Artificial intelligence (AI) Books

Book SynopsisDrones are transforming warfare through the use of artificial intelligence, drone swarms, and surveillance—leading to competition between the US, China, Israel, and Iran. Who will be the next drone superpower?In the battle for the streets of Mosul in Iraq, drones in the hands of ISIS terrorists made life hell for the Iraq army and civilians. Today, defense companies are racing to develop the lasers, microwave weapons, and technology necessary for confronting the next drone threat. Seth J. Frantzman takes the reader from the midnight exercises with Israel’s elite drone warriors, to the CIA headquarters where new drone technology was once adopted in the 1990s to hunt Osama bin Laden. This rapidly expanding technology could be used to target nuclear power plants and pose a threat to civilian airports. In the Middle East, the US used a drone to kill Iranian arch-terrorist Qasem Soleimani, a key Iranian commander. Drones are transforming the battlefield from Syria to Libya and Yemen. For militaries and security agencies—the main users of expensive drones—the UAV market is expanding as well; there were more than 20,000 military drones in use by 2020. Once the province of only a few militaries, drones now being built in Turkey, China, Russia, and smaller countries like Taiwan may be joining the military drone market. It’s big business, too—$100 billion will be spent over the next decade on drones. Militaries may soon be spending more on drones than tanks, much as navies transitioned away from giant vulnerable battleships to more agile ships. The future wars will be fought with drones and won by whoever has the most sophisticated technology.Trade Review"A riveting account of one of the most significant developments in contemporary warfare—the evolution and proliferation of drones. Seth Frantzman provides a compelling description of this development and of the challenges facing the US and other countries as they grapple with the rapidly emerging threats posed by the new technology. He also conveys a sobering analysis about how this technology is transforming warfare and a convincing case for better defenses against drones in the hands of terrorists, non-state actors, and near-peer adversaries. This is a very important book." -- General David Petraeus, US Army (Ret.), former Commander of the Surge in Iraq, US Central Command, and Coalition and US Forces in Afghanistan, and former Director of the CIA"A fast-paced account of the pioneers behind today's military drones, in Drone Wars, author Seth J. Frantzman sheds a light on the shadowy world of military drones and how these new technologies are changing the modern battlefield. The global proliferation of drones and their incorporation by militaries and terror groups creates an urgency for developing and fielding defenses against drones and keeping up with countries and groups that may pose an increasing threat." -- Richard Kemp, former Commander of British forces in Afghanistan and led the international terrorism team at Britain's Joint Intelligence Committee

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Book SynopsisCovers encoding and binary digits, entropy, language and meaning, efficient encoding and the noisy channel, and explores ways in which information theory relates to physics, cybernetics, psychology, and art. 1980 edition.

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Book SynopsisIn 2018 DeepMind published the shocking results of their chess-playing artificial intelligence software, AlphaZero. Chess players looked in disbelief and immediately wondered how AI would affect the future of chess. Less than a year later, a whole new wave of chess engines emerged that were based on using neural networks to evaluate positions in a completely new way. This book is about the extraordinary impact that AI has had on modern chess. The games of top chess players since the end of 2018 have reflected the use of these new engines in home analysis. They have significantly developed opening theory as well as the general understanding of middlegame concepts. By analysing these games with the help of neural network engines, FIDE Master Joshua Doknjas discusses numerous exciting ideas and examines areas of chess that had previously been overlooked. With thorough explanations, questions, and exercises, this book provides fascinating material for masters and less experienced players alike.

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Book SynopsisBernard Marr is one of the world's leading voices in business and technology. A futurist and strategic performance consultant, he has worked with many of the world's best-known organizations and writes a regular column for Forbes. Marr is also a major influencer with a combined following of 4 million people across his social media channels and was ranked by LinkedIn as one of the top 5 business influencers in the world. He is the author of The Intelligence Revolution, Data Strategy and Data-Driven HR, all published by Kogan Page. He is based in Milton Keynes, UK.

