Wrap up by a group discussion about what the results were. Notice if there are differences in response when the same prompt is used. The reason the same prompt input into the same language model may return different results is due to the model’s design for generating diverse outputs. This variability is a feature, not a flaw, promoting creativity and wide-ranging responses. It’s like how a brainstorming session might yield different ideas each time, even with the same starting point. The model draws from a vast dataset, applying randomness and probability to select words, leading to varied outcomes for similar prompts. This ensures users receive fresh, unique responses, enhancing the tool’s utility and engagement.