Attention Mechanisms

Developed by Google researchers, the attention mechanisms allow a neural network to focus on the most relevant parts of the input data when making predictions. Instead of processing the entire input uniformly, attention mechanisms assign weights to different parts of the input, indicating their importance. These weights are then used to create a weighted average of the input, which is used for further processing. This allows the model to selectively attend to the most informative parts of the input, improving performance, especially in tasks involving sequential data like text or images.