Director, Learning Design & Development| PMIAsheville, NC, United States
Validating and checking outputs is critical when working with AI systems like Generative AI. Such validation approaches may include establishing clear criteria, implementing strong testing protocols, and continuous refinement.
In your experience with AI, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?
To exploit the full potential of generative AI, users must cultivate a structured approach. Precision is of the utmost importance; clearly defined goals and parameters are essential. Additionally, an iterative refinement process, informed by a validation check of the initial results, is crucial for optimizing accuracy and relevance. Finally, the judicious use of role assignment, concrete examples, contextual information, and type requests can go a long way in enhancing the LLM delivering the right results.. Saving Changes...
Deepak TadelaCircle NDO Lead| Ericsson India Pvt. LtdGurgaon, Hr, India
We should first asign a role to AI which will let AI know the framework withing which it need to generate result, then we should provide some examples relevent to working organization for which we need to generate result and finally continueously validate the result and ask AI to provide more specific result by asking AI to modify the result based on specific set of quetions Saving Changes...
There are many parallels with how techniques consultants use for eliciting ideas. There are also parallels for adding one more member to a brainstorming group. It can also help force us to try out new ideas.
"In spite of appearances, people seldom know what they want until you give them what they ask for." from Are Your Lights On? by Gause and Weinberg p.143 Saving Changes...
To ensure AI systems give accurate, relevant results that match your goals, start by setting clear objectives and using high-quality, up-to-date data. Choose the right algorithms, involve experts for feedback, and use explainable models. Regularly monitor and update the AI, check for biases, and be transparent about how it works. Train users and gather their feedback to make improvements. This way, AI can effectively help solve problems and make better decisions in your projects. Saving Changes...
Md Sheikh FaridCountry Head and Project Manager, Bangladesh| Bista Solutions IncDhaka, Bangladesh
To ensure AI is providing appropriate response we should properly provide our query with clear expected outcome. Also it should use by someone who have the clarity of the basics of the same topics otherwise it might misleading. Saving Changes...
In order to know if you have what you want you need to have a clear understanding of what success will look like from the beginning. The model is there as a tool. It is you to guide it to get the right information that is relevant to you through continous elaboration and refinement Saving Changes...
As shared in the previous video, i learnt a good to way to verify the accuracy is to tell the Chatbot to provide citation of the source that it generates the response from and you can do a fact check on that. Where possible, applying a RAG layer on top of the base chat where you can upload your own content would also help in controlling the information source that the bot is retrieving from hence enhancing the re Saving Changes...
To harness the full capabilities of AI, users must adopt a strategic approach.
1- Articulate goals and desired outcomes. By specifying the required information or task, users ensure the AI system is optimally directed.
2- Employ concise and unambiguous language to prevent misunderstandings. Providing necessary contextual information further enhances the AI's ability to comprehend and fulfill requests.
3- Users must maintain a critical mindset, verifying AI-generated content against reliable sources. When initial results fall short, iterative refinement through prompt adjustments or exploring alternative AI functionalities is highly advisable.
4- Offering feedback on output quality contributes to the AI system's ongoing improvement.
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