From the course: Building Secure and Trustworthy LLMs Using NVIDIA Guardrails
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Future of guardrails and LLM safety
From the course: Building Secure and Trustworthy LLMs Using NVIDIA Guardrails
Future of guardrails and LLM safety
- [Instructor] Let's take a look at the future of guardrails and LLM safety. Our goal is to provide a forward-looking perspective on how these technologies will evolve and shape the future of AI safety and ethics. By understanding this, you'll be better prepared to contribute to the ongoing dialogue and development in AI ethics, ensuring a responsible and innovative future for AI technologies. Building controllable and safe LLM powered applications is challenging. Programming rails, while effective should not be used alone, especially for safety-specific tasks. They should always compliment embedded rails. Moving forward, we also envision more powerful models to support current methods, reducing costs and latency. By combining these approaches, we can create more robust and efficient LLM safety mechanisms. Guardrails also provide significant development in terms of benefits to developers and researchers. They supplement embedded rails and enhance retrieval-based LLM applications. For…
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