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108 results in Artificial Intelligence and Natural Language Processing

Page 1 of 6

Natural Language Processing
  • A Machine Learning Perspective
  • 2nd edition
  • Yue Zhang, Zhiyang Teng
  • Coming soon
  • Expected online publication date:
    December 2026
    Print publication:
    31 December 2026
  • This gentle introduction to the most important techniques in natural language processing uses a unified mathematical and algorithmic framework and gradually increases in complexity. Topics covered range from n-gram language models to large language models (LLMs), from perceptron to deep learning, from text classification to structured prediction (e.g., sequence labelling, segmentation, and parsing) and generation, and from discrete representation to neural representation of linguistics structures. This book provides a comprehensive overview of NLP, making it ideal for upper undergraduate and graduate students in computer science and a valuable reference for researchers and engineers. Exercises of varying difficulty are provided as well as teaching slides and tutorial videos. The new edition features three new chapters on pre-trained language models and large language models as well as a new preliminary chapter overviewing data and model as a framework for NLP methods.

Becoming an AI Researcher
  • Practical Advice for Graduate Students
  • Stefano V. Albrecht
  • Coming soon
  • Expected online publication date:
    December 2026
    Print publication:
    31 December 2026
  • Spanning the full AI Ph.D. journey, this practical guide offers clear, realistic, and action oriented advice for success. Designed as an end-to-end guide, the book leads readers from finding a research problem to experimentation, writing, conferences, and the final defense. Readers learn how to partner effectively with advisors, run productive meetings, and navigate review and rejection with confidence. The book provides guidance on responsible AI research and using LLMs effectively while safeguarding scientific integrity. The final stages of the PhD receive explicit focus, with advice on shaping publications into a coherent dissertation, preparing for the defense, and responding to examiners. This guide extends beyond graduation, exploring career paths in academia, industry, and the public sector while emphasizing transferable skills and strategic decisions. Ideal for Ph.D. students in AI and machine learning, as well as those considering starting a PhD, this book provides actionable advice that clarifies next steps and accelerates progress.

Trustworthy AI
  • Ethical Frameworks for Responsible Innovation
  • Andrea Aler Tubella, Virginia Dignum, Marçal Mora-Cantallops, Juan Carlos Nieves, Andreas Theodorou
  • Coming soon
  • Expected online publication date:
    October 2026
    Print publication:
    30 September 2026
  • Artificial intelligence is reshaping decisions that affect people, institutions, and societies. Understanding how to design, deploy, and govern AI systems that can be trusted is now essential in many disciplines. This book offers a clear, concise introduction to trustworthy AI, treating AI not just as a technical artifact but as a socio-technical system embedded in human contexts. Developed from an internationally applicable educational framework, the book is designed for teaching and learning in computer science, data science, law, policy, business, and related fields. It equips students and professionals with the concepts and judgment needed to engage critically and responsibly with AI in practice. Combining ethics, governance, and practical insight, the book explains key concepts including transparency, fairness, accountability, human oversight, and stakeholder participation. An interdisciplinary approach makes the material accessible to both technical and non-technical audiences, with realistic scenarios and reflection questions so readers connect principles to real-world AI applications.

Empathy and Artificial Intelligence
  • Challenges, Advances and Ethical Considerations
  • Edited by Anat Perry, C. Daryl Cameron
  • Coming soon
  • Expected online publication date:
    September 2026
    Print publication:
    30 September 2026
  • As artificial intelligence chatbots offer increasingly sophisticated emotional support, society faces a profound question: can a machine truly empathize? Empathy and Artificial Intelligence provides the first comprehensive roadmap for this pivotal moment. Moving beyond simple binaries of 'hype' or 'doom,' this interdisciplinary volume unites leading psychologists, philosophers, and engineers to explore the tangled web of synthetic care. Key chapters investigate the 'AI Advantage' – where machines often outperform humans in perceived empathy – alongside the 'AI Penalty,' where discovering the artifice corrodes trust. The text navigates the distinct landscapes of text-based LLMs and embodied robots, addressing urgent ethical dilemmas and exploring whether reliance on AI risks the atrophy of our moral capacities or enables synthetic agents to scaffold stronger human relationships. Essential for researchers, students, and curious observers, this book investigates whether outsourcing our emotional labor saves us time, or costs us our humanity.

