Human Machine Learning

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Human and Machine Learning

Author : Jianlong Zhou
Publisher : Springer
ISBN 13 : 3319904035
Total Pages : 485 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Human and Machine Learning by : Jianlong Zhou

Download or read book Human and Machine Learning written by Jianlong Zhou and published by Springer. This book was released on 2018-06-07 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.

Human-in-the-Loop Machine Learning

Author : Robert Munro
Publisher : Simon and Schuster
ISBN 13 : 1617296740
Total Pages : 422 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Human-in-the-Loop Machine Learning by : Robert Munro

Download or read book Human-in-the-Loop Machine Learning written by Robert Munro and published by Simon and Schuster. This book was released on 2021-07-20 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.

Human + Machine

Author : Paul R. Daugherty
Publisher : Harvard Business Press
ISBN 13 : 1633693872
Total Pages : 264 pages
Book Rating : 4.6/5 (336 download)

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Book Synopsis Human + Machine by : Paul R. Daugherty

Download or read book Human + Machine written by Paul R. Daugherty and published by Harvard Business Press. This book was released on 2018-03-20 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.

Deep Medicine

Author : Eric Topol
Publisher : Basic Books
ISBN 13 : 1541644646
Total Pages : 373 pages
Book Rating : 4.5/5 (416 download)

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Book Synopsis Deep Medicine by : Eric Topol

Download or read book Deep Medicine written by Eric Topol and published by Basic Books. This book was released on 2019-03-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Artificial Intelligence

Author : Melanie Mitchell
Publisher : Farrar, Straus and Giroux
ISBN 13 : 0374715238
Total Pages : 336 pages
Book Rating : 4.3/5 (747 download)

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Book Synopsis Artificial Intelligence by : Melanie Mitchell

Download or read book Artificial Intelligence written by Melanie Mitchell and published by Farrar, Straus and Giroux. This book was released on 2019-10-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

The Alignment Problem: Machine Learning and Human Values

Author : Brian Christian
Publisher : W. W. Norton & Company
ISBN 13 : 039363583X
Total Pages : 459 pages
Book Rating : 4.3/5 (936 download)

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Book Synopsis The Alignment Problem: Machine Learning and Human Values by : Brian Christian

Download or read book The Alignment Problem: Machine Learning and Human Values written by Brian Christian and published by W. W. Norton & Company. This book was released on 2020-10-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.

Human-Machine Shared Contexts

Author : William Lawless
Publisher : Academic Press
ISBN 13 : 0128223790
Total Pages : 448 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Human-Machine Shared Contexts by : William Lawless

Download or read book Human-Machine Shared Contexts written by William Lawless and published by Academic Press. This book was released on 2020-06-10 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of “shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. Discusses the foundations, metrics, and applications of human-machine systems Considers advances and challenges in the performance of autonomous machines and teams of humans Debates theoretical human-machine ecosystem models and what happens when machines malfunction

A Human's Guide to Machine Intelligence

Author : Kartik Hosanagar
Publisher : Penguin
ISBN 13 : 0525560904
Total Pages : 274 pages
Book Rating : 4.5/5 (255 download)

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Book Synopsis A Human's Guide to Machine Intelligence by : Kartik Hosanagar

Download or read book A Human's Guide to Machine Intelligence written by Kartik Hosanagar and published by Penguin. This book was released on 2020-03-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. 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. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Human and Machine Consciousness

Author : David Gamez
Publisher : Open Book Publishers
ISBN 13 : 1783743018
Total Pages : 205 pages
Book Rating : 4.7/5 (837 download)

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Book Synopsis Human and Machine Consciousness by : David Gamez

Download or read book Human and Machine Consciousness written by David Gamez and published by Open Book Publishers. This book was released on 2018-03-07 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consciousness is widely perceived as one of the most fundamental, interesting and difficult problems of our time. However, we still know next to nothing about the relationship between consciousness and the brain and we can only speculate about the consciousness of animals and machines. Human and Machine Consciousness presents a new foundation for the scientific study of consciousness. It sets out a bold interpretation of consciousness that neutralizes the philosophical problems and explains how we can make scientific predictions about the consciousness of animals, brain-damaged patients and machines. Gamez interprets the scientific study of consciousness as a search for mathematical theories that map between measurements of consciousness and measurements of the physical world. We can use artificial intelligence to discover these theories and they could make accurate predictions about the consciousness of humans, animals and artificial systems. Human and Machine Consciousness also provides original insights into unusual conscious experiences, such as hallucinations, religious experiences and out-of-body states, and demonstrates how ‘designer’ states of consciousness could be created in the future. Gamez explains difficult concepts in a clear way that closely engages with scientific research. His punchy, concise prose is packed with vivid examples, making it suitable for the educated general reader as well as philosophers and scientists. Problems are brought to life in colourful illustrations and a helpful summary is given at the end of each chapter. The endnotes provide detailed discussions of individual points and full references to the scientific and philosophical literature.

