検索キーワード： 機械理論・人工知能

Silicon Valley has sold us the illusion that artificial intelligence is a frictionless technology that will bring wealth and prosperity to humanity. But hidden beneath this smooth surface lies the grim reality of a precarious global workforce of millions laboring under often appalling conditions to make A.I. possible. This book presents an urgent, riveting investigation of the intricate network that maintains this exploitative system, revealing the untold truth of A.I.

What is artificial intelligence (AI)? What can it do and how is it created? In this highly accessible guide to the subject, Richard Urwin explains how AI came about and how it has developed over the years through the construction of ever more sophisticated computer programs. Along the way, you will discover numerous intriguing examples of how scientists have progressed the development of AI, as well as finding out how research into brain function is continually influencing this dynamic field.

On the eve of the Sino-American great power competition General Mattis challenged America to move forward at the speed of relevance. To compete effectively America needed to excel in its AI capacity. The call fell on deaf ears—and years later the nation found itself sliding towards a state of irrelevance on the global stage. A series of blunders contributed to what President Biden calls American AI's "failing and falling behind." This is the story of American AI's fall from grace.

The singularity is the emergence of artificial general intelligence (AGI), and the associated transformation of the human condition. Spoiler alert: That transformation will be profound. Despite the importance of the concept of the singularity, the subject receives nothing like the attention it deserves. This book seeks to dispel the confusion, to untangle the distortions, to highlight practical steps forward, and to attract much more serious attention to the singularity. The future of humanity is at stake.

While warnings of a robot world-takeover could seem dramatic, the truth is more mundane―robots have come to take our jobs. Winning in the Robotic Workplace: How to Prosper in the Automation Age will teach you the skills needed to reprogram the way you work in anticipation of this technological shift. Author John F. Wasik believes learning to thrive in the automation age can in fact humanize the workplace once again. You will learn to emphasize the conceptualization and pursuit of creative ideas, a practice that most robots are unequipped to perform in a meaningful way.

Machine learning is fast becoming an important technique used by multiple industries, and in applications and research. But you don’t have to be part of a massive organization with an endless pot of money to get involved. Even beginners using the Python programming language can be a part of machine learning, and that is what this book is for. Today, the only limit to machine learning is your imagination. In this book, I provide you with an overview of machine learning and some practical work to get your hands dirty.

Sensational media reports speculate about the "rise of the machines" but fail to see that there's no real intelligence in AI. It is not an all-seeing master, but rather a functional tool that must combine with the intelligence we possess to be effective. With The AI Republic, Terence Tse, Mark Esposito, and Danny Goh have not written a book for coders, but for everyone curious about a future shaped by AI. They demystify this life-changing technology and explain how we can build a shared space where humans and intelligent automation work together.

Are you interested in machine learning? Do you want to know how it all works and what it involves? Then you've chosen the right guide. Machine learning is a subset of computer science and artificial intelligence. There's no getting away from the fact that it is here to stay, and it is already changing how many businesses work and target their customers. It's a complex subject, but this guide will give you a concise overview of the steps required in every machine learning project.

Artificial intelligence is forecasted to have trillions of dollars of impact on businesses and the economy, yet many marketers struggle to understand what it is and how to apply it in their marketing efforts. The truth is, AI possesses the power to change everything. Marketing Artificial Intelligence draws on years of research and dozens of interviews with AI marketers, executives, engineers, and entrepreneurs. Roetzer and Kaput present the current potential of AI, as well as a glimpse into the near future.

Technology is our new life partner. No longer confined to the sidelines, new interactive technologies like AI therapists, avatar friends, and robot assistants are ready to transform technology's role from basic tools of convenience to intimate elements of our social and emotional lives.

Algorithmen, die unser Leben beeinflussen, sind längst keine Zukunftsmusik mehr, sondern stecken überall tief in unserem Alltag. Sie unterstützen Ärztinnen und Ärzte bei der Diagnose, lassen die Vergangenheit bunt werden und Personen in Kinofilmen auftauchen, die gar nicht am Dreh waren. Im Hochleistungssport verraten sie, ob und warum sich Athleten und Athletinnen verletzen könnten und leiten uns mehr oder weniger offen durch digitale Welten - was entsprechende Sorgen vor unbewusster Manipulation weckt. Ein Spektrum Kompakt rund um programmierte Helfer im Hintergrund.

The ability to hack AI and the technology industry's lack of effort to secure it is thought by experts to be the biggest unaddressed technology issue of our time. Hacking Artificial Intelligence sheds light on these hacking risks, explaining them to those who can make a difference. This book is the first-ever layman's guide to the new world of hacking AI and introduces the field to thousands of people who should be aware of these risks. From a security perspective, AI is today where the internet was thirty years ago. It is wide open and can be exploited.

It seems that just about every new technology that we bring to bear on improving our lives brings with it some downside, side effect, or unintended consequence. These issues can pose very real and growing ethical problems for all of us. For example, automated facial recognition can make life easier and safer for us—but it also poses huge issues with regard to privacy, ownership of data, and even identity theft. Technology Is Not Neutral addresses one of today’s most pressing problems: How to create and use tools and technologies to maximize benefits and minimize harms.

AI and people do not compete on a level playing field. Self-driving vehicles may be safer than human drivers, but laws often penalize such technology. People may provide superior customer service, but businesses are automating to reduce their taxes. AI may innovate more effectively, but an antiquated legal framework constrains inventive AI. In The Reasonable Robot, Ryan Abbott argues that the law should not discriminate between AI and human behavior and proposes a new legal principle that will ultimately improve human well-being.

Today, you can do things that most people never dreamed were possible. Artificial Intelligence (AI) is now part of everyday reality. Leaping into the future is real with AI. Living Smart will help you learn about practical applications and benefits. To begin with, you will find out what AI can do for you. Opportunity to improve the way you live and work is possible when you know what to do. There are endless applications. Living Smart will provide you with unique insight, tools, and logic to help guide you into the future.

Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks, procedural reuse design pattern for CNN architectures, models for mobile and IoT devices, assembling large-scale model deployments, optimizing hyperparameter tuning, and migrating a model to a production environment.

Artificial intelligence is revolutionizing the modern world. It is ubiquitous-in our homes and offices, in the present and most certainly in the future. Today, we encounter AI as our distant ancestors once encountered fire. If we manage AI well, it will become a force for good, lighting the way to many transformative inventions. If we deploy it thoughtlessly, it will advance beyond our control. As AI policy experts Ben Buchanan and Andrew Imbrie show in The New Fire, few choices are more urgent—or more fascinating—than how we harness this technology and for what purpose.

Whether we realize it or not, we think of our brains as computers. In neuroscience, the metaphor of the brain as a computer has defined the field for much of the modern era. But as neuroscientists increasingly reevaluate their assumptions about how brains work, we need a new metaphor to help us ask better questions. The computational neuroscientist Daniel Graham offers an innovative paradigm for understanding the brain. He argues that the brain is not like a single computer—it is a communication system, like the internet.

Computer technology has improved exponentially over the last 50 years. But the headroom for bigger and better electronic solutions is running out. Our best hope is to engage the power of quantum physics. Brian Clegg explains algorithms and their quantum counterparts, explores the physical building blocks and quantum weirdness necessary to make a quantum computer and uncovers the capabilities of the current generation of machines.

In How to Create a Mind, Ray Kurzweil presents a provocative exploration of the most important project in human-machine civilization: reverse-engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines. Kurzweil discusses how the brain functions, how the mind emerges, brain-computer interfaces, and the implications of vastly increasing the powers of our intelligence to address the world’s problems.