Download or read book Generative AI Research written by Anand Vemula and published by Independently Published. This book was released on 2024-06-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI Research: Mastering Foundations, Models, and Practical Applications is a comprehensive guide that delves into the fascinating world of generative artificial intelligence. This book is meticulously designed for researchers, practitioners, and enthusiasts who are keen to explore and harness the power of generative AI. Starting with an introduction to AI and machine learning, the book provides a solid foundation by explaining key concepts and the historical development of generative models. It dives into the mathematical and statistical underpinnings essential for understanding generative AI, followed by a thorough exploration of machine learning and deep learning fundamentals. The book categorizes and examines various types of generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), autoregressive models, and flow-based models. Each section covers the architecture, applications, and challenges associated with these models, supplemented with real-world examples and use cases. Readers will find detailed tutorials with complete solutions, enabling hands-on learning and practical implementation of concepts. For instance, the section on GANs provides step-by-step guidance on building and training GANs, addressing common pitfalls and optimization strategies. Moreover, the book highlights diverse applications of generative AI across various domains such as image generation, text creation, music synthesis, and video editing. Advanced topics like conditional generative models, multimodal generative models, and few-shot learning are also discussed, offering insights into cutting-edge research and developments. Practical exercises with complete solutions are included to reinforce learning and provide a robust understanding of how to apply generative AI techniques in real-world scenarios. The book also addresses the evaluation metrics for generative models, ensuring readers can effectively measure the performance of their models. Generative AI Research: Mastering Foundations, Models, and Practical Applications is an essential resource that bridges the gap between theory and practice, equipping readers with the knowledge and skills needed to excel in the dynamic field of generative AI.
Download or read book Using Generative AI for Legal Research written by Amy E. Sloan and published by Aspen Publishing. This book was released on 2024-03-17 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The promise of generative AI is awe-inspiring. Today, however, the questions about generative AI sometimes outnumber the answers. Using Generative AI for Legal Research provides a framework professors can use to introduce generative AI into the research curriculum. To use generative AI effectively, researchers must be aware both of its potential and its limitations. Using Generative AI for Legal Research explores how generative AI fits within a process for conducting legal research. Specifically, this material: Addresses advantages and risks of using AI-generated information; Outlines tasks for which generative AI is and is not useful; Describes how to prompt an AI text generator to produce useful information; and Offers guidelines for when and how to cite AI-generated information. The content follows the structure of chapters in Basic Legal Research: Tools and Strategies (Revised 8th ed., 2024) and includes research examples and a chapter checklist. Although this material fits with Basic Legal Research, it can also be used as a stand-alone supplement with other instructional materials. I hope you will find Using Generative AI for Legal Research instructive.
Download or read book The Work of the Future written by David H. Autor and published by MIT Press. This book was released on 2022-06-21 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why the United States lags behind other industrialized countries in sharing the benefits of innovation with workers and how we can remedy the problem. The United States has too many low-quality, low-wage jobs. Every country has its share, but those in the United States are especially poorly paid and often without benefits. Meanwhile, overall productivity increases steadily and new technology has transformed large parts of the economy, enhancing the skills and paychecks of higher paid knowledge workers. What’s wrong with this picture? Why have so many workers benefited so little from decades of growth? The Work of the Future shows that technology is neither the problem nor the solution. We can build better jobs if we create institutions that leverage technological innovation and also support workers though long cycles of technological transformation. Building on findings from the multiyear MIT Task Force on the Work of the Future, the book argues that we must foster institutional innovations that complement technological change. Skills programs that emphasize work-based and hybrid learning (in person and online), for example, empower workers to become and remain productive in a continuously evolving workplace. Industries fueled by new technology that augments workers can supply good jobs, and federal investment in R&D can help make these industries worker-friendly. We must act to ensure that the labor market of the future offers benefits, opportunity, and a measure of economic security to all.
Download or read book Applications of Generative AI written by Zhihan Lyu and published by Springer Nature. This book was released on with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Guidance for generative AI in education and research written by Holmes, Wayne and published by UNESCO Publishing. This book was released on 2023-09-08 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Download or read book Philosophy and Theory of Artificial Intelligence written by Vincent C. Müller and published by Springer Science & Business Media. This book was released on 2012-08-23 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here.
Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2022-06-28 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models. The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative. Discover how VAEs can change facial expressions in photos Train GANs to generate images based on your own dataset Build diffusion models to produce new varieties of flowers Train your own GPT for text generation Learn how large language models like ChatGPT are trained Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN Compose polyphonic music using Transformers and MuseGAN Understand how generative world models can solve reinforcement learning tasks Dive into multimodal models such as DALL.E 2, Imagen, and Stable Diffusion This book also explores the future of generative AI and how individuals and companies can proactively begin to leverage this remarkable new technology to create competitive advantage.
Download or read book Introduction to Generative AI written by Numa Dhamani and published by Simon and Schuster. This book was released on 2024-02-27 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI tools like ChatGPT are amazing—but how will their use impact our society? This book introduces the world-transforming technology and the strategies you need to use generative AI safely and effectively. Introduction to Generative AI gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you’ll learn: How large language models (LLMs) work How to integrate generative AI into your personal and professional workflows Balancing innovation and responsibility The social, legal, and policy landscape around generative AI Societal impacts of generative AI Where AI is going Anyone who uses ChatGPT for even a few minutes can tell that it’s truly different from other chatbots or question-and-answer tools. Introduction to Generative AI guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you’ll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren’t) capable of, and how you can use them to your greatest advantage. Foreword by Sahar Massachi. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you’ll need to use it safely and effectively. About the book Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You’ll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you’ll practice strategies for getting accurate responses and even understand how to handle misuse and security threats. What's inside How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility About the reader For anyone interested in Generative AI. No technical experience required. About the author Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is an engineer and researcher currently working on safety for large language models. The technical editor on this book was Maris Sekar. Table of Contents 1 Large language models: The power of AI Evolution of natural language processing 2 Training large language models 3 Data privacy and safety with LLMs 4 The evolution of created content 5 Misuse and adversarial attacks 6 Accelerating productivity: Machine-augmented work 7 Making social connections with chatbots 8 What’s next for AI and LLMs 9 Broadening the horizon: Exploratory topics in AI
Download or read book ChatGPT Comprehensive Study On Generative AI Tool written by Midhun Moorthi C and published by Academic Guru Publishing House. This book was released on 2023-08-09 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough introduction to two cutting-edge technologies known as Generative AI and ChatGPT. Both of these technologies have received much attention in recent years. Generative AI and ChatGPT can completely reshape sectors and society as a whole by increasing productivity and innovation and making it possible to have more tailored experiences. The natural language processing tool, ChatGPT, powered by artificial intelligence technology, enables you to engage in human-like conversation with the chatbot and provides several other benefits. The language model can answer inquiries and assist with activities such as the composition of emails, essays, and code. This book aims to give a comprehensive overview of the technologies, architectures, and training techniques mentioned above, including their history, the process by which they were developed, and their present status. This book assists in discovering novel applications of these technologies that have been put into practice to generate quantifiable advantages, such as increased efficiency, customer happiness, security, and revenue growth. The book also discusses the book's potential applicability across a variety of sectors and use cases.
