Training recurrent neural networks to perform useful functions has proven difficult, especially in networks displaying complex spontaneous activity like that seen in biological networks. Building on ideas developed in connection with so-called echo-state networks, we have developed methods for training recurrent networks to produce complex temporal outputs. I will discuss how this is done and show demos of networks learning and performing various tasks.