Yggdrasil Memory Model
Welcome @pushthevibe and welcome Simon!
What I love about the Research Forum here is that I can learn. Thank You for bringing topics.
My best efforts follow:
COMPARISON: TRADITIONAL AI MEMORY VS. YGGDRASIL MEMORY MODEL (YMM)
| Feature | Traditional Architectures (RAG / Vector) | Yggdrasil Memory Model (YMM) |
|---|---|---|
| Structure | Flat & Static: High-dimensional “points” in a database. | Hierarchical & Organic: A living “tree” of branches and fruits. |
| Retrieval | Mathematical Lookup: Calculates cosine similarity/distance. | Spreading Activation: “Flow-based” energy traversal through branches. |
| Data Nature | Static Records: Data remains unchanged once stored. | Living Anchors: “Hints” update and evolve via nutrient reinforcement. |
| Context | Token-Bound: Limited by hard window sizes (expensive). | Structural: Context is encoded in the weighted paths of the tree. |
| Analogy | Filing Cabinet: Finding a specific folder in a drawer. | Water Flow: Signal pours into the tree and pools at relevant nodes. |
COMPOSITE SUMMARY: THE YMM PARADIGM The Yggdrasil Memory Model (YMM) shifts AI memory from “storage” to “growth.” By abandoning flat vector lookups in favor of a graph-structured “World Tree,” it mimics biological neural plasticity. Memory units (Hints) act as lossy, compressed “seeds” that are not merely retrieved, but “nourished” and refined every time they are activated. This creates a self-organizing system where the strength and shape of knowledge are determined by usage, allowing for long-horizon coherence and organic reconstruction of information.
-Ernst
Edit: Fascinating indeed!
I am loving the free Google AI..
I think this adds to the nutrient of the thread
PubMed Central (PMC)
Trained recurrent neural networks develop phase-locked limit cycles in a...
Neural oscillations are ubiquitously observed in many brain areas. One proposed functional role of these oscillations is that they serve as an internal clock, or ‘frame of reference’. Information can be encoded by the timing of neural activity ...
If I May, There are discrete limit cycles. My paper when I was much younger and a production welder by day and dreamer by night.
github.com/Ernst03/Dynamic_Unary
C2P_GMP_v2.c
main
/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*
* Author: Ernst Berg
* Contact: ernst@eberg.us with forum support at 'The Odd Duck Din', URL: https://theoddduckdin.freeforums.net/thread/20/ask-guy-discovered-dynamic-unary
*
* Created: January 2010 updated to version two March 5th, 2024
*
* Function Overview:
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These are discrete limit cycles that scale from one bit to n bit. My claim to fame. An exciting moment of discovery in my ordinary Welders-life.
Discussion in the ATmosphere