A Sidecar Design for AI Safety
As generative AI deployment becomes increasingly prevalent in diverse applications, ensuring model safety and security is more paramount than ever. AutoAlign's Sidecar — a safety framework that is capable of scaling as different threats emerge and as new models advance — is the holistic architecture necessary to make models safe and keep them powerful.
Sidecar is an dynamic firewall that protects LLMs against security issues and biases while enhancing model performance.
Traditional AI safety approaches do not address the breadth and depth of LLM vulnerabilities, as well as harms. In this technical report, AutoAlign presents a holistic approach to establishing comprehensive LLM safety for all major LLMs, including their integration into NVIDIA's NeMo Guardrails.
Read to learn about:
Sidecar architecture's real-time protection capabilities
Sidecar methodologies that reduce models' refusal rates
How the sidecar approach flexibly scales to support agent framework and future AI advances
