Ai Renaissance Machines
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| Author | : Erik J. Larson |
| Publisher | : Harvard University Press |
| Total Pages | : 321 |
| Release | : 2021-04-06 |
| Genre | : Computers |
| ISBN | : 0674983513 |
“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.
| Author | : Jeremy Kahn |
| Publisher | : Simon and Schuster |
| Total Pages | : 336 |
| Release | : 2024-07-09 |
| Genre | : Business & Economics |
| ISBN | : 1668053322 |
A Fortune magazine journalist draws on his expertise and extensive contacts among the companies and scientists at the forefront of artificial intelligence to offer dramatic predictions of AI’s impact over the next decade, from reshaping our economy and the way we work, learn, and create to unknitting our social fabric, jeopardizing our democracy, and fundamentally altering the way we think. Within the next five years, Jeremy Kahn predicts, AI will disrupt almost every industry and enterprise, with vastly increased efficiency and productivity. It will restructure the workforce, making AI copilots a must for every knowledge worker. It will revamp education, meaning children around the world can have personal, portable tutors. It will revolutionize health care, making individualized, targeted pharmaceuticals more affordable. It will compel us to reimagine how we make art, compose music, and write and publish books. The potential of generative AI to extend our skills, talents, and creativity as humans is undeniably exciting and promising. But while this new technology has a bright future, it also casts a dark and fearful shadow. AI will provoke pervasive, disruptive, potentially devastating knock-on effects. Leveraging his unrivaled access to the leaders, scientists, futurists, and others who are making AI a reality, Kahn will argue that if not carefully designed and vigilantly regulated AI will deepen income inequality, depressing wages while imposing winner-take-all markets across much of the economy. AI risks undermining democracy, as truth is overtaken by misinformation, racial bias, and harmful stereotypes. Continuing a process begun by the internet, AI will rewire our brains, likely inhibiting our ability to think critically, to remember, and even to get along with one another—unless we all take decisive action to prevent this from happening. Much as Michael Lewis’s classic The New New Thing offered a prescient, insightful, and eminently readable account of life inside the dot-com bubble, Mastering AI delivers much-needed guidance for anyone eager to understand the AI boom—and what comes next.
| Author | : Niklas Hageback |
| Publisher | : CRC Press |
| Total Pages | : 69 |
| Release | : 2021-08-25 |
| Genre | : Art |
| ISBN | : 1000433056 |
AI for Arts is a book for anyone fascinated by the man–machine connection, an unstoppable evolution that is intertwining us with technology in an ever-greater degree, and where there is an increasing concern that it will be technology that comes out on top. Thus, presented here through perhaps its most esoteric form, namely art, this unfolding conundrum is brought to its apex. What is left of us humans if artificial intelligence also surpasses us when it comes to art? The articulation of an artificial intelligence art manifesto is long overdue, so hopefully this book can fill a gap that will have repercussions not only for aesthetic and philosophical considerations but possibly more so for the development of artificial intelligence.
| Author | : Gregory Zuckerman |
| Publisher | : Penguin |
| Total Pages | : 401 |
| Release | : 2019-11-05 |
| Genre | : Business & Economics |
| ISBN | : 0735217998 |
NEW YORK TIMES BESTSELLER Shortlisted for the Financial Times/McKinsey Business Book of the Year Award The unbelievable story of a secretive mathematician who pioneered the era of the algorithm--and made $23 billion doing it. Jim Simons is the greatest money maker in modern financial history. No other investor--Warren Buffett, Peter Lynch, Ray Dalio, Steve Cohen, or George Soros--can touch his record. Since 1988, Renaissance's signature Medallion fund has generated average annual returns of 66 percent. The firm has earned profits of more than $100 billion; Simons is worth twenty-three billion dollars. Drawing on unprecedented access to Simons and dozens of current and former employees, Zuckerman, a veteran Wall Street Journal investigative reporter, tells the gripping story of how a world-class mathematician and former code breaker mastered the market. Simons pioneered a data-driven, algorithmic approach that's sweeping the world. As Renaissance became a market force, its executives began influencing the world beyond finance. Simons became a major figure in scientific research, education, and liberal politics. Senior executive Robert Mercer is more responsible than anyone else for the Trump presidency, placing Steve Bannon in the campaign and funding Trump's victorious 2016 effort. Mercer also impacted the campaign behind Brexit. The Man Who Solved the Market is a portrait of a modern-day Midas who remade markets in his own image, but failed to anticipate how his success would impact his firm and his country. It's also a story of what Simons's revolution means for the rest of us.
