Fascinating approach — using VSA to compress graph traversals into O(1) SIMD operations is a clever way to sidestep the RAG vs graph DB trade-off. Curious about a couple of things: how do you handle fact deletion or correction once something is superposed into the accumulators? And what does the query interface look like from the agent's perspective — is it purely similarity-based via Hamming distance, or do you support structured relational queries too?
Fascinating approach — using VSA to compress graph traversals into O(1) SIMD operations is a clever way to sidestep the RAG vs graph DB trade-off. Curious about a couple of things: how do you handle fact deletion or correction once something is superposed into the accumulators? And what does the query interface look like from the agent's perspective — is it purely similarity-based via Hamming distance, or do you support structured relational queries too?
I'm interested in this, but only passingly familiar with it from several years ago. Can you link to what you believe the current state of the art is?
State of the art for HDC/VSA? Or for agentic memory?
great and neat project! I would like to ask, where do you see the value here? a lot of tools on memory, context, etc