Before building applications, you need to understand how LLMs process text. This chapter covers the four building blocks:
Tokenization — how text is broken into tokens (the LLM’s “alphabet”)
Embeddings — how tokens are mapped to high-dimensional vectors that capture meaning
TF-IDF — a classical approach to measuring word importance (contrast with embeddings)
Attention — the mechanism that lets transformers understand context and relationships between words