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Book SynopsisIn the era of far-reaching technological innovation, from artificial intelligence to Big Data, it is possible that there will be conscious machines in our lifetime. This book establishes a foundation for the philosophy of technology and investigates how the digital age might alter our most basic political practices and ideas.Trade Review'Human beings are unprepared for the consequences of artificial intelligence and big data analysis - consequences for human rights, democratic government, public spheres, distributive justice, individual dignity, pursuit of meaningful human lives, and the moral status of potentially self-guided artificial intelligence itself. Drawing on a range of political theories and welcome common sense, Mathias Risse briskly frames the agenda to prepare for a world of 'deepfakes,' surveillance capitalism, and machines that alter human lives while operating without human supervision. Especially helpful in challenging assumptions such as that those who gather our data also own it, this book points the way toward preserving both individual and social lives of meaning and deliberate choices.' Martha Minow, Harvard Law School'In this outstanding book, Harvard's Mathias Risse explores hitherto uncharted terrain of political theory. The liberal-egalitarian tradition, with Rawls as its central figure, has by and large ignored the political nature of technology, thus condemning itself to irrelevance with regard to one of the most pressing political questions of our time: How will digital technology affect human life in the decades to come? [Without appropriate political steps, it is imaginable that humanity will not survive the further development of artificial intelligence. So we, ordinary citizens of the world, had better pay close attention.] Starting from the Rawlsian idea of public reason, Risse's explorative study draws on intellectual traditions ranging from Marxism to science and technology studies in order to toughen up liberal-egalitarian philosophy for the challenge. I hope this well-written book will find a broad readership and inspire much- needed work on this topic of topics.' Michael Schefczyk, Karlsruhe Institute of Technology'Risse could not be more right that we need to do political theory for a digital age, to come to grips with the political dimensions of our social lives as the very notion of social life is transformed by advances in AI in both the near and far terms. Weaving together insights from the philosophy of technology, rights theory, science and technology studies, and traditional political theory and political philosophy, Risse reveals both the depth of challenges we face across a spectrum of issues in the immediate and distant future, and the promise of a reconfigured political theory for resolving them. The breadth and care that Risse takes with both the technological possibilities and the philosophical and political foundations is remarkable. This is a must-read!' John Basl, Northeastern UniversityTable of Contents1. Introduction: digital lifeworlds in human history; 2. Learning from the Amish: political philosophy as philosophy of technology in the digital century; 3. Artificial intelligence and the past, present, and future of democracy; 4. Truth will not set you free: is there a right to it anyway? Elaborating on the work public reason does in life 2.0; 5. Knowing and being known: investigating epistemic entitlements in digital lifeworlds; 6. Beyond porn and discreditation: epistemic promises and perils of deepfake technology; 7. The fourth generation of human rights: epistemic rights in life 2.0 and life 3.0; 8. On surveillance capitalism, instrumentarian power, and social physics: securing the enlightenment for digital lifeworlds; 9. Data as social facts: distributive justice meets big data; 10. God, Golem, and gadget worshippers: meaning of life in the digital age; 11. Moral status and political membership: toward a political theory for life 3.0; Epilogue.

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Book SynopsisAnne Rooney is an award-winning author who has written several bestselling books on history, philosophy and science. She was longlisted for the prestigious Aventis Science Prize in 2004, was shortlisted for the ALCS Educational Writers' Award in 2015 and won the School Library Association Information Book Award in 2018. She has a degree and a PhD from Trinity College, Cambridge and has been a Royal Literary Fund Fellow at Newnham College, Cambridge. Her books have been translated into 22 languages.

