Physical AI, taught and built.
Machines that see, think and act are going to be everywhere, on this planet and past it. That part is already being settled by economics. The open question is how fast, and its answer is physical: energy, compute, and the loop between them. This is where that gets taught, measured, and built in the open.
Every physical machine runs one loop.
Perceive, simulate, act, then again, faster than thought. It's the single idea beneath every course, lab, and system here.
It sees.
Cameras, LiDAR, and touch collapse into one picture of the world: depth, objects, and the free space to move through, built on the device in milliseconds.
It predicts.
Before it moves, the machine runs the future in a digital twin, many routes and many rollouts, and keeps the plan that survives contact with reality.
It acts.
Before it commits, the action is checked against the one energy the body descends, a proof it won't diverge, then becomes motion: torque, balance, grip. The world it's moving through changes.
It never stops.
Perceive, simulate, act, then perceive again, many times a second. That closed loop (on the device, certifying each action before it commits) is agency: a body that holds its own boundary, on its own power. Intelligence is the other axis.
Seven doors in.
Learn it, build it, play it, discover it, map it, launch it, or just watch the show. Start wherever you are.
Education
Instructors, courses, and live labs.
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The Lab
Every runnable bench in one place: write code, drive robots, run the physics.
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Play
The Arena and the games: code your way onto the leaderboard.
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Research
Researchers, projects, and reproducible experiments.
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Intelligence
A living, geographic knowledge map of Physical AI.
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Entrepreneurship
Start a company, get startup-ready, pitch, and get funded.
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Drink · Think · Burn
A scrolling comedy special about thermodynamics: what a chatbot question really costs, and the physics trying to make the bill disappear.
Open →Looking for something specific? Search all 190 instruments, courses, papers & topics ⌕ →
The work, newest first.
45 papers, 25 courses and 32 research topics, newest first. Drag the row, or use the arrows.
Joules per Punch
Where the energy of a humanoid strike goes, why every segmented spine tested loses to one waist joint, and what a spine is actually for.
The Hardware Lottery: Energy-Based Models and Post-von-Neumann Architecture
In 2020 Sara Hooker described a mechanism she called the hardware lottery: a research idea advances partly because it suits the available hardware, an
The Energy Lab
Derive the memory tax yourself, then price the transition
RELAX/1
Ten operations, an MLIR and NIR-style exchange form, and a lowering matrix across substrates.
The Unattended Plant: Energy That Ships, Intelligence That Crews It
Portable nuclear is the first energy technology that moves to its load instead of tethering the load to a grid, and a plant too small to carry a round
Sim to Real: the road to physical agency
Four walls stand between a policy that works in simulation and one that works on a body. What the record measures at each, read in twenty-three langua
The Physical AI hardware lottery
A robot can hold several right answers at once by learning a landscape instead of a number. That needs an operation today's chips are the wrong shape
Physics-fidelity benchmark
Score whether a model obeys physics, not whether it looks right
OER/1 and DRIFT/1
A receipt schema for energy claims, and a benchmark protocol for learning under drift.
Energy as Evidence: What a Machine Can Prove About Itself
Software asserts. Energy is spent. A power trace is the one account of a machine's activity its own code cannot simply write, which makes energy the n
The portable core
Energy that ships to its load needs a crew that is not there. The world is building that autonomy; this review did not locate work on the layer that l
The live classroom
An AI teacher draws runnable simulations on a shared board
Physical AI and the Department of Transportation
Opportunities for automation across diverse geographies: what the work is, which constraint binds it, and how far along each class actually sits.
Measuring Energy in Physical AI: Where You Put the Meter
A robot energy figure is only meaningful once you say where the meter was and which definition of energy you used. This module builds both, on one two
Harnessing energy observability
A machine's power draw reports what it actually did, not what its software says it did. How far that report reaches is decided by the body it is measu
Forge
Describe a robot, simulate it, then teach it to walk in your browser
Can a machine prove it is itself?
A drivetrain carries a manufacturing signature you can measure. Priced in bits it buys verification, and it does not buy a cryptographic key.
The Future of Commerce Using Physical AI
Eleven hypotheses about physical AI in commerce, tested against eighteen graded deployment records, three BLS series, four frontline experiments of which three are randomised, and the physical quantities that set what sensing and manipulation cost. Each resolves to a position on the trajectory, a named binding constraint and the measured change that moves it.
The Energy-First Turn: Computing as a Function of Energy
Electricity, not transistors, is now what schedules the next model. This course teaches you to price computing in joules and to tell a well-founded en
The global energy database
Eighty-five claims, each with its verification grade
Verified Fluids: A Differentiable Computational Fluid Dynamics Stack for Physical AI, in the Browser
One open Rust stack spanning every solver paradigm, each checked against an analytic or reference oracle, differentiable end to end, and deployed self-verifying to WebAssembly.
Physical AI for Space Logistics and Transportation
Space logistics is a velocity budget you compose and a chain of maneuvers an autonomy stack flies. Compute the rocket-equation wall and pay it down wi
Two certificates: one for danger, one for waste
A safety proof checked before every action keeps a compromised policy from going anywhere unsafe. A second proof, written over energy rather than dist
Pilot
Drive an embodied policy with a real controller
One Digest: Bit-Identical Neural Computation Across Heterogeneous Compute Fabrics
Making a transformer forward pass compute the same bits in a browser tab, on Apple silicon, and on an NVIDIA GPU: the mechanisms that break it, the pins that hold it, and the measured price.
Energy First Architecture
The physics-first thesis, built in the browser: one scalar energy a body descends to act, and the same energy is the proof it will not diverge. Descen
Quantum information at the edge
What quantum information science actually offers on-device Physical AI, mostly quantum-inspired structure, run classically, held with attention to the
The Diffusion Layer: Accelerating the Spread of Silicon-Design Competency for Physical AI. A Survey and Research Position
Physical AI is bottlenecked less by fabs than by the people who can design for them. This report treats that competency as an innovation to diffuse, and the training as the technology that sets its speed.
All publications →All coursesAll researchSearch everything ⌕
The software behind the lessons.
Physics simulation, CAD, and compiled firmware: the engines each course runs on. Open one to try it.
Robot control
Write a control loop and a real differential-drive robot drives to the goal on DeepMind's MuJoCo physics.
MuJoCo · PythonTry it live →Visual programming
Snap blocks together. They become real Python that drives the same robot.
Blockly → PythonTry it live →
Parametric CAD
Model a part in code on the actual OpenCascade kernel engineers use, and watch the solid render.
build123d · OpenCascadeTry it live →
Embedded Rust
Write no_std firmware; it compiles in the cloud to WebAssembly and runs as the robot's real control loop.
Rust → WASM · edge-compiledTry it live →Device physics
Tune a mechanism's parameters and watch real physics settle it to spec.
MuJoCo · MJCFTry it live →Factory twin
Balance a virtual production line (bottlenecks, throughput, cost) as a live simulation.
Discrete-event simTry it live →Train, research, and partner with us.
The Institute for Physical AI is an autonomous division of Bailey Military Institute, a 501(c)(3) aviation-education nonprofit. Explore Bailey, its courses, and how to support the mission.