The aqueous environment of natural swimmers mediates magnificent patterns of schooling as well as their escape and attack routines. We study the fluid mechanics of single and multiple swimmers through simulations that rely on state of the art multi-resolution vortex methods. Stochastic optimisation and  machine learning algorithms are used to find optimal shapes and motions for single and synchronised patterns for multiple swimmers. I will discuss how the orchestration of body deformations and vortex dynamics can result in thrust and energy savings for these artificial swimmers and juxtapose these findings with swimming patterns of natural organisms. Lessons learned can assist the design and operation of energy efficient swimming devices.