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Book Synopsis'Real science can be far stranger than science fiction, and much more satisfying'Will artificial intelligence outsmart us?Is there other intelligent life in the universe?Throughout his extraordinary career, Stephen Hawking expanded our understanding of the universe and unravelled some of its greatest mysteries. Will Artificial Intelligence Outsmart Us? considers the threat of artificial super-intelligence - as well as the likelihood of intelligent life beyond our planet.'Modest, profound and sometimes very funny' Sunday TimesBrief Answers, Big Questions: this stunning paperback series offers electrifying essays from one of the greatest minds of our age, taken from the original text of the No. 1 bestselling Brief Answers to the Big Questions.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisKeeping students involved and actively learning is challenging. Instructors in computer science are aware of the cognitive value of modelling puzzles and often use logical puzzles as an efficient pedagogical instrument to engage students and develop problem-solving skills. This unique book is a comprehensive resource that offers teachers and students fun activities to teach and learn logic. It provides new, complete, and running formalisation in Propositional and First Order Logic for over 130 logical puzzles, including Sudoku-like puzzles, zebra-like puzzles, island of truth, lady and tigers, grid puzzles, strange numbers, or self-reference puzzles. Solving puzzles with theorem provers can be an effective cognitive incentive to motivate students to learn logic. They will find a ready-to-use format which illustrates how to model each puzzle, provides running implementations, and explains each solution. This concise and easy-to-follow textbook is a much-needed support tool for students willing to explore beyond the introductory level of learning logic and lecturers looking for examples to heighten student engagement in their computer science courses. Trade Review“The purpose of this book is to introduce first-order logic (FOL) to newcomers. … The book is a treasure trove of puzzles like this. … All of these are motivated in an approachable, fun way. … the book is a hands-on guide to Prover9 and Mace4 … . It is quite valuable to have so many puzzles in a single book.” (Jesse Adam Alama, Mathematical Reviews, October, 2022)Table of ContentsPreface.- Getting Started with Prover9 and Mace4.- Micro Arithmetic Puzzles.- Strange Numbers.- Practical Puzzles.- Lady and Tigers.- Einstein Puzzles.- Island of Truth.- Love and Marriage.- Grid Puzzles.- Japanese Puzzles.- Russian Puzzles.- Polyomino Puzzles.- Self-reference and Other Puzzles.- Epigraph in Natural Language

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Book SynopsisThis book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.Table of ContentsInformation visualization.- Data analytics.- Visual analytics.- Intelligent information systems.- Business analytics,- Virtual data machine.- Big data architecture.- Security of big data.- Big data applications.- Tensor-based computation and modeling.- High performance computing cluster.- Big data technologies.

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Book SynopsisEverybody knows them. Smartphones that talk to us, wristwatches that record our health data, workflows that organize themselves automatically, cars, airplanes and drones that control themselves, traffic and energy systems with autonomous logistics or robots that explore distant planets are technical examples of a networked world of intelligent systems. Machine learning is dramatically changing our civilization. We rely more and more on efficient algorithms, because otherwise we will not be able to cope with the complexity of our civilizing infrastructure. But how secure are AI algorithms? This challenge is taken up in the 2nd edition: Complex neural networks are fed and trained with huge amounts of data (big data). The number of necessary parameters explodes exponentially. Nobody knows exactly what is going on in these "black boxes". In machine learning we need more explainability and accountability of causes and effects in order to be able to decide ethical and legal questions of responsibility (e.g. in autonomous driving or medicine)! Besides causal learning, we also analyze procedures of tests and verification to get certified AI-programs. Since its inception, AI research has been associated with great visions of the future of mankind. It is already a key technology that will decide the global competition of social systems. "Artificial Intelligence and Responsibility" is another central supplement to the 2nd edition: How should we secure our individual liberty rights in the AI world? This book is a plea for technology design: AI must prove itself as a service in society.Table of ContentsIntroduction: What is AI?.- A brief history of AI.- Logical thinking becomes automatic.- Systems become experts.- Computers learn to speak.- Algorithms simulate evolution.- Neural networks simulate brains.- Robots become social.- Automobiles become autonomous.- Factories become intelligent.- From natural to artificial to super intelligence?.

