Comment by cs702

The problem is even more fundamental: Today's models stop learning once they're deployed to production.

There's pretraining, training, and finetuning, during which model parameters are updated.

Then there's inference, during which the model is frozen. "In-context learning" doesn't update the model.

We need models that keep on learning (updating their parameters) forever, online, all the time.