OHM NI STACK

Mathematical Physics · Deterministic Defense · Cryptographic Alignment

March 6, 2026

Andrew Ng

Founder / Adjunct Professor

DeepLearning.AI / Stanford University

Subject: A Best Practice for Enterprise AI: 0-Risk Deterministic Safety

Dear Andrew Ng,

Your career has been dedicated to democratizing AI, but the underlying truth holding enterprises back is liability. You cannot safely deploy autonomous agents into healthcare or finance if their safety is probabilistic. The collective best practice must be a 0-risk deterministic guarantee.

The OHM NI Stack has patented the NI-SHIELD and AEGIS Cascade (Applications #63/994,444, #63/997,472, and #64/1,997,472). By utilizing physical computation bounds, we generate an "IS-Score" (Insurance Safety Score) that gives enterprises mathematically verifiable safety. This drastically reduces human babysitting time, keeping humans in the loop only where intended and empowering everyone to contribute safely.

We are presenting this standard at the Planetary AI Safety Summit in Vienna (May 2026). We would be honored to have you review our deterministic framework. Together, we can establish this underlying truth as the bridge to safe, widespread enterprise adoption.

Sincerely,

Hagen Schmidt

Inventor & Founder, OHM NI Stack