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Book SynopsisPolitical issues people care about such as racism, climate change, and democracy take on new urgency and meaning in the light of technological developments such as AI. How can we talk about the politics of AI while moving beyond mere warnings and easy accusations? This is the first accessible introduction to the political challenges related to AI. Using political philosophy as a unique lens through which to explore key debates in the area, the book shows how various political issues are already impacted by emerging AI technologies: from justice and discrimination to democracy and surveillance. Revealing the inherently political nature of technology, it offers a rich conceptual toolbox that can guide efforts to deal with the challenges raised by what turns out to be not only artificial intelligence but also artificial power. This timely and original book will appeal to students and scholars in philosophy of technology and political philosophy, as well as tech developers, innovation leaders, policy makers, and anyone interested in the impact of technology on society.​Trade Review“The disciplines of AI ethics and political philosophy focus on many of the same issues, but only rarely do we see the rich history of the latter discipline being used to make sense of the politics of AI. Coeckelbergh provides a welcome exception with this important book.”Henrik Skaug Sætra, Østfold University College “Artificial intelligence is fundamentally political, and this book illuminates why. It spans the debates about inequality, democracy, power, and posthumanism, and shows the importance of social and political theory to understanding AI.”Kate Crawford, author of Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence“Coeckelbergh[‘s] […] real focus is on showing a few thousand years’ worth of philosophical thought will not automatically become obsolete through feats of digital engineering.”Scott McLemee, Inside Higher EdTable of ContentsAcknowledgements 1 Introduction 2 Freedom: Manipulation by AI and Robot Slavery3 Equality and Justice: Bias and Discrimination by AI4 Democracy: Echo Chambers and Machine Totalitarianism 5 Power: Surveillance and (Self-)disciplining by Data6 What about Non-Humans? Environmental Politics and Posthumanism 7 Conclusion: Political TechnologiesReferencesIndex

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Book Synopsis Paul Deitel, CEO and Chief Technical Officer of Deitel & Associates, Inc., is a graduate of MIT, where he studied Information Technology. Through Deitel & Associates, Inc., he has delivered hundreds of programming courses worldwide to clients, including Cisco, IBM, Siemens, Sun Microsystems, Dell, Fidelity, NASA at the Kennedy Space Center, the National Severe Storm Laboratory, White Sands Missile Range, Rogue Wave Software, Boeing, SunGard Higher Education, Nortel Networks, Puma, iRobot, Invensys and many more. He and his co-author, Dr. Harvey M. Deitel, are the world's best-selling programming-language textbook/professional book/video authors. Dr. Harvey Deitel, Chairman and Chief Strategy Officer of Deitel & Associates, Inc., has over 50 years of experience in the computer field. Dr. Deitel earned B.S. and M.S. degrees in Electrical Engineering from MIT and a Ph.D. in Mathematics from Boston University. He has extensive college teaching experienTrade Review“The chapters are clearly written with detailed explanations of the example code. The modular structure, wide range of contemporary data science topics, and code in companion Jupyter notebooks make this a fantastic resource for readers of a variety of backgrounds. Fabulous Big Data chapter—it covers all of the relevant programs and platforms. Great Watson chapter! The chapter provides a great overview of the Watson applications. Also, your translation examples are great because they provide an ‘instant reward’—it’s very satisfying to implement a task and receive results so quickly. Machine Learning is a huge topic, and the chapter serves as a great introduction. I loved the California housing data example—very relevant for business analytics. The chapter was visually stunning.” —Alison Sanchez, Assistant Professor in Economics, University of San Diego “A great introduction to Big Data concepts, notably Hadoop, Spark, and IoT. The examples are extremely realistic and practical. The authors do an excellent job of combining programming and data science topics. The material is presented in digestible sections accompanied by engaging interactive examples. Nearly