Potential energy surface (PES) of a molecular system is a function that represents the mapping correlation between the configuration and the energy. At a specified configuration, the PES function returns its energy. A given energy may correspond to many different configurations. Recent years have witnessed huge advances in developing full-dimensional accurate PESs based on tens even hundreds of thousands of configuration points, whose electronic energies are generally computed at the levels of MRCI or CCSD(T). These advances in the PES construction are boosted by diverse factors, including the increasing computing power, the development in the algorithms of electronic structure methods, and advanced machine learning models.