Stress testing enterprise AI models to find failure modes.
- Deploying AI in enterprise environments requires ensuring their robustness and safety.
This is especially crucial when models are exposed to inputs that deviate from their training distribution.
As these models become increasingly sophisticated, the potential risks under out-of-distribution conditions amplify, especially in high-stakes environments.
This underscores the critical need for systematic stress testing.
We provide a repository of stress testing, jailbreaking, and red teaming methods—a knowledge base to understand and improve the performance and safety of AI models.