Naturligt sprog og maskinoversættelse

"My Child, the Algorithm describes encounters between a single parent, a curious, verbal toddler, and a language-producing algorithm. Like a male seahorse, Hannah Silva carried a baby made from her partner's egg. But when she gave birth, her partner left, and Hannah found herself navigating life alone with her child, surviving on United Kingdom universal credit, humor, and buckets of imagination. As she navigates friendship, dating, and life as a queer parent in London, Hannah begins cowriting with an open-source language model, a precursor to ChatGPT, feeding the algorithm language and receiving language in return. Through her interactions with her toddler and the algorithm, expressions of humor, play, and insight begin to emerge. With the help and disruption of these unreliable narrators, Hannah deconstructs her story and constructs a new one, unraveling what she has been taught to want, finding alternative ways of thinking, loving, and parenting today"--

Visualize your team's productivity soaring, KPIs shattering ceilings, and your organizational growth skyrocketing. This is achievable with an AI-powered mentor available 24/7-a mentor versed in AI prompting and AI prompts engineering.AI's proven effectiveness in leadership development isn't just talk; it's a transformation outlined in leadership books. Step into the role of an innovative leader with our book's 111 groundbreaking prompts and corresponding formulas. They are crafted to enhance your unique position, industry, and goals. Discover the Strategic Advantages of this Book:Speedy Implementation: Picture converting every leadership challenge into an actionable plan in real-time, thanks to AI prompt engineering.Quality Enhancement: Imagine a team excelling due to AI-enabled coaching, a technique that is not even in the latest coaching books.Customization: Envision an adaptive leadership strategy, fine-tuned for each team member, reflecting the essence of coaching.Exclusive Bonuses with Your Book Purchase:Exclusive access to 'My Coaching, Mentoring & Leadership Advisor' GPT: Personalized leadership, coaching, & mentoring guidance, significantly enhancing your professional growth with custom-tailored insights. E-copy of the book: Maximize your efficiency with our PDF. Effortlessly copy, paste, and tailor prompts to your needs. 222 Actionable AI Prompt Examples: Strengthen your position in business with prompts from real business cases. Comprehensive Guide to AI ChatGPT: Effortlessly embrace the world of AI. Our guide simplifies AI, providing you with a clear route to incorporate AI strategies into your work. 1100 Follow-Up Prompts: Promote ongoing growth and creativity. Follow-up prompts are a continual flow of new and innovative ideas.Click "Buy Now" to start your transformative journey today.

'Generativ AI: 17 vinkler til forståelse og anvendelse' er en lærerig bog, der åbner døren til en spændende verden af generativ kunstig intelligens. Skrevet af to brødre med passion for AI, tager denne bog dig med på en rejse fra teori til praksis, og fra nysgerrighed til forståelse af generativ AI.Med et særligt fokus på populære sprogmodeller som ChatGPT og tekst-til-billede værktøjer, giver bogen dig indblik i, hvordan generativ AI kan påvirke vores måde at tænke, skabe og interagere med teknologi på. Struktureret i 17 uafhængige 'vinkler', dækker bogen et bredt spektrum af emner - fra grundlæggende principper til diverse anvendelsesmetoder.Ud over at give dig en teoretisk forståelse, baseret på den nyeste forskning på området, får du også en praktisk håndbog, der kan tage din brug af AI til et højere niveau. Uanset om du er nybegynder eller erfaren bruger, giver bogen dig værktøjerne og viden til selv at udforske og anvende generativ AI, hvor end du ønsker.Du kan læse mere om bogen på hjemmesiden:https://momentum-ai.dk/bog/

Dieses Buch zeigt die Grundlagen des KI-Tools ChatGPT und viele einfache Anwendungsmöglichkeiten, mit denen die Künstliche Intelligenz die Arbeit leichter macht.

