Attention Mechanism

In a long sentence, not every word matters equally to understanding the next word. An attention mechanism lets an AI model calculate which parts of its input deserve more weight at a particular moment. Transformer models use self-attention to compare elements within the same sequence, allowing them to link related words even when they are far apart. Multi-head attention repeats this comparison in parallel to capture several kinds of relationships. The same principle can be applied to image regions, audio segments, and combined text-and-image inputs. Attention is a foundation of modern language and multimodal systems used for generation, translation, summarization, speech processing, and visual understanding.