Every new robot starts from scratch
Today's approach to robot intelligence is fundamentally broken. Every new robot morphology requires months of training, thousands of GPU hours, and massive datasets. Switch the body? Start over. Change the environment? Retrain everything.
The industry is spending billions scaling parameters and stacking GPUs, but a human toddler learns to walk in months with a 20-watt brain. Something is deeply wrong with the paradigm.
Biomimetic intelligence from first principles
20n takes a radically different path. Instead of training neural networks on data, we built a brain architecture inspired by how biological brains actually work:
- Active Inference: the brain predicts sensory input and acts to minimize surprise
- Predictive Coding: hierarchical prediction and error correction, like the neocortex
- Free Energy Principle: a single mathematical framework unifying perception, learning, and action
The result is a single architecture that adapts to any robot body in seconds — not months. No pre-training, no fine-tuning, no cloud dependency.
Same brain, three bodies
One architecture. Three entirely different robot morphologies. Zero retraining between them.
- Walker2d: bipedal locomotion, stable forward gait
- Ant: quadruped navigation, adaptive limb coordination
- Humanoid: 17-DOF full body control, MaxSurv 1000 steps
All running on CPU only. No GPU required. No cloud. Just pure biomimetic computation at 20 watts.
What makes it different
The 20n brain is not a neural network in the traditional sense. It's a generative model that maintains beliefs about the world and updates them in real-time through sensory prediction errors.
- Morphology-agnostic: automatically maps to any sensor/actuator configuration
- Real-time adaptation: converges in seconds, not training epochs
- Edge-native: runs entirely on-device, no internet required
- Intrinsically motivated: explores and learns without reward shaping