Frozen After Training
A free lesson from Swipe AI · AI Fundamentals, level 2 · updated October 2026
By the Swipe team, founded by Colin · how we make lessons
Once training finishes, a model's parameters are typically frozen: they stay exactly as training left them while people actually use the model. This surprises a lot of people, because it means most consumer AI tools do not learn from your individual conversations in real time the way a person would after talking to you.
Within a single conversation, a model can appear to "remember" what you said earlier — but that's because your earlier messages are being fed back in as part of the current input (more on this in Level 4), not because its underlying parameters changed. Once that conversation ends, none of it has altered the model itself.
Updating a model's actual parameters again generally requires a separate, deliberate retraining or fine-tuning process, run by whoever built it — not something that happens automatically as a side effect of ordinary conversations. It's a meaningful distinction: a frozen model behaves consistently between updates, for better or worse.
Do most consumer AI chatbots permanently learn from your individual conversations with them in real time?
After training ends, a model's parameters are typically ____, meaning ordinary use does not change them.
A model appearing to remember earlier messages in the same conversation means its underlying parameters have changed.
What More Data & Compute Actually Buys You
10 questions · pass with 60% — just like in the app.
What does "diminishing returns" mean for training data and compute?
Training large models has real costs in time, money, and electricity.
The pattern where each extra chunk of data or compute buys a smaller improvement than the last is called ____.
What tends to happen when a model is trained mostly on narrow or unrepresentative data?
A bigger training dataset is always better than a smaller one, no matter its quality.
Data that is narrow or contains errors tends to produce a model whose outputs are similarly ____.
Do most consumer AI tools permanently learn from your personal conversations with them in real time?
A model's parameters are typically frozen after training and don't change through ordinary use.
After training ends, a model's parameters are typically ____, meaning normal use doesn't change them.
How does a model appear to "remember" earlier messages within one conversation, if its parameters are frozen?
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