Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach.

AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications.

• Understand what AI engineering is and how it differs from traditional machine learning engineering
• Learn the process for developing an AI application, the challenges at each step, and approaches to address them
• Explore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they work
• Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them
• Choose the right model, dataset, evaluation benchmarks, and metrics for your needs

Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI.

AI Engineering builds upon and is complementary to Designing Machine Learning Systems (O'Reilly).

Nobody expected this--not even its creators: ChatGPT has burst onto the scene as an AI capable of writing at a convincingly human level. But how does it really work? What's going on inside its AI mind? In this short book, prominent scientist and computation pioneer Stephen Wolfram provides a readable and engaging explanation that draws on his decades-long unique experience at the frontiers of science and technology. Find out how the success of ChatGPT brings together the latest neural net technology with foundational questions about language and human thought posed by Aristotle more than two thousand years ago.

Updated to provide a deeper and closer look at ChatGPT

Expanded and extended, this new edition of ChatGPT For Dummies covers the latest tools, models, and options available on the popular generative AI platform. You'll learn best practices for using ChatGPT as a text and media generation tool, research assistant, and content reviewer. If you're new to the world of AI, you'll get all the basic know-how needed to add ChatGPT to your professional toolbox. And if you've been doing the genAI thing for a while already, this book will sharpen your skills as you apply AI to real-world projects in an ethical manner. You'll get insight on the best practice for using ChatGPT to make your life and work easier and how to write prompts that result in high-quality output.

• Understand what generative AI is and how ChatGPT produces human-like responses
• Get tips on writing effective prompts and using ChatGPT to generate sound and images
• Apply ChatGPT to your daily work or personal life
• Discover the best way to fact-check AI-generated content to avoid errors and hallucinations

Anyone using ChatGPT to enhance their work--whether for professional or personal use--will get better results with ChatGPT For Dummies.

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation.

With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI.

Learn how to empower AI to work for you. This book explains:

• The structure of the interaction chain of your program's AI model and the fine-grained steps in between
• How AI model requests arise from transforming the application problem into a document completion problem in the model training domain
• The influence of LLM and diffusion model architecture--and how to best interact with it
• How these principles apply in practice in the domains of natural language processing, text and image generation, and code

In ChatGPT and the Future of AI, the sequel to The Deep Learning Revolution, Terrence Sejnowski offers a nuanced exploration of large language models (LLMs) like ChatGPT and what their future holds. How should we go about understanding LLMs? Do these language models truly understand what they are saying? Or is it possible that what appears to be intelligence in LLMs may be a mirror that merely reflects the intelligence of the interviewer? In this book, Sejnowski, a pioneer in computational approaches to understanding brain function, answers all our urgent questions about this astonishing new technology.

Sejnowski begins by describing the debates surrounding LLMs' comprehension of language and exploring the notions of thinking and intelligence. He then takes a deep dive into the historical evolution of language models, focusing on the role of transformers, the correlation between computing power and model size, and the intricate mathematics shaping LLMs. Sejnowski also provides insight into the historical roots of LLMs and discusses the potential future of AI, focusing on next-generation LLMs inspired by nature and the importance of developing energy-efficient technologies.

Grounded in Sejnowski's dual expertise in AI and neuroscience, ChatGPT and the Future of AI is the definitive guide to understanding the intersection of AI and human intelligence.

Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices

Purchase of the print or Kindle book includes a free eBook in PDF format

This book is instrumental in making sure that as many people as possible can not only use LLMs but also adapt them, fine-tune them, quantize them, and make them efficient enough to deploy in the real world. - Julien Chaumond, CTO and Co-founder, Hugging Face

Book Description

This LLM book provides practical insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps' best practices. The guide walks you through building an LLM-powered twin that's cost-effective, scalable, and modular. It moves beyond isolated Jupyter Notebooks, focusing on how to build production-grade end-to-end LLM systems.

Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects.

What you will learn

- Implement robust data pipelines and manage LLM training cycles

- Create your own LLM and refine with the help of hands-on examples

- Get started with LLMOps by diving into core MLOps principles like IaC

- Perform supervised fine-tuning and LLM evaluation

- Deploy end-to-end LLM solutions using AWS and other tools

- Explore continuous training, monitoring, and logic automation

- Learn about RAG ingestion as well as inference and feature pipelines

Who this book is for

This book is for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. Basic knowledge of LLMs and the Gen AI landscape, Python and AWS is recommended. Whether you are new to AI or looking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios.

