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Deep Generative Models
This book constitutes the proceedings of the 4th workshop on Deep Generative Models for Medical Image Computing and Computer Assisted Intervention, DGM4MICCAI 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024.The 21 papers presented here were carefully reviewed and selected from 40 submissions. These papers deal with a broad range of topics, ranging from methodology (such as Causal inference, Latent interpretation, Generative factor analysis) to Applications (such as Mammography, Vessel imaging, Surgical videos and more).
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Beiträge zur generativen Grammatik
1 Vorarbeiten zu diesem Referat wurden im Rahmen eines von der DFG geförderten Forschungsprojekts von Herrn Professor Dr. Finkenstaedt durchgeführt. 2 In einem chronologischen Wörterbuch können solche Probleme weiter verfolgt werden (cf. Finkenstaedt, Leisi, Wolff 19'70) - Die Frage der Äquivalenz zwischen Wortableitungen und längeren Konstruktionen, die ihnen in der semantischen Struktur entsprechen, ist von Chomsky (1969,16) in anderem Zusammenhang diskutiert worden. Lakoffs (1969,52;'70) Er- widerung gibt die nötige Abgrenzung des Begriffs 'Satz- semantik' gegenüber einer Semantik des Sprachgebrauchs und der Sprechsituation, um die es hier nicht geht. Dieses Grundverständnis ist schon in der Port Royal Grammatik (Brekle 1966,68) angelegt. Bibliographie Brekle, H. ed. (1966) Grammaire generale et raisonnee (31676) (= Grammatica Universalis 1), Stuttgart. Chapin, P. (1967) On the Syntax of Word-Derivation in English, unpublished Doctoral dissertation, MIT. Chomsky, N. (1968) Remarks on Nominalization, reproduced by The Linguistics Club, Indians Universit, y. --- (1969) Deep Structure, Surface Structure, and Semantic Interpretation, reproduced by The Linguistics Club, Ind.U. Finkenstaedt, T., E. Leisi, D. Wolff (19'70) A Chronological English Dictions, Heidelberg Fodor, J.A. (19'70) nThree Reasons for Not Deriving 'Kill' from 'Cause to Die'," Linguistic Inquiry 1,429-438. Lakoff, G. (1969) On Generative Semantics, reproduced by The Linguistics Club, Indians Universit, y. - 184 - Senta Plötz Institut für Kommunikationsforschung und Phonetik der Universität Bonn Über die transformationelle Theorie bei Harris * Zusammenfassung: Es wird gezeigt. daß die transformationelle Analyse herauswuchs aus den Untersuchungen von englischen Texten. die Harris Anfang der 50er Jahre an der University of Pennsylvania durchführte.
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Enterprise Guide for Implementing Generative AI and Agentic AI
Generative AI and Agentic AI together are revolutionizing the technology landscape, with profound and far-reaching impacts across industries. Organizations are increasingly adopting these technologies to drive innovation, enhance unstructured content management, and improve problem-solving capabilities. With Agentic AI, enterprises are moving towards the development of intelligent systems that can plan, reason, and act with autonomy. While early proof-of-concepts (POCs) demonstrated the potential of these technologies, the current shift is toward responsible and scalable production implementations that leverage both generative and agentic capabilities.This book begins by guiding you through the technological evolution of AI, from early machine learning to today's large language models (LLMs) and agentic systems. It then explores a wide range of use cases across industries, highlighting how LLMs can support decision-making, and how Agentic AI enables dynamic, collaborative systems that act with autonomy and intent. This is followed by Design Patterns across the lifecycle of AI solution development, deployment and monitoring. Readers will then gain insights into the methodologies for developing and deploying Generative and Agentic AI solutions at an enterprise level. A featured implementation demonstrates how Agentic AI can be effectively put into action.The book also introduces essential concepts such as MLOps, LLMOps, and Responsible AI principles which are critical for transitioning the AI solutions from experimentation to production. These principles ensure that AI deployments are scalable, secure, ethical and compliant. The book concludes with key takeaways and best practices for developing, evaluating, deploying and scaling AI applications responsibly and effectively within enterprise settings. You Will: Understand key design patterns to develop, deploy and monitor a Generative AI solution effectively.Learn how to develop and implement a production-ready Agentic AI use case.Discover best practices for building scalable, secure, and enterprise-grade AI solutions.Understand how to assess and mitigate risks using Responsible AI principles and LLMOps best practices. This book is for: Enterprise Software Engineers and Architects
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Automate It with Zapier and Generative AI
