Text Embeddings Explained
Introduction: Turning Language into Mathematics Text embeddings are the invisible engine behind modern information retrieval. They are the reason a search for "automobile" can find documents about "cars," why a question in English can retrieve answers in Spanish, and why a...
How LLMs Understand Natural Language
Language is messy. The same sentence can mean different things depending on context, tone, or who's speaking. Words have multiple meanings, sarcasm flips a sentence's intent entirely, and pronouns can point to almost anything nearby. Yet LLMs handle this messiness remarkably...
Tokens: The Building Blocks of LLMs (Part 2)
Every time you type a message to ChatGPT or Claude, something happens before the model even starts "thinking": your text gets chopped up into small pieces called tokens. Tokens are the fundamental units that large language models actually read, process, and generate — and...
Tokens: The Building Blocks of LLMs
If you've ever noticed that AI pricing is measured in "tokens," or seen a model get confused by an unusual word, you've bumped into one of the most fundamental — and least discussed — parts of how LLMs work. Before a model can predict, reason, or write a single sentence, it first …