The Google team has recently proposed a generative image dynamics approach that can transform static images into dynamic videos. This method begins by extracting motion trajectories from real videos containing natural oscillatory movements, and then utilizes this data to train a model to learn the prior knowledge of image dynamics. For any given input image, the model can predict the long-term motion representation of each pixel and convert it into motion trajectories to generate a video. Additionally, the method supports user interaction with objects in the image. Users can drag points within the image to elicit corresponding responsive movements. This approach opens up new possibilities for generating dynamic videos from a single image and holds broad application prospects.