Perception
Segment Anything (SAM)
Segment Anything (SAM) is a promptable image segmentation foundation model released by Meta AI in 2023, trained on the SA-1B dataset of over one billion masks, that produces object masks from point, box, or mask prompts and generalizes zero-shot to unseen domains. SAM 2 (2024) extended the model to video with streaming memory for real-time mask tracking. Robotics pipelines widely use SAM to segment target objects for grasping, tracking, and data annotation without task-specific training.
Why it matters for physical AI
Off-the-shelf, promptable segmentation removed a whole category of perception engineering from robot pipelines, letting manipulation systems isolate arbitrary objects with a click or a language-grounded detector.
Build physical AI
Put these concepts to work on real hardware
Axol is a dual-arm robot built for physical AI — teleoperate it, collect demonstrations, and deploy learned policies out of the box.