Knowledge / Physical AI
Physical AI — Knowledge Base
Guides to physical AI: AI that perceives and acts in the physical world. What physical AI is, how edge inference works on robots, and how robots are trained in simulation. Written by Haink, which builds physical-AI software and supplies the edge and GPU hardware it runs on.
Physical AI Solutions →
Looking for the services themselves? See edge AI inference, robotics integration, and the Physical AI overview, plus robotics hardware.
Guides
- What Is Physical AI? — AI that senses and acts in the real world: the components, where it's used, and what hardware it needs.
- Edge AI for Robotics: Hardware and How On-Device Inference Works — Why inference runs on the robot, the Jetson platforms, and how models are optimized to fit.
- Sim-to-Real: How Robots Learn in Simulation — Training in simulation, the sim-to-real gap, domain randomization and the hardware it needs.
- What Are VLA Models? Vision-Language-Action Explained — How robots turn what they see plus an instruction into motion, why VLA matters in 2026, and the hardware it needs.
- NVIDIA Jetson Orin vs Thor: Which to Choose — A buyer's guide: specs, when to pick each, IGX safety variants, availability and cost.
- How Much Does a Physical AI Deployment Cost? — Cost breakdown for hardware, data and training, integration, and robotics-as-a-service.
- Humanoid Robots in Industry (2026) — Where humanoids are deployed, which companies use them, and the AI and hardware inside.
- Teleoperation and Synthetic Data for Robot Training — The two main robot-data sources, what they cost, and how teams blend them.