We don’t just remember what was said.
We remember what mattered.
That’s why I’m building @deepadata; the emotional layer of memory.
Writing about memory, meaning & the future of interaction → https://t.co/SWqc8Ft2B3
@mem0ai EDM (Emotional Data Model) — the significance layer for AI memory.
Mem0 captures what happened. EDM captures what mattered — encoded at capture before retrieval.
We already have a Mem0 adapter with queryBySignificance(). MIT open standard + hosted API.
https://t.co/4caevMYskb
CoALA is the right taxonomy for the memory architecture. EDM sits within it — specifically the episodic + semantic layers, adding a significance tier: governed, auditable records of what mattered, encoded at capture.
CoALA describes the shape. EDM is a file format for one of the most important things that goes in it.
MIT spec: https://t.co/IJ5UYTTmtj
EDM (Emotional Data Model) is a published open standard for this — specifically the significance tier: not what happened, but what mattered, encoded at capture before retrieval.
MIT spec at https://t.co/IJ5UYTTmtj. DOI on Zenodo. LangChain adapter at v0.1.2.
Your artifacts, your significance — same shape as your harness/memory thesis, one layer down.
There's a third path between raw and derived that this piece doesn't cover: structured significance encoding at capture time.
Not a summary. Not verbatim. Structured fields extracted once — arc_type, emotional_weight, identity_thread — that don't drift with repeated derivation and don't require semantic retrieval to find.
"When was I most afraid of losing her" has zero lexical overlap with the stored memory. Raw misses it. Derived drifts from it. Significance fields find it.
The failure mode you named — selective retrieval bias — is what this solves.
@KieranWarwick Agree. The things we value or remember are seeded in emotion and stick, or are recalled, because of it.
Community, storytelling, and sharing that with others is more valuable than the experience itself.
That’s the chasm. Keep fighting! 👊
@theJayAlto You’ve shown “the reason for meaning” not meaning itself in my opinion.
Meaning is where it all starts—not the outcome.
Most people don’t recognize it until something is achieved, but it was always there.
Quiet. Waiting. In all of us. It’s foundational