I’ve been working on short and long term memory windows at allofus.ai for about 6 months now and it’s way more complex than I had originally thought it would be.
Even if you can magically extend the content window, the added data confuses and waters down the reasoning of the LLM. You must do layered abstraction and compression with goal based memory for it to continue to reason without distraction of irrelevant data.
It’s an amazing realization, almost like a proof that memory is a kind of layered reasoning compression system. Intelligence of any kind can’t understand everything forever. It must cull the irrelevant details, process the remains and reason on a vector that arises from them.
I don't really know what any sort of "big leap" beyond this people are expecting, incremental performance for sure. But what else?
When you enable it, it is pretty shocking. And it’s pretty simple to enable. You just give it a meta instruct to decide when to message you and what to store to introspect on.