In the context of AI tools and language models, tokens are essentially pieces of words that are used to break down text for processing. In layman's terms, think of tokens like the building blocks of a sentence.

When an AI processes text, it doesn't always handle whole sentences or words like humans do. Instead, it breaks the text into smaller parts called tokens. These can be complete words, parts of words, or even individual characters, depending on the language and complexity.

For example, the word "cat" would be one token, whereas a longer word like "running" might be split into two tokens like "run" and "ing." This breakdown helps the AI understand and generate text by analyzing and predicting each piece individually, allowing it to manage language more effectively.

The number of tokens is an important factor because AI models have limits on how many tokens they can process at once. This affects how much text you can input or output in a single interaction.