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Autonomous Vehicles and Future Mobility presents novel methods for examining the long-term effects on individuals, society, and on the environment for a wide range of forthcoming transport scenarios, such as self-driving vehicles, workplace mobility plans, demand responsive transport analysis, mobility as a service, multi-source transport data provision, and door-to-door mobility. With the development and realization of new mobility options comes change in long-term travel behavior and transport policy. This book addresses these impacts, considering such key areas as the attitude of users towards new services, the consequences of introducing new mobility forms, the impacts of changing work related trips, and more. By examining and contextualizing innovative transport solutions in this rapidly evolving field, the book provides insights into the current implementation of these potentially sustainable solutions. It will serve as a resource of general guidelines and best practices for researchers, professionals and policymakers.
THE ARTIFICIAL INTELLIGENCE MCQ (MULTIPLE CHOICE QUESTIONS) SERVES AS A VALUABLE RESOURCE FOR INDIVIDUALS AIMING TO DEEPEN THEIR UNDERSTANDING OF VARIOUS COMPETITIVE EXAMS, CLASS TESTS, QUIZ COMPETITIONS, AND SIMILAR ASSESSMENTS. WITH ITS EXTENSIVE COLLECTION OF MCQS, THIS BOOK EMPOWERS YOU TO ASSESS YOUR GRASP OF THE SUBJECT MATTER AND YOUR PROFICIENCY LEVEL. BY ENGAGING WITH THESE MULTIPLE-CHOICE QUESTIONS, YOU CAN IMPROVE YOUR KNOWLEDGE OF THE SUBJECT, IDENTIFY AREAS FOR IMPROVEMENT, AND LAY A SOLID FOUNDATION. DIVE INTO THE ARTIFICIAL INTELLIGENCE MCQ TO EXPAND YOUR ARTIFICIAL INTELLIGENCE KNOWLEDGE AND EXCEL IN QUIZ COMPETITIONS, ACADEMIC STUDIES, OR PROFESSIONAL ENDEAVORS. THE ANSWERS TO THE QUESTIONS ARE PROVIDED AT THE END OF EACH PAGE, MAKING IT EASY FOR PARTICIPANTS TO VERIFY THEIR ANSWERS AND PREPARE EFFECTIVELY.
This book examines the digitalization of longstanding problems of technological advance that produce inequalities and automated governance, which relieves subjects of agency and critical thought, and prompts a need to weaponize thoughtfulness against technocratic designs. The book situates digital-era problems relative to those of previous sociotechnical milieux and argues that technical advance perennially embeds corrosive effects on social relations and relations of production, recognizing variation across contexts and relative to entrenched societal hierarchies of race and other axes of difference and their intersections. Societal tolerance, despite abundant evidence for harmful effects of digital technologies, requires attention. The book explains blindness to social injustice by technocratic thinking delivered through education as well as truths embraced in the data sciences coupled with governance in universities and the private sector that protect these truths from critique. Institutional inertia suggests benefits of communitarianism, which strives for change emanating from civil society. Scaling postcapitalist communitarian values through communitybased peer production presents opportunities. However, enduring problems require critical reflection, continual revision of strategies, and active participation among diverse community citizens. This book is written with critical geographic sensibilities for an interdisciplinary audience of scholars and graduate and undergraduate students in the social sciences, humanities, and data sciences.
Witness the Tech Revolution Transforming Our World How far will AI take us? What challenges lie ahead? Dive into an exhilarating journey through the evolving landscape of artificial intelligence with "AI Revolution: The Future Unveiled". This book meticulously unpacks the fascinating past, dynamic present, and possible future of AI, capturing readers' imaginations with vivid stories and informed predictions. Starting from the very roots, explore early concepts and the pivotal figures who laid the groundwork in AI research. Then, venture through the key technologies propelling this transformation – machine learning, neural networks, and natural language processing, to name a few. Each technological breakthrough is explained in an engaging and accessible manner, drawing in not just technophiles but anyone curious about the future. Experience the profound impact of AI across various industries such as manufacturing, healthcare, and finance. Understand how AI is reshaping our daily lives with personal assistants, smart homes, and even the media we consume. The book doesn't shy away from the dark sides either, addressing ethical dilemmas, workforce disruptions, and privacy concerns, presenting a balanced view that encourages thoughtful reflection. This comprehensive guide also focuses on the societal implications of AI. From education to national security, from economic impact to environmental sustainability, each chapter sheds light on how AI is altering norms and creating new paradigms. Additionally, thought-provoking interviews with leading experts and real-world case studies offer unique insights and lessons learned. Curious about what's next? Predicting future trends, "AI Revolution" explores speculative scenarios and long-term implications that will leave you pondering the endless possibilities. Whether you are an industry professional, a student, or simply a curious mind, this book is a captivating must-read that will prepare you for the inevitable AI-driven future.
