attention and calculation

Attention in machine learning is like focusing on the most relevant parts of information to understand or solve a problem. For example, when reading a paragraph, you pay more attention to key sentences that help with comprehension. In calculations, attention assigns different weights to data points based on their importance, allowing models to prioritize significant details. This process helps models process complex information efficiently, improving tasks like language translation or image recognition by emphasizing the most relevant features in the data.