GenAI and LLm Guardrails and Governance
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Generative AI guardrails are a set of rules and limitations designed to keep AI outputs safe and aligned with ethical principles. This includes filtering harmful content, preventing bias, and safeguarding against the misuse of sensitive information. LLM guardrails, a specific type of generative AI guardrail, focus on large language models (LLMs) – AI systems that generate text, translate languages, and write different kinds of creative content. LLM guardrails address unique challenges like prompt injection vulnerabilities, where malicious prompts can trick the LLM into revealing sensitive data. Here's the key difference: generative AI guardrails encompass a broader range of AI systems that produce creative text, code, or images, while LLM guardrails specifically target the quirks and vulnerabilities of large language models. Governance controls, on the other hand, are broader guidelines that set the overall direction and goals for AI development and use. They encompass guardrails but also include things like human oversight, transparent development processes, and clear accountability measures. Governance controls provide the framework, while guardrails are the specific tools used to ensure responsible AI practices within that framework. |
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