This talk provides a comprehensive introduction to Large Language Models (LLMs), explaining their fundamental architecture as two files (parameters and run code) and the resource-intensive pre-training process that compresses vast internet data. It details how fine-tuning transforms these models into helpful assistants and explores advanced capabilities like tool use and multimodality. The speaker also delves into future directions such as System 2 thinking, self-improvement, and customization, conceptualizing LLMs as the kernel of an emerging operating system, while also highlighting critical security challenges like jailbreak, prompt injection, and data poisoning attacks.