Introduction to Generative Ai, Second Edition: Reliable, Responsible, and Real-World Applications
暫譯: 生成式人工智慧導論（第二版）：可靠、負責任及實際應用
Dhamani, Numa, Engler, Maggie
- 出版商: Manning
- 出版日期: 2026-01-20
- 售價: $2,710
- 貴賓價: 9.8 折 $2,656
- 語言: 英文
- 頁數: 480
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1633434885
- ISBN-13: 9781633434882
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相關分類:
Large language model
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相關主題
商品描述
Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book. AI tools like ChatGPT and Gemini, automated coding tools like Cursor and Copilot, and countless LLM-powered agents have become a part of daily life. They've also spawned a storm of misinformation, hype, and doomsaying that makes it tough to understand exactly what Generative AI actually is and what it can really do. This book delivers a clear, well-written survey of generative AI fundamentals along with the techniques and strategies you need to use AI safely and effectively. It guides you from your first eye-opening interaction with tools like ChatGPT to how AI tools can transform your personal and professional life safely and responsibly. AI moves fast--and so this second edition has been completely revised to reflect the latest developments in the field. In this easy-to-read introduction, you'll learn: - How large language models (LLMs) work
- How to apply AI across personal and professional work
- The social, legal, and policy landscape around generative AI
- Emerging trends like reasoning models and vibe coding About the technology Generative AI tools like ChatGPT, Gemini, and Claude can draft emails, generate marketing copy, and prototype product designs. They can also produce poetry, realistic images or videos, and even generate computer code. But how do they do all that? This accessible book reveals how generative AI works in plain, jargon-free language, so you can use it safely and effectively. About the book Introduction to Generative AI, Second Edition is a completely revised and updated guide to the capabilities, risks, and limitations of generative AI. You'll understand the latest innovations in AI, AI agents, multimodal training, reasoning models, retrieval-augmented generation (RAG), and more. Along the way, you'll explore how AI is impacting the world, with an expert-level look at AI in industry, education, and society. What's inside - How AI and foundation models work
- Applications across daily life and work
- Balancing innovation with responsibility About the reader No technical experience required. About the author Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is a researcher and engineer working on safety for generative AI systems. Table of Contents 1 Large language models: The foundation of generative AI
2 Training large language models: Learning at scale
3 Data privacy and safety: Technical and legal controls
4 AI and the creative economy: Innovation and intellectual property
5 Misuse and adversarial attacks: Challenges and responsible testing
6 Machine-augmented work: Productivity, education, and economy
7 Prompt engineering: Strategies for guiding and evaluating LLMs
8 AI agents: The rise of autonomous AI systems
9 Human connections: The social role of chatbots
10 The future of responsible AI: Risks, practices, and policy
11 Frontiers of AI: Open questions and global trends
- How to apply AI across personal and professional work
- The social, legal, and policy landscape around generative AI
