The Language 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.

Creative AI defines art and media practices that have AI embedded into the process of creation, but also encompass novel AI approaches in the realisation and experience of such work, e.g. robotic art, distributed AI artworks across locations, AI performers, artificial musicians, synthetic images generated by neural networks, AI authors and journalist bots. This book builds on the discourse of AI and creativity and extends the notion of embedded and co-operative creativity with intelligent software. It does so through a human-centred approach in which AI is empowered to make the human experience more creative. It presents ways-of-thinking and doing by the creators themselves so as to add to the ongoing discussion of AI and creativity at a time when the field needs to expand its thinking. This will avoid over-academization of this emerging field, and help counter engrained prejudice and bias. The Language of Creative AI contains technical descriptions, theoretical frameworks, philosophical concepts and practice-based case studies. It is a compendium of thinking around creative AI for technologists, human-computer interaction researchers and artists who are wishing to explore the creative potential of AI.

To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.

Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.

ChatGPT is an artificial intelligence language model that has the ability to process and generate human-like text. It is a product of the latest breakthroughs in natural language processing (NLP) and machine learning, which has enabled it to become one of the most advanced language models to date. The development of ChatGPT started with a research paper published in 2018 by OpenAI, a leading research lab in the field of artificial intelligence. In the paper, the researchers introduced a new model called GPT (Generative Pre-trained Transformer) that could generate coherent and human-like text using unsupervised learning. The initial GPT model had 117 million parameters and was pre-trained on a large corpus of text data from the internet. Over time, the researchers at OpenAI continued to improve the GPT model, leading to the development of larger and more sophisticated versions of the model, with up to 1.75 billion parameters. In June 2020, OpenAI released its most advanced version yet, known as GPT-3, which had a whopping 175 billion parameters and was capable of performing an unprecedented number of tasks, including translation, summarization, and even creative writing. ChatGPT is a variant of GPT-3 that has been fine-tuned to specialize in conversational interactions with humans. It has been pre-trained on a large corpus of conversational data, allowing it to understand and generate natural language responses in a conversational setting. When a user inputs a text prompt, ChatGPT uses its pre-trained models to analyze the prompt and generate a response that is likely to be appropriate and relevant to the context. The development of ChatGPT and other advanced language models has brought about a significant shift in the field of NLP and AI. These models have the potential to revolutionize the way humans communicate with machines and with each other, opening up new possibilities for language-based applications and interactions. In the following chapters of this book, we will delve deeper into the technical details of how ChatGPT works, explore its capabilities, and discuss the ethical and societal implications of using such advanced language models. But first, let's take a closer look at how ChatGPT was developed and the research that went into making it a reality.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and phi losophical psychology through issues in cognitive psychology and socio biology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemologi cal aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. Among the most challenging and difficult projects within the scope of artificial intelligence is the development and implementation of com puter programs suitable for processing natural language. Our purpose in compiling the present volume has been to contribute to the foundations of this enterprise by bringing together classic papers devoted to crucial problems involved in understanding natural language, which range from issues of formal syntax and logical form to those of possible-worlds and situation semantics. The book begins with a comprehensive introduc tion composed by Jack Kulas, the senior editor of this work, which pro vides a systematic orientation to this complex field, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these problems, they will have been worthwhile. J. H. F.

Embark on a journey into the heart of artificial intelligence (AI) with a guide designed for those intrigued by AI technologies. This book shines a light on the essentials of AI, emphasizing the groundbreaking impact of Large Language Models (LLMs). It offers a clear pathway to understanding AI's evolution, from its foundational concepts like neural networks and natural language processing to the advanced realms of generative AI that shape our future. Discover how AI is revolutionizing various industries, including healthcare, finance, education, and the arts, demonstrating its potential to transform the world. The narrative also tackles the ethical, privacy, and societal challenges accompanying AI's rise, fostering a dialogue on bias, data privacy, and the evolving landscape of work in an AI-enhanced world. Ideal for AI enthusiasts, professionals seeking to grasp AI's relevance to their fields, and anyone interested in the broader implications of AI technologies, this book provides an insightful introduction to AI and LLMs. It invites readers to explore the opportunities and navigate the changes AI brings, preparing them to thrive amidst the ongoing AI revolution.