Definition of the Token in Era of AI Model world
In AI—especially in natural language processing (NLP)—a token is a piece of text that the model reads and processes as a unit. Tokens are typically: Words (e.g., “apple” is one token) Parts of words (e.g., “unhappiness” might be split into “un”, “happi”, and “ness”) Or even punctuation and whitespace (like “,” or “ ”) Examples: Sentence : “I’m happy.” Tokens : ["I", "’", "m", "happy", "."] (5 tokens) Different models use different tokenization rules. For example: OpenAI’s GPT models use a tokenizer called Byte Pair Encoding (BPE) . “ChatGPT is awesome!” would be broken into tokens like ["Chat", "G", "PT", " is", " awesome", "!"] Why It Matters: Models have token limits . E.g., GPT-4-turbo can handle up to 128,000 tokens. You’re often billed by tokens if using paid APIs. Understanding token count helps you manage input/output length efficien...