing with Business Intelligence, process management, AI and, last but not least, financial audit.
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Artificial Intelligence Poetry
Jurečka, Otakar ; Zmrzlá, Petra (referee) ; Kotásek, Miroslav (advisor)
Tato bakalářská práce podává přehled o programech, které jsou určeny k psaní básnických textů. Obsahuje informace o tom, jak se s jednotlivými představenými aplikacemi pracuje, a jejich schopnosti jsou demonstrovány jejich zkušebním použitím. Tyto vygenerované texty jsou analyzovány. Je také vysvětleno fungování těchto počítačových programů. Dále je také zmíněna historie umělé inteligence, její prvotní myšlenka i její novější technologický vývoj.
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ICT and climate change: Are information and communication technologies the problem or the answer?
Abrarova, Alsu ; Rujbrová, Šárka (referee) ; Šedrlová, Magdalena (advisor)
The role of Information and Communication Technology (ICT) in addressing climate change is controversial. This thesis aims to identify if ICT is the cause or solution to climate change by analyzing its negative and positive environmental impacts. To begin with, the carbon and energy footprints of the main ICT components will be presented, as well as ways of minimizing the negative impacts. Furthermore, the potential of ICT to reduce carbon emissions in other sectors will be analyzed. Literature related to the latest technologies, climate change, and reports from companies whose main goal is a sustainable future were reviewed. The findings of this study show that ICT has both negative and positive environmental impacts. However, it has a major potential to tackle climate change by reducing the carbon footprint and increasing energy efficiency in other sectors, which outweighs ICT’s negative impacts. It is done with the aid of new technologies, such as 5G, Internet of Things (IoT), and Artificial Intelligence (AI). Moreover, it is important to highlight the importance of further studies and collaboration of government, businesses, and consumers towards environmentally friendly ICT and a sustainable future with reduced climate change.
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Security log anonymization tool focusing on artificial intelligence techniques
Šťastná, Ariela ; Jurek, Michael (referee) ; Safonov, Yehor (advisor)
Systémy SIEM zohrávajú v rámci bezpečnostného monitoringu zásadnú úlohu. Zozbierané záznamy agregujú, normalizujú a filtrujú, čo predstavuje základ pre aplikovanie techník dolovania dát. Týmto spôsobom SIEMy prezentujú výborný zdroj veľkých objemov normalizovaných dát. Tieto dáta nesú potenciál pre dosiahnutie pokroku v bezpečnostnom výskume, dolovaní dát a umelej inteligencii, kde môžu viesť k zlepšeniu existujúcich metód prieskumu, sprehľadneniu skenovania siete a odhaleniu sofistikovanejších vektorov útoku. Avšak jedným z hlavných problémov pre využívanie týchto dát je skutočnosť, že dáta v logových záznamoch sú v mnohých prípadoch citlivé a môžu predstavovať riziko z hľadiska bezpečnosti. Z toho dôvodu bol vytvorený nástroj pre anonymizáciu citlivých údajov v logových záznamoch, ktorý zachováva korelácie medzi dátami. Hlavným cieľom bakalárskej práce je zamerať sa na technické a právne aspekty spracovania logov a anonymizáciu pre umelú inteligenciu. V rámci výskumu bola vykonaná analýza najčastejšie sa vyskytujúcich dát v logoch spolu s vyhodnotením ich rizikovosti, výsledkom čoho je vytvorenie kategórií dát vzhľadom na ich citlivosť. V práci je ďalej prezentovaná analýza súčasných SIEM systémov spolu s meta kľúčmi, ktoré využívajú.
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Humans, artificial intelligence and sentience
Mendelová, Michaela ; Vostal, Filip (advisor) ; Tremčinský, Martin (referee)
The thesis is based on the secondary analysis of data from the 2021 AIMS study. It is centered on the sentience, moral consideration, and social integration of artificial intelligence. My goal was to use a segmenting procedure (latent class analysis) to calculate classes or groups of respondents, based on their opinions on topics such as the inclusion of sentient AI and robots, animals, and the environment in the moral circle, granting legal rights to sentient AI, and support of the well-being of AI in the form of protection from harm or the perceived danger of AI for society. The analysis offers some results suggesting that there are 3 groups within the respondents and therefore possibly some groups in the US society. Class 1 is very contradictory, some respondents in this class are very supportive of AI, and some of them are not. Yet, overall, they tend to think that sentient technology can be dangerous. This class is generally the oldest and least frequently informed about AI. Class 2 is generally supportive of the welfare of AI, but these respondents prefer passive support. These respondents do not think that sentient AI can be dangerous for them, but they think that it can be dangerous to future people. This class is generally the youngest. Class 3 are respondents who had the biggest chance to...
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How can Factors Underlying Human Preferences Lead to Methods of Formal Characterizations towards Developing Safe Artificial General Intelligence?
Al-Nusair, Rana Ghalib ; Špelda, Petr (advisor) ; Butler, Eamonn (referee) ; Biagini, Erika (referee)
This research aims to investigate the Artificial Intelligence (AI) value alignment problem, which refers to the challenge in developing a safe and reliable AI that can achieve our goals and adhere to our values as we intend it to do. A misaligned AI, especially one which transcends all domains of cognitive abilities and has acquired vast computational powers, will be nearly impossible to manage and it will threaten our security. Research addressing this problem is now focused on understanding how to develop AI that can reliably infer our values from our preferences. Thus, preferences are the primary conceptual unit of analysis to the AI value alignment problem. This paper investigates our preferences and seeks to shed light on the issue of obtaining a formal truth that is fundamentally constitutive of our preferences, for the aim of using said formal truth to create a value aligned AI. To do this, this paper gathers data from economics, biological evolution, and neurocognitive studies to bridge the current gaps on the conceptual problem of preferences. The paper concludes with presenting a new kind of security dilemma which stems from the notion of combining a general theoretical framework that fully captures our preferences with the crucial elementof uncertainty inAI, effectively showcasing how...
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