From the course: Building Secure and Trustworthy LLMs Using NVIDIA Guardrails
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Next steps in building LLM applications
From the course: Building Secure and Trustworthy LLMs Using NVIDIA Guardrails
Next steps in building LLM applications
- [Instructor] As we wrap up our journey through the world of Nvidia guardrails for LLMs, I want to thank you for joining me on this insightful exploration. We've delved into the principles and techniques that ensure ethical and secure deployment of large language models, and I hope you feel empowered to apply some of these tools in your own projects, but the learning of course, doesn't stop here. To further enhance your understanding and skills, I highly recommend exploring additional resources like the Nvidia Guardrails documentation, which is a great resource for deepening your knowledge and staying up to date with the latest features and capabilities. For a broader perspective on responsible AI practices, I also encourage checking out the course Leading Responsible AI in Organizations by Elizabeth M. Adams on LinkedIn Learning. This course provides a comprehensive understanding of how to manage AI ethically within an organization. Additionally, I invite you to visit my website…
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