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A fascinating look at Artificial Intelligence, from its humble Cold War beginnings to the dazzling future that is just around the corner. When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate. In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible--and possibly terrifying--future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to broaden itself to include intelligent machines.
A fascinating look at Artificial Intelligence, from its humble Cold War beginnings to the dazzling future that is just around the corner. When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate. In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible--and possibly terrifying--future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to broaden itself to include intelligent machines.
This book explores historical traces of human life within the discourse of artifical intelligence. It addresses a matrix of themes about technology and change, ranging from the realm of the inanimate to the animate. It traces the ways in which the human spirit looks beyond its limitations and ponders the potentia of 'being human.'
Offers an illustrated telling of the story of Ada Byron Lovelace, from her early creative fascination with mathematics and science and her devastating bout with measles, to the ground-breaking algorithm she wrote for Charles Babbage's analytical engine.
Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks. This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning. Presents a clear understanding of various available machine learning hardware accelerator solutions that can be applied to selected machine learning algorithms Offers key insights into the development of hardware, from algorithms, software, logic circuits, to hardware accelerators Introduces the baseline characteristics of deep neural network models that should be treated by hardware as well Presents readers with a thorough review of past research and products, explaining how to design through ASIC and FPGA approaches for target machine learning models Surveys current trends and models in neuromorphic computing and neural network hardware architectures Outlines the strategy for advanced hardware development through the example of deep learning accelerators
A scientist who has spent a career developing Artificial Intelligence takes a realistic look at the technological challenges and assesses the likely effect of AI on the future. How will Artificial Intelligence (AI) impact our lives? Toby Walsh, one of the leading AI researchers in the world, takes a critical look at the many ways in which "thinking machines" will change our world. Based on a deep understanding of the technology, Walsh describes where Artificial Intelligence is today, and where it will take us. * Will automation take away most of our jobs? * Is a "technological singularity" near? * What is the chance that robots will take over? * How do we best prepare for this future? The author concludes that, if we plan well, AI could be our greatest legacy, the last invention human beings will ever need to make.
This irascible genius, this diminutive egghead scientist, known to the world as “The Thinking Machine,” is no less than the newly rediscovered literary link between Sherlock Holmes and Nero Wolfe: Professor Augustus S. F. X. Van Dusen, who—with only the power of ratiocination—unravels problems of outrageous criminous activity in dazzlingly impossible settings. He can escape from the inescapable death-row “Cell 13.” He can fathom why the young woman chopped off her own finger. He can solve the anomaly of the phone that could not speak. These twenty-three Edwardian-era adventures prove (as The Thinking Machine reiterates) that “two and two make four, not sometimes, but all the time.”
A call-to-arms about the broken nature of artificial intelligence, and the powerful corporations that are turning the human-machine relationship on its head. We like to think that we are in control of the future of "artificial" intelligence. The reality, though, is that we -- the everyday people whose data powers AI -- aren't actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can't see and have no input into -- one largely free from regulation or oversight. The big nine corporations -- Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple--are the new gods of AI and are short-changing our futures to reap immediate financial gain. In this book, Amy Webb reveals the pervasive, invisible ways in which the foundations of AI -- the people working on the system, their motivations, the technology itself -- is broken. Within our lifetimes, AI will, by design, begin to behave unpredictably, thinking and acting in ways which defy human logic. The big nine corporations may be inadvertently building and enabling vast arrays of intelligent systems that don't share our motivations, desires, or hopes for the future of humanity. Much more than a passionate, human-centered call-to-arms, this book delivers a strategy for changing course, and provides a path for liberating us from algorithmic decision-makers and powerful corporations.
Who will inherit the earth? Will it the the mechanical men we have developed to do the world's hard work? Androids-- imitation flesh-and-blood men? Or the electronic brain, with a consciousness, even a soul?
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.