Tokenization Explained: The Hidden Step Behind Every LLM

0:00 Part 1 — Text Is Not Numbers: The First Step in Every LLM 4:46 Part 2 — Why Not Just Characters or Words? 10:42 Part 3 — Byte-Pair Encoding: Learning the Vocabulary by Merging 16:21 Part 4 — Bytes, Not Letters: How GPT Never Says UNK 22:44 Part 5 — 100,000 Tokens: Real Tokenizers and Their Vocabularies 28:34 Part 6 — Why ChatGPT Can't Count the R's in Strawberry 33:59 Part 7 — The Hidden Cost: Tokens, Money, and Language Fairness How does a language model actually read your words? Before any "AI" happens, your text is shredded into subword pieces called tokens — and that invisible step shapes what GPT can count, what it costs, and who gets a fair deal. This 40-minute deep dive covers the full story from first principles to real-world failure modes.