Then & Now
A visual history of AI inference. From non-deterministic experimentation to cryptographically verifiable systems.
Then (Non-Deterministic)
- Opaque model behavior
- Unreproducible outputs
- No audit trails
- "Trust me" security posture
Now (Deterministic)
- Verifiable execution receipts
- Bit-perfect reproducibility
- Token-level audit trails
- Cryptographic proof chains
The Shift
Traditional AI inference treats models as black boxes. Inputs go in, outputs come out, but the internal state remains opaque. This approach works for experimental systems but fails in regulated environments.
The Requirement
Government-facing and enterprise deployments require reproducibility. Not just similar results—exact, bit-perfect replayability. This demands determinism at the runtime level, not just at the model level.
The Evidence
Deterministic inferen ce produces verifiable execution receipts. Each inference event leaves a cryptographic trail that binds inputs, routing decisions, and outputs into a single, tamper-evident artifact.