- Emerging trends like reasoning models and vibe coding About the technology Generative AI tools like ChatGPT, Gemini, and Claude can draft emails, generate marketing copy, and prototype product designs. They can also produce poetry, realistic images or videos, and even generate computer code. But how do they do all that? This accessible book reveals how generative AI works in plain, jargon-free language, so you can use it safely and effectively. About the book Introduction to Generative AI, Second Edition is a completely revised and updated guide to the capabilities, risks, and limitations of generative AI. You'll understand the latest innovations in AI, AI agents, multimodal training, reasoning models, retrieval-augmented generation (RAG), and more. Along the way, you'll explore how AI is impacting the world, with an expert-level look at AI in industry, education, and society. What's inside - How AI and foundation models work
- Applications across daily life and work
- Balancing innovation with responsibility About the reader No technical experience required. About the author Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is a researcher and engineer working on safety for generative AI systems. Table of Contents 1 Large language models: The foundation of generative AI
2 Training large language models: Learning at scale
3 Data privacy and safety: Technical and legal controls
4 AI and the creative economy: Innovation and intellectual property
5 Misuse and adversarial attacks: Challenges and responsible testing
6 Machine-augmented work: Productivity, education, and economy
7 Prompt engineering: Strategies for guiding and evaluating LLMs
8 AI agents: The rise of autonomous AI systems
9 Human connections: The social role of chatbots
10 The future of responsible AI: Risks, practices, and policy
11 Frontiers of AI: Open questions and global trends
商品描述(中文翻譯)
購買印刷書籍時，您將獲得Manning提供的免費電子書（PDF或ePub），以及在線liveBook格式的訪問權限（及其AI助手，能以任何語言回答您的問題）。
像ChatGPT和Gemini這樣的AI工具，自動化編碼工具如Cursor和Copilot，以及無數基於大型語言模型（LLM）的代理，已成為日常生活的一部分。它們也引發了一場關於錯誤信息、炒作和悲觀預測的風暴，使人們難以準確理解生成式AI究竟是什麼以及它能真正做什麼。本書提供了一個清晰、寫得很好的生成式AI基礎知識概述，以及您需要安全有效使用AI的技術和策略。本書將引導您從第一次與像ChatGPT這樣的工具互動開始，了解AI工具如何安全且負責任地改變您的個人和專業生活。AI發展迅速，因此本第二版已完全修訂，以反映該領域的最新進展。在這本易讀的介紹中，您將學到： - 大型語言模型（LLMs）如何運作- 如何在個人和專業工作中應用AI
- 生成式AI周圍的社會、法律和政策環境
- 新興趨勢，如推理模型和情感編碼 關於技術 像ChatGPT、Gemini和Claude這樣的生成式AI工具可以撰寫電子郵件、生成市場文案和原型產品設計。它們還可以創作詩歌、生成逼真的圖像或視頻，甚至生成計算機代碼。但它們是如何做到這些的呢？這本易於理解的書籍以簡單、無行話的語言揭示了生成式AI的運作方式，讓您能夠安全有效地使用它。 關於本書 生成式AI導論，第二版 是一本完全修訂和更新的指南，介紹生成式AI的能力、風險和限制。您將了解AI、AI代理、多模態訓練、推理模型、檢索增強生成（RAG）等最新創新。在此過程中，您將探索AI如何影響世界，並深入了解AI在行業、教育和社會中的應用。 內容概覽 - AI和基礎模型如何運作
- 在日常生活和工作中的應用
- 在創新與責任之間取得平衡關於讀者 不需要技術經驗。 關於作者 Numa Dhamani 是一位自然語言處理專家，專注於技術與社會的交集。Maggie Engler 是一位研究員和工程師，專注於生成式AI系統的安全性。 目錄 1 大型語言模型：生成式AI的基礎
2 訓練大型語言模型：大規模學習
3 數據隱私與安全：技術和法律控制
4 AI與創意經濟：創新與知識產權
5 誤用與對抗性攻擊：挑戰與負責任的測試
6 機器增強工作：生產力、教育與經濟
7 提示工程：指導和評估LLMs的策略
8 AI代理：自主AI系統的崛起
9 人際連結：聊天機器人的社會角色
10 負責任AI的未來：風險、實踐與政策
11 AI的前沿：未解問題與全球趨勢
作者簡介
Numa Dhamani is a natural language processing expert with domain expertise in information warfare, security, and privacy. She has developed machine learning systems for Fortune 500 companies and social media platforms, as well as for startups and nonprofits. Numa has advised companies and organizations, served as the Principal Investigator on the United States Department of Defense's research programs, and contributed to multiple international peer-reviewed journals. Maggie Engler is an engineer and researcher currently working on safety for large language models. She focuses on applying data science and machine learning to abuses in the online ecosystem, and is a domain expert in cybersecurity and trust and safety. Maggie is also an adjunct instructor at the University of Texas at Austin School of Information.
作者簡介(中文翻譯)
Numa Dhamani 是一位自然語言處理專家，擁有資訊戰、資訊安全和隱私領域的專業知識。她為《財富》500 強公司和社交媒體平台開發了機器學習系統，並且也為初創公司和非營利組織提供服務。Numa 曾為公司和組織提供建議，擔任美國國防部研究計畫的首席研究員，並為多本國際同行評審期刊貢獻文章。
Maggie Engler 是一位工程師和研究人員，目前專注於大型語言模型的安全性。她專注於將數據科學和機器學習應用於線上生態系統中的濫用行為，並且是網絡安全及信任與安全領域的專家。Maggie 也是德克薩斯州大學奧斯汀分校資訊學院的兼任講師。
