Zero knowledge verification for frontier AI training is possible
Frontier AI governance frameworks increasingly use cumulative training compute as the primary criterion for designating high-impact models, but enforcement rests on self-reporting because no technical verification primitive for training exists. Any future international agreement on frontier AI faces the same problem at higher stakes: coordinated regulation of technologies with significant externalities has historically rested on technical verification, without which agreements are declaratory. Recent governance analyses judge zero-knowledge proofs a promising candidate but currently impractical at frontier scale [26, 4]. We argue the impracticality is paradigm-bound rather than fundamenta...
| Authors | Pierre Peigné, Ky Nguyen, Paul Wang |
|---|---|
| Primary category | cs.AI |
| Published | 3 June 2026 |
| Last updated at source | 22 August 2026 |
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