Our modern economy overwhelmingly depends on the electricity infrastructure or the grid. The architecture of the grid owes its origins to Tesla, Edison and their industrial partners, and has remained largely unchanged since then. But this paradigm is being challenged by a confluence of factors, namely, age of the physical assets, cyber-physical security, weather-related stresses, and rapidly reducing cost of renewable electricity and storage. These are producing some unmistakable trends towards increased integration of distributed generation and storage. Furthermore, the integration of communication, computing and control to automate system operation is at its early stages. At scale, the resulting architecture will produce coupling of two large networks - electricity and information. Finally, the abundance and low cost of natural gas has already led to increased dependence of natural gas for electricity generation. The coupling between natural gas and electricity networks is producing dramatic fluctuations in prices with severe economic impact. This talk will discuss the changing landscape of the electricity infrastructure, the challenges that may arise from network coupling, and opportunities to use machine learning to address these challenges.