Introduction to Generative AI, Second Edition

Numa Dhamani (Autor)

Buch | Hardcover

325 Seiten

2026 | 2nd edition
Manning Publications (Verlag)
978-1-63343-488-2 (ISBN)

Noch nicht erschienen (ca. März 2026)
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ChatGPT feels magical, yet its limits and risks stay frustratingly unclear. News headlines hype breakthroughs while warnings shout about existential disaster. You need clarity, not fear, to decide how AI fits your world. This book hands you the plain language blueprint behind every generative AI headline. Understand what models do, why they fail, and where they create value. Move from confused spectator to informed, responsible participant in the AI revolution.

Core concepts demystified: Grasp LLM architecture, training, and prompting without needing coding experience.

Real-world case studies: See how businesses, education, and creativity already extract measurable AI value.

Risk and ethics primer: Navigate privacy, bias, and regulation to implement AI responsibly.

Practical toolkits: Apply step-by-step checklists for evaluating, testing, and integrating generative systems.

Foresight on trends: Anticipate reasoning models and vibe coding to future-proof your strategy.

Accessible format: Short chapters, visuals, and summaries enable quick learning and reference on demand.

Introduction to Generative AI, Second Edition by NLP expert Numa Dhamani and LLM safety researcher Maggie Engler delivers a timely, hype-free field guide.

You start with the simplest question, what is generative AI, then build to policy and economic impacts. Clear diagrams, chapter checklists, and myth-busting sidebars keep learning engaging and grounded in reality. Finish with the confidence to explore ChatGPT prompts, evaluate vendor claims, and brief stakeholders on risks. You will know when to trust AI, when to question it, and how to progress responsibly.

Perfect for managers, educators, students, and curious professionals seeking a practical, nontechnical AI starting point.

Numa Dhamani is a natural-language-processing researcher known for translating complex language science into actionable insight. With years at the intersection of technology and society, Numa brings clarity, curiosity, and social awareness to every page. She distills her expertise into practical guidance that empowers readers to explore AI responsibly.  Maggie Engler is an engineer and safety researcher working on large language models at a pioneering AI lab. With deep experience in measuring harms and building safeguards, Maggie offers balanced, evidence-based advice wrapped in an empathetic voice. She turns cutting-edge research into usable frameworks that help readers champion trustworthy AI systems.

1 LARGE LANGUAGE MODELS: THE POWER OF AI

2 TRAINING LARGE LANGUAGE MODELS

3 DATA PRIVACY AND SAFETY WITH LLMS

4 THE EVOLUTION OF CREATED CONTENT

5 MISUSE AND ADVERSARIAL ATTACKS

6 ACCELERATING PRODUCTIVITY: MACHINE-AUGMENTED WORK

7 MAKING SOCIAL CONNECTIONS WITH CHATBOTS

8 WHAT'S NEXT FOR AI AND LLMS

9 BROADENING THE HORIZON: EXPLORATORY TOPICS IN AI

APPENDIXES

APPENDIX A: REFERENCES

Erscheint lt. Verlag	4.3.2026
Verlagsort	New York
Sprache	englisch
Themenwelt	Geisteswissenschaften ► Sprach- / Literaturwissenschaft ► Literaturwissenschaft
	Informatik ► Software Entwicklung ► UML
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Informatik ► Weitere Themen ► Zertifizierung
	Sozialwissenschaften ► Pädagogik ► Erwachsenenbildung
ISBN-10	1-63343-488-5 / 1633434885
ISBN-13	978-1-63343-488-2 / 9781633434882
Zustand	Neuware