This book constitutes the refereed proceedings of the First International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018, held in Seattle, WA, USA, in December 2018. The 20 full papers presented were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections named: AI Benchmarking; Cloud; Big Data; Modelling and Prediction; and Algorithm and Implementations.
Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook Description Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries. What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is for If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.
When young, we didn’t have cellular devices but communicated through handwritten letter. We walked miles to school, in the sun and the rain. It’s mind-boggling to think how far we’ve come technologically. “Objects in mirror are closer than they appear.” That familiar warning applies to the windshield, not the rear view mirror when it comes to technology. And in case of exponential technologies, almost everything is closer than it appears. Today’s students will be graduating in and around 2030. Over 65% of the jobs of that time have not been invented yet. What knowledge, skills and dispositions will our learners need for a successful future? How will exponential changes in technology influence them? How can they shape the future instead of being shaped by it? There is an urgent need to be aware of exponential technologies which will usher in singularity, a point in time when artificial intelligence will equal and then surpass biological intelligence. An exploratory design of medical nanotechnology and robotics is creating mechanical artificial red blood cells, called respirocytes, which will deliver 236 times more oxygen to the tissues per unit volume. One can then do an Olympic sprint in fifteen minutes without taking a breath. Earth is awash with the sun’s rays carrying 10,000 times more energy than we need but we cannot harness it. In a foreseeable future, highly efficient, lightweight, nano-engineered solar panels will be able to store solar energy in distributed nanotechnology-based fuel cells. In the field of health, we are going to have tools to reprogram biology to block diseases and delay aging. We need our future scientists and engineers to be wholesome human beings with the ability to think critically and pay heed to the moral and ethical issues of future technologies. Notwithstanding these issues, all great technological breakthroughs are absolutely necessary to alleviate poverty, disease, suffering and create abundance.
A computer beats the reigning human champion of Go, a game harder than chess. Another is composing classical music. Labs are creating life-forms from synthetic DNA. A doctor designs an artificial trachea, uses a 3D printer to produce it, and implants it and saves a child's life. Astonishing technological advances like these are arriving in increasing numbers. Scholar and entrepreneur Vivek Wadhwa uses this book to alert us to dozens of them and raise important questions about what they may mean for us. Breakthroughs such as personalized genomics, self-driving vehicles, drones, and artificial intelligence could make our lives healthier, safer, and easier. But the same technologies raise the specter of a frightening, alienating future: eugenics, a jobless economy, complete loss of privacy, and ever-worsening economic inequality. As Wadhwa puts it, our choices will determine if our future is Star Trek or Mad Max. Wadhwa offers us three questions to ask about every emerging technology: Does it have the potential to benefit everyone equally? What are its risks and rewards? And does it promote autonomy or dependence? Looking at a broad array of advances in this light, he emphasizes that the future is up to us to create—that even if our hands are not on the wheel, we will decide the driverless car's destination.
The first book in the Fast Future series, Beyond Genuine Stupidity: Ensuring AI Serves Humanity, explores critical emerging issues arising from the rapid pace of development in artificial intelligence (AI). The authors argue for a forward-looking and conscious approach to the development and deployment of AI to ensure that it genuinely serves humanity's best interest. Through a series of articles, they present a compelling case to get beyond the genuine stupidity of narrow, short-term and alarmist thinking and look at AI from a long-term holistic perspective. The reality is that AI will impact current sectors and jobs—and hopefully enable new ones. A smart approach requires us to think about and experiment with strategies for adopting and absorbing the impacts of AI—encompassing education systems, reskilling the workforce, unemployment and guaranteed basic incomes, robot taxes, job creation, encouraging new ventures, research and development to enable tomorrow's industries, and dealing with the mental health impacts. The book explores the potential impacts on sectors ranging from healthcare and automotive to legal and education. The implications for business itself are also examined from leadership and HR to sales and business ethics.