UX for Enterprise ChatGPT Solutions. A practical guide to designing enterprise-grade LLMs - Helion
Tytuł oryginału: UX for Enterprise ChatGPT Solutions. A practical guide to designing enterprise-grade LLMs
ISBN: 9781835463802
stron: 446, Format: ebook
Data wydania: 2024-09-06
Księgarnia: Helion
Cena książki: 98,10 zł (poprzednio: 109,00 zł)
Oszczędzasz: 10% (-10,90 zł)
Many enterprises grapple with new technology, often hopping on the bandwagon only to abandon it when challenges emerge. This book is your guide to seamlessly integrating ChatGPT into enterprise solutions with a UX-centered approach.
UX for Enterprise ChatGPT Solutions empowers you to master effective use case design and adapt UX guidelines through an engaging learning experience. Discover how to prepare your content for success by tailoring interactions to match your audience’s voice, style, and tone using prompt-engineering and fine-tuning. For UX professionals, this book is the key to anchoring your expertise in this evolving field. Writers, researchers, product managers, and linguists will learn to make insightful design decisions. You’ll explore use cases like ChatGPT-powered chat and recommendation engines, while uncovering the AI magic behind the scenes. The book introduces a care and feeding model, enabling you to leverage feedback and monitoring to iterate and refine any Large Language Model solution. Packed with hundreds of tips and tricks, this guide will help you build a continuous improvement cycle suited for AI solutions.
By the end, you’ll know how to craft powerful, accurate, responsive, and brand-consistent generative AI experiences, revolutionizing your organization’s use of ChatGPT.
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Spis treści
UX for Enterprise ChatGPT Solutions. A practical guide to designing enterprise-grade LLMs eBook -- spis treści
- 1. Recognizing the Power of Design in ChatGPT
- 2. Conducting Effective User Research
- 3. Identifying Optimal Use Cases for ChatGPT
- 4. Scoring Stories
- 5. Defining the Desired Experience
- 6. Gathering Data – Content is King
- 7. Prompt Engineering
- 8. Fine-Tuning
- 9. Guidelines and Heuristics
- 10. Monitoring and Evaluation
- 11. Process
- 12. Conclusion