Deterministic Protein Computation

Modern AI excels at pattern recognition, but science requires more than correlation. In biology, chemistry, and medicine, systems must explain causality, remain stable under repeated reasoning, and support auditability in regulated environments.

This white paper introduces Deterministic Intelligence — a new class of computation that reasons over physical constraints rather than probabilities. By resolving constraints step by step, deterministic systems enable repeatable, mechanistic computation where probabilistic AI breaks down.

Because biological systems evolve through physical constraint resolution, models based on statistical inference discard formation history and context, limiting their reliability and generalizability. Deterministic Intelligence addresses this gap by grounding computation in first principles.