How do AI Tokens and Embeddings Work?

When you talk to Large Language Models (LLMs) like ChatGPT, Claude, or Llama, they don't actually process text word-by-word or character-by-character. Instead, they break down your text into smaller pieces called Tokens.

What is a Token?

A token can be a full word, a syllable, or even just a single character. For example, common words like "apple" might be one token, but a complex word like "antidisestablishmentarianism" might be split into several smaller tokens. The tokenizer assigns a unique integer ID to each piece. This makes it highly efficient for AI models to process languages.

What is an Embedding?

Once text is tokenized, it is passed into the neural network which converts these tokens into high-dimensional vectors known as Embeddings. An embedding is a list of floating-point numbers that captures the semantic meaning of the text. Words with similar meanings will have embeddings that are closer together in the mathematical space. This is what allows AI to "understand" context, sentiment, and intent.

100% Private & Local

This visualizer uses a lightweight Machine Learning model that downloads directly to your browser cache. All tokenization and embedding generation happens locally on your device. Your text is never sent to any external server or API, guaranteeing complete privacy.