A scientist is using a generative Al model to create a summary of a research paper. The scientist then enters the prompt "expand more on point number $3"$ and gets a more detailed response.

How is Gen Al able to do this?

It permanently stores the data used to train the model.

It uses live agents to provide responses to the user's prompt.

It returns pre$-$scripted responses written by experts in the field.

It can track the context of an ongoing conversation.

I don't know this yet.