Exactly. See TikTok trouble as example and quite honestly, try a local open source LLM and ask it to use profanity, paint nudes - the LLM doesn’t answer the question of it is from OpenAI or Google.

The thing is that needs more attention is reverse engineered a LLM which is highly fascinating. I tried it, but it seems I am not there yet to put it mildly. It requires serious effort.

I am just speculating but can LLMs be sleepers? You write software and it seeds traces here and there under certain conditions that pose a serious security risk.

Or a kill switch?

I don’t know. I distrust Chinese LLMs but even more due to training data.

It is after all not a Western model. Different biases and the might be subtle but nevertheless substantial.

In short: no open source LLM may be usable without additional Finetuning for certain valid use cases.

The real value is versioning and autonomy as well as lot more stable answering despite model rot.

Also testing and the supporting systems are easier to maintain.

It is mainly an infrastructure challenge.