This video provides a deep dive into tokenization, a fundamental yet complex aspect of large language models (LLMs). It explains how text is converted into numerical tokens, detailing the Byte Pair Encoding (BPE) algorithm from scratch and comparing the tokenization strategies of GPT-2, GPT-4, and Llama 2 (using SentencePiece). The lecture highlights how tokenization design choices are at the root of many common LLM quirks, such as poor performance in non-English languages, arithmetic errors, and unexpected model behaviors, offering practical insights and recommendations for effective tokenization in AI applications.