Did you know that predicting what might happen next is an important skill  not just for people, but for computers too? In the world of Artificial Intelligence (AI), prediction means using knowledge and experience to guess what could happen in the future. For example, AI helps us figure out what the weather will be like tomorrow by looking at lots of information and patterns. Want to know how AI is enabling the function of prediction about a future outcome?

You may have heard the term Agentic AI popping up lately. Simply put, it describes a way for different AI “helpers” to work together as a team to solve a bigger problem. Each AI agent is like a digital assistant that knows how to do one specific job—such as finding information, organizing tasks, or checking answers—and they rely on AI models to do their work. When these agents collaborate, they can handle more complex tasks efficiently. In this article, we’ll explore everyday examples of how Agentic AI is used and why  this team-based approach can help create smarter, more scalable technology that may increasingly show up in tools used at home and in classrooms

Perplexity is an AI-powered search engine that searches the web to deliver accessible, conversational answers backed by verifiable sources. Each response includes citations and links to original sources, enabling you to verify the information and explore topics in greater depth.

An algorithm is simply a set of clear, step-by-step instructions for completing a task—much like a recipe or directions for a game. Sorting means putting things into a certain order, such as arranging blocks from smallest to largest. These simple activities help children build important problem-solving and thinking skills they’ll use later in math, science, and everyday life. Want to know more?

Automation has changed the way people work for many years, and AI is part of this ongoing story. It is a fact that automation has always disrupted the labor market. What feels new and sometimes worrying is that today’s Generative AI can help with creative and thinking-based tasks—things like writing, designing, or problem-solving—that were once done only by trained professionals. It’s natural for people to wonder how this might affect jobs such as programming, journalism, design, or advertising. In this article, the Makerville hosts explore how AI may both challenge and support different professions, and how it can influence the way we think, work, and stay productive in a changing world.

How can we make a machine forget part of what it learnt earlier?  This is a grand challenge for the AI researchers.