Frequently Asked Questions

Generative Artificial Intelligence refers to AI models capable of producing new content such as text, images, videos, music, or code based on patterns learned from large datasets. It does not "think" like a human but predicts the most appropriate output based on its training.

GenAI systems analyze massive datasets using deep learning and neural networks to identify patterns and relationships. Once trained, the model generates new content by predicting the next probable sequence of information.

Popular tools include ChatGPT, Google Gemini, Midjourney, DALL·E, Claude, GitHub Copilot, character AI models, image generators, and text-to-speech platforms.

GenAI supports creative content generation, automates repetitive tasks, summarizes information, assists with programming, analyzes data, and increases productivity across education, research, and business.

Risks include factual inaccuracies, biased outputs, hallucinated information, privacy concerns, inconsistency, and dependency issues. Human oversight is essential to evaluate AI-generated content.

Cross-check outputs with credible sources, verify citations, confirm technical accuracy, and apply human judgment before using AI-generated content in academic or professional contexts.