Working with AI

Author : Thomas H. Davenport
Publisher : MIT Press
ISBN 13 : 0262047241
Total Pages : 312 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Working with AI by : Thomas H. Davenport

Download or read book Working with AI written by Thomas H. Davenport and published by MIT Press. This book was released on 2022-09-27 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.

The Human-Machine Team: How to Create Synergy Between Human and Artificial Intelligence That Will Revolutionize Our World

Author : Brigadier Y.S
Publisher :
ISBN 13 :
Total Pages : 198 pages
Book Rating : 4.7/5 (491 download)

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Book Synopsis The Human-Machine Team: How to Create Synergy Between Human and Artificial Intelligence That Will Revolutionize Our World by : Brigadier Y.S

Download or read book The Human-Machine Team: How to Create Synergy Between Human and Artificial Intelligence That Will Revolutionize Our World written by Brigadier Y.S and published by . This book was released on 2021-05-05 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the world's leading managers in the field of Artificial Intelligence unveils the secrets to creating synergy between human and artificial intelligence that will revolutionize our world. Today, we are merely at the threshold of the acceleration of the Digital Era. But what will happen in the coming years, when artificial intelligence (AI) is going to dramatically change the world? A machine can use big data to generate information better than humans. However, a machine can't understand context, doesn't have feelings or ethics, and can't think 'out of the box'. Therefore, rather than prioritize between humans and machines, we should create The Human-Machine Team, which will combine human intelligence and artificial intelligence, creating a 'super cognition'. Brigadier General Y.S, an expert analyst, technology director, commander of an elite intelligence unit, and winner of the prestigious Israel Defense Prize for his artificial intelligence based anti-terrorism project, wrote his book, The Human-Machine Team, to address how the combination between human and artificial intelligence can solve national security challenges and threats, lead to victory in war, and be a growth engine for humankind. He offers a new perspective on how to lead nations and organizations to the future that has already become the present.

Human-Like Machine Intelligence

Author : Stephen Muggleton
Publisher : Oxford University Press
ISBN 13 : 0198862539
Total Pages : 533 pages
Book Rating : 4.1/5 (988 download)

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Book Synopsis Human-Like Machine Intelligence by : Stephen Muggleton

Download or read book Human-Like Machine Intelligence written by Stephen Muggleton and published by Oxford University Press. This book was released on 2021 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, authored by an array of internationally recognised researchers, is of direct relevance to all those involved in Academia and Industry wanting to obtain insights into the topics at the forefront of the revolution in Artificial Intelligence and Cognitive Science.

Augmented Intelligence

Author : Judith Hurwitz
Publisher : CRC Press
ISBN 13 : 0429589719
Total Pages : 155 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Augmented Intelligence by : Judith Hurwitz

Download or read book Augmented Intelligence written by Judith Hurwitz and published by CRC Press. This book was released on 2019-12-13 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: The AI revolution is moving at a breakneck speed. Organizations are beginning to invest in innovative ways to monetize their data through the use of artificial intelligence. Businesses need to understand the reality of AI. To be successful, it is imperative that organizations understand that augmented intelligence is the secret to success. Augmented Intelligence: The Business Power of Human–Machine Collaboration is about the process of combining human and machine intelligence. This book provides business leaders and AI data experts with an understanding of the value of augmented intelligence and its ability to help win competitive markets. This book focuses on the requirement to clearly manage the foundational data used for augmented intelligence. It focuses on the risks of improper data use and delves into the ethics and governance of data in the era of augmented intelligence. In this book, we explore the difference between weak augmentation that is based on automating well understood processes and strong augmentation that is designed to rethink business processes through the inclusion of data, AI and machine learning. What experts are saying about Augmented Intelligence "The book you are about to read is of great importance because we increasingly rely on machine learning and AI. Therefore, it is critical that we understand the ability to create an environment in which businesses can have the tools to understand data from a holistic perspective. What is imperative is to be able to make better decisions based on an understanding of the behavior and thinking of our customers so that we can take the best next action. This book provides a clear understanding of the impact of augmented intelligence on both society and business."—Tsvi Gal, Managing Director, Enterprise Technology and Services, Morgan Stanley "Our mission has always been to help clients apply AI to better predict and shape future outcomes, empower higher value work, and automate how work gets done. I have always said, ’AI will not replace managers, but managers who use AI will replace managers who don't.’ This book delves into the real value that AI promises, to augment existing human intelligence, and in the process, dispels some of the myths around AI and its intended purpose."—Rob Thomas, General Manager, Data and AI, IBM

