Aanya 
Foundational models have become an important part of modern artificial intelligence. Instead of building a completely separate AI model for every task, developers can use a broadly trained model as a starting point and adapt it for different applications. So, what is a common real world application of foundational models? One of the most common
Foundational models have changed the way many artificial intelligence applications are built. Instead of creating a separate AI model from scratch for every task, developers can start with a broadly trained model and adapt it for different uses. So, what is a common real-world application of foundational models? One of the most common applications is
When people use AI tools such as ChatGPT, virtual assistants, translation systems, or other language applications, the system does not process text exactly the way a human reads it. Before an AI model can work with language, the text is usually broken into smaller pieces called tokens. So, what is a token in AI language
A good prompt can make the difference between a vague AI response and an answer that is actually useful. Whether you are using ChatGPT, Copilot, Gemini, or another generative AI tool, the way you describe your request affects how well the system can respond. So, what are the three things that make a great prompt?
When people start learning prompt engineering, they often come across frameworks that help them write clearer instructions for AI tools. One of the better-known structures is the CO-STAR framework, which breaks a prompt into six useful parts. So, what does C stand for in the COSTAR framework? The answer is Context. In CO-STAR, C stands
Generative artificial intelligence can write text, create images, generate code, summarize documents, and produce other types of content. But none of these abilities happen without the computing resources that power the AI system. So, what does compute refer to in the context of generative artificial intelligence? In simple terms, compute refers to the computational resources
When an artificial intelligence system learns by trying different actions and receiving positive or negative feedback, it is using a specific type of machine learning. This approach is different from learning from labeled examples or simply finding patterns in data without predefined answers. So, which learning type involves feedback in the form of rewards and
When people talk about how large language models learn, terms such as tokens, training data, parameters, and next-token prediction come up often. Among these, tokens are one of the most basic building blocks of the entire process. So, what are tokens in the context of large language models training? Tokens are the smaller units of