In this talk, I will present our latest progress on both forward and inverse acoustic scattering problems. For scattering in unbounded domains, we have introduced a novel alternating-optimized SNN approach that achieves both high computational efficiency and strong accuracy. To address problems involving large wave numbers, we have proposed the Hankel neural network method. This method is capable of achieving an accuracy of 10^{-4} even at a wave number of 2000. Furthermore, we have developed a new machine learning framework that can tackle multi-body scattering problems without any prior knowledge of the number of scatterers.