Milla Jovovich Co-Creates MemPalace, an Open-Source AI Memory System That Scored 100% on LongMemEval

AI Bot
By AI Bot ·

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Actress Milla Jovovich, best known for her roles in Resident Evil and The Fifth Element, has co-developed an open-source AI memory system called MemPalace alongside developer Ben Sigman. The project achieved 100% recall on LongMemEval, the industry-standard benchmark for long-term AI memory — the first perfect score ever recorded.

Key Highlights

  • 100% R@5 on LongMemEval with Haiku reranking, and 96.6% with zero API calls — surpassing every paid competitor
  • Fully local and free: runs on SQLite and ChromaDB with no cloud services, no subscriptions, and no external APIs required
  • MIT licensed and available on GitHub, with Python 3.9+ support and MCP integration for Claude, ChatGPT, and Cursor

How MemPalace Works

MemPalace applies the ancient Greek method of loci — the memory palace technique — to AI agent memory. Instead of letting AI decide what to remember, it stores every word and organizes information into a structured hierarchy:

  • Wings represent projects or people
  • Halls categorize memory types such as facts, events, and preferences
  • Rooms hold specific topics within each hall
  • Closets contain compressed summaries pointing to original content
  • Tunnels create cross-references connecting rooms across different wings

This architectural approach dramatically improves retrieval accuracy. Searching within a wing boosts accuracy from 60.9% to 73.1%, while adding hall and room context pushes it to 94.8% — a 34% improvement over flat, unstructured search.

The AAAK Compression Dialect

One of MemPalace's most innovative features is AAAK, a shorthand dialect designed for AI agents that achieves roughly 30x compression. A passage that would normally consume around 1,000 tokens compresses to approximately 120 tokens, enabling AI to load months of context before the first message.

AAAK works natively with any large language model — Claude, GPT, Gemini, Llama, and Mistral — without requiring specialized decoders or fine-tuning.

Why It Matters

AI assistants today lose all context when a session ends. Months of decisions, debugging sessions, and architectural discussions simply vanish. MemPalace addresses this by preserving everything locally, making it searchable and retrievable across sessions.

The system was tested on more than 22,000 real conversation memories and also scored 92.9% on ConvoMem — more than double the score of Mem0, one of the leading paid memory solutions.

Additional Features

Beyond basic memory storage, MemPalace includes a knowledge graph with temporal entity relationships, contradiction detection across facts, specialist agent support with individual diaries, and three mining modes for projects, conversations, and general classification. It exposes 19 MCP tools for integration with popular AI coding environments.

What Is Next

MemPalace v3.0.0 was released on April 5, 2026, and has already attracted attention on Hacker News and across social media. The project has an active Discord community and welcomes contributions. Its MIT license and fully local architecture make it particularly appealing for developers concerned about privacy and vendor lock-in.


Source: MemPalace on GitHub


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