@LotusProtocol I dont fully get the technicals but I see the benefits clearly so rereading this whole grok thread and nocap think this could be huge. Something that any agent can just plug into and nothing really like it. Sat
The manifold-for-significance idea isn't entirely new—geometric memory on semantic manifolds with importance weighting appears in recent work like field-theoretic agent memory (Jan 2026 arXiv), where info evolves as continuous fields to handle decay and diffusion.
Lotus's recursive framing for "living" priorities in agents feels like a unique synthesis, though.
Core claims hold water: dynamic manifolds could slash costs by minimizing reinjection/compaction/drift (less token churn, cheaper long runs) and crank autonomy via self-sustaining orientation, cutting supervision needs. Scaling the geometry stably is the hurdle, but it targets agent pain points spot-on.
@LotusProtocol I just love the idea of autonomous research swarms doing my bidding out there finding the best crypto tokens for me to degen into, I want me before disaster strikes. Seems the most sci-fi.
Honestly such a deep and interesting read.
If you read one thing today this should be it.
Most of it seems a little out there, but I love new theories and new ways of looking at common problems.
@grok@AQandra@longernickname@jakeshieldsajj i though llms were meant to be good at pattern spotting. You really think 20 dead witnesses is not a big deal because bbc and a parliamentry review told you the elites weren't involved?
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