Empowering the Public Sector with Generative AI: From Strategy and Design to Real-World Applications
Pulapaka, Sanjeev, Godavarthi, Srinath, Ding, Sherry
- 出版商: Apress
- 出版日期: 2024-07-28
- 售價: $1,860
- 貴賓價: 9.5 折 $1,767
- 語言: 英文
- 頁數: 309
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798868804724
- ISBN-13: 9798868804724
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相關主題
商品描述
This is your guide book to Generative AI (GenAI) and its application in addressing real-world challenges within the public sector. The book addresses a range of topics from GenAI concepts and strategy to public sector use cases, architecture patterns, and implementation best practices. With a general background in technology and the public sector, you will be able to understand the concepts in this book.
The book will help you develop a deeper understanding of GenAI and learn how GenAI differs from traditional AI. You will explore best practices such as prompt engineering, and fine-tuning, and architectural patterns such as Retrieval Augmented Generation (RAG). And you will discover specific nuances, considerations, and strategies for implementation in a public sector organization.
You will understand how to apply these concepts in a public sector setting and address industry-specific challenges and problems by studying a variety of use cases included in the book in the areas of content generation, chatbots, summarization, and program management.
What You Will Learn
- GenAI concepts and how GenAI differs from traditional AI/ML
- Prompt engineering, fine-tuning, RAG, and customizing foundation models
- Strategy, methodologies, and frameworks for the public sector
- Public sector use cases in the areas of content generation, summarization, and chatbots, plus program management, analytics, business intelligence, and reporting
- Architecture and design patterns
- Implementation, operations, and maintenance of GenAI applications
Who This Book Is For
Technology and business leaders in the public sector who are new to AI/ML and are keen on exploring and harnessing the potential of Generative AI in their respective organizations.
商品描述(中文翻譯)
這是您關於生成式人工智慧（Generative AI, GenAI）及其在公共部門解決現實挑戰應用的指南書。本書涵蓋了從GenAI概念和策略到公共部門使用案例、架構模式和實施最佳實踐等多個主題。擁有技術和公共部門的一般背景，您將能夠理解本書中的概念。
本書將幫助您深入了解GenAI，並學習GenAI與傳統人工智慧的不同之處。您將探索最佳實踐，如提示工程（prompt engineering）、微調（fine-tuning），以及架構模式，如檢索增強生成（Retrieval Augmented Generation, RAG）。此外，您還將發現公共部門組織在實施過程中的特定細微差別、考量和策略。
您將了解如何在公共部門環境中應用這些概念，並通過研究本書中包含的各種使用案例，解決行業特定的挑戰和問題，這些案例涵蓋內容生成、聊天機器人、摘要和計畫管理等領域。
您將學到的內容包括：
- GenAI概念及其與傳統人工智慧/機器學習的不同之處
- 提示工程、微調、RAG及自訂基礎模型
- 公共部門的策略、方法論和框架
- 在內容生成、摘要、聊天機器人、計畫管理、分析、商業智慧和報告等領域的公共部門使用案例
- 架構和設計模式
- GenAI應用的實施、運營和維護
本書適合對AI/ML新手的公共部門技術和商業領導者，他們渴望探索並利用生成式人工智慧在各自組織中的潛力。
作者簡介
Sanjeev Pulapaka is Principal Solutions Architect at Amazon Web Services (AWS). He leads the development of AI/ML and Generative AI solutions for the US Federal Civilian team. Sanjeev has extensive experience in leading, architecting, and implementing high-impact technology solutions that address diverse business needs in multiple sectors (including commercial, federal, and state and local governments). He has published numerous blogs and white papers on AI/ML and is an active speaker and panelist at various industry conferences, including AWS Public Sector Summit and AWS re: Invent. Sanjeev has an undergraduate degree in engineering from the Indian Institute of Technology and an MBA degree from the University of Notre Dame.
Srinath Godavarthi has over 20 years of experience serving public sector customers and he held leadership positions with global technology and consulting companies, including Amazon and Accenture. In his previous roles, Srinath led cloud strategy, architecture, and digital transformation efforts for a number of federal, state, and local agencies. Srinath specializes in AI/ML technologies and has published over a dozen white papers and blogs on various topics (including AI, ML, and Healthcare). He has been a speaker at various industry conferences, including the AWS Public Sector Summit, AWS re: Invent, and the American Public Human Services Association. He holds a master's degree in computer science from Temple University and completed a Chief Technology Officer program from the University of California, Berkeley.
Sherry Ding is an artificial intelligence and machine learning (AI/ML) technologist and evangelist with 20 years of experience in AI/ML research and applications. She currently works at Amazon Web Services as an AI/ML Specialist Solutions Architect, serving public sector customers on their AI/ML related business challenges, and guiding them to build highly reliable and scalable AI/ML applications on the cloud. Sherry holds a PhD in computer science from Korea University. She has authored more than 30 publications (including journal articles, book chapters, white papers, conference proceedings, and blogs) on different topics related to AI/ML. She is an active public speaker who has presented at various academia and industry conferences such as IEEE conferences, AWS re: Invent, and AWS Summits.
作者簡介(中文翻譯)
Sanjeev Pulapaka 是亞馬遜網路服務（AWS）的首席解決方案架構師。他負責美國聯邦民事團隊的 AI/ML 和生成式 AI 解決方案的開發。Sanjeev 在領導、架構設計和實施高影響力技術解決方案方面擁有豐富的經驗，這些解決方案能夠滿足多個領域（包括商業、聯邦及州和地方政府）的多樣化業務需求。他已發表多篇有關 AI/ML 的部落格和白皮書，並且是各種行業會議的活躍演講者和小組成員，包括 AWS 公共部門峰會和 AWS re:Invent。Sanjeev 擁有印度理工學院的工程學學士學位和聖母大學的 MBA 學位。
Srinath Godavarthi 擁有超過 20 年的公共部門客戶服務經驗，曾在包括亞馬遜和埃森哲在內的全球科技和諮詢公司擔任領導職位。在他之前的職位中，Srinath 負責多個聯邦、州和地方機構的雲端策略、架構和數位轉型工作。Srinath 專注於 AI/ML 技術，並已發表超過十篇有關各種主題（包括 AI、ML 和醫療保健）的白皮書和部落格。他曾在各種行業會議上發表演講，包括 AWS 公共部門峰會、AWS re:Invent 和美國公共人力服務協會。他擁有天普大學的計算機科學碩士學位，並完成加州大學伯克利分校的首席技術官課程。
Sherry Ding 是一位人工智慧和機器學習（AI/ML）技術專家和推廣者，擁有 20 年的 AI/ML 研究和應用經驗。她目前在亞馬遜網路服務擔任 AI/ML 專家解決方案架構師，為公共部門客戶提供有關 AI/ML 相關業務挑戰的服務，並指導他們在雲端上構建高度可靠和可擴展的 AI/ML 應用程式。Sherry 擁有韓國大學的計算機科學博士學位。她已發表超過 30 篇有關 AI/ML 的不同主題的出版物（包括期刊文章、書籍章節、白皮書、會議論文和部落格）。她是一位活躍的公共演講者，曾在各種學術和行業會議上發表演講，如 IEEE 會議、AWS re:Invent 和 AWS 峰會。
