Deep reinforcement learning has rapidly grown as a research field with far-reaching potential for artificial intelligence. Large set of ATARI games have been used as the main benchmark domain for many fundamental developments. As the field matures, it is important to develop more sophisticated learning systems with the aim of solving more complex tasks. I will describe some recent research from DeepMind that allows end-to-end learning in challenging environments with real-world variability and complex task structure.