Optimistic Verifiable Training by Controlling Hardware Nondeterminism
Optimistic Verifiable Training by Controlling Hardware Nondeterminism
The increasing compute demands of AI systems has led to the emergence of services that train models on behalf of clients lacking necessary resources. However, ensuring correctness of training and guarding against potential training-time attacks, such as data poisoning, poses challenges. Existing works on verifiable training largely fall into two …