Download or read book Generative Artificial Intelligence and Innovation written by Marcello Mariani and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Purpose - This work defines Generative Artificial Intelligence (Gen-AI) and discusses its conceptual foundations and developments in innovation research. It also sketches research propositions that contribute to a promising research agenda.Design/methodology/approach - The study consists of a conceptual reflection on academic and non-academic research articles that deal with forms of Generative Artificial Intelligence. Findings - This work generates several findings. First, defining Generative Artificial Intelligence (Gen-AI) in innovation is a complicated task, one that has to rely on multiple disciplines that construe similar terms and concepts in a different way. As such, our definition is one that takes into account innovation outcomes such as product/service, process, and business model innovation, as they represent the most relevant outcomes of innovation in the business and management literature dealing with AI (Mariani, 2020; Mariani et al., 2022). Second, such a definition has to take into account: (1) the macro environment including the political, economic, social, technological, ecological and legal environment; (2) the industry encompassing organizations/firms, their suppliers, customers, competitors, complementors and potential entrants. This implies that different level of analysis should be adopted: the macro level (e.g., technological environment), meso level (e.g., technological resources, capabilities, culture at the firm level) and micro level (e.g., individual consumers' attitudes and preferences). Third, when conceptualizing the relationship between Gen-AI and innovation from a business perspective, a framework helping to identify benefits and critical challenges of Generative AI for business innovation is missing. Fourth, as Gen-AI will originally complements (instead of replacing) human-led innovation, important issues to address are: (1) how humans - be them innovation managers, customers and new product testers - and Gen-AI will interact for product, process, and business model innovation; (2) if and how new products/services and processes generated by AI will be patented; (3) if and how intellectual property generated by AI will be protected; (4) who will retain intellectual property for new business ideas, patents, as well new products/services and processes stemming from Gen-AI; (5) if and how innovation managers will make sure that the use of Gen-AI will be ethical and moral given the ongoing relevant debate around the morality of AI (Floridi & Sanders, 2004); (6) who will control if new products/services and processes stemming from Gen-AI are authentic, do not infringe others' IP and comply with laws and regulations; (7) if and to what extent Gen-AI brings about incremental rather than radical innovation; (8) how long it will take for Gen-AI to lead to breakthrough innovation; (9) how shall business models be modified to support Gen-AI; (10) how organization boundaries should be modified to accommodate Gen-AI; (11) if a Gen-AI department or office should be created along the R&D one.Research limitations/implications - This work critically synthesizes academic and non-academic research on generative AI. Policy and managerial implications for innovation managers and entrepreneurs are put forward. Some of them enrich recent empirical and anecdotal evidence on the use of AI for tasks such as writing articles (GPT-3, 2020; Floridi & Chiriatti, 2020), developing deepfakes (Floridi, 2021) and developing a range of other “new” products (Marr, 2022; Sparkes, 2022). Our conceptual development seems to suggest that Gen-AI can at best help innovation managers to: (1) identify the best among different solutions to a customer problem; (2) identify the best among different customer problems. However, and consistently with extant critical perspectives on AI vs. intelligence (Floridi, 2017), Gen-AI's ability to solve problems in the innovation domain more effectively than humans should not eb confused with intelligent ways through which Gen-AI, by itself, can generate new products/services and processes. Originality/value - This study contributes to define and conceptualize Generative Artificial Intelligence (Gen-AI) in relation to innovation in the business and management field, and discusses its conceptual foundations and developments in business research. It also sketches research propositions that contribute to build a promising research agenda.
Download or read book Social Sensing written by Dong Wang and published by Morgan Kaufmann. This book was released on 2015-04-17 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book
Download or read book Redesigning AI written by Daron Acemoglu and published by MIT Press. This book was released on 2021-05-25 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: A look at how new technologies can be put to use in the creation of a more just society. Artificial Intelligence (AI) is not likely to make humans redundant. Nor will it create superintelligence anytime soon. But it will make huge advances in the next two decades, revolutionize medicine, entertainment, and transport, transform jobs and markets, and vastly increase the amount of information that governments and companies have about individuals. AI for Good leads off with economist and best-selling author Daron Acemoglu, who argues that there are reasons to be concerned about these developments. AI research today pays too much attention to the technological hurtles ahead without enough attention to its disruptive effects on the fabric of society: displacing workers while failing to create new opportunities for them and threatening to undermine democratic governance itself. But the direction of AI development is not preordained. Acemoglu argues for its potential to create shared prosperity and bolster democratic freedoms. But directing it to that task will take great effort: It will require new funding and regulation, new norms and priorities for developers themselves, and regulations over new technologies and their applications. At the intersection of technology and economic justice, this book will bring together experts--economists, legal scholars, policy makers, and developers--to debate these challenges and consider what steps tech companies can do take to ensure the advancement of AI does not further diminish economic prospects of the most vulnerable groups of population.
Download or read book Integrating Generative AI in Education to Achieve Sustainable Development Goals written by Doshi, Ruchi and published by IGI Global. This book was released on 2024-06-03 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new challenge has become present in the field of generative artificial intelligence (AI). The fundamental nature of education, a vital element for advancing the United Nations' Sustainable Development Goals (SDGs), now grapples with the transformative impact of AI technologies. As we stand at this intersection of progress and pedagogy, critical questions surface about the future roles of educators and the integrity of assessment processes. AIs rapid progression prompts an exploration of the competencies our education systems must cultivate in a world where human and machine intelligence are becoming increasingly interconnected. Against this backdrop of transformative uncertainty, Integrating Generative AI in Education to Achieve Sustainable Development Goals addresses profound challenges and offers promising solutions at the crossroads of AI and education. This book assembles distinguished academics, researchers, and practitioners, forming a collective voice on the intersection of Generative AI and education. The three-part structure dissects the technical aspects of AI-powered innovations in educational design, explores multidisciplinary applications enhancing educational content, and highlights AI-driven solutions to address equality and inclusion concerns within educational systems. The book also underscores the importance of ethical considerations of generative AI to ensure a future where technology serves the broader goals of sustainability and equitable education.
