Build Guardrails for Your AI with Open Source
Master the art of building AI guardrails with open-source tools. Learn how to create safe, ethical, and compliant AI systems by implementing robust guardrails for AI model behavior.
At a Glance
Protect your company and brand reputation, enhance user safety and trust with advanced measures, ensuring ethical and responsible interactions. Learn to build guardrails quickly and inexpensively using open source technologies.
A Look at the Project Ahead
Artificial Intelligence holds tremendous promise for almost any business or a brand. At the same time it can also be a existential threat to the reputation of any organization that throws caution to the wind and unleashes unrestrained AI. The whole purpose of Generative AI is to generate a conversation between your company, your organization, your brand and your customers, partners, users etc. This conversation must be conducted in a respectful, inclusive, and polite way and it must be on topic that is acceptable to both you and your audience. “Guardrails” is the term used to describe technology to keep AI conversations on topic and with the proper tone to protect your organization’s reputation. In our opinion, no AI should be deployed in production without proper guardrails in place.
In this project you will learn what “guardrails” are in the context in Artificial Intelligence (AI), and how you can implement them on your own AI using open-source tools. By the end of this guided project, you will know:
- Why guardrails are important for AI.
- How to implement guardrails on your own AI.
- The current limitations of open-source guardrails and how to overcome them.
What You’ll Need
However, don’t worry if you don’t have much experience with the above. This project will explain each step along the way, and you may learn as-you-need along the way.
IBM Skills Network Labs environment also comes with many technical requisites pre-installed to save the hassle of setting everything up, so we won’t be dealing with any environment issues.
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