The Charlot Lab.
The Charlot Lab works on the foundations of trustworthy embodied AI — systems that are provable, physically grounded, and cheap enough to run on the device. Two threads: Interface Engineering and Swap-2C Constrained AI.
Led by Dr. Charlot.
Two threads.
What the lab works on.
Clean seams between parts
The engineering of the interfaces between the pieces of an embodied system — hardware, software, sensors, and subsystems — so modular systems compose without bespoke glue.
Provable, grounded, cheap to run
AI grounded in physics and math rather than language: closed-form primitives, controllers traced to a Lyapunov function, and a picojoule energy receipt on every call — so behavior is provable and the power cost is known before deployment. It runs in a WebGPU browser in under 400 KB.
Live work.
The lab's research runs in the open, as working sites you can use.
Math-Ground AI
The Swap-2C runtime — physics- and math-grounded primitives, closed-form control, and energy accounting.
Visit ↗Pattern-Lang
A lawful route to AGI — recognizing patterns by naming, composing, and verifying them over a small finite lexicon, instead of learning them from billions of examples.
Visit ↗Play Dimension
A strategy game whose mechanics map to ideas from AI and neuroscience.
Visit ↗Build this with us.
The lab takes on students through internships, and works with investigators across the Institute.