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Edge AI by Xiaofei Wang,Yiwen Han,Victor C. M. Leung,Dusit Niyato,Xueqiang Yan,Xu Chen Pdf
As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.
Artificial Intelligence for Cloud and Edge Computing by Sanjay Misra,Amit Kumar Tyagi,Vincenzo Piuri,Lalit Garg Pdf
This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.
Mobile Edge Artificial Intelligence by Yuanming Shi,Kai Yang,Zhanpeng Yang,Yong Zhou Pdf
Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms is demonstrated, along with their abilities to make low-latency, reliable and private intelligent decisions at network edge. With the availability of massive datasets, high performance computing platforms, sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains. As such, intelligent wireless networks will be designed to leverage advanced wireless communications and mobile computing technologies to support AI-enabled applications at various edge mobile devices with limited communication, computation, hardware and energy resources. Presents advanced key enabling techniques, including model compression, wireless MapReduce and wireless cooperative transmission Provides advanced 6G wireless techniques, including over-the-air computation and reconfigurable intelligent surface Includes principles for designing communication-efficient edge inference systems, communication-efficient training systems, and communication-efficient optimization algorithms for edge machine learning
An unprecedented high-level master narrative of America's intelligence wars, demonstrating in a time of new threats that espionage and the search for facts are essential to our democracy For General Michael Hayden, playing to the edge means playing so close to the line that you get chalk dust on your cleats. Otherwise, by playing back, you may protect yourself, but you will be less successful in protecting America. "Play to the edge" was Hayden's guiding principle when he ran the National Security Agency, and it remained so when he ran CIA. In his view, many shortsighted and uninformed people are quick to criticize, and this book will give them much to chew on but little easy comfort; it is an unapologetic insider's look told from the perspective of the people who faced awesome responsibilities head on, in the moment. How did American intelligence respond to terrorism, a major war and the most sweeping technological revolution in the last 500 years? What was NSA before 9/11 and how did it change in its aftermath? Why did NSA begin the controversial terrorist surveillance program that included the acquisition of domestic phone records? What else was set in motion during this period that formed the backdrop for the infamous Snowden revelations in 2013? As Director of CIA in the last three years of the Bush administration, Hayden had to deal with the rendition, detention and interrogation program as bequeathed to him by his predecessors. He also had to ramp up the agency to support its role in the targeted killing program that began to dramatically increase in July 2008. This was a time of great crisis at CIA, and some agency veterans have credited Hayden with actually saving the agency. He himself won't go that far, but he freely acknowledges that CIA helped turn the American security establishment into the most effective killing machine in the history of armed conflict. For 10 years, then, General Michael Hayden was a participant in some of the most telling events in the annals of American national security. General Hayden's goals are in writing this book are simple and unwavering: No apologies. No excuses. Just what happened. And why. As he writes, "There is a story here that deserves to be told, without varnish and without spin. My view is my view, and others will certainly have different perspectives, but this view deserves to be told to create as complete a history as possible of these turbulent times. I bear no grudges, or at least not many, but I do want this to be a straightforward and readable history for that slice of the American population who depend on and appreciate intelligence, but who do not have the time to master its many obscure characteristics."
Author : Steven J. Stein,Howard E. Book Publisher : John Wiley & Sons Page : 375 pages File Size : 49,7 Mb Release : 2011-04-26 Category : Business & Economics ISBN : 9780470681619
REVISED AND UPDAT ED WITH NEW RESEARCH INTO EQ AND PERSONAL AND CAREER SUCCESS What is the formula for success at your job? As a spouse? A parent? A Little League baseball coach or behind the bench of a minor hockey team? What does it take to get ahead? To separate yourself from the competition? To lead a less stressful and happier existence? To be fulfilled in personal and professional pursuits? What is the most important dynamic of your makeup? Is it your A) intelligence quotient? or B) emotional quotient? If you picked "A", you are partly correct. Your intelligence quotient can be a predictor of things such as academic achievement. But your IQ is fixed and unchangeable. The real key to personal and professional growth is your emotional intelligence quotient, which you can nurture and develop by learning more about EQ from the international bestseller The EQ Edge. Authors Steven J. Stein and Howard E. Book show you how the dynamic of emotional intelligence works. By understanding EQ, you can build more meaningful relationships, boost your confidence and optimism, and respond to challenges with enthusiasm-all of which are essential ingredients of success. The EQ Edge offers fascinating-and sometimes surprising-insights into what it takes to be a top law-enforcement officer, lawyer, school principal, student, doctor, dentist or CEO. You will learn what the top EQ factors are across many different kinds of jobs, from business managers and customer service representatives to HR professionals and public servants. The EQ Edge will help you determine which personnel are the right fit for job opportunities and who among your staff are the most promising leaders and drivers of your business. And because all of us have other roles-parent, spouse, caregiver to aging parents, neighbor, friend-The EQ Edge also describes how everyone can be more successful in these relationships. "Finally, a practical and usable guide to what emotional intelligence is all about. This book peels the onion on what EQ really is and teaches the reader to assess their own EQ and how to increase it. This is the holy grail for career success."—Michael Feiner, Professor, Columbia Graduate School of Business and author of The Feiner Points of Leadership