Human-Machine Learning

Author : Corinne Schillizzi
Publisher : Corinne Schillizzi
ISBN 13 :
Total Pages : 202 pages
Book Rating : 4./5 ( download)

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Book Synopsis Human-Machine Learning by : Corinne Schillizzi

Download or read book Human-Machine Learning written by Corinne Schillizzi and published by Corinne Schillizzi. This book was released on 2023-10-22 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: ...This book explores AI ethics, surveys system thinking, and offers actionable tactics for aligning with engineering and product teams in the tech realm. Its engaging narrative provides a roadmap for iterative "designing in loops" product development in today’s AI-driven industry. — John Maeda, Author of How To Speak Machine Forget to design a solution once and for all - with Machine Learning, it simply doesn’t work! Since learning is inherently dynamic, designers must harness feedback loops to create solutions that adapt to changing environments and data. Discover how to work backward from humans, partner with ML field experts, build effective feedback loop mechanisms and design data-aware interactions. With Machine Learning, designers are crucial in keeping humans and society at the center. The book guides the reader in understanding the challenges and peculiarities of designing these systems. It provides methods and tools to apply a human-centered approach to problem-framing and solving. 'Human-Machine learning’ is a design paradigm that enables humans and machines to learn and adapt. Shifting our perspective from a growth to an adaptive mindset, the book presents the Human-Machine Learning paradigm as a way to tackle complex problems and drive positive change systemically. Six things you will find in this book: 1. The role of feedback in shaping human and machine learning 2. The role of designers in working backward from human needs in ML projects 3. How to design with and for data 4. How to design feedback loops at three levels of interactions: individual, organizational, and societal 5. A systemic perspective on designing with ML with a humanity-centered approach 6. How to design for Human-Machine Continual Learning

Human-Machine Reconfigurations

Author : Lucille Alice Suchman
Publisher : Cambridge University Press
ISBN 13 : 9780521675888
Total Pages : 332 pages
Book Rating : 4.6/5 (758 download)

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Book Synopsis Human-Machine Reconfigurations by : Lucille Alice Suchman

Download or read book Human-Machine Reconfigurations written by Lucille Alice Suchman and published by Cambridge University Press. This book was released on 2007 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher description

Human/Machine

Author : Daniel Newman
Publisher : Kogan Page Publishers
ISBN 13 : 074948425X
Total Pages : 265 pages
Book Rating : 4.7/5 (494 download)

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Book Synopsis Human/Machine by : Daniel Newman

Download or read book Human/Machine written by Daniel Newman and published by Kogan Page Publishers. This book was released on 2019-07-03 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Will the workplace of the future be overrun by machines and robots? Are the new frontiers of artificial intelligence (AI) on the cusp of dethroning us in efficiency, intelligence and innovative potential? Automation and AI will augment our human world and potential. The winners of the future of work are those that harness the power of machines to their advantage. Human/Machine is the only guide you need to understand the fourth industrial revolution. It sets out a road map to the challenges ahead, but also unlocks the wondrous opportunities that it offers. Human/Machine explores how we will work symbiotically with machines, detailing how institutions, companies, individuals and education providers will evolve to integrate seamlessly with new technologies. With exclusive case studies, this book offers a glimpse into the future and details how top companies are already thriving on this very special relationship. From gamification in job training to project management teams integrated with bots and predictive technologies that fix problems in the supply chain before they happen, the authors deliver a powerful manifesto for the adoption and celebration of automation and AI. In a much more fluid, skills-based economy, we will all need to prove our worth and future-proof our skills base. This book offers a blueprint to avoid being left behind and unearth the opportunities unique to human-machine partnership ecosystems.

Lifelong Machine Learning, Second Edition

Author : Zhiyuan Sun
Publisher : Springer Nature
ISBN 13 : 3031015819
Total Pages : 187 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Lifelong Machine Learning, Second Edition by : Zhiyuan Sun

Download or read book Lifelong Machine Learning, Second Edition written by Zhiyuan Sun and published by Springer Nature. This book was released on 2022-06-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.