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Author: Mike Walsh
Publisher: Page Two
ISBN: 1989025331
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
The greatest threat we face is not robots replacing us, but our reluctance to reinvent ourselves. We live in an age of wonder: cars that drive themselves, devices that anticipate our needs, and robots capable of everything from advanced manufacturing to complex surgery. Automation, algorithms, and AI will transform every facet of daily life, but are we prepared for what that means for the future of work, leadership, and creativity? While many already fear that robots will take their jobs, rapid advancements in machine intelligence raise a far more important question: what is the true potential of human intelligence in the twenty-first century? Futurist and global nomad Mike Walsh has synthesized years of research and interviews with some of the world's top business leaders, AI pioneers and data scientists into a set of 10 principles about what it takes to succeed in the algorithmic age. Across disparate cultures, industries, and timescales, Walsh brings to life the history and future of ideas like probabilistic thinking, machine learning, digital ethics, disruptive innovation, and de-centralized organizations as a foundation for a radically new approach to making decisions, solving problems, and leading people. The Algorithmic Leader offers a hopeful and practical guide for leaders of all types, and organizations of all sizes, to survive and thrive in this era of unprecedented change. By applying Walsh's 10 core principles, readers will be able to design their own journey of personal transformation, harness the power of algorithms, and chart a clear path ahead--for their company, their team, and themselves.
Author: Mike Walsh
Publisher: Page Two
ISBN: 1989025331
Category : Business & Economics
Languages : en
Pages : 0
Get Book Here
Book Description
The greatest threat we face is not robots replacing us, but our reluctance to reinvent ourselves. We live in an age of wonder: cars that drive themselves, devices that anticipate our needs, and robots capable of everything from advanced manufacturing to complex surgery. Automation, algorithms, and AI will transform every facet of daily life, but are we prepared for what that means for the future of work, leadership, and creativity? While many already fear that robots will take their jobs, rapid advancements in machine intelligence raise a far more important question: what is the true potential of human intelligence in the twenty-first century? Futurist and global nomad Mike Walsh has synthesized years of research and interviews with some of the world's top business leaders, AI pioneers and data scientists into a set of 10 principles about what it takes to succeed in the algorithmic age. Across disparate cultures, industries, and timescales, Walsh brings to life the history and future of ideas like probabilistic thinking, machine learning, digital ethics, disruptive innovation, and de-centralized organizations as a foundation for a radically new approach to making decisions, solving problems, and leading people. The Algorithmic Leader offers a hopeful and practical guide for leaders of all types, and organizations of all sizes, to survive and thrive in this era of unprecedented change. By applying Walsh's 10 core principles, readers will be able to design their own journey of personal transformation, harness the power of algorithms, and chart a clear path ahead--for their company, their team, and themselves.
Author: Marco Iansiti
Publisher: Harvard Business Press
ISBN: 1633697630
Category : Business & Economics
Languages : en
Pages : 175
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Book Description
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
Author: Ed Finn
Publisher: MIT Press
ISBN: 0262035928
Category : Computers
Languages : en
Pages : 267
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Book Description
The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek. We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things. If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.
Author: Kartik Hosanagar
Publisher: Viking Adult
ISBN: 0525560882
Category : Business & Economics
Languages : en
Pages : 274
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Book Description
In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives.
