The lack of concept of "knowledge" is a big one for me - if that's an emergent thing it hasn't even shown hints of this yet. This to me seems a pretty hard line

The lack of concept of "knowledge" is a big one for me - if that's an emergent thing it hasn't even shown hints of this yet. This to me seems a pretty hard line right now, as it limits their capability of things even inexperienced humans can do - namely decide if they actually know something, and identify when they don't know something and attempt to fix that - e.g. asking for clarification on vague inputs, or deciding if something is actually truth or fiction. That then ties into another limitation right now - how after a training the model is pretty static, so cannot learn and has no state outside it's context buffer. This could just be another point where a few orders of magnitude more computing power can "fix" it, doing whole training steps between each input to actually incorporate new information and corrections into itself instead of relying on a fixed size small context. But I'm not deep enough into things to say if they're fundamental issues, or current techniques will start displaying those effects as emergent characteristics as the complexity and training increases. There's been a few other examples when "known" techniques start to show unexpected characteristics down the line as they are scaled up, so can't really say for sure they'll /never/ be shown, just that the current examples don't seem to show even the beginnings of that sort of thing.