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Linguistics for the Age of AI by Marjorie Mcshane,Sergei Nirenburg Pdf
A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.
The Age of Artificial Intelligence: An Exploration by Steven S. Gouveia Pdf
With worldwide spending estimates of over $97 billion by 2023, it is no surprise that Artificial Intelligence (A.I.) is one of the hottest topics at present in both the private and public spheres. Comprising of vital contributions from the most influential researchers in the field, including Daniel Dennett, Roman V. Yampolskiy, Frederic Gilbert, Stevan Harnad, David Pearce, Natasha Vita-More, Vernon Vinge and Ben Goertzel, ‘The Age of Artificial Intelligence: An Exploration’ discusses a variety of topics ranging from the various ethical issues associated with A.I. based technologies in terms of morality and law to subjects related to artificial consciousness, artistic creativity and intelligence. The volume is organized as follows: Section I is dedicated to reflections on the Intelligence of A.I., with chapters by Soenke Ziesche and Roman V. Yampolskiy, Stevan Harnad, Daniel Dennett and David Pearce. Next, Section II discusses the relationship between consciousness, simulation and artificial intelligence, with chapters by Gabriel Axel Montes and Ben Goertzel, Cody Turner, Nicole Hall and Steven S. Gouveia. Section III, dedicated to aesthetical creativity and language in artificial intelligence, includes chapters by Caterina Moruzzi, René Mogensen, Mariana Chinellato Ferreira and Kulvinder Panesar. The subsequent Section IV is on the Ethics of the Bionic Brain with the participation of Peter A. DePergola II, Tomislav Miletić and Frederic Gilbert, Aníbal M. Astobiza, Txetxu Ausin, Ricardo M. Ferrer and Stephen Rainey and Natasha Vita-More. Finally, Section V follows on the Ethics of Artificial Intelligence with chapters by Federico Pistono and Roman V. Yamploskiy, Hasse Hämäläinen, Vernon Vinge and Eray Özkural. The Age of Artificial Intelligence is imminent, if not here already. We should ensure that we invest in the right people and the right ideas to create the best possible solutions to the problems of the present and prepare for those of the future. This edited volume will be of particular interest to researchers in the field of A.I. as well of those in Cognitive Science (Philosophy of the Mind, Neuroscience, and Linguistics), Aesthetics and Arts, Applied Ethics and Political Philosophy / Law. Students studying the aforementioned topics can also benefit from its contents.
Transforming the Language Teaching Experience in the Age of AI by Kartal, Galip Pdf
Transforming the Language Teaching Experience in the Age of AI, edited by Galip Kartal, is a vital resource that addresses the evolving challenges in language education due to technological advancements. This book offers a comprehensive analysis of AI's impact on language education, providing innovative research, practical insights, and interdisciplinary collaboration opportunities. From AI-driven language learning methods to ethical considerations, the book equips educators, policymakers, and researchers with valuable insights to shape effective educational strategies and policies, inspiring the adoption of innovative approaches that harness AI's potential to enhance language teaching. Through successful case studies and forward-thinking perspectives, Transforming the Language Teaching Experience in the Age of AI envisions a future where AI-driven methodologies redefine global language education. This publication not only facilitates a deeper understanding of AI's role in language education but also fosters a shared vision among educators and researchers, promoting a transformative and collaborative learning experience for students worldwide.
Architecture in the Age of Artificial Intelligence by Neil Leach Pdf
Artificial intelligence is everywhere – from the apps on our phones to the algorithms of search engines. Without us noticing, the AI revolution has arrived. But what does this mean for the world of design? The first volume in a two-book series, Architecture in the Age of Artificial Intelligence introduces AI for designers and considers its positive potential for the future of architecture and design. Explaining what AI is and how it works, the book examines how different manifestations of AI will impact the discipline and profession of architecture. Highlighting current case-studies as well as near-future applications, it shows how AI is already being used as a powerful design tool, and how AI-driven information systems will soon transform the design of buildings and cities. Far-sighted, provocative and challenging, yet rooted in careful research and cautious speculation, this book, written by architect and theorist Neil Leach, is a must-read for all architects and designers – including students of architecture and all design professionals interested in keeping their practice at the cutting edge of technology.
Toward Human-Level Artificial Intelligence by Philip C. Jackson, Jr Pdf
How can human-level artificial intelligence be achieved? What are the potential consequences? This book describes a research approach toward achieving human-level AI, combining a doctoral thesis and research papers by the author. The research approach, called TalaMind, involves developing an AI system that uses a 'natural language of thought' based on the unconstrained syntax of a language such as English; designing the system as a collection of concepts that can create and modify concepts to behave intelligently in an environment; and using methods from cognitive linguistics for multiple levels of mental representation. Proposing a design-inspection alternative to the Turing Test, these pages discuss 'higher-level mentalities' of human intelligence, which include natural language understanding, higher-level forms of learning and reasoning, imagination, and consciousness. Dr. Jackson gives a comprehensive review of other research, addresses theoretical objections to the proposed approach and to achieving human-level AI in principle, and describes a prototype system that illustrates the potential of the approach. This book discusses economic risks and benefits of AI, considers how to ensure that human-level AI and superintelligence will be beneficial for humanity, and gives reasons why human-level AI may be necessary for humanity's survival and prosperity.