Author: Herbert L. Roitblat
Publisher: MIT Press
ISBN: 0262044129
Category : Computers
Languages : en
Pages : 340
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Book Description
Why a new approach is needed in the quest for general artificial intelligence. Since the inception of artificial intelligence, we have been warned about the imminent arrival of computational systems that can replicate human thought processes. Before we know it, computers will become so intelligent that humans will be lucky to kept as pets. And yet, although artificial intelligence has become increasingly sophisticated—with such achievements as driverless cars and humanless chess-playing—computer science has not yet created general artificial intelligence. In Algorithms Are Not Enough, Herbert Roitblat explains how artificial general intelligence may be possible and why a robopocalypse is neither imminent, nor likely. Existing artificial intelligence, Roitblat shows, has been limited to solving path problems, in which the entire problem consists of navigating a path of choices—finding specific solutions to well-structured problems. Human problem-solving, on the other hand, includes problems that consist of ill-structured situations, including the design of problem-solving paths themselves. These are insight problems, and insight is an essential part of intelligence that has not been addressed by computer science. Roitblat draws on cognitive science, including psychology, philosophy, and history, to identify the essential features of intelligence needed to achieve general artificial intelligence. Roitblat describes current computational approaches to intelligence, including the Turing Test, machine learning, and neural networks. He identifies building blocks of natural intelligence, including perception, analogy, ambiguity, common sense, and creativity. General intelligence can create new representations to solve new problems, but current computational intelligence cannot. The human brain, like the computer, uses algorithms; but general intelligence, he argues, is more than algorithmic processes.
Author: Wan Fokkink
Publisher: MIT Press
ISBN: 0262026775
Category : Computers
Languages : en
Pages : 242
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Book Description
A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation.
Author: Florian Jaton
Publisher: MIT Press
ISBN: 0262542145
Category : Computers
Languages : en
Pages : 401
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Book Description
A laboratory study that investigates how algorithms come into existence. Algorithms--often associated with the terms big data, machine learning, or artificial intelligence--underlie the technologies we use every day, and disputes over the consequences, actual or potential, of new algorithms arise regularly. In this book, Florian Jaton offers a new way to study computerized methods, providing an account of where algorithms come from and how they are constituted, investigating the practical activities by which algorithms are progressively assembled rather than what they may suggest or require once they are assembled.
Author: Brennan Pursell
Publisher: Rowman & Littlefield
ISBN: 1538136252
Category : Business & Economics
Languages : en
Pages : 225
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Book Description
From factories to smartphones, Artificial Intelligence is already taking over. Outsmarting AI is not a how-to guide on making AI work, but making it work for YOU to boost profits and productivity. Each development in Artificial Intelligence (AI) technology brings about apprehension and panic for the future of society and for business. We’re bombarded with stories about the impending human-less workplace; it is no longer a question if man can be replaced by machine in certain tasks, but when. However, AI was not manufactured to destroy life as we know it. These emerging technologies were developed and are constantly updating with a particular goal in mind: optimization. AI feeds on data and information to improve outputs and increase potential. With this enhanced productivity, profit and productivity will be sure to follow. Written by Brennan Pursell, a business consultant and professor who hates jargon, and Joshua Walker, an AI pioneer with 18 years of experience in solutions and applications, Outsmarting AI is the first plain-English how-to guide on adapting AI for the non-coding proficient business leader. This book will help readers to Cut through the fog of AI hype See exactly what AI can actually do for people in business Identify the areas of their organization in most need of AI tools Prepare and control their data – AI is useless without it Adopt AI and develop the right culture to support it Track the productivity boost, cost savings, and increased profits Manage and minimize the threat of crippling lawsuits
Author: David De Cremer
Publisher: Harriman House Limited
ISBN: 0857198297
Category : Business & Economics
Languages : en
Pages : 175
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Book Description
With artificial intelligence on the rise, the way we run our organisations will change—and drastically. But what exactly will that future look like? And who will take the leading role: machines or people? In this compelling new book, leading management guru David De Cremer identifies the key areas where algorithms will collide with human skills, and assesses the likely outcomes. Will your next boss be a robot? Can an AI boss display the human qualities that define a good leader: compassion, empathy, imagination, ethics, and strategic awareness? Drawing on his own research findings, and those from thought leaders around the world, the author presents fascinating insights into the challenges that an automated work environment poses for organisations of the future. Leadership by Algorithm offers some startling conclusions that make clear the true nature of the power struggle between man and machine. It also identifies the leadership qualities needed to deal with this struggle most effectively.
Author: Hans-Joachim Böckenhauer
Publisher: Springer Science & Business Media
ISBN: 354071913X
Category : Science
Languages : en
Pages : 395
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Book Description
This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. Figures, chapter summaries, detailed derivations, and examples, are provided.