Operationalizing Responsible AI
  • Edited by Daniele Quercia, Marios Constantinides
  • Coming soon
  • Expected online publication date:
    August 2026
    Print publication:
    31 August 2026
  • How can we build and govern trustworthy AI? Operationalizing Responsible AI brings together leading scholars and practitioners to address this urgent question. Each chapter explores a key dimension of responsibility - fairness, explainability, psychological safety, accountability, consent, transparency, auditability, and contextualization – defining what it means, why it matters, and how it can be achieved in practice. Through interdisciplinary perspectives and real-world examples, the book bridges ethical principles, legal frameworks such as the EU AI Act, and technical approaches including explainable AI and audit methodologies. Written for researchers, policymakers, and professionals, the book offers both conceptual clarity and practical guidance for advancing Responsible AI that is fair, transparent, and aligned with human values.

Generative AI and Stochastic Thermodynamics
  • A Tale of Free Energies
  • Max Welling, Sirui Lu, Lars Holdijk
  • Coming soon
  • Expected online publication date:
    July 2026
    Print publication:
    31 July 2026
  • Originating from lectures delivered at the African Institute of Mathematical Sciences, this book presents a unifying perspective on traditional and modern methods in generative AI and stochastic thermodynamics. By relating the core topics in machine learning to the notion of (variational) free-energy, a bridge is built between methods such as latent variable models, variational auto-encoders, optimal control, optimal transport, normalizing flows and diffusion models and concepts such as entropy production and fluctuation theorems in stochastic thermodynamics. Structured into three main parts, the book commences by setting up the required mathematical and statistical physics preliminaries needed to make it broadly accessible. The largest part of the book then focuses on building intuition of major advances in generative AI by considering discrete time processes and their relationship to topics in stochastic thermodynamics. Finally, the authors take a short excursion to the continuous time domain for the more advanced learner.

Speech Technology
  • A Theoretical and Practical Introduction
  • Michael Hammond
  • Coming soon
  • Expected online publication date:
    May 2026
    Print publication:
    12 March 2026
  • In recent years, speech recognition devices have become central to our everyday lives. Systems such as Siri, Alexa, speech-to-text, and automated telephone services, are built by people applying expertise in sound structure and natural language processing to generate computer programmes that can recognise and understand speech. This exciting new advancement has led to a rapid growth in speech technology courses being added to linguistics programmes; however, there has so far been a lack of material serving the needs of students who have limited or no background in computer science or mathematics. This textbook addresses that need, by providing an accessible introduction to the fundamentals of computer speech synthesis and automatic speech recognition technology, covering both neural and non-neural approaches. It explains the basic concepts in non-technical language, providing step-by-step explanations of each formula, practical activities and ready-made code for students to use, which is also available on an accompanying website.

Translate
  • Multilingual Access to Critical Services in the Age of AI
  • Lucas N. Vieira
  • Coming soon
  • Expected online publication date:
    May 2026
    Print publication:
    11 June 2026
  • Automated translations can break down language barriers and increase access to information, but they can also be highly inaccurate. This timely book explores the social challenges and ethical considerations of using artificial intelligence (AI) translations in high-stakes professional environments. Based on contributions from over two thousand professionals from critical sectors including healthcare, social work, emergency services and the police, the analysis explores the motivations and consequences of multilingual uses of AI across these sectors. Real-life examples provided throughout the book bring home the delicate balance of risks and benefits of using AI to serve and communicate with multilingual communities. By drawing on concepts such as virtue, trust, empathy and AI literacy, this book makes a case for nuance and flexibility, defends the value of language access, and calls for greater transparency in the development and deployment of AI translation tools. This title is also available as open access on Cambridge Core.

Knowledge-Infused Learning
  • Neurosymbolic AI for Explainability, Interpretability, and Safety
  • Manas Gaur, Amit P. Sheth
  • Published online:
    22 April 2026
    Print publication:
    07 May 2026
  • Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.

Introduction to Neuromorphic Computing
  • Shriram Ramanathan, Abhronil Sengupta
  • Published online:
    01 January 2026
    Print publication:
    22 January 2026
  • Artificial intelligence is transforming industries and society, but its high energy demands challenge global sustainability goals. Biological intelligence, in contrast, offers both good performance and exceptional energy efficiency. Neuromorphic computing, a growing field inspired by the structure and function of the brain, aims to create energy-efficient algorithms and hardware by integrating insights from biology, physics, computer science, and electrical engineering. This concise and accessible book delves into the principles, mechanisms, and properties of neuromorphic systems. It opens with a primer on biological intelligence, describing learning mechanisms in both simple and complex organisms, then turns to the application of these principles and mechanisms in the development of artificial synapses and neurons, circuits, and architectures. The text also delves into neuromorphic algorithm design, and the unique challenges faced by algorithmic researchers working in this area. The book concludes with a selection of practice problems, with solutions available to instructors online.

