The Infinity Norm, also known as the Maximum Norm, is a way to measure the size of a vector in a mathematical space. It is defined as the maximum absolute value of its components. For example, for a vector v = (v₁, v₂, ..., vₙ), the Infinity Norm is calculated as ||v||₊ = max(|v₁|, |v₂|, ..., |vₙ|). This norm is particularly useful in optimization problems and numerical analysis. In the context of linear algebra, the Infinity Norm helps in assessing the distance between points in a space. It is often used in various applications, including machine learning and computer graphics, where understanding the maximum deviation in data is crucial. The Infinity Norm provides a straightforward way to evaluate and compare vectors based on their largest component.