Attention refers to the ability of a model to focus on a specific subset of its inputs, or “attend” to them, while processing a given task. It enables machines to focus on the most relevant information and ignore irrelevant or less important input. For example, in Natural Language Processing (NLP), an attention mechanism might allow a language model to focus on certain words or phrases in a sentence to better understand the meaning or intent of the text. Attention mechanisms have become an important tool in deep learning, as they help models handle large and complex input data and perform tasks that require selective focus, or “attention” to certain elements of the input.
