In the context of Generative AI, "Temperature" refers to a parameter in the probability distribution function used during the generation process. It controls the randomness of predictions by scaling the logits before applying softmax. A high temperature value results in more random outputs, while a low temperature value makes the model's outputs more deterministic and similar to the training data. It's a crucial factor in balancing between diversity and quality of generated content.
In an analog to human cogitation one could compare the temperature value to the level of creativity, where a high temperature value would result in more creative outputs, while a low temperature value would result in more objective outputs.
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