Efficiently transform your initial designs into big systems by learning the foundations of infrastructure, algorithms, and ethical considerations for modern software productsKey FeaturesLearn how to scale-up your machine learning software to a professional levelSecure the quality of your machine learning pipeline at runtimeApply your knowledge to natural languages, programming languages, and imagesBook DescriptionAlthough creating a machine learning pipeline or developing a working prototype of a software system from that pipeline is easy and straightforward nowadays, the journey toward a professional software system is still extensive. This book will help you get to grips with various best practices and recipes that will help software engineers transform prototype pipelines into complete software products.The book begins by introducing the main concepts of professional software systems that leverage machine learning at their core. As you progress, you'll explore the differences between traditional, non-ML software, and machine learning software. The initial best practices will guide you in determining the type of software you need for your product. Subsequently, you will delve into algorithms, covering their selection, development, and testing before exploring the intricacies of the infrastructure for machine learning systems by defining best practices for identifying the right data source and ensuring its quality.Towards the end, you'll address the most challenging aspect of large-scale machine learning systems - ethics. By exploring and defining best practices for assessing ethical risks and strategies for mitigation, you will conclude the book where it all began - large-scale machine learning software.What you will learnIdentify what the machine learning software best suits your needsWork with scalable machine learning pipelinesScale up pipelines from prototypes to fully fledged softwareChoose suitable data sources and processing methods for your productDifferentiate raw data from complex processing, noting their advantagesTrack and mitigate important ethical risks in machine learning softwareWork with testing and validation for machine learning systemsWho this book is forIf you're a machine learning engineer, this book will help you design more robust software, and understand which scaling-up challenges you need to address and why. Software engineers will benefit from best practices that will make your products robust, reliable, and innovative. Decision makers will also find lots of useful information in this book, including guidance on what to look for in a well-designed machine learning software product.Table of ContentsMachine Learning Compared to Traditional SoftwareElements of a Machine Learning Software SystemData in Software Systems - Text, Images, Code, FeaturesData Acquisition, Data Quality and NoiseQuantifying and Improving Data PropertiesTypes of Data in ML SystemsFeature Engineering for Numerical and Image DataFeature Engineering for Natural Language DataTypes of Machine Learning Systems - Feature-Based and Raw Data Based (Deep Learning)Training and evaluation of classical ML systems and neural networksTraining and evaluation of advanced algorithms - deep learning, autoencoders, GPT-3Designing machine learning pipelines (MLOps) and their testingDesigning and implementation of large scale, robust ML software - a comprehensive exampleEthics in data acquisition and management(N.B. Please use the Look Inside option to see further chapters)

En la era de la inteligencia artificial, la traducción automática ha superado niveles de calidad imprevisibles hace escasamente diez años. El volumen de cambio es tal que, desde los estudios de traducción, se hace necesario reflexionar sobre su repercusión en las diferentes especialidades de traducción. El presente volumen recoge aportaciones valiosas para poder entender la evolución de la traducción automática, así como el estado actual de la misma en los ámbitos especializados.

This book constitutes the refereed proceedings of the 19th International Conference on Formal Aspects of Component Software, FACS 2023, which took place virtually during October 19-20, 2023.The 11 full papers included in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: cloud computing, cyber-physical and critical systems, and the Internet of Things.

Escape the 9-to-5 Trap: Discover the AI-Powered Path to Passive IncomeA Beginner's Guide to Financial Freedom through ChatGPT and AIAre you tired of the daily grind, working long hours, and feeling like there's got to be more to life than just a paycheck? You're not alone. The world is changing, and technology is opening up new opportunities for people just like you to take control of their financial futures. In "Make Money with ChatGPT" we offer you a simple and easy-to-understand guide for beginners who want to break free from the 9-to-5 cycle and create a reliable stream of passive income. No gimmicks, no get-rich-quick schemes, just practical advice and real-world strategies that can help you leverage the power of AI to your advantage. Discover how AI, particularly ChatGPT, can be your ticket to financial independence. We provide you with step-by-step instructions on setting up your passive income ventures and crafting effective AI prompts. Whether you want to create your own online business or provide AI services to existing enterprises, this book has you covered. You'll discover:The true potential of AI in generating income online.Proven strategies and real-world applications of ChatGPT.Practical, step-by-step instructions to set up your passive income business.How to scale your income streams and achieve financial freedom.Solutions to common challenges, pitfalls, and risks - tailor-made for beginners.Expert insights on monitoring, optimizing, and staying ahead in the AI-driven landscape.And much more!If you're ready to take the first step toward financial freedom. Grab your copy today!

This book unveils the most advanced techniques and innovative applications in the natural language processing (NLP) field. It uncovers the secrets to enhancing language understanding, and presents practical solutions to different NLP tasks, as text augmentation, paraphrase generation, and restoring spaces and punctuation in multiple languages. It unlocks the potential of hierarchical multi-task learning for cross-lingual phoneme recognition, and allows readers to explore more real-world applications such as error correction, aggregating industrial security findings as well as predicting music emotion values from social media conversations. "Practical Solutions for Diverse Real-World NLP Applications" is the suitable guidebook for researchers, students, and practitioners as it paves the way for them by delivering invaluable insights and knowledge.