Artificial Intelligence in Schools
  • Educational Challenges and Opportunities
  • Thomas Nygren
  • Published online:
    24 December 2025
    Print publication:
    30 October 2025
  • Designed for educators, researchers, and policymakers, this insightful book equips readers with practical strategies, critical perspectives, and ethical insights into integrating AI in education. First published in Swedish in 2023, and here translated, updated, and adapted for an English-speaking international audience, it provides a user-friendly guide to the digital and AI-related challenges and opportunities in today's education systems. Drawing upon cutting-edge research, Thomas Nygren outlines how technology can be usefully integrated into education, not as a replacement for humans, but as a tool that supports and reinforces students' learning. Written in accessible language, topics covered include AI literacy, source awareness, and subject-specific opportunities. The central role of the teacher is emphasized throughout, as is the importance of thoughtful engagement with technology. By guiding the reader through the fastevolving digital transformation in education globally, it ultimately enables students to become informed participants in the digital world.

Lost in Automatic Translation
  • Navigating Life in English in the Age of Language Technologies
  • Vered Shwartz
  • Published online:
    08 October 2025
    Print publication:
    21 August 2025
  • The last decade has seen an exponential increase in the development and adoption of language technologies, from personal assistants such as Siri and Alexa, through automatic translation, to chatbots like ChatGPT. Yet questions remain about what we stand to lose or gain when we rely on them in our everyday lives. As a non-native English speaker living in an English-speaking country, Vered Shwartz has experienced both amusing and frustrating moments using language technologies: from relying on inaccurate automatic translation, to failing to activate personal assistants with her foreign accent. English is the world's foremost go-to language for communication, and mastering it past the point of literal translation requires acquiring not only vocabulary and grammar rules, but also figurative language, cultural references, and nonverbal communication. Will language technologies aid us in the quest to master foreign languages and better understand one another, or will they make language learning obsolete?

Human-AI Interaction and Collaboration
  • Edited by Dan Wu, Shaobo Liang
  • Published online:
    19 September 2025
    Print publication:
    09 October 2025
  • The integration of AI into information systems will affect the way users interface with these systems. This exploration of the interaction and collaboration between humans and AI reveals its potential and challenges, covering issues such as data privacy, credibility of results, misinformation, and search interactions. Later chapters delve into application domains such as healthcare and scientific discovery. In addition to providing new perspectives on and methods for developing AI technology and designing more humane and efficient artificial intelligence systems, the book also reveals the shortcomings of artificial intelligence technologies through case studies and puts forward corresponding countermeasures and suggestions. This book is ideal for researchers, students, and industry practitioners interested in enhancing human-centered AI systems and insights for future research.

Metacognitive Artificial Intelligence
  • Edited by Paulo Shakarian, Hua Wei
  • Published online:
    08 September 2025
    Print publication:
    25 September 2025
  • This groundbreaking volume is designed to meet the burgeoning needs of the research community and industry. This book delves into the critical aspects of AI's self-assessment and decision-making processes, addressing the imperative for safe and reliable AI systems in high-stakes domains such as autonomous driving, aerospace, manufacturing, and military applications. Featuring contributions from leading experts, the book provides comprehensive insights into the integration of metacognition within AI architectures, bridging symbolic reasoning with neural networks, and evaluating learning agents' competency. Key chapters explore assured machine learning, handling AI failures through metacognitive strategies, and practical applications across various sectors. Covering theoretical foundations and numerous practical examples, this volume serves as an invaluable resource for researchers, educators, and industry professionals interested in fostering transparency and enhancing reliability of AI systems.

Acting, Planning, and Learning
  • Malik Ghallab, Dana Nau, Paolo Traverso
  • Foreword by Michela Milano
  • Published online:
    19 May 2025
    Print publication:
    05 June 2025
  • AI's next big challenge is to master the cognitive abilities needed by intelligent agents that perform actions. Such agents may be physical devices such as robots, or they may act in simulated or virtual environments through graphic animation or electronic web transactions. This book is about integrating and automating these essential cognitive abilities: planning what actions to undertake and under what conditions, acting (choosing what steps to execute, deciding how and when to execute them, monitoring their execution, and reacting to events), and learning about ways to act and plan. This comprehensive, coherent synthesis covers a range of state-of-the-art approaches and models –deterministic, probabilistic (including MDP and reinforcement learning), hierarchical, nondeterministic, temporal, spatial, and LLMs –and applications in robotics. The insights it provides into important techniques and research challenges will make it invaluable to researchers and practitioners in AI, robotics, cognitive science, and autonomous and interactive systems.

