Reviewing and synthesising complex theoretical texts is a fundamental yet time-consuming aspect of academic research. Recent developments in generative AI offer new tools to assist scholars in the comparative analysis of scientific literature. This post presents a tailored prompt designed to support such work, illustrated through the example of two
Communicating research clearly and quickly is becoming an essential part of academic work. To support and simplify this process, we introduce a tailored prompt that helps transform published research articles into concise news following a predefined format. This tool streamlines dissemination by converting complex academic content into accessible updates ready
As part of testing the synthetic data generation capabilities of GenAI models, we assigned a seemingly simple task to some of the most popular language models: to generate 50 unique customer feedback entries about a smartwatch, including specified fields (name, age, city, feedback, and date of purchase) and a varied
Synthetic data is critical across numerous fields, enabling researchers and practitioners to emulate realistic scenarios while safeguarding personal privacy. This blog presents a case study in which we applied this methodology to generate customer feedback for a smartwatch product using several AI models. The exercise explored the general capabilities of
One of the most practical — and remarkably simple — applications of Generative AI (GenAI) in academic work is its ability to support early-stage thinking. Whether preparing a research paper, essay, or seminar discussion, getting started with a topic can often be the most challenging step. With a well-crafted prompt, GenAI tools
Classifying gender based on names might initially appear straightforward, yet different AI models vary significantly in how accurately and effectively they handle this task. This blog explores the performance of various models when provided with a structured prompt for name-based gender classification using an uploaded .xlsx file. The evaluation specifically
