This course introduces generative AI and large language models (LLMs), focusing on their educational applications. LLMs, built on transformer architecture, generate text by tokenizing input, predicting subsequent tokens probabilistically, and incorporating randomness for creativity. The course uses a fictional educational startup as a case study, exploring both the potential and challenges of LLMs in improving global learning accessibility. This segment provides a concise yet comprehensive overview of the evolution of generative AI, tracing its origins from early chatbots in the 1950s and 60s to the emergence of virtual assistants and finally, the current state-of-the-art large language models. It highlights key milestones like the shift to statistical approaches in the 1990s, advancements in machine learning algorithms, and the crucial role of transformer architecture in enabling the capabilities of modern generative AI. The historical context is essential for understanding the current capabilities and limitations of the technology.