 Smart grids are the current trend in power systems, with artificial intelligence, AI, playing a key role in their development. The decreasing cost of computing power, abundance of data, and improved algorithms have enabled AI to enter a new phase of development, AI 2.0. Three main AI techniques, Deep Learning, DL, Reinforcement Learning, RL, and Deep Reinforcement Learning, DRL, are representative of this new era. These methods have been applied to various aspects of smart grids, such as energy management, demand response, and renewable energy integration. Researchers have also explored the use of these techniques in other areas of smart grids, including distribution automation, microgrid control, and cybersecurity. This article was authored by Dongxia Zhang, Shaoqing Han, and Chunideng.