Attention Networks

Attention networks are a type of machine learning model that helps computers focus on the most relevant parts of input data, streamlining understanding and decision-making. For example, when translating a sentence, attention allows the model to "pay attention" to specific words important for accurate translation, rather than processing the entire sentence equally. This mechanism improves efficiency and accuracy in tasks like language processing, image recognition, and more. Essentially, attention acts like a spotlight, highlighting the most important information to help the model perform better on complex tasks.