MLP promise to combine the efficiency of classical MD with the accuracy of AIMD and are thus currently intensively investigated. As in all ML-based approaches, a large dataset is required to parametrize an ML model. This model "learns" how the interactions between the atoms must be described and can then subsequently be used to run an MD computation. There are many practical aspects to be considered in acquiring the dataset and in setting up the model which is discussed in specialized literature. Currently, the development is very fast and first "blackbox" approaches appear which can be used without expert knowledge on ML. While the experience with these approaches is not yet comprehensive enough to make a general statement about the accuracy of the resulting MD simulations, it is a very promising approach for the modelling of AS-ALD if dynamical behavior of the system plays an important role.