all concepts are accompanied by a worked-out example. A comprehensive overview of object-oriented programming in Python—the use of card image graphics is sure to engage the reader.” —Garrett Dancik, Eastern Connecticut State University “Covers some of the most modern Python syntax approaches and introduces community standards for style and documentation. The machine learning chapter does a great job of walking people through the boilerplate code needed for ML in Python. The case studies accomplish this really well. The later examples are so visual. Many of the model evaluation tasks make for really good programming practice. I can see readers feeling really excited about playing with the animations.” —Elizabeth Wickes, Lecturer, School of Information Sciences, University of Illinois at Urbana-Champaign “An engaging, highly accessible book that will foster curiosity and motivate beginning data scientists to develop essential foundations in Python programming, statistics, data manipulation, working with APIs, data visualization, machine learning, cloud computing, and more. Great walkthrough of the Twitter APIs—sentiment analysis piece is very useful. I’ve taken several classes that cover natural language processing and this is the first time the tools and concepts have been explained so clearly. I appreciate the discussion of serialization with JSON and pickling and when to use one or the other—with an emphasis on using JSON over pickle—good to know there’s a better, safer way!” —Jamie Whitacre, Data Science Consultant “For a while, I have been looking for a book in Data Science using Python that would cover the most relevant technologies. Well, my search is over. A must-have book for any practitioner of this field. The machine learning chapter is a real winner!! The dynamic visualization is fantastic.” —Ramon Mata-Toledo, Professor, James Madison University “I like the new combination of topics from computer science, data science, and stats. This is important for building data science programs that are more than just cobbling together math and computer science courses. A book like this may help facilitate expanding our offerings and using Python as a bridge for computer and data science topics. For a data science program that focuses on a single language (mostly), I think Python is probably the way to go.” —Lance Bryant, Shippensburg University “You’ll develop applications using industry standard libraries and cloud computing services.” —Daniel Chen, Data Scientist, Lander Analytics “Great introduction to Python! This book has my strongest recommendation both as an introduction to Python as well as Data Science.” —Shyamal Mitra, Senior Lecturer, University of Texas “IBM Watson is an exciting chapter. The code examples put together a lot of Watson services in a really nifty example.” —Daniel Chen, Data Scientist, Lander Analytics “Fun, engaging real-world examples will encourage readers to conduct meaningful data analyses. Provides many of the best explanations of data science concepts I’ve encountered. Introduces the most useful starter machine learning models—does a good job explaining how to choose the best model and what ‘the best’ means. Great overview of all the big data technologies with relevant examples.” —Jamie Whitacre, Data Science Consultant “A great introduction to deep learning.” —Alison Sanchez, University of San Diego “The best designed Intro to Data Science/Python book I have seen.” —Roland DePratti, Central Connecticut State University “I like the new combination of topics from computer science, data science, and stats.” —Lance Bryant, Shippensburg University “The book’s applied approach should engage readers. A fantastic job providing background on various machine learning concepts without burdening the users with too many mathematical details.” —Garrett Dancik, Assoc. Prof. of Computer Science/Bioinformatics, Eastern Connecticut State University “Helps readers leverage the large number of existing libraries to accomplish tasks with minimal code. Concepts are accompanied by rich Python examples that readers can adapt to implement their own solutions to data science problems. I like that cloud services are used.” —David Koop, Assistant Professor, U-Mass Dartmouth “I enjoyed the OOP chapter—doctest unit testing is nice because you can have the test in the actual docstring so things are traveling together. The line-by-line explanations of the static and dynamic visualizations of the die rolling example are just great.” —Daniel Chen, Data Scientist, Lander Analytics “A lucid exposition of the