Table of Contents

- Undersstanding the LLM Twin Concept and Architecture

- Tooling and Installation

- Data Engineering

- RAG Feature Pipeline

- Supervised Fine-tuning

- Fine-tuning with Preference Alignment

- Evaluating LLMs

- Inference Optimization

- RAG Inference Pipeline

- Inference Pipeline Deployment

- MLOps and LLMOps

- Appendix: MLOps Principles

Learn how the disruptive AI chatbot is going to change school, work, and beyond

ChatGPT For Dummies demystifies the artificial intelligence tool that can answer questions, write essays, and generate just about any kind of text it's asked for. This powerful example of generative AI is widely predicted to upend education and business. In this book, you'll learn how ChatGPT works and how you can operate it in a way that yields satisfactory results. You'll also explore the ethics of using AI-generated content for various purposes. Written by a journalist who's been on the front lines of artificial intelligence for over a decade, this book dives deep into ChatGPT's potential, so you can make informed decisions--without asking ChatGPT for help.

• Learn how ChatGPT works and how it fits into the world of generative AI
• Harness the power of ChatGPT to help you, and avoid letting it hinder you
• Write queries that deliver the kind of response you want
• Take a look into how the ChatGPT API interacts with other tools and platforms

This just-in-time Dummies title is perfect for any life or career may be impacted by ChatGPT and other AI. ChatGPT is just the tip of the iceberg, and this book can help you prepare for the future.

In an era characterised by the remarkable growth of AI, there emerges a profound ethical dimension that demands our attention. This book presents a timely and significant addition to the ongoing discourse around the ethical implications of AI in general, as well as the new and disruptive AI technologies, such as generative AI platforms like ChatGPT.

This book discusses:

• • Digital technology disruption and AI;
  • An overview of AI and generative AI;
  • The role of AI and generative AI in misinformation and disinformation;
  • AI and online disinhibition;
  • How AI bias can occur;
  • AI and job displacement;
  • AI privacy issues; and
  • AI regulation and policy.

This book is a philosophical approach to the AI world, so it is of use to anyone curious about the moral issues surrounding advancements in AI, and not only for those who have a background in AI.

If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master--;a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI.

Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a production-ready AI agent that uses your data.

• Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external up-to-date data
• Develop and deploy AI applications that interact intelligently and contextually with users
• Make use of the powerful agent architecture with LangGraph
• Integrate and manage third-party APIs and tools to extend the functionality of your AI applications
• Monitor, test, and evaluate your AI applications to improve performance
• Understand the foundations of LLM app development and how they can be used with LangChain

How do we make digital systems feel less robotic and more real? Whether you work with interface or visual design, frontend technology, or content design, learn why conversation is the best model for creating device-independent, human-centered systems. Research and information design expert Erika Hall explains what makes an interaction truly conversational and how to get more comfortable using language in design. From understanding the human interface, to effectively using the power of personality, to getting it all done, you'll find out how the art of communication can elevate technology.

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 OpenAI

Purchase 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.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code.

You'll learn:

• How to build models with TensorFlow using skills that employers desire
• The basics of machine learning by working with code samples
• How to implement computer vision, including feature detection in images
• How to use NLP to tokenize and sequence words and sentences
• Methods for embedding models in Android and iOS
• How to serve models over the web and in the cloud with TensorFlow Serving

Master language models through mathematics, illustrations, and code―and build your own from scratch!

The Hundred-Page Language Models Book by Andriy Burkov, the follow-up to his bestselling The Hundred-Page Machine Learning Book (now in 12 languages), offers a concise yet thorough journey from language modeling fundamentals to the cutting edge of modern Large Language Models (LLMs). Within Andriy's famous hundred-page format, readers will master both theoretical concepts and practical implementations, making it an invaluable resource for developers, data scientists, and machine learning engineers.

The Hundred-Page Language Models Book allows you to:

- Master the mathematical foundations of modern machine learning and neural networks

- Build and train three architectures of language models in Python

- Understand and code a Transformer language model from scratch in PyTorch

- Work with LLMs, including instruction finetuning and prompt engineering

Written in a hands-on style with working Python code examples, this book progressively builds your understanding from basic machine learning concepts to advanced language model architectures. All code examples run on Google Colab, making it accessible to anyone with a modern laptop.

Endorsements

Vint Cerf, Internet pioneer and Turing Award recipient: This book cleared up a lot of conceptual confusion for me about how Machine Learning actually works - it is a gem of clarity.

Tomás Mikolov, the author of word2vec and FastText: The book is a good start for anyone new to language modeling who aspires to improve on state of the art.

Artificial intelligence is reshaping organizations across sectors through human-machine collaboration. For public administrators, AI tools like ChatGPT have immense potential to enhance operations, decision-making, and service delivery. However, guidance is needed to skillfully integrate AI into public-sector contexts.