Deep Learning and Linguistic Representation by Shalom Lappin Pdf
The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.
Proposing a new approach to the study of language, this book argues for the need to consider syntax in context and to engage with a wider variety of perspectives that better reflect the modern world and the changes to our language prompted by increased cultural diversity, the prevalence of social media, AI, and more. Referencing big data and drawing on a corpus of linguistic research, the book explores in particular the socio-pragmatic sensitivity and complexity within East Asian languages including Chinese, Japanese, and Korean, offering new insights that step away from traditional approaches to formal syntax. In tracing the history of syntactic theory, it highlights the shifts in our communication as we adapt to technological developments, and focuses in particular on the significant advances in AI. Arguing that traditional syntactic theory is no longer in keeping with real life communication, Jieun Kiaer scrutinises current approaches and raises key questions about the need for a more appropriate grammar better suited to the diversity of human language.
How to educate the next generation of college students to invent, to create, and to discover—filling needs that even the most sophisticated robot cannot. Driverless cars are hitting the road, powered by artificial intelligence. Robots can climb stairs, open doors, win Jeopardy, analyze stocks, work in factories, find parking spaces, advise oncologists. In the past, automation was considered a threat to low-skilled labor. Now, many high-skilled functions, including interpreting medical images, doing legal research, and analyzing data, are within the skill sets of machines. How can higher education prepare students for their professional lives when professions themselves are disappearing? In Robot-Proof, Northeastern University president Joseph Aoun proposes a way to educate the next generation of college students to invent, to create, and to discover—to fill needs in society that even the most sophisticated artificial intelligence agent cannot. A “robot-proof” education, Aoun argues, is not concerned solely with topping up students' minds with high-octane facts. Rather, it calibrates them with a creative mindset and the mental elasticity to invent, discover, or create something valuable to society—a scientific proof, a hip-hop recording, a web comic, a cure for cancer. Aoun lays out the framework for a new discipline, humanics, which builds on our innate strengths and prepares students to compete in a labor market in which smart machines work alongside human professionals. The new literacies of Aoun's humanics are data literacy, technological literacy, and human literacy. Students will need data literacy to manage the flow of big data, and technological literacy to know how their machines work, but human literacy—the humanities, communication, and design—to function as a human being. Life-long learning opportunities will support their ability to adapt to change. The only certainty about the future is change. Higher education based on the new literacies of humanics can equip students for living and working through change.
Cecile L. Paris,William R. Swartout,William C. Mann
Author : Cecile L. Paris,William R. Swartout,William C. Mann Publisher : Springer Science & Business Media Page : 414 pages File Size : 54,7 Mb Release : 2013-03-14 Category : Computers ISBN : 9781475759457
Natural Language Generation in Artificial Intelligence and Computational Linguistics by Cecile L. Paris,William R. Swartout,William C. Mann Pdf
One of the aims of Natural Language Processing is to facilitate .the use of computers by allowing their users to communicate in natural language. There are two important aspects to person-machine communication: understanding and generating. While natural language understanding has been a major focus of research, natural language generation is a relatively new and increasingly active field of research. This book presents an overview of the state of the art in natural language generation, describing both new results and directions for new research. The principal emphasis of natural language generation is not only to facili tate the use of computers but also to develop a computational theory of human language ability. In doing so, it is a tool for extending, clarifying and verifying theories that have been put forth in linguistics, psychology and sociology about how people communicate. A natural language generator will typically have access to a large body of knowledge from which to select information to present to users as well as numer of expressing it. Generating a text can thus be seen as a problem of ous ways decision-making under multiple constraints: constraints from the propositional knowledge at hand, from the linguistic tools available, from the communicative goals and intentions to be achieved, from the audience the text is aimed at and from the situation and past discourse. Researchers in generation try to identify the factors involved in this process and determine how best to represent the factors and their dependencies.
Natural Language Processing: Concepts, Methodologies, Tools, and Applications by Management Association, Information Resources Pdf
As technology continues to become more sophisticated, a computer’s ability to understand, interpret, and manipulate natural language is also accelerating. Persistent research in the field of natural language processing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror natural language processes that have existed for centuries. Natural Language Processing: Concepts, Methodologies, Tools, and Applications is a vital reference source on the latest concepts, processes, and techniques for communication between computers and humans. Highlighting a range of topics such as machine learning, computational linguistics, and semantic analysis, this multi-volume book is ideally designed for computer engineers, computer and software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of natural language processing.
Applied Natural Language Processing in the Enterprise by Ankur A. Patel,Ajay Uppili Arasanipalai Pdf
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Artificial Intelligence: A Very Short Introduction by Margaret A. Boden Pdf
The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction , Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.
The Myth of Artificial Intelligence by Erik J. Larson Pdf
“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.
New Methods In Language Processing by D. B. Jones,H. Somers Pdf
Studies in Computational Linguistics presents authoritative texts from an international team of leading computational linguists. The books range from the senior undergraduate textbook to the research level monograph and provide a showcase for a broad range of recent developments in the field. The series should be interesting reading for researchers and students alike involved at this interface of linguistics and computing.
