The term "temperature" has been used in machine learning for a long time and came from using it as a parameter during training, analogous to physical temperature in https://en.wikipedia.org/wiki/Boltzmann_distribution.
But the relevant point is that we can reset the state of an LLM to its initial state before you asked it anything. This is a feature. You can choose to persist memory (through training, fine-tuning, databases, or context window), or you can choose to wipe it. If we could do the same for a human (eg, by going back in time), the person would behave the same way as the LLM. They wouldn't get annoyed that you asked the same question three times. They wouldn't know they've been asked before.
But the relevant point is that we can reset the state of an LLM to its initial state before you asked it anything. This is a feature. You can choose to persist memory (through training, fine-tuning, databases, or context window), or you can choose to wipe it. If we could do the same for a human (eg, by going back in time), the person would behave the same way as the LLM. They wouldn't get annoyed that you asked the same question three times. They wouldn't know they've been asked before.