In AI, tokens are often used in combination with other techniques, such as:

1. Tokenization: The process of breaking down text into individual tokens.
2. Token embedding: The process of converting tokens into numerical vectors that can be used by machine learning models.
3. Tokenization algorithms: algorithms that can be used to tokenize text, such as wordpiece tokenization or character-level tokenization.

In summary, tokens are a fundamental unit of representation in AI, used to break down text into smaller parts, represent language, build language models, generate text, and classify and analyze text.