The Cambridge Companion to Religion and Artificial Intelligence
  • Edited by Beth Singler, Fraser Watts
  • Published online:
    20 November 2024
    Print publication:
    21 November 2024
  • Religion and artificial intelligence are now deeply enmeshed in humanity's collective imagination, narratives, institutions, and aspirations. Their growing entanglement also runs counter to several dominant narratives that engage with long-standing historical discussions regarding the relationship between the 'sacred” and the 'secular' - technology and science. This Cambridge Companion explores the fields of Religion and AI comprehensively and provides an authoritative guide to their symbiotic relationship. It examines established topics, such as transhumanism, together with new and emerging fields, notably, computer simulations of religion. Specific chapters are devoted to Judaism, Christianity, Islam, Hinduism, and Buddhism, while others demonstrate that entanglements between religion and AI are not always encapsulated through such a paradigm. Collectively, the volume addresses issues that AI raises for religions, and contributions that AI has made to religious studies, especially the conceptual and philosophical issues inherent in the concept of an intelligent machine, and social-cultural work on attitudes to AI and its impact on contemporary life. The diverse perspectives in this Companion demonstrate how all religions are now interacting with artificial intelligence.

Artificial Intelligence
  • Economic Perspectives and Models
  • Wim Naudé, Thomas Gries, Nicola Dimitri
  • Published online:
    23 May 2024
    Print publication:
    30 May 2024
  • Is Artificial Intelligence a more significant invention than electricity? Will it result in explosive economic growth and unimaginable wealth for all, or will it cause the extinction of all humans? Artificial Intelligence: Economic Perspectives and Models provides a sober analysis of these questions from an economics perspective. It argues that to better understand the impact of AI on economic outcomes, we must fundamentally change the way we think about AI in relation to models of economic growth. It describes the progress that has been made so far and offers two ways in which current modelling can be improved: firstly, to incorporate the nature of AI as providing abilities that complement and/or substitute for labour, and secondly, to consider demand-side constraints. Outlining the decision-theory basis of both AI and economics, this book shows how this, and the incorporation of AI into economic models, can provide useful tools for safe, human-centered AI.

Search Methods in Artificial Intelligence
  • Deepak Khemani
  • Published online:
    30 April 2024
    Print publication:
    24 October 2024
  • This book is designed to provide in-depth knowledge on how search plays a fundamental role in problem solving. Meant for undergraduate and graduate students pursuing courses in computer science and artificial intelligence, it covers a wide spectrum of search methods. Readers will be able to begin with simple approaches and gradually progress to more complex algorithms applied to a variety of problems. It demonstrates that search is all pervasive in artificial intelligence and equips the reader with the relevant skills. The text starts with an introduction to intelligent agents and search spaces. Basic search algorithms like depth first search and breadth first search are the starting points. Then, it proceeds to discuss heuristic search algorithms, stochastic local search, algorithm A*, and problem decomposition. It also examines how search is used in playing board games, deduction in logic and automated planning. The book concludes with a coverage on constraint satisfaction.

The Cambridge Handbook of Private Law and Artificial Intelligence
  • Edited by Ernest Lim, Phillip Morgan
  • Published online:
    21 March 2024
    Print publication:
    28 March 2024
  • AI appears to disrupt key private law doctrines, and threatens to undermine some of the principal rights protected by private law. The social changes prompted by AI may also generate significant new challenges for private law. It is thus likely that AI will lead to new developments in private law. This Cambridge Handbook is the first dedicated treatment of the interface between AI and private law, and the challenges that AI poses for private law. This Handbook brings together a global team of private law experts and computer scientists to deal with this problem, and to examine the interface between private law and AI, which includes issues such as whether existing private law can address the challenges of AI and whether and how private law needs to be reformed to reduce the risks of AI while retaining its benefits.

Deep Learning for Natural Language Processing
  • A Gentle Introduction
  • Mihai Surdeanu, Marco Antonio Valenzuela-Escárcega
  • Published online:
    01 February 2024
    Print publication:
    08 February 2024
  • Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to deep learning for natural language processing. It covers both theoretical and practical aspects, and assumes minimal knowledge of machine learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern deep learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems.

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