Download or read book Advanced Applications of Generative AI and Natural Language Processing Models written by Ahmed Jabbar Obaid and published by . This book was released on 2023-12-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Models equips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.
Download or read book Artificial Intelligence Products in the United States written by Syarif M and published by Pocket Analytica. This book was released on 2023-11-14 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research, conducted through desk research, offers key insights into the ever-changing AI landscape in the United States. These findings are a valuable resource for businesses, policymakers, and stakeholders seeking to navigate and leverage the evolving AI landscape in the United States. Details: 50 Pages 20+ Charts Projections for the market size of each AI sector from 2023 to 2030 in the United States, including the Compound Annual Growth Rate (CAGR) for each sector. Data Sources: Mainly obtained from Statista Premium, which exceeded 3000 USD for the data alone. AI's Impact on Business: Gain a deep understanding of the positive impact of AI technologies on increasing revenue and reducing costs across various business functions. Table of Content: Chapter 1: Executive Summary Scope and Limitation Chapter 2: Market Overview Historical Development of AI Software Current Market Landscape Key Approaches in AI business Strategy Leading U.S. AI Product Companies AI Software Ecosystem Companies Chapter 3: AI Segments AI Robotics Autonomous & Sensor Technology Computer Vision Generative AI Machine Learning Natural Language Processing Chapter 4: Market Growth and Projections User Share in Generative AI Businesses User Segmentation in United States Generative AI Adoption Across U.S. Generations U.S. 2021 Public Opinion Segmentation in AI Control Factors Driving Market Growth Investment and Funding Trends Chapter 5: Market Challenges Ethical and Regulatory Challenges Data Privacy and Security Concerns Talent Shortage Chapter 6: Competitive Analysis Competitive Landscape, AI Robotics Competitive Landscape, Autonomous & Sensor Technology Competitive Landscape, Computer Vision Competitive Landscape, Generative AI Competitive Landscape, Machine Learning Competitive Landscape, Natural Language Processing Competitive Strategies in AI Business Against Industry Giants Chapter 7: Global AI Business Impact by Function Increased Revenue in 2021 Cost Reduction in 2022 Supply Chain Benefits 2022 Chapter 8: Breakthrough Technologies Artificial Emotional Intelligence Reinforcement Learning Deep Learning Sequential Learning Chapter 9: Conclusion Chapter 10: Appendices Methodology: Extensive Desk Research, emphasizing data collection primarily from statista.com
Download or read book Artificial Intelligence Research and Development written by J. Sabater-Mir and published by IOS Press. This book was released on 2019-10-02 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence has now become an indispensible tool at the centre of problem-solving in a huge range of digital technologies, and remains one of the most vibrant topics for discussion and research. This book presents a compilation of the articles presented at the 22nd (2019) edition of the International Conference of the Catalan Association for Artificial Intelligence (CCIA), held in Mallorca, Spain, from 23 – 25 October 2019. This annual conference is an international event that serves as a meeting point for researchers into artificial intelligence based in the area of the Catalan speaking territories and for researchers from around the world. The book is divided into 8 sections. The first contains summaries of the 3 invited talks presented at the conference: ‘New methods for fusing information and the computational brain’, by Javier Fernandez; ‘From correlation to imagination: Deep generative models for artificial intelligence’ by Joan Serrà; and ‘Explainable AI’ by Anna Monreale. The remaining 7 sections contain 47 papers covering ethics and E-governance; machine learning; constraints and SAT, optimization and fuzzy; data science, recommender systems and decision support systems; agent-based and multi-agent systems; computer vision; and sentiment analysis and text analysis. The book provides an overview of the latest developments in the field, and as such will be of interest to all those whose work involves the study and application of artificial intelligence.
