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Integrated Human-Machine Intelligence: Beyond Artificial Intelligence focuses on deep situational awareness in human-computer integration, covering the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. The book also details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making to provide basic theoretical support for a development strategy in the field of national intelligence. Sections focus on describing a new form of intelligence produced by the interaction of human, machine and environmental systems which will become the next generation of AI. From the perspective of deep situational awareness in human-computer integration, the book studies the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. In addition, it details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making, so as to provide basic theoretical support for a development strategy in the field of national intelligence. - Summarizes the key ideas of computing, perception, cognition and insight into intelligence - Provides intelligent omni-directional multi-angle stereo understanding, including the relevant basic concepts and the realization process of intelligence - Proposes the concept, definition and framework of deep situational awareness, which is conducive to the realization and development of man-machine integrated intelligent systems - Outlines the essence of intelligence, such as facts and values, reason and sensibility, contradiction and balance, etc.
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.
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
This prescient Research Handbook analyses the ethical development of Artificial Intelligence systems through the prism of meaningful human control. It encapsulates a multitude of disciplinary lenses including technical, philosophical and legal, making a crucial contribution to the ongoing discourse about control and responsibility in the field of AI.
The book presents selected research papers from the 2023 Chinese Intelligent Automation Conference (CIAC2023), held in Nanjing, China, on October 2-5, 2023. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT, and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.
Get started with artificial intelligence in your business. This book will help you understand AI, its implications, and how to adopt a strategy that is rational, relevant, and practical. Beyond the buzzwords and the technology complexities, organizations are struggling to understand what AI means for their industry and how they can start their journey. How to Compete in the Age of Artificial Intelligence is not a book about complex formulas or solution architectures. It goes deeper into explaining the meaning and relevance of AI for your business. You will learn how to apply AI thinking across enterprise functions, including disruptive technologies such as IoT, Blockchain, and cloud, and transform your organization. What You'll Learn: Know how to spot AI opportunities and establish the right organizational imperatives to grow your business ; Understand AI in the context of changing business dynamics and the workforce/skills required to succeed ; Discover how to apply AI thinking across enterprise functions, from the boardroom to cybersecurity, IoT, IT operations, policies, and implement a sustainable and integrated human-machine collaboration strategy.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
This completely revised edition, of the Handbook of Human-Computer Interaction, of which 80% of the content is new, reflects the developments in the field since the publication of the first edition in 1988. The handbook is concerned with principles for design of the Human-Computer Interface, and has both academic and practical purposes. It is intended to summarize the research and provide recommendations for how the information can be used by designers of computer systems. The volume may also be used as a reference for teaching and research. Professionals who are involved in design of HCI will find this volume indispensable, including: computer scientists, cognitive scientists, experimental psychologists, human factors professionals, interface designers, systems engineers, managers and executives working with systems development. Much of the information in the handbook may also be generalized to apply to areas outside the traditional field of HCI.
Please see Volume I for a full description.