Strategize and create automated business workflows with Zapier, including AI-integrated functionalities such as the ChatGPT plugin and the OpenAI integration, to minimize repetitive tasks without using codeKey FeaturesDiscover the newest Zapier features including OpenAI integration and the ChatGPT pluginExplore expert tips and real-life examples to connect 6000+ business apps and automate tasks with ZapierLearn how to manage your account effectively and troubleshoot problems with your ZapsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionOrganizations experience significant issues with productivity when dealing with manual and repetitive tasks. Automate it with Zapier and Generative AI, second edition has been extensively revised to help you analyze your processes and identify repetitive tasks that can be automated between 6000+ cloud-based business applications.This book includes all Zapier’s newest features such as AI functionality using the ChatGPT plugin, drafts, reordering and duplicating steps and paths, subfolders and version history, as well as built-in apps such as Looping, Sub-Zap, Interfaces, Tables, and Transfer. The chapters also contain examples covering various use cases sourced from the Zapier user community.You'll learn how to implement automation in your organization along with key principles and terminology, and take the first steps toward using Zapier. As you advance, you'll learn how to use Zapier’s native functionality and all 27 built-in apps such as Filter, Paths, Formatter, Digest, and Scheduler to enable you to build multi-step Zaps. You’ll also discover how to manage your Zapier account effectively, as well as how to troubleshoot technical problems with your workflows, and use the OpenAI integration to automate AI tasks.By the end of this book, you'll be able to automate your manual and repetitive tasks using Zapier.What you will learnThink outside the box to simplify business workflows and solve productivity problemsStrategize how to optimally structure and build your workflow automation in Zapier to prevent errors and excessive task usageExplore the latest built-in apps including Transfer, Interfaces, Tables, Looping, Sub-Zap, and the ChatGPT pluginDiscover how to use AI-integrated apps and features with automationCreate complex multi-step Zaps using logic, formatting, and calculationsEffectively manage your account and troubleshoot problems with your ZapsWho this book is forThis book is for business owners, operations managers, and teams in micro, small, or medium-sized businesses looking at automating repetitive tasks and increasing their productivity using Zapier and AI-integrated features. Service providers offering digital process improvement, systemization, and automation services to their clients such as solutions architects, process consultants, business analysts, virtual assistants, CRM consultants, OBMs, bookkeepers and accountants will find this book extremely useful. Suitable fo
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Multi-LLM Agent Collaborative Intelligence
Today's large language models excel at pattern recall yet falter on long-range planning, self-critique, context loss, and the tendency of maximum-likelihood training to reward popularity over quality. MACI offers a promising route to AGI by orchestrating specialized LLM agents through explicit protocols rather than enlarging a single model. Several modules remedy complementary weaknesses: adversarial-collaborative debate surfaces hidden assumptions; critical-reading rubrics filter incoherent arguments; information-theoretic signals steer dialogue quantitatively; transactional memory enables reliable long-horizon execution; and a dual-agent ethical court adjudicates outputs. Crucially, MACI also modulates linguistic behavior, tuning each agent's contentiousness and emotional tone, so the collective explores ideas from contrasting, affect-aware perspectives before converging.Fourteen aphorisms distill the framework's philosophy, including "Intelligence emerges from regulated collaboration, not isolated brilliance" and "Exploration must remain in tension with exploitation." Across healthcare diagnosis, investment support, scheduling, supply-chain management, and news-bias mitigation, MACI ensembles deliver significant improvements in reasoning depth, planning horizon, and reliability compared with similar-sized single models. By uniting structured debate, information-theoretic coordination, persistent memory, affect-aware discourse, and deliberative ethics, MACI demonstrates that rigorously validated multi-agent collaboration provides a practical, interpretable path toward robust general intelligence.
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Generativity Advantage
How can businesses systematically profit from innovations they never predicted, created by people they've never met, solving problems they didn't even know existed? While many businesses celebrate user innovation, few take their user-innovators seriously enough as entrepreneurs. The Generativity Advantage brings powerful ideas from technology generativity theory into the domains of business strategy and entrepreneurship. It explores ways to specifically design products to spur user innovation (product generativity), and to build dynamic markets for those innovations (market generativity), in order to achieve a strategic "generativity advantage"—the ability to systematically profit from the unpredicted innovations of others on a massive scale. Through numerous case studies—from Apple and Google to emerging leaders in generative AI and no-code technology like OpenAI, Anthropic, Bubble, Notion, Coda, and Webflow—it shows how product generativity and market generativity can together create a powerful flywheel effect and sustained competitive advantage. Yet the book also demonstrates that achieving a generativity advantage is neither easy nor trivial; the world's leading companies struggle to implement these ideas effectively. The book’s key lesson is to help your user-innovators succeed as serious entrepreneurs and you will benefit generously in turn. Whether you're building a digital platform, a marketplace, or any product that allows users to innovate, this book provides the conceptual tools and practical strategies needed to transform your platform into an engine of continuous innovation. Learn how to move beyond celebrating user creativity to systematically enabling and profiting from user entrepreneurship, creating value at scales previously unimaginable.
