LightMem-Ego: Everyday AI Memory
zjunlp · hf · 2026-07-14
LightMem-Ego is a lightweight streaming multimodal memory system for daily life assistants. It aims to continuously record users' visual and audio streams on smartphones and wearables while answering questions about past experiences.
The system does three things:
- Continuously captures egocentric visual/audio streams and aligns them to a unified timeline.
- Organizes memory into a hierarchical structure: current memory, short-term memory, and long-term memory.
- Dynamically routes queries to the appropriate memory layer and generates answers based on multimodal evidence.
The authors state the demo can be deployed on smartphones and AI glasses, supporting object finding, conversation recall, life summarization, daily routine discovery, and personalized assistance. Code is open-sourced on GitHub: zjunlp/LightMem-Ego.
More from Embodied
- ECCV26 Oral: Flow Matching Enables Single-Stage Multi-View Point Cloud Registration — ducha_aiki · 2026-09-11
- Polish developers build iPhone app that detects nearby Meta smart glasses — Low-Honeydew6483 · 2026-09-11
- Ant's Afu health AI hits 150M users, unveils AI+hardware health alliance at Bund Summit — APPSO · 2026-09-11
- Johns Hopkins Launches Full-Stack Hands-on Robot Learning Class with SO-101 Arm Kits — _krishna_murthy · 2026-09-11
- SyncWorld: In-Context Robot World Model Simulates Unseen Views and Embodiments Zero-Shot — ChongZzZhang · 2026-09-11
- A 3D Pose Dataset for Dogs Released — ducha_aiki · 2026-09-11