Blog
Research Insights
Technical deep-dives, research updates, and perspectives on the future of Physical AI and embodied intelligence.
Why Simulation-to-Real Transfer Is the Key to Scalable Robotics
Training robots in the real world is slow, expensive, and dangerous. We explore how high-fidelity simulation environments can dramatically accelerate the path from research to deployment.
Read more →Foundation Models for Physical Tasks: Beyond Language and Vision
Language models transformed digital workflows. We believe a similar revolution is coming for the physical world — here's how foundation models can learn to perceive, reason, and act.
Read more →Learning from Demonstration: Teaching Robots by Showing, Not Programming
Our approach to imitation learning enables robots to acquire new skills from human demonstrations in minutes, not months of engineering effort.
Read more →The Case for Hardware-Agnostic Physical AI
Why we believe the intelligence layer should be decoupled from specific robot hardware — and how this approach unlocks automation at scale across diverse environments.
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