This book provides an analysis of acoustic features of polysemous strings and an implementation of a speech disambiguation program based on the phonetic information. Throughout the book, the term ¿polysemous string¿ refers to idioms with plausible literal interpretations, restrictive and non¿restrictive relative clauses, and the same expressions used as quotations and appearing in a non¿quotational context. The author explains how, typically, context is sufficient to determine the intended meaning. But there is enough evidence in psycholinguistic and phonetic literature to suspect that these superficially identical strings exhibit different acoustic features. In the experiment presented in the book, the participants were asked to read short excerpts containing corresponding elements of polysemous strings placed in the same intonational position. The acoustic analyses of ditropic pairs and subsequent statistical tests revealed that there is almost no difference in the duration, pitch, or intensity in literal and figurative interpretations. However, the analysis of relative clauses and quotations demonstrated that speakers are more likely to use acoustic cues to differentiate between the two possible readings. The book argues that the acoustic analysis of polysemous phrases could be successfully implemented in designing automatic speech recognition systems in order to improve their performance in disambiguating polysemous phrases.Analyzes acoustic features of polysemous strings and an implementation of a speech disambiguation programIncludes evidence that superficially identical strings exhibit different acoustic featuresArgues that acoustic analysis of polysemous phrases can be successfully implemented in automatic speech recognition

This book provides readers with a brief account of the history of Language Identification (LI) research and a survey of the features and methods most used in LI literature. LI is the problem of determining the language in which a document is written and is a crucial part of many text processing pipelines. The authors use a unified notation to clarify the relationships between common LI methods. The book introduces LI performance evaluation methods and takes a detailed look at LI-related shared tasks. The authors identify open issues and discuss the applications of LI and related tasks and proposes future directions for research in LI.

The European Summer School in Logic, Language and Information (ESSLLI) is organized every year by the Association for Logic, Language and Information (FoLLI) in different sites around Europe. The papers cover vastly dierent topics, but each fall in the intersection of the three primary topics of ESSLLI: Logic, Language and Computation. The 13 papers presented in this volume have been selected among 81 submitted papers over the years 2019, 2020 and 2021. The ESSLLI Student Session is an excellent venue for students to present their work and receive valuable feedback from renowned experts in their respective fields. The Student Session accepts submissions for three different tracks: Language and Computation (LaCo), Logic and Computation (LoCo), and Logic and Language (LoLa).

Enhance your writing with AI by mastering prompt engineering techniques and become an expert in developing and utilizing LLM prompts across applicationsKey FeaturesMaster prompt engineering techniques to harness AI's writing potentialDiscover diverse LLM applications for content creation and beyondLearn through practical examples, use cases, and hands-on guidancePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionUnlocking the Secrets of Prompt Engineering is your key to mastering the art of AI-driven writing. This book propels you into the world of large language models (LLMs), empowering you to create and apply prompts effectively for diverse applications, from revolutionizing content creation and chatbots to coding assistance.Starting with the fundamentals of prompt engineering, this guide provides a solid foundation in LLM prompts, their components, and applications. Through practical examples and use cases, you'll discover how LLMs can be used for generating product descriptions, personalized emails, social media posts, and even creative writing projects like fiction and poetry. The book covers advanced use cases such as creating and promoting podcasts, integrating LLMs with other tools, and using AI for chatbot development. But that's not all. You'll also delve into the ethical considerations, best practices, and limitations of using LLM prompts as you experiment and optimize your approach for best results.By the end of this book, you'll have unlocked the full potential of AI in writing and content creation to generate ideas, overcome writer's block, boost productivity, and improve communication skills.What you will learnExplore the different types of prompts, their strengths, and weaknessesUnderstand the AI agent's knowledge and mental modelEnhance your creative writing with AI insights for fiction and poetryDevelop advanced skills in AI chatbot creation and deploymentDiscover how AI will transform industries such as education, legal, and othersIntegrate LLMs with various tools to boost productivityUnderstand AI ethics and best practices, and navigate limitations effectivelyExperiment and optimize AI techniques for best resultsWho this book is forThis book is for a wide audience, including writers, marketing and business professionals, researchers, students, tech enthusiasts, and creative individuals. Anyone looking for strategies and examples for using AI co-writing tools like ChatGPT effectively in domains such as content creation, drafting emails, and inspiring artistic works, will find this book especially useful. If you are interested in AI, NLP, and innovative software for personal or professional use, this is the book for you.Table of ContentsUnderstanding Prompting & Prompt TechniquesGenerating Text with AI for Content CreationCreating and Promoting a Podcast Using ChatGPT and Other Practical ExamplesLLMs for Creative WritingUnlocking Insights from Unstructured Text - AI Techniques for Text AnalysisApplications of LLMs in Education and LawThe Rise of AI Pair Programmers: Teaming Up with Intelligent Assistants for Better CodeAI for ChatbotsBuilding Smarter Systems: Advanced LLM IntegrationsGenerative AI - Emerging Issues at the Intersection of Ethics and InnovationConclusion

