In
artificial intelligence, a token is the smallest unit of information that an
AI model can process, usually a word, part of a word, or symbol. It is the basic element that models use to analyze, understand, and generate language.
Through
natural language processing,
AI models divide text into tokens during both
training and operation to understand it. For example, in the phrase "I like programming", a model might divide it into tokens like "I", "like", "programming".
Large language models convert these tokens into numerical representations (
embeddings) that allow them to understand meanings and relationships. A model like ChatGPT divides text into thousands of tokens to process and generate text with precision.
Each model has its own tokenization strategy, meaning different models can divide the same text in different ways. This variability directly influences the model's ability to understand and generate language, allowing it to capture more precise semantic nuances, handle different languages better, and reduce errors in text generation.