PHYSICAL AI, TRAINED AGAINST REALITY
REALITY IS THE ONLY BENCHMARK.
Embodied Physics measures the physics that simulators get wrong and turns it into data you can design physical AI against.
We correct the simulator with measured data and make the correction differentiable, so physical AI trains against reality at software speed and software cost.
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AI will produce more hardware designs than anyone can build.
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The designs worth finding sit outside the region where any simulator was ever checked against reality.
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Out there, an optimizer finds the simulator's errors before it finds physics.
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Ground truth cannot be simulated, scraped, or synthesized. It has to be measured.
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The experiment worth running is the one with the most information per dollar. That is a computable quantity.
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Whoever owns the measurements owns the reward signal for physical AI.
A capital allocator whose only asset class is physical evidence.
PHYSICAL AI CAN ONLY
GET AS GOOD AS
THE WORLD WE
CAN SIMULATE.
Today that world is too crude. Embodied Physics builds a better one.
- 01
Every regime a simulator gets wrong is a regime physical AI cannot train in. We measure it, and the correction becomes part of the simulator. The world it trains in gets larger with every campaign.
- 02
The correction is differentiable. It is not a check you run at the end; it is part of the loss. Physical AI trained this way meets reality already knowing where the simulator was wrong.
If your simulator is wrong exactly where your designs get interesting,
you already need us.
hello@embodiedphysics.com