Physics-Native State Space Models for Real-Time Physical World Intelligence

Manifold's core architecture is built on a State Space Model world model with linear O(n) complexity, maintaining a unified, deterministic representation of the physical world. Unlike transformer-based approaches that scale quadratically and approximate physics through pattern matching, Manifold calculates physics continuously through the same fundamental equations that govern how the physical world works.

The platform achieves 98.9% accuracy on yield-stress fluid dynamics and 77% on complex rigid-body tasks. Both zero-shot, with no task-specific training. For comparison, NVIDIA's approach using advanced training achieved 39% on similar rigid-body tasks.