The accessibility of third-party large language models (LLMs) has lowered the barrier for companies to develop generative AI-powered applications. However, concerns about the consequences of AI risk have given companies caution.
In order for companies to protect against AI risk, they first need to understand the vulnerabilities of generative models. They can then take steps to identify and mitigate risk, resulting in safe and impactful applications.
This is best accomplished through the comprehensive testing, or red teaming, of models for security, ethical, and operational vulnerabilities.In this white paper, we cover:
- Top 10 generative AI risks
- Best practices for managing generative AI risk
- How Robust Intelligence can help