Automation World

From mechanical looms to the combustion engine to the first computers, new technologies have always provoked panic about workers being replaced by machines. For centuries, such fears have been misplaced, and many economists maintain that they remain so today. But as Daniel Susskind demonstrates, this time really is different. Breakthroughs in artificial intelligence mean that all kinds of jobs are increasingly at risk.

This is the first reference book on intelligent automation (IA). Also called hyperautomation, it is one of the most recent trends in the field of artificial intelligence. IA is a cutting-edge combination of methods and technologies involving people, organizations, machine learning, low-code platforms, robotic process automation (RPA), and more. This book is for everyone - whether you are an experienced practitioner, new to the topic, or simply interested in what the future holds for enterprises, work, life, and society as a whole.

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.

Test automation is a fantastic field of engineering. Unfortunately, most test automation efforts fail soon after being initiated. From the many promises of ease of automation to oversimplified vendor demonstrations, it's easy to spend significant time and cost pursuing test automation with little to show in the end. If only there was a way to avoid the pitfalls encountered when embarking upon test automation? Greg Paskal shares his best insights learned as a successful test automation engineer.

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.

What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Drawing upon real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created.

From the Industrial Revolution to the age of artificial intelligence, The Technology Trap takes a sweeping look at the history of technological progress and how it has radically shifted the distribution of economic and political power among society’s members.

What if we could hit the reset button on the way we create money, work, commerce, and community? This is not an idle question, for technology now enables us to hit that reset button and organize the creation of money, work, commerce, and community in new ways. If we could start from scratch, what would a new system look like? To answer that, we must understand why the current system is failing. The current system is based on five principles that are assumed to be true.

Take a look at the vehicle sitting in your driveway. It may be the last one you ever own. With an estimated 33 million fully autonomous cars and taxis projected to hit the road by 2040, an automotive renaissance is soon to be upon us. Personal car ownership currently costs the average sedan owner $9,000 annually. But car ownership may soon be a thing of the past.

In Autonomy, former GM executive and current advisor to the Google Self-Driving Car project Lawrence Burns offers a sweeping history of the race to make the driverless car a reality. In the past decade, Silicon Valley companies like Google, Tesla and Uber have positioned themselves to revolutionize the way we move around by developing driverless vehicles while traditional auto companies like General Motors, Ford, and Daimler have been fighting back by partnering by with new tech start-ups.

What to Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on artificial intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans, it raises profound questions on the future of work and how companies compete.