Recent advancements in generative AI have led to the introduction of several innovative methods aimed at enhancing image and video generation capabilities. Notable developments include Proximal Reward Difference Prediction (PRDP), which improves image quality using diffusion models, and Predicated Diffusion, which enhances text-to-image accuracy. Stability AI has launched Stable Video 4D, a generative AI model that allows users to create video variations from uploaded footage, facilitating applications in game development and virtual reality. Other significant contributions include SV4D, a latent video diffusion model for creating realistic 3D scenes, and MedM2G, a model designed for generating various medical images like CT scans and MRIs. Additionally, methods such as Gaussian-Flow and DITTO focus on efficient 3D scene reconstruction, while DiffusionRegPose aims to improve human pose estimation in complex environments. The research landscape is further enriched by techniques like ViewDiff, which generates 3D images from text, and DiffMorpher, which facilitates smooth image transitions. These advancements reflect a growing trend in the field of generative AI, particularly in the realms of 3D modeling and video synthesis.