Temperature

In the context of AI and machine learning, temperature is a parameter used in sampling methods, particularly in natural language processing and generative models. It controls the randomness of predictions made by the model, influencing how creative or conservative the outputs are. A higher temperature results in more diverse and creative outputs, while a lower temperature yields more focused and deterministic responses. This concept is commonly applied in text generation tasks, such as chatbots or language models, where varying the temperature can significantly alter the tone and style of the generated text.