This paper introduces a new model for generating captions for images, which means automatically writing descriptions of what's happening in a picture. The model is inspired by how humans pay attention to different parts of an image when describing it. It uses a special technique called "attention," which helps the model focus on the most important parts of the image as it's writing the caption. There are two types of attention: "hard" attention, where the model picks one specific spot to look at, and "soft" attention, where the model considers all parts of the image but gives more weight to the most important ones. The model uses a convolutional neural network to extract features from the image and a recurrent neural network to generate the words in the caption. The authors tested their model on three datasets of images and captions and found that it performed better than other models. They also showed that you can visualize the attention of the model, which means you can see which parts of the image the model was focusing on when it wrote the caption.