Language is the most complex and intimate tool we have for communicating with one another in the enormous field of human communication. From the elegant poetry of classical literature to the quick words of the modern digital age, language has always been at our side, changing along with us and expressing our identity, history, and culture. The fascinating field of natural language processing (NLP), which lies at the junction of computer science and linguistics, is committed to understanding, interpreting, and harnessing the power of language. Welcome to "Natural Language Processing: Decoding Human Language- Algorithms, Techniques, and Applications." This e-book aims to introduce you to the field of natural language processing (NLP) and explore its various applications, methodologies, and algorithms. This e-book contains value for all readers, including seasoned researchers, professionals in the field, students, and those with a curious mind.Artificial intelligence (AI) advances have been revolutionary, and natural language processing (NLP) is at the core of many AI applications. NLP is the silent workhorse behind virtual assistants like Siri and Alexa, which can understand our commands and even generate text that appears eerily human.We'll examine the fundamental components of human language in the upcoming chapters, which will provide you with an understanding of the difficulties and complexities linguists and engineers face in their attempts to make machines "understand" humans. We'll explore the methods and algorithms-both traditional and innovative-that serve as the foundation for current NLP studies and applications. Beyond the technicalities, we'll talk about the ethics and biases in NLP as a reminder that although technology is neutral, its applications and consequences are seldom.

This book constitutes the refereed proceedings of the 26th Brazilian Symposium on Formal Methods, SBMF 2023, held in Manaus, Brazil, during December 4-8, 2023.The 7 full papers and 2 short papers presented in this book were carefully reviewed and selected from 16 submissions.The papers are divided into the following topical sections: specification and modeling languages; testing; and verification and validation.

This book presents a comprehensive overview of Natural Language Interfaces to Databases (NLIDBs), an indispensable tool in the ever-expanding realm of data-driven exploration and decision making. After first demonstrating the importance of the field using an interactive ChatGPT session, the book explores the remarkable progress and general challenges faced with real-world deployment of NLIDBs. It goes on to provide readers with a holistic understanding of the intricate anatomy, essential components, and mechanisms underlying NLIDBs and how to build them. Key concepts in representing, querying, and processing structured data as well as approaches for optimizing user queries are established for the reader before their application in NLIDBs is explored. The book discusses text to data through early relevant work on semantic parsing and meaning representation before turning to cutting-edge advancements in how NLIDBs are empowered to comprehend and interpret human languages. Various evaluation methodologies, metrics, datasets and benchmarks that play a pivotal role in assessing the effectiveness of mapping natural language queries to formal queries in a database and the overall performance of a system are explored. The book then covers data to text, where formal representations of structured data are transformed into coherent and contextually relevant human-readable narratives. It closes with an exploration of the challenges and opportunities related to interactivity and its corresponding techniques for each dimension, such as instances of conversational NLIDBs and multi-modal NLIDBs where user input is beyond natural language. This book provides a balanced mixture of theoretical insights, practical knowledge, and real-world applications that will be an invaluable resource for researchers, practitioners, and students eager to explore the fundamental concepts of NLIDBs.

Primitive software chatbots emerged in the 1960s, evolving swiftly through the decades and becoming able to provide engaging human-to-computer interactions sometime in the 1990s. Today, conversational technology is ubiquitous in many homes. Paired with web-searching abilities and neural networking, modern chatbots are capable of many tasks and are a major driving force behind machine learning and the quest for strong artificial intelligence, also known as artificial general intelligence (AGI).Sophisticated artificial intelligence is changing the online world as advanced software chatbots can provide customer service, research duties, and assist in healthcare. Modern chatbots have indeed numerous applications ¿ including those of a malicious nature. They can write our essays, conduct autonomous scams, and potentially influence politics.The Book of Chatbots is both a retrospective and a review of current artificial intelligence-driven conversational solutions. It explores their appeal to businesses and individuals as well as their greater social aspects, including the impact on academia. The book explains all relevant concepts for readers with no previous knowledge in these topics. Unearthing the secrets of virtual assistants such as the (in)famous ChatGPT and many other exciting technologies, The Book of Chatbots is meant for anyone interested in the topic, laypeople and IT-enthusiasts alike.

