At its core, an LLM functions as a next-token prediction engine. It predicts the most likely next word in a sequence based on the context provided by the preceding text. The process of generating text usually involves some level of randomness in the choice of the next token. This randomness allows the model to produce varied and creative outputs instead of the same response every time given the same input, making the generation process non-deterministic. |