Linguistics For The Age Of Ai

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.

"An explantion of a knowledge-based system for creating computational agents with human-like language ability"--

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, 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.

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.

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.

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.