Quick hook. What if algorithms could propose a new drug candidate, predict a protein’s 3-D shape , and run thousands of experiments in an automated lab all in the time it would take a human team to run a few? That is not sci-fi. Generative AI is already part of real scientific workflows in 2025, and this guide explains how , why , what works , what doesn’t , and how you can learn and experiment with these tools. 1. Plain-language definition: what is “generative AI for science”? Generative AI are machine-learning models that create   they generate text, images, molecular graphs, 3-D structures, or even experimental plans instead of only classifying or labeling. In scientific discovery these models are used to: propose new hypotheses, molecules or materials; predict structures and behavior (e.g., protein folding); design experiments and optimize conditions; run closed loops with robots that execute experiments and feed back results. These systems don’t replace sc...

Augmented Reality (AR) is poised to revolutionize education by transforming the way students interact with content, making learning more engaging, interactive, and immersive. Here's a detailed examination of how AR can reshape various aspects of education: Immersive Learning Experiences 1. Enhanced Engagement AR can bring textbook content to life. For example, history students can explore ancient civilizations through interactive 3D models, while biology students can examine the human body in detailed, life-like layers. 2. Real-World Applications AR bridges the gap between theoretical knowledge and practical application. Engineering students can use AR to visualize and manipulate complex machinery, while medical students can practice surgical procedures in a risk-free virtual environment. Virtual Labs 1. Safe and Cost-Effective Traditional science labs require expensive equipment and materials, and safety can be a concern. AR provides virtual labs where students can conduct experim...

Que - Explain functional dependency and its types with examples in detail. Ans -   Functional dependency is a crucial concept in the field of relational databases. It describes the relationship between attributes (or columns) in a relation (or table). In simpler terms, it tells us how one attribute's value determines another attribute's value within a table. Let's dive deeper into the definition and types of functional dependencies with examples: Definition: A functional dependency � → � X → Y in a relation holds if and only if, for every valid instance of � X , there is exactly one corresponding instance of � Y . This means that if two tuples (rows) in a relation agree on a set of values for � X , they must also agree on the corresponding values for � Y . Types of Functional Dependencies: Full Functional Dependency: A full functional dependency occurs when removing any attribute from the determinant � X results in a loss of the functional dependency. In other words, ...