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Resident Evil Star Milla Jovovich Builds AI Memory Tool With Engineer Ben Sigman

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3 hours ago
AI summarizes in 5 seconds.
  • Milla Jovovich co-created Mem-Palace, an open-source artificial intelligence (AI) memory tool that reached ~7,000 Github stars by April 7, 2026.
  • Mem-Palace scored 96.6% on LongMemEval R@5, outperforming paid rivals Mem0 and Zep at roughly 85%.
  • Ben Sigman engineered the v3.0.0 release, with MCP integration supporting 19 tools for Claude, ChatGPT, and other LLMs.

Milla Jovovich, best known for her roles in “The Fifth Element” and the “Resident Evil” franchise, designed the core architecture of the tool after months of frustration with AI file retrieval while working on personal projects. Her technical co-founder, engineer Ben Sigman, handled implementation and fine-tuning to bring the system to release.

The project dubbed Mem-Palace solves a problem that daily AI users know well: when a session ends in tools like Claude, ChatGPT, or Gemini, the conversational history disappears. Mem-Palace stores all data locally, verbatim, with no summarization and no data loss.

The system organizes memory using a structure borrowed from ancient Greek orators, who memorized long speeches by placing information inside imagined physical spaces. Mem-Palace applies that same logic digitally, sorting data into Wings, Rooms, Halls, and Drawers.

The tool runs entirely on a user’s machine using Python 3.9 or later. It requires no internet connection, no API keys, and no cloud service after installation. It works with any text-based large language model, including Claude, GPT, Gemini, Llama, and Mistral.

Performance benchmarks from version 3.0.0, released around April 6, 2026, place Mem-Palace at 96.6 percent on LongMemEval R@5 without an API call, and at 100 percent when using a lightweight Haiku rerank. Paid competitors Mem0 and Zep score around 85 percent on the same benchmark.

However, there is an X Community Note tied to Ben Sigman’s X post about Jovovich’s tool that states:

“The claimed 100% LongMemEval score uses targeted fixes for the 3 failing questions and LLM reranking (held-out score: 98.4%). The 100% LoCoMo score uses top-k=50 exceeding session count with reranking (honest top-10 no rerank: 88.9%).”

The system’s palace structure alone improves retrieval by 34 percent over flat storage. A four-layer memory stack loads only relevant context on startup, keeping token usage to roughly 170 tokens for wake-up.

Mem-Palace also includes AAAK Compression, a lossless dialect that compresses data at 30 times the original size while remaining readable by any text-based LLM. A Temporal Knowledge Graph built on SQLite and ChromaDB tracks entity relationships with validity windows, meaning facts can expire or be invalidated over time.

For developers building AI agents, Jovovich’s Mem-Palace tool ships with Model Context Protocol integration across 19 tools, including auto-save functionality inside Claude Code.

Jovovich described the idea’s origin in Instagram and Facebook videos posted in April 2026. She said she had spent months organizing files carefully only to find AI could not reliably retrieve them. Reading about how ancient Greeks memorized speeches led her to the concept of a virtual memory palace.

The Github repository began gaining traction on Hacker News, Reddit’s r/ContextEngineering, Linkedin, and X over the last 48 hours. Responses across those platforms centered on surprise that a working Hollywood actress had shipped a functional open-source developer tool.

The project is MIT-licensed and available via pip install mem-palace. Jovovich is listed as the repository owner under the Github username milla-jovovich.

Separately, in December 2025, Jovovich participated in a viral Instagram reel series by director Sergio Cilli titled “Will AI Replace Us?!” The videos showed her auditioning head-to-head against an AI-generated actor for a role in an action thriller, drawing tens of thousands of views across platforms.

Mem-Palace remains under active development as of April 7, 2026, with recent updates adding narrative palace walkthroughs and expanded benchmark documentation.

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