Introduction to Generative AI by Numa Dhamani; Maggie Engler Generative AI tools like ChatGPT are amazing--but how will their use impact our society? This book introduces the world-transforming technology and the strategies you need to use generative AI 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 workflows 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 your greatest advantage. Foreword by Sahar Massachi. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you'll need to use it safely and effectively. About the book Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You'll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you'll practice strategies for getting accurate responses and even understand how to handle misuse and security threats. What's inside How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility About the reader For anyone interested in Generative AI. 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 an engineer and researcher currently working on safety for large language models. The technical editor on this book was Maris Sekar. Table of Contents 1 Large language models: The power of AI Evolution of natural language processing 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

Modern Generative AI with ChatGPT and OpenAI Models: Leverage the Capabilities of OpenAI's LLM for Productivity and Innovation with GPT3 and GPT4. by Valentina Alto Harness the power of AI with innovative, real-world applications, and unprecedented productivity boosts, powered by the latest advancements in AI technology like ChatGPT and OpenAIPurchase of the print or Kindle book includes a free PDF eBook Key Features Explore the theory behind generative AI models and the road to GPT3 and GPT4 Become familiar with ChatGPT's applications to boost everyday productivity Learn to embed OpenAI models into applications using lightweight frameworks like LangChain Book Description Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data.Next, you'll explore use cases where ChatGPT can boost productivity and enhance creativity. You'll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster.You'll also discover enterprise-level scenarios that leverage OpenAI models' APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you'll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications.By the end of this book, you'll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models' APIs in your own projects. What you will learn Understand generative AI concepts from basic to intermediate level Focus on the GPT architecture for generative AI models Maximize ChatGPT's value with an effective prompt design Explore applications and use cases of ChatGPT Use OpenAI models and features via API calls Build and deploy generative AI systems with Python Leverage Azure infrastructure for enterprise-level use cases Ensure responsible AI and ethics in generative AI systems Who this book is for This book is for individuals interested in boosting their daily productivity; businesspersons looking to dive deeper into real-world applications to empower their organizations; data scientists and developers trying to identify ways to boost ML models and code; marketers and researchers seeking to leverage use cases in their domain - all by using Chat GPT and OpenAI Models.A basic understanding of Python is required; however, the book provides theoretical descriptions alongside sections with code so that the reader can learn the concrete use case application without running the scripts. ]]>

Regulating the Synthetic Society: Generative AI, Legal Questions, and Societal Challenges by Bart van der Sloot Experts predict that in 5 years' time, more than 90% of all digital content will be wholly or partially AI generated. In a synthetic society, it may no longer be possible to establish what is real and what is not. Central to this open access book are 4 technologies on the frontline of this trend: humanoid robots, deepfakes, augmented reality, and virtual reality. Although they are only in their relative infancy, these technologies can already produce content that is indistinguishable from authentic material. The impact of this new reality on democracy, the judicial system, the functioning of the press, as well as on personal relationships will be unprecedented. Van der Sloot describes the technological fundaments of each of those technologies and maps their positive uses for educational purposes as well as for the treatment of patients, for the entertainment and creative industries, and the retail and financial sectors. The book also conceptualises their negative uses for fraud, deception, exploitation, identity-theft and exploitation, and shows their deeper effects on the post-truth society, the privatisation of the public sphere, and the loss of individual autonomy and societal trust. The book evaluates how the current European legal paradigm applies to these technologies, focussing on the right to privacy and data protection, freedom of expression, procedural law, tort law, and the regulation of AI. It discusses regulatory alternatives to solve existing regulatory gaps and shows that there are no easy answers. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com.