Machine Conversationsis a collection of some of the best research available in the practical arts of machine conversation. The book describes various attempts to create practical and flexible machine conversation - ways of talking to computers in an unrestricted version of English or some other language. While this book employs and advances the theory of dialogue and its linguistic underpinnings, the emphasis is on practice, both in university research laboratories and in company research and development. Since the focus is on the task and on the performance, this book provides some of the first-rate work taking place in industry, quite apart from the academic tradition. It also reveals striking and relevant facts about the tone of machine conversations and closely evaluates what users require. Machine Conversations is an excellent reference for researchers interested in computational linguistics, cognitive science, natural language processing, artificial intelligence, human computer interfaces and machine learning.

A brilliant probe into the political and psychological effects of our changing relationship with social media Former social media executives tell us that the system is an addiction-machine. We are users, waiting for our next hit as we like, comment and share. We write to the machine as individuals, but it responds by aggregating our fantasies, desires and frailties into data, and returning them to us as a commodity experience. The Twittering Machine is an unflinching view into the calamities of digital life: the circus of online trolling, flourishing alt-right subcultures, pervasive corporate surveillance, and the virtual data mines of Facebook and Google where we spend considerable portions of our free time. In this polemical tour de force, Richard Seymour shows how the digital world is changing the ways we speak, write, and think. Through journalism, psychoanalytic reflection and insights from users, developers, security experts and others, Seymour probes the human side of the machine, asking what we’re getting out of it, and what we’re getting into. Social media held out the promise that we could make our own history–to what extent did we choose the nightmare that it has become?

A strikingly original exploration of what it might mean to be authentically human in the age of artificial intelligence, from the author of the critically-acclaimed Interior States. • "At times personal, at times philosophical, with a bracing mixture of openness and skepticism, it speaks thoughtfully and articulately to the most crucial issues awaiting our future." —Phillip Lopate “[A] truly fantastic book.”—Ezra Klein For most of human history the world was a magical and enchanted place ruled by forces beyond our understanding. The rise of science and Descartes's division of mind from world made materialism our ruling paradigm, in the process asking whether our own consciousness—i.e., souls—might be illusions. Now the inexorable rise of technology, with artificial intelligences that surpass our comprehension and control, and the spread of digital metaphors for self-understanding, the core questions of existence—identity, knowledge, the very nature and purpose of life itself—urgently require rethinking. Meghan O'Gieblyn tackles this challenge with philosophical rigor, intellectual reach, essayistic verve, refreshing originality, and an ironic sense of contradiction. She draws deeply and sometimes humorously from her own personal experience as a formerly religious believer still haunted by questions of faith, and she serves as the best possible guide to navigating the territory we are all entering.

"Mind-opening, thought-provoking and incredibly timely… An absolutely spectacular read."—Cory Doctorow, BoingBoing A million listeners trust NPR's Brooke Gladstone to guide them through the complexities of the modern media. Bursting onto the page in vivid comics by acclaimed artist Josh Neufeld, this brilliant radio personality guides us through two millennia of media history, debunking the notion that "The Media" is an external force beyond our control and equipping us to be savvy consumers and shapers of the news.

Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content – like emotions, but also satirical expressions – and applications in the healthcare field. NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson’s disease, or help psychotherapists. This book is intended for a wide audience. Beginners will find useful chapters providing a general introduction to NLP techniques, while experienced professionals will appreciate the chapters about advanced management of emotion, empathy, and non-literal content.

This volume presents the results of the Neural Information Processing Systems Competition track at the 2018 NeurIPS conference. The competition follows the same format as the 2017 competition track for NIPS. Out of 21 submitted proposals, eight competition proposals were selected, spanning the area of Robotics, Health, Computer Vision, Natural Language Processing, Systems and Physics. Competitions have become an integral part of advancing state-of-the-art in artificial intelligence (AI). They exhibit one important difference to benchmarks: Competitions test a system end-to-end rather than evaluating only a single component; they assess the practicability of an algorithmic solution in addition to assessing feasibility. The eight run competitions aim at advancing the state of the art in deep reinforcement learning, adversarial learning, and auto machine learning, among others, including new applications for intelligent agents in gaming and conversational settings, energy physics, and prosthetics.