Hacking Artificial Intelligence: A Leader`s Guide from Deepfakes to Breaking Deep Learning, Gibian Davey
Автор: Peter Norvig Название: Paradigms of Artificial Intelligence Programming, ISBN: 1558601910 ISBN-13(EAN): 9781558601918 Издательство: Elsevier Science Рейтинг: Цена: 9599.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Paradigms of AI Programming teaches advanced Common Lisp techniques in the context of building major AI systems.
Описание: This book explores the complex ways in which algorithms and big data are reshaping everyday culture, while at the same time perpetuating inequality and intersectional discrimination. It situates issues of humanity, identity, and culture in relation to free will, surveillance, capitalism, neoliberalism, consumerism, solipsism, and creativity.
Автор: Dilip Singh Sisodia, Ram Bilas Pachori, Lalit Garg Название: Advancement of Artificial Intelligence in Healthcare Engineering ISBN: 179982120X ISBN-13(EAN): 9781799821205 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 39640.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides comprehensive research on the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of healthcare engineering solutions. The book features a range of topics such as genetic algorithms, mobile robotics, and neuroinformatics.
Описание: A comprehensive look at the interplay between artificial intelligence and international economic law (IEL), this volume is a valuable guide for scholars, students, practitioners, and policymakers in the fields of IEL, technology law, administrative law, and global AI governance. This title is also available as Open Access on Cambridge Core.
Автор: Ashutosh Kumar Singh, Rajiv Singh Название: Computational Methodologies for Electrical and Electronics Engineers ISBN: 1799833283 ISBN-13(EAN): 9781799833284 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 29779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial intelligence has been applied to many areas of science and technology, including the power and energy sector. Renewable energy in particular has experienced the tremendous positive impact of these developments. With the recent evolution of smart energy technologies, engineers and scientists working in this sector need an exhaustive source of current knowledge to effectively cater to the energy needs of citizens of developing countries.
Computational Methodologies for Electrical and Electronics Engineers is a collection of innovative research that provides a complete insight and overview of the application of intelligent computational techniques in power and energy. Featuring research on a wide range of topics such as artificial neural networks, smart grids, and soft computing, this book is ideally designed for programmers, engineers, technicians, ecologists, entrepreneurs, researchers, academicians, and students.
Описание: This book addresses the role of public policy in regulating the autonomous artificial intelligence and related civil liability for damage caused by the robots (and any form of artificial intelligence).
Автор: Alex Lui, Anna Farzinder, Mingboo Gong Название: Transforming Healthcare with Big Data and AI ISBN: 1641138971 ISBN-13(EAN): 9781641138970 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field.
This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Dan Zhang, Bin Wei Название: Novel Design and Applications of Robotics Technologies ISBN: 1522552766 ISBN-13(EAN): 9781522552765 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 29938.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Through expanded intelligence, the use of robotics has fundamentally transformed a variety of fields, including manufacturing, aerospace, medical, social services, and agriculture. Providing successful techniques in robotic design allows for increased autonomous mobility, which leads to a greater productivity level.Novel Design and Applications of Robotics Technologies provides innovative insights into the state-of-the-art technologies in the design and development of robotic technologies and their real-world applications. The content within this publication represents the work of interactive learning, microrobot swarms, and service robots. It is a vital reference source for computer engineers, robotic developers, IT professionals, academicians, and researchers seeking coverage on topics centered on the application of robotics to perform tasks in various disciplines.
From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning---especially when it comes to discerning the truth and differentiating fact from fiction.
This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics.
How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias -- which gets amplified in harmful data feedback loops. Don't be afraid: with this book you'll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope.
What You Will Learn
The ways that data labeling and storage impact machine learning and how feedback loops can occur
The history and inner-workings of YouTube's recommendation algorithm
The state-of-the-art capabilities of AI-powered text generation (GPT-3) and video synthesis/doctoring (deepfakes) and how these technologies have been used so far
The algorithmic tools available to help with automated fact-checking and truth-detection
Who This Book is For
People who don't have a technical background (in data, computers, etc.) but who would like to learn how algorithms impact society; business leaders who want to know the powers and perils of relying on artificial intelligence. A secondary audience is people with a technical background who want to explore the larger social and societal impact of their work.
Автор: Min Wu, Xiaoli Li, Zhenghua Chen Название: Generalization With Deep Learning: For Improvement On Sensing Capability ISBN: 9811218838 ISBN-13(EAN): 9789811218835 Издательство: World Scientific Publishing Рейтинг: Цена: 15840.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing.
Автор: by Shashi Narayan, Claire Gardent Название: Deep Learning Approaches to Text Production ISBN: 1681737604 ISBN-13(EAN): 9781681737607 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14276.00 р. Наличие на складе: Нет в наличии.
Описание: Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.
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