| Author | : Jon Adams |
| Publisher | : Green Mountain Computing |
| Total Pages | : 181 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
Dive into the pioneering realm of Artificial General Intelligence with Jon Adams'sAI Foundations of Artificial General Intelligence (AGI), the first installment of the enlightening Foundations Of series. This groundbreaking book serves as a comprehensive guide to the evolving field of AI, offering a deep dive into the quest for Artificial General Intelligence (AGI) – a frontier of technology aiming to create machines that rival human intelligence in their versatility and creativity. Structured in a reader-friendly format, this book covers an impressive array of topics: The Genesis of AI: Explore the origins and evolution of artificial intelligence, setting the stage for a journey towards AGI. Understanding Machine Learning: Get to grips with the core concepts and techniques that fuel the growth of AI. Neural Networks and Deep Learning: Delve into the architectures that mimic the human brain's functionality. Cognitive Architectures – A Blueprint for AGI: Understand the frameworks designed to support the development of AGI. Narrow AI vs General AI: Learn about the differences between AI for specific tasks and the envisioned AGI capable of human-like reasoning. Defining Human-Like Intelligence: Investigate what it means for a machine to possess intelligence indistinguishable from humans. Computer Science Meets Neuroscience: Discover the intersection between computational models and the complexities of the human brain. Challenges in Replicating Human Thought: Examine the hurdles in simulating human cognitive processes. Toward the Future of AGI: Speculate on the potential directions and implications of achieving AGI. AGI and Human Identity – Redefining the Species: Reflect on how AGI could transform our understanding of human identity. Preempting Skynet – Safeguarding Against AGI Risks: Address the ethical considerations and safety measures in the development of AGI. AI Foundations of AGI is meticulously crafted for both novices and seasoned enthusiasts of artificial intelligence. Adams simplifies complex concepts without sacrificing depth, making advanced topics in AI and AGI accessible to all. This book not only sheds light on the technical aspects of AI development but also encourages readers to ponder the philosophical implications of creating machines with human-like intelligence. Whether you're a student, professional, or simply curious about the future of AI, this book offers valuable insights into the ambitious goal of achieving AGI. Join Jon Adams on a captivating exploration of AI's potential to redefine our world, armed with the knowledge and foresight to navigate the challenges and opportunities that lie ahead.
| Author | : LucieArt |
| Publisher | : Lucie Art |
| Total Pages | : 74 |
| Release | : 2024-08-25 |
| Genre | : Computers |
| ISBN | : |
Unlock the secrets of Artificial Intelligence with “Mastering AI for Beginners: A Step-by-Step Guide to Understanding Artificial Intelligence.” This comprehensive guide provides a clear, engaging introduction to the essentials of AI and how it is transforming the world around us. Whether you’re a complete novice or have a basic understanding of AI, this book is your perfect starting point. Explore core concepts such as machine learning, neural networks, and natural language processing. Discover how AI is revolutionizing various industries, from healthcare and finance to entertainment. “Mastering AI for Beginners” combines practical examples, easy-to-understand explanations, and current case studies to deliver valuable insights. Learn how to harness the power of AI, understand its potential, and navigate its challenges with confidence. Dive into the future of technology and become an informed participant in the AI revolution! Keywords 1. Artificial Intelligence Basics 2. Introduction to Machine Learning 3. Beginner’s Guide to Neural Networks 4. Understanding AI Technology 5. AI in Healthcare and Finance 6. Practical AI Applications 7. Learning AI for Beginners
| Author | : Arun Kumar Rana |
| Publisher | : CRC Press |
| Total Pages | : 271 |
| Release | : 2024-11-22 |
| Genre | : Computers |
| ISBN | : 1040051707 |
This book focuses on the fusion of artificial intelligence and machine learning in advanced image processing, data analysis, and cyber security, as well as compiles and discusses various engineering solutions using various artificial intelligence paradigms. It looks at recent technological advancements and considers how artificial intelligence, machine learning, deep learning, soft computing, and evolutionary computing techniques can be used to design, implement, and optimize advanced image processing, data analysis, and cyber security engineering solutions. It will readers develop the insight required to use the tools of digital imaging to solve new problems. The book is divided into sections that deal with Artificial intelligence and machine learning in medicine and healthcare Intelligent decision-making and analysis technology Machine learning and deep learning for agriculture Artificial intelligence and machine learning for security solutions Automation in image processing Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing, Data Analysis, and Cyber Security offers a selection of chapters on the application of artificial intelligence and machine learning for advanced image processing, data analysis, and cyber security. This book will surely enhance the knowledge of readers interested in these areas.
