Recently, the advent of three-dimensional Gaussian splatting (3DGS) technology has brought revolutionary changes to the development of differentiable rendering techniques. Although neural radiance field (NeRF) has been a milestone in differentiable rendering, achieving breakthroughs in high-fidelity novel view synthesis, it still suffers from issues such as implicit expression and low training efficiency. In contrast, 3DGS technology addresses the pain points of NeRF by employing an explicit point cloud representation and a highly parallelizable differentiable rasterization pipeline. Compared to NeRF, 3DGS improves training speed and rendering efficiency while offering greater scene control. 3DGS technology propels differentiable rendering to a new height with remarkable achievements in areas such as novel view synthesis and dynamic scene reconstruction. 3DGS has been demonstrated to have broad application prospects and tremendous potential. This study aims to showcase the latest developments in 3DGS technology to inspire in-depth exploration of differentiable rendering techniques, with the hope of providing insights for technological advancements in the future.