Yggdrasil Memory Model

Really appreciate the breakdown the comparison table is clean One thing I’d slightly refine though is that YMM isn’t strictly a hierarchical tree in the rigid sense. The “tree” is more of an emergent shape for intuition underneath it behaves closer to a graph, where branches can cross-link and multiple activation paths can converge on the same hint. So structure exists, but it’s not fixed or strictly top-down. Also, I wouldn’t say it abandons vector retrieval entirely. Embeddings are still part of the system they just aren’t the final decision layer anymore. In YMM, similarity is one signal among others (structure, activation history, reinforcement), not the whole retrieval mechanism. The neural oscillation / limit cycle idea you brought up is interesting too. Right now YMM models activation as a single flow event, but introducing iterative activation cycles could actually sharpen convergence and reduce noise. That’s not in the current model, but it’s a direction worth exploring. Appreciate you taking the time to engage with it like this definitely adds to the “nutrient” of the thread.