From the course: Building Secure and Trustworthy LLMs Using NVIDIA Guardrails
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Securing LLMs against sensitive topics
From the course: Building Secure and Trustworthy LLMs Using NVIDIA Guardrails
Securing LLMs against sensitive topics
- [Instructor] Let's take a look at advanced strategies to ensure that large language models do not engage in sensitive or inappropriate discussions. Our goal is to maintain high ethical standards, which is a critical aspect of LLM management. We will be equipping ourselves with the skills to navigate this complex social and ethical landscape in AI deployment by learning about this. So let's delve right in. So let's start by discussing why securing LLMs is so important. Ensuring that AI systems operate within ethical boundaries is crucial. We want to foster user trust and ensure that the AI's societal impact is positive. Ethical AI can prevent misuse and promote fairness and inclusivity. One of our primary goals is to prevent discussions around sensitive or inappropriate topics. This protection is vital to avoid causing harm or distress to our users. Finally, adhering guidelines, regulations, and compliance is not just about following laws, it's also about setting a standard for…
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