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The AI Value Playbook

You're reading from   The AI Value Playbook How to make AI work in the real world

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835461754
Length 440 pages
Edition 1st Edition
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Author (1):
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Lisa Weaver-Lambert Lisa Weaver-Lambert
Author Profile Icon Lisa Weaver-Lambert
Lisa Weaver-Lambert
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Toc

Table of Contents (43) Chapters Close

1. In Praise of The AI Value Playbook FREE CHAPTER 2. Chapter 1: Introduction
3. Chapter 2: Overview of AI Concepts and Technology Stack
4. Chapter 3: Sam Liang
5. Chapter 4: Amr Awadallah
6. Chapter 5: Philipp Heltewig
7. Chapter 6: Miao Song
8. Chapter 7: Ruben Ortega
9. Chapter 8: Joshua Rubin
10. Chapter 9: Nadine Thomson
11. Chapter 10: Sarvarth Misra
12. Chapter 11: Edward Fine
13. Chapter 12: Sanjeevan Bala
14. Chapter 13: Nathalie Gaveau
15. Chapter 14: Phil Harvey
16. Chapter 15: Elizabeth Ajayi
17. Chapter 16: Louis DiCesari
18. Chapter 17: Vickey Rodrigues
19. Chapter 18: Sean McDonald
20. Chapter 19: Julie Gray
21. Chapter 20: Peter Jackson
22. Chapter 21: Mark Beckwith
23. Chapter 22: Kshira Saagar
24. Chapter 23: Joe Romata
25. Chapter 24: Tomasz Ullman
26. Chapter 25: Oz Krakowski
27. Case Study
28. Chapter 26: LLMs and RAG Enable Hyper-Personalized Education for Healthcare Technicians 29. Case Study
30. Chapter 27: AI Personalization Increases Engagement in Nascent Tech Communities 31. Case Study
32. Chapter 28: AI-Powered Virtual Agent Augments Service Efficiency 33. Case Study
34. Chapter 29: Generative AI Creates a Paradigm Shift in Innovation Processes 35. Case Study
36. Chapter 30: Unlocking Profit Potential – Leveraging Enterprise Data for Customer Profitability 37. Case Study
38. Chapter 31: Minimizing Customer Churn with AI 39. Case Study
40. Chapter 32: Enhancing Marketing Strategies Through the Power of LLMs 41. Case Study
42. Chapter 33: Multimodal LLMs Redefine Software Development and Customer Innovation 43. Chapter 34: Where We’ve Got To and What’s Next

AI Personalization Increases Engagement in Nascent Tech Communities

In conversation with Harsh Singhal: Data scientist and current head of AI and machine learning at Koo, a microblogging social media platform targeting non-English-speaking audiences with English-to-regional-language keyboards, local language newsfeeds, and hyper-local hashtags. Koo’s AI-based “Topics” feature on the site allows users to select their areas of interest, enhancing content relevance, user engagement, and positive feedback.

LinkedIn: harshsinghal

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