Training vs inference
Does a model learn from my conversation while I use it?
A model does not learn from your chat. During inference its weights are frozen. It can adapt to examples you put in the prompt, but that adaptation lasts only for that one request.
A common worry, and a common misunderstanding: does the model learn from what I tell it? In the usual sense, no. While you are using a model, its weights are frozen. Your conversation does not rewrite them. Anything the model “remembers” later comes from a separate training run on collected data, not from your chat updating it live.
There is one twist that looks like learning but is not. If you put a few examples directly in your prompt, the model can pick up the pattern and follow it for that answer. The GPT-3 authors showed this clearly: the model was “applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model.”[1] The examples steer the answer, but no weights change, and the effect vanishes once the prompt is gone.
So it helps to keep two ideas apart. Real learning means changing the weights, which happens during training. Adapting to your prompt happens during inference and lasts only for that one request. The model that answers your next question is exactly the same model that answered your last one.
References
- Language Models are Few-Shot Learners (arXiv:2005.14165) — Brown et al., OpenAI