Generative AI tools like ChatGPT are amazing—but how can you get the most out of them in your daily work? This book introduces cutting-edge AI tools and the practical techniques you need to use them safely and effectively.
Introduction to Generative AI
gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you’ll learn:
- How large language models (LLMs) work
- How to integrate generative AI into your personal and professional work
- Balancing innovation and responsibility
- The social, legal, and policy landscape around generative AI
- Societal impacts of generative AI
- Where AI is going
Anyone who uses ChatGPT for even a few minutes can tell that it’s truly different from other chatbots or question-and-answer tools. Introduction to Generative AI
guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you’ll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren’t) capable of, and how you can use them to greatest advantage.
about the book
In Introduction to Generative AI: An ethical, societal, and legal overview
, AI engineers Numa Dhamani and Maggie Engler reveal both the power and limitations of AI tools and explore their impact on society, the economy, and the law. Our expert authors share best practices for responsibly using LLMs, drawing on years of experience in machine learning, data security, and ethical AI. You’ll learn strategies for getting accurate and useful responses, techniques for integrating generative AI in your workflow, and even how to handle misuse and adversarial attacks.
about the reader
For anyone interested in generative AI.
about the authors
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.
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.