Foundations · Beginner · 3-5 hours
Physical AI
AI systems that perceive, reason, and act through physical machines in the real world.
Direct answer
What is Physical AI?
AI systems that perceive, reason, and act through physical machines in the real world.
Definition and scope
AI systems that perceive, reason, and act through physical machines in the real world.
A physical AI system combines perception, a model of the task and environment, planning or policy inference, and closed-loop control.
Why it matters
Physical AI connects advances in foundation models with robotics, control, sensing, and real-world constraints.
How it works
A physical AI system combines perception, a model of the task and environment, planning or policy inference, and closed-loop control.
Beginner learning path
Start with the difference between software-only agents and embodied systems. Then learn perception, control, and robot learning.
Recommended next topics
Primary sources
Key papers
RT-1: Robotics Transformer for Real-World Control at Scale
RT-1 trains one transformer policy on a large multi-task dataset of real robot demonstrations.
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
RT-2 co-trains vision-language models on web and robot data so semantic knowledge can influence actions.
OpenVLA: An Open-Source Vision-Language-Action Model
OpenVLA is an open 7B-parameter VLA trained on the Open X-Embodiment dataset.
Gemini Robotics 1.5
Gemini Robotics 1.5 turns visual observations and instructions into motor commands while supporting multi-step physical tasks.
Cosmos 3: Omnimodal World Models for Physical AI
Cosmos 3 unifies language, image, video, audio, and action into an open world-model backbone for physical AI.
pi0: A Vision-Language-Action Flow Model for General Robot Control
pi0 is a generalist robot policy trained on broad robot data to follow language instructions across dexterous tasks.
Research ecosystem
Organizations working in this area
Organization
Google DeepMind
World models, robot learning, VLA systems, embodied reasoning
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NVIDIA
Robot foundation models, simulation, synthetic data, edge deployment, and functional safety
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Physical Intelligence
Generalist robot foundation models
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World Labs
Spatial intelligence, multimodal world models, generative 3D environments
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Figure AI
General-purpose humanoid robots and onboard VLA systems
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Frequently asked questions
What is Physical AI?
AI systems that perceive, reason, and act through physical machines in the real world.
Why does Physical AI matter for Physical AI?
Physical AI connects advances in foundation models with robotics, control, sensing, and real-world constraints.
How should a beginner learn Physical AI?
Start with the difference between software-only agents and embodied systems. Then learn perception, control, and robot learning.