Summary Of Ajay Agrawal Joshua Gans Avi Goldfarb S Prediction Machines
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Summary Of Ajay Agrawal Joshua Gans Avi Goldfarb S Prediction Machines
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Author : Everest Media,
language : en
Publisher: Everest Media LLC
Release Date : 2022-06-10T22:59:00Z
Summary Of Ajay Agrawal Joshua Gans Avi Goldfarb S Prediction Machines written by Everest Media, and has been published by Everest Media LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10T22:59:00Z with Computers categories.
Please note: This is a companion version & not the original book. Sample Book Insights: #1 AI is everywhere. It is in our phones, cars, shopping experiences, romantic matchmaking, hospitals, banks, and all over the media. No wonder corporate directors, CEOs, vice presidents, managers, team leaders, and entrepreneurs are anxiously racing to learn about AI: it is about to fundamentally change their businesses. #2 The new wave of artificial intelligence does not bring us intelligence, but rather a critical component of intelligence: prediction. Each startup in our lab is based on the benefits of better prediction. We provide you with an understanding of AI’s impact on management and decisions, as well as on the economy. #3 Prediction Machines is not a recipe for success in the AI economy. Instead, it emphasizes trade-offs. More data means less privacy. More speed means less accuracy. More autonomy means less control. #4 The current wave of advances in artificial intelligence doesn’t actually bring us intelligence, but instead a critical component of intelligence: prediction. Prediction is a central input into decision-making.
Prediction Machines Updated And Expanded
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Author : Ajay Agrawal
language : en
Publisher: Harvard Business Press
Release Date : 2022-11-15
Prediction Machines Updated And Expanded written by Ajay Agrawal and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Business & Economics categories.
Named one of "The five best books to understand AI" by The Economist The impact AI will have is profound, but the economic framework for understanding it is surprisingly simple. Artificial intelligence seems to do the impossible, magically bringing machines to life—driving cars, trading stocks, and teaching children. But facing the sea change that AI brings can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many either cower in fear or predict an impossibly sunny future. But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this masterful stroke, they lift the curtain on the AI-is-magic hype and provide economic clarity about the AI revolution as well as a basis for action by executives, policy makers, investors, and entrepreneurs. In this new, updated edition, the authors illustrate how, when AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions amid uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity—operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business strategies to compete. The authors reset the context, describing the striking impact the book has had and how its argument and its implications are playing out in the real world. And in new material, they explain how prediction fits into decision-making processes and how foundational technologies such as quantum computing will impact business choices. Penetrating, insightful, and practical, Prediction Machines will help you navigate the changes on the horizon.
The Economics Of Artificial Intelligence
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Author : Ajay Agrawal
language : en
Publisher: University of Chicago Press
Release Date : 2024-03-05
The Economics Of Artificial Intelligence written by Ajay Agrawal and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-05 with Business & Economics categories.
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Practical Time Series Analysis
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Author : Aileen Nielsen
language : en
Publisher: O'Reilly Media
Release Date : 2019-09-20
Practical Time Series Analysis written by Aileen Nielsen and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
Our Robots Ourselves
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Author : David A. Mindell
language : en
Publisher: Penguin
Release Date : 2015-10-13
Our Robots Ourselves written by David A. Mindell and has been published by Penguin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-13 with Business & Economics categories.
“[An] essential book… it is required reading as we seriously engage one of the most important debates of our time.”—Sherry Turkle, author of Reclaiming Conversation: The Power of Talk in a Digital Age From drones to Mars rovers—an exploration of the most innovative use of robots today and a provocative argument for the crucial role of humans in our increasingly technological future. In Our Robots, Ourselves, David Mindell offers a fascinating behind-the-scenes look at the cutting edge of robotics today, debunking commonly held myths and exploring the rapidly changing relationships between humans and machines. Drawing on firsthand experience, extensive interviews, and the latest research from MIT and elsewhere, Mindell takes us to extreme environments—high atmosphere, deep ocean, and outer space—to reveal where the most advanced robotics already exist. In these environments, scientists use robots to discover new information about ancient civilizations, to map some of the world’s largest geological features, and even to “commute” to Mars to conduct daily experiments. But these tools of air, sea, and space also forecast the dangers, ethical quandaries, and unintended consequences of a future in which robotics and automation suffuse our everyday lives. Mindell argues that the stark lines we’ve drawn between human and not human, manual and automated, aren’t helpful for understanding our relationship with robotics. Brilliantly researched and accessibly written, Our Robots, Ourselves clarifies misconceptions about the autonomous robot, offering instead a hopeful message about what he calls “rich human presence” at the center of the technological landscape we are now creating.
The Deep Learning Revolution
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Author : Terrence J. Sejnowski
language : en
Publisher: MIT Press
Release Date : 2018-10-23
The Deep Learning Revolution written by Terrence J. Sejnowski and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-23 with Computers categories.
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. 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. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Power And Prediction
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Author : Ajay Agrawal
language : en
Publisher: Harvard Business Press
Release Date : 2022-11-15
Power And Prediction written by Ajay Agrawal and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Business & Economics categories.
Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines can help you prepare. Artificial intelligence (AI) has impacted many industries around the world—banking and finance, pharmaceuticals, automotive, medical technology, manufacturing, and retail. But it has only just begun its odyssey toward cheaper, better, and faster predictions that drive strategic business decisions. When prediction is taken to the max, industries transform, and with such transformation comes disruption. What is at the root of this? In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it. The rise of AI is shifting prediction from humans to machines, relieving people from this cognitive load while increasing the speed and accuracy of decisions. This sets the stage for a flourishing of new decisions and has profound implications for system-level innovation. Redesigning systems of interdependent decisions takes time—many industries are in the quiet before the storm—but when these new systems emerge, they can be disruptive on a global scale. Decision-making confers power. In industry, power confers profits; in society, power confers control. This process will have winners and losers, and the authors show how businesses can leverage opportunities, as well as protect their positions. Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policymaker on how to make the coming AI disruptions work for you rather than against you.
Programming Collective Intelligence
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Author : Toby Segaran
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2007-08-16
Programming Collective Intelligence written by Toby Segaran and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-16 with Computers categories.
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect
The Butterfly Defect
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Author : Ian Goldin
language : en
Publisher: Princeton University Press
Release Date : 2015-10-20
The Butterfly Defect written by Ian Goldin and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-20 with Political Science categories.
How to better manage systemic risks—from cyber attacks and pandemics to financial crises and climate change—in a globalized world The Butterfly Defect addresses the widening gap between the new systemic risks generated by globalization and their effective management. It shows how the dynamics of turbo-charged globalization has the potential and power to destabilize our societies. Drawing on the latest insights from a wide variety of disciplines, Ian Goldin and Mike Mariathasan provide practical guidance for how governments, businesses, and individuals can better manage globalization and risk. Goldin and Mariathasan demonstrate that systemic risk issues are now endemic everywhere—in supply chains, pandemics, infrastructure, ecology and climate change, economics, and politics. Unless we address these concerns, they will lead to greater protectionism, xenophobia, nationalism, and, inevitably, deglobalization, rising inequality, conflict, and slower growth. The Butterfly Defect shows that mitigating uncertainty and risk in an interconnected world is an essential task for our future.
Intelligent Decision Making An Ai Based Approach
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Author : Gloria Phillips-Wren
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-04
Intelligent Decision Making An Ai Based Approach written by Gloria Phillips-Wren and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-04 with Mathematics categories.
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.