> ... that something as smart as an LLM does not learn.
what? training is learning, as long as weights are available continual learning is perfectly feasible: just keep training the LLM with the user corpus alternated with a frozen version to prevent catastrophic drift / collapse.
it's not because model providers don't want to provide user specific continual learning, that we don't know how to do it.
it would be a lot more expensive to host user-specific model weights, and would prevent amortizing the weights over many requests in batches...
what? training is learning, as long as weights are available continual learning is perfectly feasible: just keep training the LLM with the user corpus alternated with a frozen version to prevent catastrophic drift / collapse.
it's not because model providers don't want to provide user specific continual learning, that we don't know how to do it.
it would be a lot more expensive to host user-specific model weights, and would prevent amortizing the weights over many requests in batches...