Prezi’s new AI tool promises to transform documents into ready-made presentations. Our tests show that while the tool produces visually appealing slides, the generated content often drifts away from the uploaded source material. Using sustainability reports from Audi and the Hungarian National Bank, as well as an academic article,
In our earlier blog post, Harnessing GenAI for Searching Literature: Current Limitations and Practical Considerations, we examined the reliability of generative AI models for scholarly literature searching. To assess whether the newest releases represent any improvement, we tested them on the same narrowly defined academic topic. The results indicate modest
In a previous blog post, we focused on input file handling in leading GenAI interfaces, mapping out which formats could be uploaded and processed reliably, and where the main limitations were. This time, we turn to the other side of the equation—output generation—with a concrete test case: producing
In a previous blog, we examined the file handling capabilities of leading GenAI interfaces. That analysis detailed which formats they could process reliably and where they encountered difficulties—particularly with structured data and technical file types. Since then, the landscape has shifted. While downloadable file generation still faces notable constraints,
NotebookLM’s Mind Map function offers researchers a powerful way to quickly grasp the structure and key findings of any uploaded PDF, from academic papers to policy reports. By automatically generating an interactive visual overview, users can explore a study’s objectives, methods, results, and conclusions at a glance. Clicking
We tested the new OpenAI Agent to assess its usefulness in academic research tasks, comparing it directly with Manus.ai and Perplexity’s research mode. Our aim was to evaluate how effectively each tool finds relevant scholarly and policy sources, navigates restricted websites (including captchas and Cloudflare protections), and allows
In an earlier post, we tested Gemini’s Audio Overview as a tool for open science, examining its capacity to transform written research into accessible spoken summaries. While that experiment revealed both strengths and limitations, it also raised the question of how other AI systems address the same task. Notebook
These tools provide dedicated spaces for creating, refining, and managing content alongside artificial intelligence interactions, facilitating tasks from data visualisation to manuscript drafting. This guide, tailored for researchers, examines their practical applications, operational mechanisms, distinctions, version control capabilities, memory management, and availability in other models. By leveraging these interfaces, researchers
Academia.edu has recently introduced an AI-based Reviewer tool, positioned as a solution for generating structured feedback on academic manuscripts. While the concept is promising, our evaluation revealed a number of significant limitations. We encountered recurring technical issues during both file uploads and Google Docs integration, often requiring multiple attempts
Ensuring a manuscript perfectly adheres to a journal's unique and often complex formatting guidelines is a familiar, laborious task for every researcher. It represents a final, time-consuming hurdle before submission, where minor errors can lead to delays or even desk rejection. But what if this critical checking process
Can artificial intelligence make academic research more accessible to non-specialist audiences—or even to busy researchers on the go? Gemini’s new ‘Audio Overview’ feature provides a novel way to experience scientific papers: through short, conversational audio summaries. Available even in the free version of Gemini 2.5 Flash, this
High-quality feedback is essential for researchers aiming to improve their work and navigate the peer review process more effectively. Ideally, such feedback would be available before formal submission—allowing authors to identify the strengths and weaknesses of their research early on. This is precisely the promise of OpenReviewer, an automated
