This ground-breaking study, the first of its kind, outlines a theory of publishing that allows publishing houses to focus on their core competencies in times of crisis. Tracing the history of publishing from the press works of fifteenth-century Germany to twenty-first-century Silicon Valley, via Venice, Beijing, Paris and London, and fusing media theory and business experience, ‘The Content Machine’ offers a new understanding of content, publishing and technology, and defiantly answers those who contend that publishing has no future in a digital age.

Content Machine outlines a strategy for using content marketing to build a 7-figure business with zero advertising. Whether you are a blogger, content marketer, entrepreneur or marketing manager, Content Machine will help you see the return you deserve from your content marketing efforts.

“This gonzo-journalistic exploration of the Silicon Valley techno-utopians’ pursuit of escaping mortality is a breezy romp full of colorful characters.” —New York Times Book Review (Editor's Choice) Transhumanism is a movement pushing the limits of our bodies—our capabilities, intelligence, and lifespans—in the hopes that, through technology, we can become something better than ourselves. It has found support among Silicon Valley billionaires and some of the world’s biggest businesses. In To Be a Machine, journalist Mark O'Connell explores the staggering possibilities and moral quandaries that present themselves when you of think of your body as a device. He visits the world's foremost cryonics facility to witness how some have chosen to forestall death. He discovers an underground collective of biohackers, implanting electronics under their skin to enhance their senses. He meets a team of scientists urgently investigating how to protect mankind from artificial superintelligence. Where is our obsession with technology leading us? What does the rise of AI mean not just for our offices and homes, but for our humanity? Could the technologies we create to help us eventually bring us to harm? Addressing these questions, O'Connell presents a profound, provocative, often laugh-out-loud-funny look at an influential movement. In investigating what it means to be a machine, he offers a surprising meditation on what it means to be human.

Visionary designer and technologist John Maeda defines the fundamental laws of how computers think, and why you should care even if you aren't a programmer. "Maeda is to design what Warren Buffett is to finance." --Wired John Maeda is one of the world's preeminent interdisciplinary thinkers on technology and design. In How to Speak Machine, he offers a set of simple laws that govern not only the computers of today, but the unimaginable machines of the future. Technology is already more powerful than we can comprehend, and getting more powerful at an exponential pace. Once set in motion, algorithms never tire. And when a program's size, speed, and tirelessness combine with its ability to learn and transform itself, the outcome can be unpredictable and dangerous. Take the seemingly instant transformation of Microsoft's chatbot Tay into a hate-spewing racist, or how crime-predicting algorithms reinforce racial bias. How to Speak Machine provides a coherent framework for today's product designers, business leaders, and policymakers to grasp this brave new world. Drawing on his wide-ranging experience from engineering to computer science to design, Maeda shows how businesses and individuals can identify opportunities afforded by technology to make world-changing and inclusive products--while avoiding the pitfalls inherent to the medium.

Like many content creators today, I’ve faced the same problems that plague any industry that’s surging in demand. Losing sleep on projects, taking on too many clients, burning out, you know the drill. There’s a price for success in the content creation industry if you’re doing it all on your own. My name is Vanessa Lau and I’ve spent the past four years learning, tweaking, and refining the perfect system of how you can deliver exceptional thought leadership content sustainability and consistently. This is what I call the content machine.

AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.

"My stomach feels like it's tied up in a knot. My knees lock up, and my face feels hot. You know what I mean? I'm Wilma Jean, The Worry Machine." Anxiety is a subjective sense of worry, apprehension, and/or fear. It is considered to be the number one health problem in America. Although quite common, anxiety disorders in children are often misdiagnosed and overlooked. Everyone feels fear, worry and apprehension from time to time, but when these feelings prevent a person from doing what he/she wants and/or needs to do, anxiety becomes a disability. This fun and humorous book addresses the problem of anxiety in a way that relates to children of all ages. It offers creative strategies for parents and teachers to use that can lessen the severity of anxiety. The goal of the book is to give children the tools needed to feel more in control of their anxiety. For those worries that are not in anyone's control (i.e. the weather) a worry hat is introduced. A fun read for Wilmas of all ages! Includes a note to parents and educators with tips on dealing with an anxious child.

Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you'll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You'll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author's extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer.

Doing homework becomes a thing of the past! Meet the D Squad, a foursome of fifth graders at the Grand Canyon School made up of a geek, a class clown, a teacher's pet, and a slacker. They are bound together by one very big secret: the homework machine. Because the machine, code-named Belch, is doing their homework for them, they start spending a lot of time together, attracting a lot of attention. And attention is exactly what you don't want when you are keeping a secret. Before long, things start to get out of control, and Belch becomes much more powerful than they ever imagined. Now the kids are in a race against their own creation, and the loser could end up in jail...or worse!

Third-grader Aven Green has been solving mysteries for a really long time—a whole month! She’s solved many important cases like The Mystery of the Cranky Mom, The Mystery of the Missing Ice Cream, and The Mystery of the Smelly Feet. Her record is nearly 100% (only The Mystery of the Cereal in My Underpants remains unsolved to this day). Aven asks all the right questions, wields her detective kit carefully, and follows up on every clue. Then her teacher’s lunch bag (with her lunch still in it) is taken and Aven’s great-grandma’s beloved dog goes missing! Can this perceptive detective crack two cases at the same time? Luckily, Aven has a super-powered brain full of lots of extra brain cells to take on both cases. See, she was born without arms, so all of the cells that were supposed to make her arms went into making her brain instead. At least that’s her working theory for The Mystery of Why I Have So Many Extra Brain Cells.