Ergebnis Anbieter "Tantor Audio" in Informatik

In this absorbing and frequently contentious book, Roger Penrose puts forward his view that there are some facets of human thinking that can never be emulated by a machine. The book's central concern is what philosophers call the "mind-body problem". Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness.

The world's most infamous hacker offers an insider's view of the low-tech threats to high-tech security. Kevin Mitnick's exploits as a cyber-desperado and fugitive form one of the most exhaustive FBI manhunts in history and have spawned dozens of articles, books, films, and documentaries. Since his release from federal prison, in 1998, Mitnick has turned his life around and established himself as one of the most sought-after computer security experts worldwide.

What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award-winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression. This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity.  

In this visionary book, Leslie Valiant argues that understanding the nature of our own educability is crucial to safeguarding our future. After breaking down how we process information to learn and apply knowledge, and drawing comparisons with other animals and AI systems, he explains why education should be humankind's central preoccupation. Will the unique capability that has been so foundational to our achievements and civilization continue to drive our progress, or will we fall victim to our vulnerabilities?

In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. Getting up in the morning, for example: You get up, take a shower, get dressed, eat breakfast. This simple daily routine solves a recurring problem through a series of well-defined steps. In computer science, such a routine is called an algorithm. 

Behind the familiar surfaces of the telephone, radio, and television lies a sophisticated and intriguing body of knowledge known as information theory. This is the theory that has permitted the rapid development of all sorts of communication, from color television to the clear transmission of photographs from the vicinity of Jupiter. Even more revolutionary progress is expected in the future.  

In the fall of 1980, Genentech, Inc., a little-known California genetic engineering company, became the overnight darling of Wall Street, raising over $38 million in its initial public stock offering. Lacking marketed products or substantial profit, the firm nonetheless saw its share price escalate from $35 to $89 in the first few minutes of trading. Coming at a time of economic recession and declining technological competitiveness in the United States, the event ignited a period of speculative frenzy over biotechnology.

After billions of dollars and 50 years of effort, researchers are finally cracking the code on artificial intelligence. As society stands on the cusp of unprecedented change, Jerry Kaplan unpacks the latest advances in robotics, machine learning, and perception powering systems that rival or exceed human capabilities. Driverless cars, robotic helpers, and intelligent agents that promote our interests have the potential to usher in a new age of affluence and leisure.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

This book will teach you to: understand what AI and machine learning are, and learn about new developments like ChatGPT; discover strategies for engaging students more fully using AI; automate administrative tasks, grading and feedback, and assessments; use AI in innovative ways to promote higher-order thinking skills; and examine ethical considerations of AI, including the achievement gap, privacy concerns, and bias.

ChatGPT For Dummies demystifies the artificial intelligence tool that can answer questions, write essays, and generate just about any kind of text it's asked for. This powerful example of generative AI is widely predicted to upend education and business. In this book, you'll learn how ChatGPT works and how you can operate it in a way that yields satisfactory results. You'll also explore the ethics of using AI-generated content for various purposes.

Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be. Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence and what it would take to get there.  

In The Patient Will See You Now, Eric Topol, one of the nation's top physicians, examines what he calls medicine's "Gutenberg moment". Much as the printing press liberated knowledge from the control of an elite class, new technology is poised to democratize medicine. In this new era, patients will control their data and be emancipated from a paternalistic medical regime in which "the doctor knows best."

Join journalist Barry Werth as he pulls back the curtain on Vertex, a start-up pharmaceutical company, and witness firsthand the intense drama being played out in the pioneering and hugely profitable field of drug research. Founded by Joshua Boger, a dynamic Harvard- and Merck-trained scientific whiz kid, Vertex is dedicated to designing - atom by atom - both a new life-saving immunosuppressant drug and a drug to combat the virus that causes AIDS.

In this audiobook, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. Science and technology buffs will find this audiobook an essential guide to a future in which machines can outsmart people.  

Everywhere we turn, a new device promises to transfigure our lives. But at what cost? In this urgent and revelatory excavation of our Information Age, leading technology thinker Adam Greenfield forces us to reconsider our relationship with the networked objects, services, and spaces that define us. It is time to re-evaluate the Silicon Valley consensus determining the future. We're told that innovations - from augmented - reality interfaces and virtual assistants to autonomous delivery drones and self-driving cars - will make life easier, more convenient, and more productive.

In Regenesis, George Church and science writer Ed Regis explore the possibilities of the emerging field of synthetic biology. Synthetic biology, in which living organisms are selectively altered by modifying substantial portions of their genomes, allows for the creation of entirely new species of organisms. These technologies - far from the out-of-control nightmare depicted in science fiction - have the power to improve human and animal health, increase our intelligence, enhance our memory, and even extend our life span. 

How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in AI strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network? As Peter Robin Hiesinger argues, "the information problem" underlies both fields. 

We live in an incredible period in history. The computer revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before. But our love of computers should not cloud our thinking about their limitations. The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted. 

In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally - hiring, driving, paying bills, even choosing romantic partners - that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology.