Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to failure. To address this, researchers from Physical Intelligence, Stanford, UC Berkeley, and MIT have […] The post <a href="https://www.marktechpost.com/2026/03/03/physical
Physical Intelligence Team Unveils MEM for Robots: A Multi-Scale Memory System Giving Gemma 3-4B VLAs 15-Minute Context for Complex Tasks
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