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Parsing the Turing Test by Robert Epstein,Gary Roberts,Grace Beber Pdf
An exhaustive work that represents a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate weighty issues such as whether a self-conscious computer would create an internet ‘world mind’. This hugely important volume explores nothing less than the future of the human race itself.
Parsing the Turing Test by Robert Epstein,Gary Roberts,Grace Beber Pdf
An exhaustive work that represents a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate weighty issues such as whether a self-conscious computer would create an internet ‘world mind’. This hugely important volume explores nothing less than the future of the human race itself.
A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place. “Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there is also a prize, strange and intriguing, for the “Most Human Human.” Brian Christian—a young poet with degrees in computer science and philosophy—was chosen to participate in a recent competition. This
Turing's Imitation Game by Kevin Warwick,Huma Shah Pdf
Useful for undergraduate study, this book provides an account of the Turing Test, its history, context and implications, illustrated with practical tests.
Historical and contemporary papers on the philosophical issues raised by the Turing Test as a criterion for intelligence. The Turing Test is part of the vocabulary of popular culture—it has appeared in works ranging from the Broadway play "Breaking the Code" to the comic strip "Robotman." The writings collected by Stuart Shieber for this book examine the profound philosophical issues surrounding the Turing Test as a criterion for intelligence. Alan Turing's idea, originally expressed in a 1950 paper titled "Computing Machinery and Intelligence" and published in the journal Mind, proposed an "indistinguishability test" that compared artifact and person. Following Descartes's dictum that it is the ability to speak that distinguishes human from beast, Turing proposed to test whether machine and person were indistinguishable in regard to verbal ability. He was not, as is often assumed, answering the question "Can machines think?" but proposing a more concrete way to ask it. Turing's proposed thought experiment encapsulates the issues that the writings in The Turing Test define and discuss. The first section of the book contains writings by philosophical precursors, including Descartes, who first proposed the idea of indistinguishablity tests. The second section contains all of Turing's writings on the Turing Test, including not only the Mind paper but also less familiar ephemeral material. The final section opens with responses to Turing's paper published in Mind soon after it first appeared. The bulk of this section, however, consists of papers from a broad spectrum of scholars in the field that directly address the issue of the Turing Test as a test for intelligence. Contributors John R. Searle, Ned Block, Daniel C. Dennett, and Noam Chomsky (in a previously unpublished paper). Each chapter is introduced by background material that can also be read as a self-contained essay on the Turing Test
Artificial Intelligence with Python by Alberto Artasanchez,Prateek Joshi Pdf
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.
The Turing Test Argument by Bernardo Gonçalves Pdf
This book departs from existing accounts of Alan Turing's imitation game and test by placing Turing's proposal in its historical, social, and cultural context. It reconstructs a controversy in England, 1946–1952, over the intellectual capabilities of digital computers, which led Turing to propose his test. It argues that the Turing test is best understood not as a practical experiment, but as a thought experiment in the modern scientific tradition of Galileo Galilei. The logic of the Turing test argument is reconstructed from the rhetoric of Turing’s irony and wit. Turing believed that learning machines should be understood as a new kind of species, and their thinking as different from human thinking and yet capable of imitating it. He thought that the possibilities of the machines he envisioned were not utopian dreams. And yet he hoped that they would rival and surpass chauvinists and intellectuals who sacrifice independent thinking to maintain their power. These would be transformed into ordinary people, as work once considered 'intellectual' would be transformed into non-intellectual, 'mechanical' work. The Turing Test Argument will appeal to scholars and students in the sciences and humanities and all those interested in Turing's vision of the future of intelligent machines in society and nature.
This book gives the most comprehensive, in depth and contemporary assessment of this classic topic in artificial intelligence. It is the first to elaborate in such detail the numerous conflicting points of view on many aspects of this multifaceted, controversial subject. It offers new insights into Turing's own interpretation and is essential reading for research on the Turing test and for teaching undergraduate and graduate students in philosophy, computer science, and cognitive science.
Applied Natural Language Processing in the Enterprise by Ankur A. Patel,Ajay Uppili Arasanipalai Pdf
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Artificial Intelligence and Machine Learning Fundamentals by Zsolt Nagy Pdf
Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
The Turing Guide by Jack Copeland,Jonathan Bowen,Mark Sprevak,Robin Wilson Pdf
Alan Turing has long proved a subject of fascination, but following the centenary of his birth in 2012, the code-breaker, computer pioneer, mathematician (and much more) has become even more celebrated with much media coverage, and several meetings, conferences and books raising public awareness of Turing's life and work. This volume will bring together contributions from some of the leading experts on Alan Turing to create a comprehensive guide to Turing that will serve as a useful resource for researchers in the area as well as the increasingly interested general reader. The book will cover aspects of Turing's life and the wide range of his intellectual activities, including mathematics, code-breaking, computer science, logic, artificial intelligence and mathematical biology, as well as his subsequent influence.
The Definitive ANTLR 4 Reference by Terence Parr Pdf
Programmers run into parsing problems all the time. Whether it's a data format like JSON, a network protocol like SMTP, a server configuration file for Apache, a PostScript/PDF file, or a simple spreadsheet macro language--ANTLR v4 and this book will demystify the process. ANTLR v4 has been rewritten from scratch to make it easier than ever to build parsers and the language applications built on top. This completely rewritten new edition of the bestselling Definitive ANTLR Reference shows you how to take advantage of these new features. Build your own languages with ANTLR v4, using ANTLR's new advanced parsing technology. In this book, you'll learn how ANTLR automatically builds a data structure representing the input (parse tree) and generates code that can walk the tree (visitor). You can use that combination to implement data readers, language interpreters, and translators. You'll start by learning how to identify grammar patterns in language reference manuals and then slowly start building increasingly complex grammars. Next, you'll build applications based upon those grammars by walking the automatically generated parse trees. Then you'll tackle some nasty language problems by parsing files containing more than one language (such as XML, Java, and Javadoc). You'll also see how to take absolute control over parsing by embedding Java actions into the grammar. You'll learn directly from well-known parsing expert Terence Parr, the ANTLR creator and project lead. You'll master ANTLR grammar construction and learn how to build language tools using the built-in parse tree visitor mechanism. The book teaches using real-world examples and shows you how to use ANTLR to build such things as a data file reader, a JSON to XML translator, an R parser, and a Java class->interface extractor. This book is your ticket to becoming a parsing guru! What You Need: ANTLR 4.0 and above. Java development tools. Ant build system optional(needed for building ANTLR from source)
JFLAP: An Interactive Formal Languages and Automata Package is a hands-on supplemental guide through formal languages and automata theory. JFLAP guides students interactively through many of the concepts in an automata theory course or the early topics in a compiler course, including the descriptions of algorithms JFLAP has implemented. Students can experiment with the concepts in the text and receive immediate feedback when applying these concepts with the accompanying software. The text describes each area of JFLAP and reinforces concepts with end-of-chapter exercises. In addition to JFLAP, this guide incorporates two other automata theory tools into JFLAP: JellRap and Pate.
If you’re just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. Designed from the beginning for high performance, Julia is a general-purpose language ideal for not only numerical analysis and computational science but also web programming and scripting. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Julia is perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand types, methods, and multiple dispatch Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design and data structures through case studies
The Elements of Computing Systems by Noam Nisan,Shimon Schocken Pdf
This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system.