Ask HN: What do you think of continuously learning LLMs in production

What do you think of continuous learning in LLM apps? Current LLM technology only allows generation or offline training, but not much support of continuous learning. This means that LLM apps cannot directly benefit from feedback acquired in production, for instance from user or environment feedback. I see use cases that this can enable, like coding assistants learning from interpreter results, user feedback on customer support LLM agent, an AI browser learning from a failed tool usage or an AI worker going through an initial onboarding or training. Current state of research can somehow enable this, like RAG, DPO, KTO or model editing but still some issues like sample efficiency and catastrophic forgetting.

Though the big question is whether learning should always happen offline or it would be useful to have models learn in production. Let me hear your thoughts.