Deep learning can help automate the signal analysis process in power side channel analysis. So far, power side channel analysis relies on the combination of cryptanalytic science, and the art of signal processing. Deep learning is essentially a classification algorithm, but instead of training it on cats, we train it to recognize different leakages in a chip. Even more so, we do this such that typical signal processing problems such as noise reduction and re-alignment are automatically solved by the deep learning network. We show we can break a lightly protected AES, an AES implementation with masking countermeasures and a protected ECC implementation and show a live demo of the attack in action. These experiments show that where previously side channel analysis had a large dependency on the skills of the human, first steps are being developed that bring down the attacker skill required for such attacks. This talk is targeted at a technical audience that is interested in latest developments on the intersection of deep learning, side channel analysis and security.