Attention Mechanism

The attention mechanism is a deep learning technique that enables neural networks to focus on specific parts of the input data, such as text or images, when making predictions or decisions. By selectively weighting the importance of different input elements, attention mechanisms improve the performance and interpretability of AI models in applications like natural language processing, computer vision, and speech recognition, making them a crucial component of many state-of-the-art research models.