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Cognitive Plausibility in Natural Language Processing
This book explores the cognitive plausibility of computational language models and why it’s an important factor in their development and evaluation. The authors present the idea that more can be learned about cognitive plausibility of computational language models by linking signals of cognitive processing load in humans to interpretability methods that allow for exploration of the hidden mechanisms of neural models. The book identifies limitations when applying the existing methodology for representational analyses to contextualized settings and critiques the current emphasis on form over more grounded approaches to modeling language. The authors discuss how novel techniques for transfer and curriculum learning could lead to cognitively more plausible generalization capabilities in models. The book also highlights the importance of instance-level evaluation and includes thorough discussion of the ethical considerations that may arise throughout the various stages of cognitive plausibility research.
AI for Disease Surveillance and Pandemic Intelligence
This book aims to highlight the latest achievements in the use of artificial intelligence for digital disease surveillance, pandemic intelligence, as well as public and clinical health surveillance. The edited book contains selected papers presented at the 2021 Health Intelligence workshop, co-located with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. While disease surveillance has always been a crucial process, the recent global health crisis caused by COVID-19 has once again highlighted our dependence on intelligent surveillance infrastructures that provide support for making sound and timely decisions. This book provides information for researchers, students, industry professionals, and public health agencies interested in the applications of AI in population health and personalized medicine.
AI Leadership Handbook
The pressure on leaders to incorporate AI into their business has never been higher. Despite their best efforts, 85 percent of AI projects fail. But that is rarely just because of technology. Between unrealistic expectations of what AI can do, isolated science projects turned into money pits, and employees looking for clarity on how AI influences their jobs, learning how to successfully introduce AI into your organization can be difficult. Getting it right on the second or third attempt is not an option. In order for your AI program to be successful, you need to be aware of all the facets involved, not just the technology—a daunting task. The AI Leadership Handbookprepares you to master th...
Semantic Relations Between Nominals, Second Edition
Opportunity and Curiosity find similar rocks on Mars. One can generally understand this statement if one knows that Opportunity and Curiosity are instances of the class of Mars rovers, and recognizes that, as signalled by the word on, rocks are located on Mars. Two mental operations contribute to understanding: recognize how entities/concepts mentioned in a text interact and recall already known facts (which often themselves consist of relations between entities/concepts). Concept interactions one identifies in the text can be added to the repository of known facts, and aid the processing of future texts. The amassed knowledge can assist many advanced language-processing tasks, including sum...
Computer Vision
Computer vision has made enormous progress in recent years, and its applications are multifaceted and growing quickly, while many challenges still remain. This book brings together a range of leading researchers to examine a wide variety of research directions, challenges, and prospects for computer vision and its applications. This book highlights various core challenges as well as solutions by leading researchers in the field. It covers such important topics as data-driven AI, biometrics, digital forensics, healthcare, robotics, entertainment and XR, autonomous driving, sports analytics, and neuromorphic computing, covering both academic and industry R&D perspectives. Providing a mix of breadth and depth, this book will have an impact across the fields of computer vision, imaging, and AI. Computer Vision: Challenges, Trends, and Opportunities covers timely and important aspects of computer vision and its applications, highlighting the challenges ahead and providing a range of perspectives from top researchers around the world. A substantial compilation of ideas and state-of-the-art solutions, it will be of great benefit to students, researchers, and industry practitioners.
Breeding, production recording, health and the evaluation of farm animals
"This publication focuses on the various aspects of domestic animal recording, aimed at improving the management of herds and increasing their productivity. New strategies for recording are illustrated and the most updated technologies are presented, on the basis of national experiences where such technologies are already adopted. Although cattle is the prominent species, two parts are dedicated to small ruminants recording and to buffalo recording. Future challenges and opportunities for further development of ICAR and the definition of the future scenarios in the animal recording sector are also described. A special section is dedicated to 'Improving the health traits by recording and eval...
Semantic Modeling for Data
What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to extract business gold—but you still fail. The reason? Bad data semantics. In this practical and comprehensive field guide, author Panos Alexopoulos takes you on an eye-opening journey through semantic data modeling as applied in the real world. You’ll learn how to master this craft to increase the usability and value of your data and applications. You’ll also explore the pitfalls to avoid and dilemmas to overcome for building high-quality and valuable semantic representations of data. Understand the fundamental...
A Companion to Chomsky
A COMPANION TO CHOMSKY Widely considered to be one of the most important public intellectuals of our time, Noam Chomsky has revolutionized modern linguistics. His thought has had a profound impact upon the philosophy of language, mind, and science, as well as the interdisciplinary field of cognitive science which his work helped to establish. Now, in this new Companion dedicated to his substantial body of work and the range of its influence, an international assembly of prominent linguists, philosophers, and cognitive scientists reflect upon the interdisciplinary reach of Chomsky's intellectual contributions. Balancing theoretical rigor with accessibility to the non-specialist, the Companion...
Distributional Semantics
This book provides a comprehensive foundation of distributional methods in computational modeling of meaning. It aims to build a common understanding of the theoretical and methodological foundations for students of computational linguistics, natural language processing, computer science, artificial intelligence, and cognitive science.
