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Learn to Implement Guardrails in Generative AI Applications
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In this comprehensive tutorial video, I will guide you through the process of implementing guardrails in generative AI applications using GPT-3, a powerful language model, and RAIL (Reliable AI Markup Language).
First, I will introduce you to the concept of guardrails and why they are essential when deploying AI models in real-world applications. Guardrails provide a way to ensure responsible and safe usage of AI systems by setting boundaries and mitigating potential risks, such as inappropriate or offensive outputs.
Next, I will showcase a practical example by building a simple Streamlit app that leverages GPT-3 as a language translator. You will witness the capabilities of GPT-3 in action as it seamlessly translates text from one language to another.
However, to maintain control over the model's outputs, I will demonstrate how to utilize RAIL, a reliable AI markup language. Through RAIL, we can establish guardrails to specifically address the issue of profanity in the generated responses. You will learn how to effectively implement the RAIL syntax to filter and prevent inappropriate language from being generated.
Whether you are a developer, researcher, or AI enthusiast, this tutorial equips you with the necessary knowledge to safeguard your AI models and foster responsible AI practices.
#ai #python #generativeai
First, I will introduce you to the concept of guardrails and why they are essential when deploying AI models in real-world applications. Guardrails provide a way to ensure responsible and safe usage of AI systems by setting boundaries and mitigating potential risks, such as inappropriate or offensive outputs.
Next, I will showcase a practical example by building a simple Streamlit app that leverages GPT-3 as a language translator. You will witness the capabilities of GPT-3 in action as it seamlessly translates text from one language to another.
However, to maintain control over the model's outputs, I will demonstrate how to utilize RAIL, a reliable AI markup language. Through RAIL, we can establish guardrails to specifically address the issue of profanity in the generated responses. You will learn how to effectively implement the RAIL syntax to filter and prevent inappropriate language from being generated.
Whether you are a developer, researcher, or AI enthusiast, this tutorial equips you with the necessary knowledge to safeguard your AI models and foster responsible AI practices.
#ai #python #generativeai
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