Showing titles in Computer Science

Generative AI is rewriting the rulebook with its seemingly endless capabilities, from crafting intricate industrial designs, writing computer code, and producing mesmerizing synthetic voices to composing enchanting music and innovating genetic breakthroughs. In Generative AI in Practice, renowned futurist Bernard Marr offers listeners a deep dive into the captivating universe of GenAI. This comprehensive guide introduces you to the basics of this groundbreaking technology and outlines the profound impact that GenAI will have on business and society.

We are living in the computer age, in a world increasingly designed and engineered by computer programmers and software designers, by people who call themselves hackers. Who are these people, what motivates them, and why should you care? Consider these facts: Everything around us is turning into computers. Your typewriter is gone, replaced by a computer. Your phone has turned into a computer. So has your camera. Soon your TV will. Your car was not only designed on computers, but has more processing power in it than a room-sized mainframe did in 1970. 

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete...

Alan Turing was an extraordinary man who crammed into a life of only 42 years the careers of mathematician, codebreaker, computer scientist and biologist. He is widely regarded as a war hero grossly mistreated by his unappreciative country, and it has become hard to disentangle the real man from the story. It is easy to cast him as a misfit, the stereotypical professor.

The Year in Tech, 2026: The Insights You Need from Harvard Business Review will help you understand what the latest and most important tech innovations mean for your organization and how you can use them to compete and win in today's turbulent business environment.

Forget everything you’ve heard about “passive income.” This isn’t about making a few extra bucks with ChatGPT—it’s about engineering your complete escape from employment. While others use AI to build $10K/month freedom businesses, you’re still trading time for a paycheck that barely scales. The real reason you’re still stuck isn’t lack of opportunity—it’s that you’re using AI like a toy instead of a wealth-building machine. This audiobook isn’t another list of prompts. It’s a proven 12-month roadmap that stacks 3 kinds of AI income until your automated earnings eclipse your salary.

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.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a loan, how much we pay for insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: everyone is judged according to the same rules and bias is eliminated. And yet, as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated and incontestable, even when they're wrong. Most troubling, they reinforce discrimination. 

Artificial intelligence does the seemingly impossible - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

In Understanding Artificial Intelligence: Of Minds and Machines, philosopher Patrick Grim traces the story of AI from ancient legends to the neural networks behind today’s breakthroughs. You see how modern systems became so powerful so quickly. You also explore the very meaning of “intelligence,” discovering how modern AI succeeds by drawing on three resources: vast datasets that let systems learn from examples; deep-learning architectures loosely modeled on the brain’s layers; and feedback loops that help models refine their behavior.

Derek Rydall, the author behind The Abundance Project, offers an empowering and actionable guide for workers, creators, leaders, and educators to unlock their full potential and not only survive but thrive in the AI era. As AI accelerates beyond human capabilities, the real threat isn’t that...

AN INSTANT NATIONAL BESTSELLER “Evenhanded and insightful.” —Publisher’s Weekly (starred review) “An accessible, often fascinating primer.... Essential, illuminating reading.” —Kirkus From the author of the New York Times bestseller The Digital Doctor comes an engaging, clear-eyed...

If you've ever felt locked out of software development because you lack a computer science degree, this book is your breakthrough guide. "Claude Code and GitHub for Beginners" shows non-technical founders, freelancers, and creators how to build real applications using AI coding tools and professional version control.

From the coauthor of Algorithms to Live By, an exploration of the quest to use mathematics to describe the ways we think, from its origins three hundred years ago to the ideas behind modern AI systems and the ways in which they still differ from human minds. Everyone has a basic understanding of...

This is an audiobook about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can't give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right and why they might be wrong.

Information architecture (IA) is far more challenging - and necessary - than ever. To guide you through this broad ecosystem, this popular guide - now in its fourth edition - provides essential concepts, methods, and techniques for digital design that have withstood the test of time. UX designers, product managers, developers, and anyone involved in digital design will learn how to create semantic structures that will help people engage with your message.

This book isn’t about the science of AI or the ethics of robots. It’s about the very real, efficient ways AI can enhance your everyday life—right now. Whether you realise it or not, AI has already been woven into your routines. It’s in your smartphone, your streaming service, your email inbox, and even in your fridge or vacuum cleaner. And the better you understand what it can do, the more you can benefit from its silent support.

The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX! Deep Learning with Python (Third Edition) puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.

What if everything you've ever known—every thought, every emotion, every moment—was part of a simulation? Once dismissed as science fiction, the Simulation Hypothesis has surged into mainstream discussion, embraced by philosophers, physicists, and tech visionaries alike. As computing power soars and virtual realities grow more immersive, the idea that our universe might itself be a simulation becomes less absurd—and more plausible. But if we are in a simulation, the next question is both thrilling and unsettling: Who—or what—is running it? And why?

What is AI? A dominant view describes it as the quest "to solve intelligence," a solution supposedly to be found in the secret logic of the mind or in the deep physiology of the brain, such as in its complex neural networks. The Eye of the Master argues, to the contrary, that the inner code of AI is shaped not by the imitation of biological intelligence, but the intelligence of labour and social relations, as it is found in Babbage's "calculating engines" of the industrial age as well as in the recent algorithms for image recognition and surveillance.