fundamentals of Python and Data Science. Thanks for pointing out seeding the random number generator for reproducibility. I like the use of dictionary and set comprehensions for succinct programming. ‘List vs. Array Performance: Introducing %timeit’ is convincing on why one should use ndarrays. Good defensive programming. Great section on Pandas Series and DataFrames—one of the clearest expositions that I have seen. The section on data wrangling is excellent. Natural Language Processing is an excellent chapter! I learned a tremendous amount going through it.” —Shyamal Mitra, Senior Lecturer, University of Texas “I like the discussion of exceptions and tracebacks. I really liked the Data Mining Twitter chapter; it focused on a real data source and brought in a lot of techniques for analysis (e.g., visualization, NLP). I like that the Python modules helped hide some of the complexity. Word clouds look cool.” —David Koop, Assistant Professor, U-Mass Dartmouth “I love the book! The examples are definitely a high point.” —Dr. Irene Bruno, George Mason University “I was very excited to see this book. I like its focus on data science and a general purpose language for writing useful data science programs. The data science portion distinguishes this book from most other introductory Python books.” —Dr. Harvey Siy, University of Nebraska at Omaha “I’ve learned a lot in this review process, discovering the exciting field of AI. I’ve liked the Deep Learning chapter, which has left me amazed with the things that have already been achieved in this field.” —José Antonio González Seco, Consultant “An impressive hands-on approach to programming meant for exploration and experimentation.” —Elizabeth Wickes, Lecturer, School of Information Sciences, University of Illinois at Urbana-Champaign “I was impressed at how easy it was to get started with NLP using Python. A meaningful overview of deep learning concepts, using Keras. I like the streaming example.” —David Koop, Assistant Professor, U-Mass Dartmouth “Really like the use of f-strings, instead of the older string-formatting methods. Seeing how easy TextBlob is compared to base NLTK was great. I never made word clouds with shapes before, but I can see this being a motivating example for people getting started with NLP. I’m enjoying the case-study chapters in the latter parts of the book. They are really practical. I really enjoyed working through all the Big Data examples, especially the IoT ones.” —Daniel Chen, Data Scientist, Lander Analytics “I really liked the live IPython input-output. The thing that I like most about this product is that it is a Deitel & Deitel book (I’m a big fan) that covers Python.” —Dr. Mark Pauley, University of Nebraska at Omaha Table of ContentsPreface xviiBefore You Begin xxxiiiChapter 1: Introduction to Computers and Python 11.1 Introduction 21.2 A Quick Review of Object Technology Basics 31.3 Python 51.4 It’s the Libraries! 71.5 Test-Drives: Using IPython and Jupyter Notebooks 91.6 The Cloud and the Internet of Things 161.7 How Big Is Big Data? 171.8 Case Study—A Big-Data Mobile Application 241.9 Intro to Data Science: Artificial Intelligence—at the Intersection of CS and Data Science 261.10 Wrap-Up 29Chapter 2: Introduction to Python Programming 312.1 Introduction 322.2 Variables and Assignment Statements 322.3 Arithmetic 332.4 Function print and an Intro to Single- and Double-Quoted Strings 362.5 Triple-Quoted Strings 382.6 Getting Input from the User 392.7 Decision Making: The if Statement and Comparison Operators 412.8 Objects and Dynamic Typing 452.9 Intro to Data Science: Basic Descriptive Statistics 462.10 Wrap-Up 48Chapter 3: Control Statements 493.1 Introduction 503.2 Control Statements 503.3 if Statement 513.4 if...else and if...elif...else Statements 523.5 while Statement 553.6 for Statement 553.7 Augmented Assignments 573.8 Sequence-Controlled Iteration; Formatted Strings 583.9 Sentinel-Controlled Iteration 593.10 Built-In Function range: A Deeper Look 603.11 Using Type Decimal for Monetary Amounts 613.12 break and continue Statements 643.13 Boolean Operators and, or and not 653.14 Intro to Data Science: Measures of Central Tendency—Mean, Median and Mode 673.15 Wrap-Up 69Chapter 4: Functions 714.1 Introduction 724.2 Defining Functions 724.3 Functions with Multiple Parameters 754.4 Random-Number Generation 764.5 Case Study: A Game of Chance 784.6 Python Standard Library 814.7 math Module Functions 824.8 Using IPython Tab Completion for Discovery 834.9 Default Parameter Values 854.10 Keyword Arguments 854.11 Arbitrary Argument Lists 