What is
Physical AI?
Physical AI is intelligence that perceives, reasons, and acts in the real world. Instead of learning from text and images online, it learns from the physical signals all around us — sensor data, video, and language — to understand how machines, environments, and people actually behave.
WHY IT MATTERS
The biggest problems are physical, not digital
The biggest problems are physical, not digital
Most AI understands the digital world of text and images. But the hardest problems — safety, reliability, and efficiency across factories, infrastructure, and cities — live in the physical world. Billions of sensors already stream data about it, and most of that data goes unused.
HOW IT'S DIFFERENT
How Physical AI is different
How Physical AI is different
Build and deploy Physical AI agents that turn real-world data into actionable insights. Maximum output from every machine, vehicle, and system — all from one platform.
Digital AI
Learns from text and images. Each modality is handled on its own.
Physical AI
Learns from many sensor types plus video and language — fusing them in real time to reveal patterns no single signal shows.
Physical AI is bigger than robots
Physical AI is bigger than robots
Physical AI is often reduced to robots, autonomous vehicles, and humanoids. Those are one expression of it — but it's broader: any system that senses and reasons about the physical world in real time. With Newton, that intelligence comes from the sensors you already have — no robot required.
BenchmarkS
From understanding to action
From understanding to action
Physical AI powers Physical Agents — real-time applications that interpret the physical world and act on it.
Intelligence moves off the screen and into machines, infrastructure, and environments themselves: monitoring equipment, catching anomalies early, verifying tasks, and improving safety.
Go deeper
See the world model behind Physical AI
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Put Physical AI to work
Talk with one of our Physical AI experts and learn how to deploy Newton Agents across a wide range of use cases — mapped to the outcomes you care about.
