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UX for Enterprise ChatGPT Solutions

You're reading from   UX for Enterprise ChatGPT Solutions A practical guide to designing enterprise-grade LLMs

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835461198
Length 446 pages
Edition 1st Edition
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Author (1):
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Richard H. Miller Richard H. Miller
Author Profile Icon Richard H. Miller
Richard H. Miller
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Table of Contents (18) Chapters Close

Preface 1. Part 1:UX Foundation for Enterprise ChatGPT FREE CHAPTER
2. Chapter 1: Recognizing the Power of Design in ChatGPT 3. Chapter 2: Conducting Effective User Research 4. Chapter 3: Identifying Optimal Use Cases for ChatGPT 5. Chapter 4: Scoring Stories 6. Chapter 5: Defining the Desired Experience 7. Part 2: Designing
8. Chapter 6: Gathering Data – Content is King 9. Chapter 7: Prompt Engineering 10. Chapter 8: Fine-Tuning 11. Part 3: Care and Feeding
12. Chapter 9: Guidelines and Heuristics 13. Chapter 10: Monitoring and Evaluation 14. Chapter 11: Process 15. Chapter 12: Conclusion 16. Index 17. Other Books You May Enjoy

Evaluate using RAGAs

This book is about design, so product people are not expected to implement the RAGAs. RAGAs is a framework for evaluating the RAG pipeline. Any approach that takes test data, is actually used, and can measure quality reliably is fine with me. RAGAs is popular with the AI community, so it is worth covering. Call on product experts to evaluate results to validate findings. The goal is to understand the metrics and make decisions to deliver model improvements.

The RAGAs process

All good stories start at the beginning. An LLM product needs to be evaluated. Don’t wait for customers to complain; it comes too late, and customers disappear quickly if they are frustrated with quality. This is similar to phone support; when a customer has a horrible interaction, they tend to tell 20 people how bad it was, and this lack of goodwill hurts the company’s reputation. If backend systems or recommenders miss their mark, it will leave a foul taste in customers...

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