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AI in Popular Culture
This book examines the transformative impact of generative AI on cultural production, with a particular focus on how AI technologies like ChatGPT are reshaping the creation of popular culture.Through a comprehensive analysis of both Global North and South perspectives, the book offers critical insights into AI governance, ethical considerations, and the future of cultural production in an increasingly AI-integrated creative landscape. Tracing the evolution of AI in cultural industries, from its early representations in films to its current active role in content creation across various media, including film, television, music, and animation, the book explores how AI has shifted from being merely depicted in cultural works to becoming an integral tool in the creative process, from pre-production to post-production stages. It critically analyzes three core concepts—creativity, control, and credentials (3Cs)—in the context of AI-driven cultural production, putting focus on the examination of "precarious creativity," the tension between human creative expression and AI-generated content. The work addresses crucial concerns about labor rights, job security, and creative control in the cultural industries.This book will interest graduate students and researchers in media studies, cultural studies, anthropology, globalization studies, sociology, and science and technology studies (STS), as well as interested policymakers and practitioners interested in AI's impact on the creative industries.
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Generating Creative Images With DALL-E 3
Learn to craft fine art prints, NFTs, and captivating covers for books and magazines with Dall-E 3 and ChatGPTKey FeaturesExplore Dall-E 3's diverse practical applications across art, design, education, and beyondMaster AI-generated art creation through step-by-step tutorials, ranging from basic to advanced projectsEnhance your prompt crafting skills with the exclusive prompt cheat sheetPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionUnveil the extraordinary capabilities of the groundbreaking AI model, DALL-E 3, as it transforms text prompts into accurate images. This book addresses the challenge of creating meaningful images by writing prompts, guiding you step by step through creating stunning visual art regardless of your skill level.Prepare to delve deep into the inner workings of DALL-E 3's architecture and training process. With clear explanations, practical tutorials, and real-world examples that can be easily applied, you’ll unlock secrets to creating awe-inspiring AI-generated art, from fine art prints to digital designs. This book provides comprehensive insights into various lens options, camera angles, lighting techniques, and art movements, helping you integrate AI capabilities with your artistic skills. You’ll also learn to create NFTs that can be monetized and gain invaluable insights into designing compelling covers, all within the ethical boundaries of AI-generated art. And with the invaluable prompt cheat sheet by your side, you’ll hone your skills in formulating captivating prompts for diverse purposes.By the end of this book, you’ll have learned how to produce generative AI art at a rapid pace and relatively low cost and push the boundaries of imagination with DALL-E 3.What you will learnMaster DALL-E 3's architecture and training methodsCreate fine prints and other AI-generated art with precisionSeamlessly blend AI with traditional artistryAddress ethical dilemmas in AI artExplore the future of digital creativityImplement practical optimization techniques for your artistic endeavorsWho this book is forWhether you’re an artist looking to integrate AI into your work, a designer seeking new creative horizons, a tech enthusiast intrigued by the intersection of art and artificial intelligence, an educator in the fields of art and technology, or a curious individual venturing into AI-generated art, this book is for you. For anyone interested in the innovative fusion of creativity and technology, the DALL-E 3 Guide to AI Artistry offers invaluable insights and practical skills that you can apply right away.
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Generative AI Techniques for Sustainability in Healthcare Security
In a world of constant change, sustainability and technology emerge as pivotal elements in healthcare. Generative artificial intelligence (AI) presents the capabilities of more accurate diagnoses, personalized treatment plans, and drug discovery, while certain operations in healthcare, such as managing relationships with healthcare systems often necessitate a human touch, these processes can be augmented by generative AI. Sustainability and health security are becoming increasingly important. The relationship between sustainability and health security is significant, as environmental factors such as air pollution, climate change, and access to green spaces can all affect human health. Generative AI Techniques for Sustainability in Healthcare Security provides a comprehensive understanding of generative AI techniques and their application for sustainability in health security, empowering readers with the knowledge needed to leverage these cutting-edge technologies effectively. Covering topics such as disease detection, drug discovery and development, and sustainability, this book is a valuable resource for scientists, medical professionals, hospital administrators, researchers, technologists, academicians, and more.
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Automatic Question Generation
This book provides an overview of the fundamentals of Automatic Question Generation (AQG) for computational linguistics researchers, test developers, and educators. The author presents a variety of AQG system architectures, including generating questions from syntactic analyses, semantic resources, neural architectures, ontologies and knowledge graphs, and large language models. The advantages and pitfalls of a variety of AQG evaluation methods, including multi-aspect ratings by human experts, end-users, as well as crowd-sourcing and automatic evaluation techniques are discussed. The book also provides a roadmap of options for AQG targeted orientation, content selection, and focusing decisions. Machine learning opportunities for training systems to generate questions based on human-generated examples are also explored. This book offers greater depth and breadth than previous surveys of AQG. Readers will gain a comprehensive knowledge of current research, examples of applications of AQG, and inspiration for future directions for innovation and application.
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