Artificial Intelligence and Machine Learning for EDGE Computing by Rajiv Pandey,Sunil Kumar Khatri,Neeraj Kumar Singh,Parul Verma Pdf
Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
Edge Computing and Computational Intelligence Paradigms for the IoT by Nagarajan, G.,Minu, R.I. Pdf
Edge computing is focused on devices and technologies that are attached to the internet of things (IoT). Identifying IoT use across a range of industries and measuring strategic values helps identify what technologies to pursue and can avoid wasted resources on deployments with limited values. Edge Computing and Computational Intelligence Paradigms for the IoT is a critical research book that provides a complete insight on the recent advancements and integration of intelligence in IoT. This book highlights various topics such as disaster prediction, governance, and healthcare. It is an excellent resource for researchers, working professionals, academicians, policymakers, and defense companies.
Edge Intelligence in the Making by Sen Lin,Zhi Zhou,Zhaofeng Zhang,Xu Chen,Junshan Zhang Pdf
With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data. Indeed, the marriage of edge computing and AI has resulted in innovative solutions, namely edge intelligence or edge AI. Nevertheless, research and practice on this emerging inter-disciplinary field is still in its infancy stage. To facilitate the dissemination of the recent advances in edge intelligence in both academia and industry, this book conducts a comprehensive and detailed survey of the recent research efforts and also showcases the authors' own research progress on edge intelligence. Specifically, the book first reviews the background and present motivation for AI running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence. This emerging interdisciplinary field offers many open problems and yet also tremendous opportunities, and this book only touches the tip of iceberg. Hopefully, this book will elicit escalating attention, stimulate fruitful discussions, and open new directions on edge intelligence.
Fog Computing in the Internet of Things by Amir M. Rahmani,Pasi Liljeberg,Jürgo-Sören Preden,Axel Jantsch Pdf
This book describes state-of-the-art approaches to Fog Computing, including the background of innovations achieved in recent years. Coverage includes various aspects of fog computing architectures for Internet of Things, driving reasons, variations and case studies. The authors discuss in detail key topics, such as meeting low latency and real-time requirements of applications, interoperability, federation and heterogeneous computing, energy efficiency and mobility, fog and cloud interplay, geo-distribution and location awareness, and case studies in healthcare and smart space applications.
Artificial Intelligence in Financial Markets by Christian L. Dunis,Peter W. Middleton,Andreas Karathanasopolous,Konstantinos Theofilatos Pdf
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
The ability to find and analyse information quickly and accurately can give a business an edge over its competitors. The authors show how to learn the skills that help transform widely accessible raw data into useful knowledge, by adapting techniques used by such organizations as the CIA.
Right now, vast amounts of time and money are being invested all round the world in building global brands and organisations. But where are the global leaders who will lead them? Leaders who can cross cultural boundaries: between east and west, and north and south; between faiths and beliefs; between public, private and voluntary sectors; and between the generations? Where are the leaders who can lead in what Julia calls the "magnet cities†? of the world: where the world's most talented young people will convene? Because these people will simply turn their backs on bosses who demand that their teams think and behave alike. The race is on to develop leaders with CQ. And this book is designed to give readers a decisive head start. In the process, Julia has spoken to leaders all round the world, and invited them to tell their own CQ stories: successful and disastrous, serious and funny, poignant, pragmatic and often highly personal. The result is surprising, challenging and frequently uncomfortable (there is no simplistic advice here about how to exchange business cards in the correct local manner). But the ambition is huge. As is the prize for the next generation of leaders who see the opportunity she outlines - and grasp it.
Edge Intelligence by Javid Taheri,Schahram Dustdar,Albert Zomaya,Shuiguang Deng Pdf
This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.
Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review.
Next Generation Internet of Things by Vermesan, Ovidiu,Bacquet, Joël Pdf
This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment. The text builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment. The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual and augmented reality (VR/AR), and AI transformation. Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats. The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications. The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications. Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems. New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure. The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.