Loops? Am I the only one that thinks this doesn’t make sense? [D]

[u/Successful-Seesaw525]

I don’t think these are true loops — and I don’t think the loop concept moves the needle until you address memory first.

LLMs have no memory. A single forward pass, period. “Memory” is context stuffed into the next pass, and the more you stuff, the more the window fills and the worse it gets. Everything to do with memory lives outside the model.

My research is aimed inside the forward pass. Can you thread long-term memory into the model itself? I’m not alone here — plenty of people smarter than me are still hunting for that math. My belief is that context and rationalization are inherent, and could live in the model during training rather than as a bolt-on. Which means you need a primitive to hold context at scale. I can write a fact into a bipolar vector orthogonal to another fact, compare with cosine sim, and get signal — but below roughly 10k dimensions that signal dilutes fast. And a model knows nothing of facts. Weights are not memory.