Show HN: AI memory with biological decay (52% recall)

· coding ai ai-agents · Source ↗

TLDR

  • YourMemory adds persistent MCP memory to AI agents using Ebbinghaus decay curves, beating Mem0 by 16pp and Zep Cloud 2x on LoCoMo-10.

Key Takeaways

  • Benchmarked on LoCoMo-10 (1,534 QA pairs, 10 sessions): 59% Recall@5 vs Zep Cloud’s 28%, using BM25 + vector + graph + decay hybrid.
  • Hybrid retrieval: Round 1 cosine vector similarity, Round 2 graph BFS expansion surfaces semantically connected memories that vocabulary search misses.
  • Four decay categories with different survival windows: strategy ~38 days, fact ~24 days, assumption ~19 days, failure ~11 days.
  • Local-first stack: DuckDB + NetworkX + sentence-transformers (all-mpnet-base-v2, 768 dims), no Docker or external services required.
  • CC-BY-NC-4.0 license: free for personal and academic use; commercial use requires a separate written agreement.

Hacker News Comment Review

  • Decay as a pruning mechanism is contested: at least one commenter uses it only for hotness scoring, arguing erroneous memories need explicit correction logic, not time-based fading.
  • Multiple builders report memory injection adding noise: agents comingling unrelated projects and second-guessing current tasks based on stale prior-session context is a documented failure mode.
  • The harder unsolved problem flagged repeatedly is deciding what to save and avoiding redundancy – not retrieval quality or the decay math itself.

Notable Comments

  • @K0balt: Production ambient-recall system using a 4B model scanning context, injecting ~1/5 turns, with session-end wrapup ratings on all memory injections – a concrete tested alternative to store-everything approaches.

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