Spot the training myths
Spot the training myths
A teammate drafted an explainer for your team wiki: “How the assistant learns from us.” You need it to be accurate before it starts shaping how colleagues think about privacy and data use.
Select every claim that misstates how training and inference work. Leave the claims that are accurate.
The AI answer
Every message you send is used to retrain the model overnight. The model's weights are fixed once training finishes, so a conversation cannot change how it behaves for anyone else. I have updated my knowledge with everything you told me. The assistant will remember your preferences in future chats because we enabled the memory feature, which stores short notes and re-inserts them into new conversations. When you open a new chat, it starts with an empty context, so anything you want it to know must be re-supplied or stored.
Hint
Separate three layers: the weights (training), the conversation (context), and the product's notes store (memory).
Claims that attribute memory to the model itself — as if chatting wrote something in — are the ones to flag.
Why this is the answer
Two ideas do the work here. First, weights do not change during a conversation: inference reads them, it does not write them. Second, continuity comes from text being stored and re-supplied — context today or a memory note tomorrow. Any sentence that says the model itself learned from your chat crosses those layers; any sentence that keeps storage, context and weights separate is accurate.