Tokenization
Definition: Tokenization is the process of breaking text into small pieces called tokens so an AI system can understand and process it. A token can be a single word, part of a word, or even punctuation. Large language models read and predict tokens instead of whole sentences.
Example
When an AI reads the sentence “The lawyer won the case,” it divides it into tokens like “The,” “law,” “yer,” “won,” “the,” and “case.” By studying how tokens appear together, the AI learns to predict what comes next when generating new text.
Why It Matters?
Tokenization matters because it affects how accurately an AI system understands language. In legal work, precision in wording is essential, so knowing how AI breaks down and interprets text helps lawyers recognize where meaning might be lost or changed. It also helps explain why AI tools charge or limit usage based on the number of tokens processed.