2026-10-28 · America/Los_Angeles · 社区动态 · #15

After 6 months of daily building, I just released Hillock v1.0 stable: a local neuro-symbolic memory engine that runs under 1.2GB VRAM with zero hallucinations

I spent the last half year obsessing over one specific problem: why does giving a local LLM long-term memory require spinning up massive vector databases that eat gigabytes of RAM and still hallucinate? Today I finally pushed the v1.0.0 stable release of Hillock, and it runs completely offline on consumer hardware or pure laptop CPU. The biggest issue with standard local RAG is that vector cosine similarity is purely probabilistic. When your user asks about something that does not exist in your documents, standard vector search still returns the closest random noise chunks, and your 3B or 8B…

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