Modern AI isn’t just compute.

It’s movement.

Data needs to reach the right place at the right time without lag, jitter, or central chokepoints.

On an m-regular mesh, AI inference becomes:

– faster (packets take shorter average paths)

– cheaper (no overloaded super-nodes)

– more resilient (network self-healing)

– real-time (ideal for video + live signals)

AI Signals as First-Class Citizens

Our architecture treats AI tasks like living signals — they move across the mesh, replicate, optimize, and choose the fastest path automatically.

Inference doesn’t wait for a central brain.

It happens everywhere at once.