Machine World

In the fourth book of the series, James McGill is up for promotion. Not everyone is happy about that, and McGill must prove he's worth his stripes. Deployed to a strange alien planet outside the boundaries of the Galactic Empire, he's caught up in warfare and political intrigue. Earth expands, the Cephalopod Kingdom launches ships to stop us, and a grand conspiracy emerges among the upper ranks of the Hegemony military.

Authors Womack, Jones, and Roos provided a comprehensive description of the entire lean system. They exhaustively documented its advantages over the mass production model pioneered by General Motors and predicted that lean production would eventually triumph. Indeed, they argued that it would triumph not just in manufacturing but in every value-creating activity from health care to retail to distribution.

In The World’s Biggest Cash Machine, informed by interviews with key figures behind the scenes, award-winning journalist and commentator Chris Blackhurst charts the gripping story of the world’s biggest football club - as well as exploring the wider transformation of the Premier League into a playground for billionaire owners.

Liam Chapman cannot believe his good fortune. He just bought a real, working time machine at a garage sale for $3. Sure, it’s labeled “World’s Worst Time Machine,” but how bad could it be? The time machine, as it turns out, is so much worse than Liam could have imagined. First, it summons Thomas Edison, but not that Thomas Edison. This Thomas Edison is a 10-year-old aspiring gangster from 1933 who demands to be called “Tommy Twinkles” and is also very interested in robbing a bank of the future.

In June of 2024, thirty-one years after its founding in a Denny’s restaurant, Nvidia became the most valuable corporation on Earth. The Thinking Machine is the astonishing story of how a designer of video game equipment conquered the market for AI hardware, and in the process re-invented the computer. Essential to Nvidia’s meteoric success is its visionary CEO Jensen Huang, who more than a decade ago, on the basis of a few promising scientific results, bet his entire company on AI.

When we avoid taking a decision, what happens to it? In The Unaccountability Machine, Dan Davies examines why markets, institutions and even governments systematically generate outcomes that everyone involved claims not to want. He casts new light on the writing of Stafford Beer, a legendary economist who argued in the 1950s that we should regard organisations as artificial intelligences, capable of taking decisions that are distinct from the intentions of their members.

From a New York Times investigative reporter, this “authoritative and devastating account of the impacts of social media” (New York Times Book Review) tracks the high-stakes inside story of how Big Tech’s breakneck race to drive engagement—and profits—at all costs fractured the world, and is “an essential book for our times” (Ezra Klein).

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.

After a shootout in Dubai left Hamza al-Saud dead and elevated brilliant aeronautical engineer Qasim Nadar to hero status in England, everyone assumes the terrorist threat from al Qadar has been eliminated. Everyone except JSOC counterterrorism analyst Whitney Watts. But when she decides to help MI6 penetrate Nadar’s secret network, Watts gets a little too close to the truth and finds herself in a deadly situation not even her teammates from Tier One can save her from.

Artificial intelligence is smarter than humans. It can process information at lightning speed and remain focused on specific tasks without distraction. AI can see into the future, predicting outcomes and even use sensors to see around physical and virtual corners. So why does Intelligence frequently get it so wrong? The answer is us. Humans design the algorithms that define the way that AI works and the processed information reflects an imperfect world.

In November 2022, a webpage was posted online with a simple text box. It was ChatGPT, and was unlike any app people had used before. It was more human than a customer service agent, more convenient than a Google search. Behind the scenes, battles for control and prestige between the world’s two leading AI firms, OpenAI and DeepMind, who now steers Google's AI efforts, has remained elusive—until now.

Not too long ago, the cyborg NSLICE-00P—Non-Standard Leashed-Intelligence Cybernetic Enforcer—was an unstoppable machine of war. But when a fateful murder caused her to be launched into a whole new reality, she slowly began to realize that she could be something more . . . if she wanted.

To most of us, it seems like recent developments in artificial intelligence emerged out of nowhere to pose unprecedented threats to humankind. But to Dr. Joy Buolamwini, who has been at the forefront of AI research, this moment has been a long time in the making.

The tragic fate of the British airship R101—which went down in a spectacular fireball in 1930, killing more people than died in the Hindenburg disaster seven years later—has been largely forgotten. In His Majesty’s Airship, S.C. Gwynne resurrects it in vivid detail, telling the epic story of great ambition gone terribly wrong.

"You look like a thing and I love you" is one of the best pickup lines ever...according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog AI Weirdness. She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans — all to understand the technology that governs so much of our daily lives.

Unleash the power of Generative AI in less than 30 days. Turn tech curiosity into a practical skillset even if you're a beginner. Don't let your perception of what's difficult hold you back. This book is designed specifically with simplicity in mind, tailored for those who may be stepping into the world of AI for the first time. It is packed with interactive, up-to-date exercises and real-world applications, that will guide you every step of the way, ensuring that you stay connected to the most relevant and useful topics in AI.

What does it mean to be smart? To be human? What do we really want from life and the intelligence we have, or might create? With deep and exclusive reporting, across hundreds of interviews, New York Times Silicon Valley journalist Cade Metz brings you into the rooms where these questions are being answered. Where an extraordinarily powerful new artificial intelligence has been built into our biggest companies, our social discourse, and our daily lives, with few of us even noticing.

Fascinated by AI but unsure where to start? Feel like the AI revolution is racing ahead without you? You haven't missed your chance—the path to AI mastery is clearer than you imagine. AI Fundamentals makes AI accessible and exciting.

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.

In Your AI Survival Guide, Sol Rashidi delivers an insightful and practical discussion of how to deploy artificial intelligence in your company. Having helped IBM launch Watson in 2011, Sol has firsthand knowledge of the ups, downs, and change management intricacies that can help you with a successful deployment beyond all the AI hype. She walks you through various frameworks for how to establish your AI strategy, pick your use cases, prepare your non-technology teams, and overcome the most common obstacles standing in the way of successfully implementing AI in your business.