| Author | : Klaus Mainzer |
| Publisher | : Springer Nature |
| Total Pages | : 284 |
| Release | : 2019-10-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3662597179 |
Everybody knows them. Smartphones that talk to us, wristwatches that record our health data, workflows that organize themselves automatically, cars, airplanes and drones that control themselves, traffic and energy systems with autonomous logistics or robots that explore distant planets are technical examples of a networked world of intelligent systems. Machine learning is dramatically changing our civilization. We rely more and more on efficient algorithms, because otherwise we will not be able to cope with the complexity of our civilizing infrastructure. But how secure are AI algorithms? This challenge is taken up in the 2nd edition: Complex neural networks are fed and trained with huge amounts of data (big data). The number of necessary parameters explodes exponentially. Nobody knows exactly what is going on in these "black boxes". In machine learning we need more explainability and accountability of causes and effects in order to be able to decide ethical and legal questions of responsibility (e.g. in autonomous driving or medicine)! Besides causal learning, we also analyze procedures of tests and verification to get certified AI-programs. Since its inception, AI research has been associated with great visions of the future of mankind. It is already a key technology that will decide the global competition of social systems. "Artificial Intelligence and Responsibility" is another central supplement to the 2nd edition: How should we secure our individual liberty rights in the AI world? This book is a plea for technology design: AI must prove itself as a service in society.
| Author | : Andreas Sudmann |
| Publisher | : transcript Verlag |
| Total Pages | : 335 |
| Release | : 2019-10-31 |
| Genre | : Social Science |
| ISBN | : 3839447194 |
After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms?
| Author | : Cybellium Ltd |
| Publisher | : Cybellium Ltd |
| Total Pages | : 272 |
| Release | : 2023-09-05 |
| Genre | : Computers |
| ISBN | : |
Are you ready to take your AI training skills to the next level? In "Mastering AI Model Training" by Kris Hermans, you'll embark on a transformative journey that will empower you to train highly accurate and efficient artificial intelligence models. Uncover Advanced Techniques and Best Practices As AI continues to revolutionize industries, the ability to train powerful and optimized models is paramount. In this comprehensive guide, Kris Hermans reveals the secrets to mastering AI model training. Explore advanced techniques, cutting-edge algorithms, and industry best practices that will propel your AI training expertise to new heights. Become an Expert in Training AI Models Whether you're a seasoned data scientist or a passionate AI enthusiast, this book provides a structured approach to mastering AI model training. Kris Hermans demystifies complex concepts and presents them in a clear and practical manner. Through real-world examples and hands-on exercises, you'll develop the skills and intuition necessary to train AI models that achieve exceptional performance. From Fundamentals to Advanced Topics "Mastering AI Model Training" covers the full spectrum of AI training, starting from the basics of data preprocessing and feature engineering and progressing to advanced topics such as transfer learning, hyperparameter optimization, and model compression. Gain a deep understanding of different training algorithms and architectures, and learn how to adapt them to various domains and use cases. Optimize Training for Performance and Efficiency Discover strategies for improving model performance, reducing training time, and optimizing resource utilization. Explore techniques for handling large datasets, distributed training, and leveraging hardware accelerators such as GPUs and TPUs. With Kris Hermans as your guide, you'll learn how to train models that deliver superior results while maximizing computational efficiency. Practical Applications and Real-World Case Studies Immerse yourself in practical applications of AI model training across industries such as healthcare, finance, manufacturing, and more. Dive into captivating case studies that demonstrate how AI training is transforming businesses and driving innovation. Gain insights into the challenges faced by organizations and learn how they leverage AI training techniques to gain a competitive edge. Ethical Considerations and Responsible AI With great power comes great responsibility. "Mastering AI Model Training" addresses the ethical considerations associated with AI training and highlights the importance of responsible AI practices. Learn how to mitigate biases, ensure fairness, and navigate ethical challenges to build AI models that are not only accurate and efficient but also ethical and trustworthy.
