Event
Physical Intelligence publishes Multi-Scale Embodied Memory for long-horizon VLA tasks
Key points
- Physical Intelligence published Multi-Scale Embodied Memory as a way to give VLA policies both short-term and long-term task memory.
- The official page frames MEM as enabling complex tasks lasting more than ten minutes, with high-level subtasks selected at lower frequency and actions selected at high frequency.
- It matters because memory is a core missing capability for robots expected to complete long household and workplace workflows.
Company context
Physical Intelligence develops foundation models and learning algorithms for robots and other physically actuated systems. Its π-series models are designed to generalize across robot embodiments, tasks, and environments using robot data, language instructions, vision-language-action training, reinforcement learning, and multimodal context conditioning.
Context
- Company
- Physical Intelligence
- Segment
- Foundation Models
- Event type
- Research Publication
- Geography
- San Francisco, California · United States