Computer Science Technology

An inside view of the AI revolution, from the people and companies making it happen. How did we build large language models? How do they think, if they think? What will the world look like if we have billions of AIs that are as smart as humans, or even smarter?

Ready to turn your ideas into income—powered by AI? Whether you're starting from scratch or scaling your side hustle, AI Income Blueprint gives you the exact roadmap to launch, grow, and profit in the AI economy. This isn’t theory. It’s a step-by-step guide packed with proven strategies, insider secrets, and actionable tools to help you build a real business—even if you’re not “techy.”

Law today is incomplete, inaccessible, unclear, underdeveloped, and often perplexing to those whom it affects. In The Legal Singularity, Abdi Aidid and Benjamin Alarie argue that the proliferation of artificial intelligence-enabled technology–and specifically the advent of legal prediction–is on the verge of radically reconfiguring the law, our institutions, and our society for the better.

Unlock new levels of business success with AI Profit Multiplier, your guide to leveraging the power of AI apps and chatbots like ChatGPT and Claude. In this essential resource, you’ll discover how today’s most innovative digital entrepreneurs and business owners use AI to transform operations, increase productivity, and supercharge sales.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Ready to turn ChatGPT into a 24/7 income machine? Whether you're starting from scratch or scaling your digital hustle, ChatGPT Income Empire gives you the exact blueprint to earn fast, automate smart, and grow a sustainable online business using AI.

What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award-winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression. This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity.

In this absorbing and frequently contentious book, Roger Penrose puts forward his view that there are some facets of human thinking that can never be emulated by a machine. The book's central concern is what philosophers call the "mind-body problem". Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness.

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning initiatives, aka predictive AI projects, from conception to deployment.

Ready to trade like it's the future? Feeling overwhelmed by stock trading, algorithms, or all the AI hype? This beginner-friendly guide shows you exactly how to use ChatGPT, AI tools, and smart automation to start trading like a pro—with zero fluff and actionable steps that work. AI isn’t coming. It’s already here—learn how to use it to your advantage! From building custom stock screeners with ChatGPT to using bots and backtesting tools, this book gives you the blueprint to trade smarter, manage risk, and actually understand what you’re doing.

If you read (or listen to) nothing else on artificial intelligence and machine learning, listen to these ten articles. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you understand the future direction of AI, bring your AI initiatives to scale, and use AI to transform your organization.

In Survival of the Richest, Rushkoff traces the origins of The Mindset in science and technology through its current expression in missions to Mars, island bunkers, AI futurism, and the metaverse. In a dozen urgent, electrifying chapters, he confronts tech utopianism, the datafication of all human interaction, and the exploitation of that data by corporations. Through fascinating characters, Rushkoff explains why those with the most power to change our current trajectory have no interest in doing so.

Des premiers algorithmes aux systèmes d'auto-apprentissage et aux réseaux neuronaux, « Le trading IA de A à Z » offre un aperçu fascinant des coulisses d'un monde où les machines sont depuis longtemps devenues des acteurs à part entière. Vous découvrirez comment les systèmes d'IA modernes prennent des décisions, comment les modèles prédictifs identifient les tendances avant qu'elles ne se manifestent et comment vous pouvez, en tant que débutant, accéder à ce monde hautement complexe, même sans avoir fait d'études en informatique.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

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.

Paper is one of the simplest and most essential pieces of human technology. For the past two millennia, the ability to produce it in ever more efficient ways has supported the proliferation of literacy, media, religion, education, commerce, and art; it has formed the foundation of civilizations, promoting revolutions and restoring stability.

Sometimes designed objects reject their users: a computer mouse that doesn't work for left-handed people, for example, or a touchscreen payment system that only works for people who read English phrases, have 20/20 vision, and use a credit card. These mismatches are the building blocks of exclusion. In Mismatch, Kat Holmes describes how design can lead to exclusion, and how design can also remedy exclusion.

Merchants of Doubt has been praised—and attacked—around the world, for reasons easy to understand. This book tells, with “brutal clarity” (Huffington Post), the disquieting story of how a loose-knit group of high-level scientists and scientific advisers, with deep connections in politics and industry, ran effective campaigns to mislead the public and deny well-established scientific knowledge over four decades.

In this audiobook, you'll get a clear overview of artificial intelligence technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.