Noise reduction is the process of removing unwanted random variations (noise) from data to reveal the underlying meaningful patterns. In images, noise appears as grain or random pixel variations; in audio, as static or hiss; in text, as typos or irrelevant information. AI-powered noise reduction uses learned models to distinguish signal from noise, enabling clearer speech recognition, sharper image processing, and more accurate data analysis. Denoising autoencoders are a popular deep learning approach.