A large language model (LLM) is a neural network trained to predict the next token in a sequence. A token is a small piece of text. During generation, the model reads the prompt, assigns a probability to each possible next token, chooses one, and repeats the process.
The model does not look up a complete answer stored in a database. Its training has encoded patterns about language, facts, code, and common reasoning into its weights. This lets it produce useful text, but it can also produce a fluent answer that is wrong. Chat models receive extra training after basic text prediction so they can follow instructions, use tools, and respond like assistants.
Rewriting in plainer words…
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