This book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the combination of both. Developing a QA system usually requires using a combination of various important techniques, including natural language processing, information retrieval and extraction, knowledge graph processing, and machine learning.After a general introduction and an overview of the book in Chapter 1, the history of QA systems and the architecture of different QA approaches are explained in Chapter 2. It starts with early close domain QA systems and reviews different generations of QA up to state-of-the-art hybrid models. Next, Chapter 3 is devoted to explaining the datasets and the metrics used for evaluating TextQA and KBQA. Chapter 4 introduces the neural and deep learning models used in QA systems. This chapter includes the required knowledge of deep learning and neural text representation models for comprehending the QA models over text and QA models over knowledge base explained in Chapters 5 and 6, respectively. In some of the KBQA models the textual data is also used as another source besides the knowledge base; these hybrid models are studied in Chapter 7. In Chapter 8, a detailed explanation of some well-known real applications of the QA systems is provided. Eventually, open issues and future work on QA are discussed in Chapter 9.This book delivers a comprehensive overview on QA over text, QA over knowledge base, and hybrid QA systems which can be used by researchers starting in this field. It will help its readers to follow the state-of-the-art research in the area by providing essential and basic knowledge.

This book explores the subject of artificial psychology from the standpoint of how online Chatbots have infiltrated and affected societies and the world in general. The book explores the psychological effects of depending on an online entity for our needs ¿ even if it¿s a reminder of scheduled events. The author provides insight into the notion of human-Chatbot exchanges, understanding, and false emotions both from the Chatbot and from the human. He goes on to investigate and discuss the dangers of too much reliance on technology that learns from a variety of sources and how some sources can negatively influence Chatbots, and by doing so, negatively affect people. The book also discusses human-Chatbot interactions and the natural language interface(s) required to respond adequately to humans. Lastly, the author explores the notion of ethical considerations for people, based on their interactions with Chatbots, including information based on cultural differences between different regions of the world.

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.

This LNCS book is part of the FOLLI book series and constitutes the proceedings of the 9th International Workshop on Logic, Rationality, and Interaction, LORI 2023, held in Jinan, China, in October 2023.The 15 full papers presented together with 7 short papers in this book were carefully reviewed and selected from 40 submissions. The workshop covers a wide range on the following topics such as agency; argumentation and agreement; beliefrepresentation; probability and uncertainty; belief revision and belief merging; knowledgeand action; dynamics of informational attitudes; intentions, plans, and goals; decisionmaking and planning; preference and utility; cooperation; strategic reasoning andgame theory; epistemology; social choice; social interaction; speech acts; knowledgerepresentation; norms and normative systems; natural language; rationality; philosophicallogic.

This book constitutes the refereed proceedings of the 30th International Symposium on Static Analysis, SAS 2023, held in Lisbon, Portugal, in October 2023. The 20 full papers included in this book were carefully reviewed and selected from 40 submissions. Static analysis is widely recognized as a fundamental tool for program verification, bug detection, compiler optimization, program understanding, and software maintenance. The papers deal with theoretical, practical and application advances in the area.Chapter 21 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

"An advanced exploration of machine learning and AI, with each chapter asking and answering a question from the field. Divided into five sections: deep learning and neural networks; computer vision; natural language processing; production and deployment; and predictive performance and model evaluation"--

This book includes chapters which discuss effective and efficient approaches in dealing with various aspects of social media analysis by using machine learning techniques from clustering to deep learning. A variety of theoretical aspects, application domains and case studies are covered to highlight how it is affordable to maximize the benefit of various applications from postings on social media platforms. Social media platforms have significantly influenced and reshaped various social aspects. They have set new means of communication and interaction between people, turning the whole world into a small village where people with internet connect can easily communicate without feeling any barriers. This has attracted the attention of researchers who have developed techniques and tools capable of studying various aspects of posts on social media platforms with main concentration on Twitter. This book addresses challenging applications in this dynamic domain where it is not possible to continue applying conventional techniques in studying social media postings. The content of this book helps the reader in developing own perspective about how to benefit from machine learning techniques in dealing with social media postings and how social media postings may directly influence various applications.