Grok-3

Grok-3

Thematic Content Analysis of Martin Luther King Jr.'s "I Have a Dream" Speech Using Grok 3

Thematic content analysis is a key method in political text interpretation, but it typically requires human judgement to define categories and trace meaning. In this study, we explored whether Grok 3, a state-of-the-art large language model, can carry out this task autonomously—without predefined themes or external guidance. Using Martin

Does the Language of the Prompt Matter? Exploring GenAI Response Differences by Query Language

The growing use of generative AI tools in research and professional contexts raises important questions about linguistic bias and consistency in model outputs. This short study explores whether the language of a prompt—specifically, English versus Hungarian—affects the content, tone, and legal precision of responses produced by a state-of-the-art

Classifying Financial Texts into Pre-defined Subdomains

Natural Language Processing (NLP) allows us to automatically analyse and categorise textual data. With the help of GenAI, even complex classification tasks can now be executed using just a well-designed prompt. In this post, we present a practical example where GenAI classifies financial-related sentences into domain-specific categories, showcasing how effective