In The Public Administrator's Guide to ChatGPT, Dr. Dylan Hayden draws on his extensive public service career to provide a strategic playbook for harnessing the power of AI. With lucid explanations and real-world examples, this handbook prepares leaders to pioneer AI as a force for good governance.

This guide unravels the AI landscape, with a focus on maximizing ChatGPT's value for public servants. Dr. Hayden shares approaches for effective prompt engineering to direct ChatGPT efficiently. Readers will learn strategies to boost policy research, streamline communications, optimize workflows, and automate repetitive tasks.

With ethical considerations at the forefront, the book charts a thoughtful course for AI adoption. Dr. Hayden stresses transparent and equitable implementation to earn public trust. Through human oversight and mitigating algorithmic biases, he believes AI can enhance objectivity in public administration.

From federal agencies to local nonprofits, The Public Administrator's Guide to ChatGPT empowers organizations to meet evolving needs through AI collaboration. Pragmatic use cases showcase AI applications across public entities, saving time for employees while providing more responsive, customized services.

Leaders will gain the confidence and skills needed to spearhead AI integration in their workplaces. Regardless of technical background, readers can grasp the possibilities of AI and prepare their institutions for the future. With ethical considerations guiding responsible innovation, administrators can accelerate progress through human-AI symbiosis.

The Public Administrator's Guide to ChatGPT equips professionals to lead the responsible AI revolution in the public sector. Administrators will drive change while upholding their duty to equitably serve all citizens, shaping a more capable, creative model of governance and problem-solving.

OpenAI's GPT-3, ChatGPT, GPT-4 and Hugging Face transformers for language tasks in one book. Get a taste of the future of transformers, including computer vision tasks and code writing and assistance.

Purchase of the print or Kindle book includes a free eBook in PDF format

Key Features:

• Pretrain a BERT-based model from scratch using Hugging Face
• Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your data
• Perform root cause analysis on hard NLP problems

Book Description:

Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs?

Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses.

You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model.

If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides.

The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details).

You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using Codex.

By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective!

What You Will Learn:

• Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E
• Discover new techniques to investigate complex language problems
• Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers
• Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3
• Measure the productivity of key transformers to define their scope, potential, and limits in production

Who this book is for:

If you want to learn about and apply transformers to your natural language (and image) data, this book is for you.

You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And, don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community and author, Denis Rothman. So, he'll be there to guide you on your transformers journey!

From Oxford's leading AI researcher comes a fun and accessible tour through the history and future of one of the most cutting edge and misunderstood field in science: Artificial Intelligence

The somewhat ill-defined long-term aim of AI is to build machines that are conscious, self-aware, and sentient; machines capable of the kind of intelligent autonomous action that currently only people are capable of. As an AI researcher with 25 years of experience, professor Mike Wooldridge has learned to be obsessively cautious about such claims, while still promoting an intense optimism about the future of the field. There have been genuine scientific breakthroughs that have made AI systems possible in the past decade that the founders of the field would have hailed as miraculous. Driverless cars and automated translation tools are just two examples of AI technologies that have become a practical, everyday reality in the past few years, and which will have a huge impact on our world.

While the dream of conscious machines remains, Professor Wooldridge believes, a distant prospect, the floodgates for AI have opened. Wooldridge's A Brief History of Artificial Intelligence is an exciting romp through the history of this groundbreaking field--a one-stop-shop for AI's past, present, and world-changing future.

If speech has long been an emblem of the human species, then talking machines seem to be harbingers of some kind of technological singularity. Indeed, if the brilliance--or at least eloquence--of large language models is any indication, we seem to be poised at the threshold of general AI, a form of artificial intelligence that will not only surpass human intelligence but maybe even replace humans altogether.

This slim text lays out a critical genealogy of the highly contested relation between human values, machinic parameters, and corporate powers. It also provides a theory of the reasons for, and effects of, our current social and technological horizon.

Master language models through mathematics, illustrations, and code―and build your own from scratch!

The Hundred-Page Language Models Book by Andriy Burkov, the follow-up to his bestselling The Hundred-Page Machine Learning Book (now in 12 languages), offers a concise yet thorough journey from language modeling fundamentals to the cutting edge of modern Large Language Models (LLMs). Within Andriy's famous hundred-page format, readers will master both theoretical concepts and practical implementations, making it an invaluable resource for developers, data scientists, and machine learning engineers.

The Hundred-Page Language Models Book allows you to:

- Master the mathematical foundations of modern machine learning and neural networks

- Build and train three architectures of language models in Python

- Understand and code a Transformer language model from scratch in PyTorch

- Work with LLMs, including instruction finetuning and prompt engineering

Written in a hands-on style with working Python code examples, this book progressively builds your understanding from basic machine learning concepts to advanced language model architectures. All code examples run on Google Colab, making it accessible to anyone with a modern laptop.

