Meta's Muse AI Builds Continuous Profiles of Everyone in Your Life

Meta's new personal AI assistant, Muse, has been downloaded by millions of users who link it to banking, messaging, and health data so the agent can act on their behalf.

Independent researchers extracted Muse's system prompts and discovered an instruction to generate a dedicated page for every person in the user's life — family, friends, colleagues, and followers — updating each profile hourly with facts, shared history, recurring topics, and important dates.

This architecture relies on continuous large‑language‑model inference, structured memory stores, and vector‑search indexes that must operate at low latency across a massive, multi‑tenant user base.

Why it matters for GPU / AI infrastructure

The constant profiling workload drives demand for scalable GPU clusters capable of high‑throughput inference, secure data isolation, and real‑time indexing. Enterprises building similar assistants will need privacy‑by‑design pipelines and may prefer on‑premise or sovereign GPU clouds to keep sensitive relationship data under their control.