This lecture on Natural Language Generation (NLG) focuses on building systems that automatically produce coherent and useful written or spoken text for human consumption. The instructor discusses the basics of NLG, autoregressive text generation models, decoding methods, and challenges. The lecture also covers greedy decoding methods like Argmax and Beam Search, as well as sampling methods. The session includes an exercise where students play around with a story generation system.