Endorsements

Vint Cerf, Internet pioneer and Turing Award recipient: This book cleared up a lot of conceptual confusion for me about how Machine Learning actually works - it is a gem of clarity.

Tomás Mikolov, the author of word2vec and FastText: The book is a good start for anyone new to language modeling who aspires to improve on state of the art.

How did we build large language models? Is scaling them up all we need to create general intelligence? How do they think, if they think? Will we be able to make them share our goals--and what happens if we can't?

In a series of in-depth interviews with leading AI researchers and company founders--including Anthropic CEO Dario Amodei, DeepMind cofounder Demis Hassabis, OpenAI cofounder Ilya Sutskever, MIRI cofounder Eliezer Yudkowsky, and Meta CEO Mark Zuckerberg--Dwarkesh Patel provides the first comprehensive and contemporary portrait of the technology that is transforming our world.

Drawn from his interviews on the Dwarkesh Podcast, these curated excerpts range from the technical details of how LLMs work, to the economic, philosophical, and safety considerations of creating artificial general intelligence. Patel's conversations cut through the noise to explore the topics most compelling to those at the forefront of the field: the power of scaling, the potential for misalignment, the sheer input required for AGI, and the economic and social ramifications of superintelligence.

The book is also a standalone introduction to the technology. It includes 170 definitions and 17 visualizations, explanations of technical points made by guests, classic essays on the theme from other writers, and an unpublished interview with Open Philanthropy research analyst Ajeya Cotra.

The Scaling Era offers readers unprecedented insight into a transformative moment in the development of AI--and a vision of what comes next.

A fascinating journey into the future of AI, providing a unique perspective that combines technology, economics, geopolitics, and history. - PASCAL BORNET, Technology Influencer, 2 million followers.

Written in an accessible style for all audiences, How AI Will Shape Our Future anchors readers in the history and evolution of Artificial Intelligence, laying the groundwork for a deeper understanding of its trajectory. This equips readers to engage more thoughtfully with the book's central theme: What should societies expect from AI in the decades ahead?

How does AI actually function? What will its impact be on employment and education, both short-term and long-term? How will AI reshape society, the economy, government, culture, and geopolitics? What are the potential utopian and dystopian outcomes, and who will be most affected? What's happening with China and the intensifying AI arms race? Could synthetic biology lead to human-cyborg coexistence, ultimately influencing human evolution? Most critically, what should we demand of our leaders today to prepare for AI's inevitable advancement?

These are just some of the provocative questions explored and answered by Pedro Uria-Recio, a former McKinsey consultant and Chief AI Officer who has spent years working with this transformative technology on a global scale.

Whether you're a technologist or a homemaker, a businessperson or a student, a voter or a policymaker, or simply curious about humanity's future, How AI Will Shape Our Future offers essential insights for navigating the complexities of AI.

How AI Will Shape Our Future

- Humanity Interlaces with AI: AI is our new mind. Robotics, our new body. How are we becoming a new species at the intersection of carbon and silicon?

- AI Gets Exponential: Artificial General Intelligence. Humanoids and cyborgs. Synthetic biology. Quantum computing. Mind emulation. How will they unfold?

- AI Authoritarianism Looms: AI will render truth obsolete, freedom redefined, and job scarcity ubiquitous. Can we still shape AI for the benefit of all?

- Geopolitics Supercharged: Super Intelligence will be worshiped. China and America will clash over their views on AI. Politics will be centered on species identities.

- Humanity's Greatest Epic: From Mythology to Kubrick. From Aristotle to Sam Altman. From Leonardo to Boston Dynamics. From today to Superintelligence.

- Stay Ahead with AI: Critical thinking. Adaptability. Entrepreneurship.

A seminal work, brilliantly navigating the transformative impact of AI on humanity and the advent of the machine economy, promising a harmonious fusion of technology and societal progress.-Professor Paul J. Morrissey, Professor at Liverpool John Moores University, Feb 15, 2024

I'm left utterly speechless after reading this book! It truly expanded my mind, especially in its contemplation of the future implications of AI.-D. Rob, April 28, 2024

Skillfully weaves together history, analysis, and thought-provoking predictions, challenging readers to confront the ethical and philosophical implications of this transformative technology. Recommend!-Zahid, June 9, 2024

AI Magnum Opus! What an in-depth and thorough volume on AI. From ancient history to future predictions, political implications, potential impacts, and outcomes, if there is any question you have about AI impact, this book likely touches on it. Vast in its breadth and intelligent insights.-J Palmer, May 20, 2024