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Author:
Publisher: STAR SCHOLARS PRESS
ISBN:
Category : Education
Languages : en
Pages : 20
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Book Description
Generative Creations, Code, and Data: How Intellectual Property Rights Over Ownership, Use, and Image Apply to Higher education
Author:
Publisher: STAR SCHOLARS PRESS
ISBN:
Category : Education
Languages : en
Pages : 20
Get Book
Book Description
Generative Creations, Code, and Data: How Intellectual Property Rights Over Ownership, Use, and Image Apply to Higher education
Author:
Publisher: STAR SCHOLARS PRESS
ISBN: 195748036X
Category : Education
Languages : en
Pages : 322
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Book Description
ChatGPT and Global Higher Education: Using Artificial Intelligence in Teaching and Learning
Author: Damian Clifford
Publisher: Bloomsbury Publishing
ISBN: 1509966048
Category : Law
Languages : en
Pages : 301
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Book Description
This collection examines one of the fastest growing fields of regulation: data rights. The book moves debates about data beyond data and privacy protecting statutes. In doing so, it asks what private law may have to say about these issues and explores how private law may influence the interpretation and the form of legislation dealing with data. Over five parts it: sets out an overview of the themes and problems; explores theoretical justifications and challenges in understanding data; considers data through the perspective of cognate private law doctrines; assesses the contribution of private law in understanding individual rights; and finally examines the potential of private law in providing individual remedies for wrongful data use, supplementing the work of regulators. The contributors are specialists in their respective fields of private law with long-standing expertise in the challenges to data privacy posed by emerging digital technologies.
Author: Hai-Jew, Shalin
Publisher: IGI Global
ISBN:
Category : Art
Languages : en
Pages : 321
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Book Description
In the dynamic realm of generative artificial Intelligence (AI), the fusion of human creativity and machine intelligence has created a vibrant ecosystem of collaborative artmaking. However, this transformative process brings forth a myriad of concerns, ranging from ethical considerations and the need for originality to navigating the legal complexities surrounding intellectual property. As more and more online communities appear around the use of AI to aid in the creation of images, there arises a pressing need for a comprehensive guide that not only dissects the intricacies of artmaking with generative AI tools but also offers practical solutions to the evolving dilemmas faced by artists, researchers, and technologists. Making Art With Generative AI Tools emerges as an exploration of the challenges posed by this intersection of human expression and artificial intelligence. Artists engaging with generative AI find themselves grappling with issues of authenticity, social toxicity, and the commercial viability of their creations. From avoiding stereotypical visuals to ensuring proper crediting, the realm of generative AI is rife with these complexities. Furthermore, the blurred lines between human and machine authorship necessitate a deeper exploration of how these innovative tools impact creativity, representation, and the very fabric of the art world.
Author: Ana Ramalho
Publisher: Routledge
ISBN: 1000513254
Category : Law
Languages : en
Pages : 167
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Book Description
This book explores the intersection between artificial intelligence and two intellectual property rights: copyright and patents. The increasing use of artificial intelligence for generating creative and innovative output has an impact on copyright and patent laws around the world. The book aims to map and analyse that impact. The author considers how artificial intelligence systems may aid, or in some cases substitute for, human creators and inventors in the creative process. It is from this angle that the copyright and patent regimes in four jurisdictions (Europe, the United States, Australia and Japan) are investigated in depth. The author describes how these jurisdictions look at works and inventions generated through a process where artificial intelligence is present or prevalent, and examines how copyright and patent regimes should adapt to the reality of artificially intelligent creators and inventors. As the use of artificial intelligence to generate creative and innovative products becomes more common, this book will be a valuable resource to researchers, academics and policy makers alike.
Author: Julija Kalpokienė
Publisher: Taylor & Francis
ISBN: 1040113486
Category : Law
Languages : en
Pages : 120
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Book Description
This book addresses the complex issue of human creativity in the age of Artificial Intelligence. Artificial intelligence (AI) is increasingly being used to create texts, images, and musical compositions. This increase in the application of AI within the creative industries can of course enhance human performance while producing creative and commercial challenges for human authors. Against this background, this book considers how current mechanisms for incentivising creativity – including legal regulations, such as copyright, state funding and tax regimes – are inadequate in the age of AI. Acknowledging the opportunity that AI presents, the book then proposes alternative regulatory mechanisms through which human creativity can be incentivised. This book will appeal to scholars and researchers in the areas of socio-legal studies, intellectual property law, media law, and law and technology.
Author: Roshani Raut
Publisher: CRC Press
ISBN: 1000840557
Category : Computers
Languages : en
Pages : 223
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Book Description
This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum
Author: World Intellectual Property Organization
Publisher: WIPO
ISBN: 9280530070
Category : Law
Languages : en
Pages : 156
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Book Description
The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s.
Author: Matt Pearson
Publisher: Simon and Schuster
ISBN: 1638352437
Category : Computers
Languages : en
Pages : 352
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Book Description
Summary Generative Art presents both the technique and the beauty of algorithmic art. The book includes high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece using the Processing programming language. About the Technology Artists have always explored new media, and computer-based artists are no exception. Generative art, a technique where the artist creates print or onscreen images by using computer algorithms, finds the artistic intersection of programming, computer graphics, and individual expression. The book includes a tutorial on Processing, an open source programming language and environment for people who want to create images, animations, and interactions. About the Book Generative Art presents both the techniques and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific steps the author followed to create each unique piece using the Processing programming language. The book includes concise tutorials for each of the technical components required to create the book's images, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside The principles of algorithmic art A Processing language tutorial Using organic, pseudo-random, emergent, and fractal processes ================================================= Table of Contents Part 1 Creative Coding Generative Art: In Theory and Practice Processing: A Programming Language for ArtistsPart 2 Randomness and Noise The Wrong Way to Draw A Line The Wrong Way to Draw a Circle Adding Dimensions Part 3 Complexity Emergence Autonomy Fractals
Author: Lixin Fan
Publisher: Springer Nature
ISBN: 981197554X
Category : Computers
Languages : en
Pages : 233
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Book Description
Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model’s owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