864.12 Methods: Functions That Belong to Objects 874.13 Scope Rules 874.14 import: A Deeper Look 894.15 Passing Arguments to Functions: A Deeper Look 904.16 Recursion 934.17 Functional-Style Programming 954.18 Intro to Data Science: Measures of Dispersion 974.19 Wrap-Up 98Chapter 5: Sequences: Lists and Tuples 1015.1 Introduction 1025.2 Lists 1025.3 Tuples 1065.4 Unpacking Sequences 1085.5 Sequence Slicing 1105.6 del Statement 1125.7 Passing Lists to Functions 1135.8 Sorting Lists 1155.9 Searching Sequences 1165.10 Other List Methods 1175.11 Simulating Stacks with Lists 1195.12 List Comprehensions 1205.13 Generator Expressions 1215.14 Filter, Map and Reduce 1225.15 Other Sequence Processing Functions 1245.16 Two-Dimensional Lists 1265.17 Intro to Data Science: Simulation and Static Visualizations 1285.18 Wrap-Up 135Chapter 6: Dictionaries and Sets 1376.1 Introduction 1386.2 Dictionaries 1386.3 Sets 1476.4 Intro to Data Science: Dynamic Visualizations 1526.5 Wrap-Up 158Chapter 7: Array-Oriented Programming with NumPy 1597.1 Introduction 1607.2 Creating arrays from Existing Data 1607.3 array Attributes 1617.4 Filling arrays with Specific Values 1637.5 Creating arrays from Ranges 1647.6 List vs. array Performance: Introducing %timeit 1657.7 array Operators 1677.8 NumPy Calculation Methods 1697.9 Universal Functions 1707.10 Indexing and Slicing 1717.11 Views: Shallow Copies 1737.12 Deep Copies 1747.13 Reshaping and Transposing 1757.14 Intro to Data Science: pandas Series and DataFrames 1777.15 Wrap-Up 189Chapter 8: Strings: A Deeper Look 1918.1 Introduction 1928.2 Formatting Strings 1938.3 Concatenating and Repeating Strings 1968.4 Stripping Whitespace from Strings 1978.5 Changing Character Case 1978.6 Comparison Operators for Strings 1988.7 Searching for Substrings 1988.8 Replacing Substrings 1998.9 Splitting and Joining Strings 2008.10 Characters and Character-Testing Methods 2028.11 Raw Strings 2038.12 Introduction to Regular Expressions 2038.13 Intro to Data Science: Pandas, Regular Expressions and Data Munging 2108.14 Wrap-Up 214Chapter 9: Files and Exceptions 2179.1 Introduction 2189.2 Files 2199.3 Text-File Processing 2199.4 Updating Text Files 2229.5 Serialization with JSON 2239.6 Focus on Security: pickle Serialization and Deserialization 2269.7 Additional Notes Regarding Files 2269.8 Handling Exceptions 2279.9 finally Clause 2319.10 Explicitly Raising an Exception 2339.11 (Optional) Stack Unwinding and Tracebacks 2339.12 Intro to Data Science: Working with CSV Files 2359.13 Wrap-Up 241Chapter 10: Object-Oriented Programming 24310.1 Introduction 24410.2 Custom Class Account 24610.3 Controlling Access to Attributes 24910.4 Properties for Data Access 25010.5 Simulating “Private” Attributes 25610.6 Case Study: Card Shuffling and Dealing Simulation 25810.7 Inheritance: Base Classes and Subclasses 26610.8 Building an Inheritance Hierarchy; Introducing Polymorphism 26710.9 Duck Typing and Polymorphism 27510.10 Operator Overloading 27610.11 Exception Class Hierarchy and Custom Exceptions 27910.12 Named Tuples 28010.13 A Brief Intro to Python 3.7’s New Data Classes 28110.14 Unit Testing with Docstrings and doctest 28710.15 Namespaces and Scopes 29010.16 Intro to Data Science: Time Series and Simple Linear Regression 29310.17 Wrap-Up 301Chapter 11: Natural Language Processing (NLP) 30311.1 Introduction 30411.2 TextBlob 30511.3 Visualizing Word Frequencies with Bar Charts and Word Clouds 31911.4 Readability Assessment with Textatistic 32411.5 Named Entity Recognition with spaCy 32611.6 Similarity Detection with spaCy 32711.7 Other NLP Libraries and Tools 32811.8 Machine Learning and Deep Learning Natural Language Applications 32811.9 Natural Language Datasets 32911.10 Wrap-Up 330Chapter 12: Data Mining Twitter 33112.1 Introduction 33212.2 Overview of the Twitter APIs 33412.3 Creating a Twitter Account 33512.4 Getting Twitter Credentials—Creating an App 33512.5 What’s in a Tweet? 33712.6 Tweepy 34012.7 Authenticating with Twitter Via Tweepy 34112.8 Getting Information About a Twitter Account 34212.9 Introduction to Tweepy Cursors: Getting an Account’s Followers and Friends 34412.10 Searching Recent Tweets 34712.11 Spotting Trends: Twitter Trends API 34912.12 Cleaning/Preprocessing Tweets for Analysis 35312.13 Twitter Streaming API 35412.14 Tweet Sentiment Analysis 35912.15 Geocoding and Mapping 36212.16 Ways to Store Tweets 37012.17 Twitter and Time Series 37012.18 Wrap-Up 371Chapter 13: IBM Watson and Cognitive Computing 37313.1 Introduction: IBM Watson and Cognitive Computing 37413.2 IBM Cloud Account and Cloud Console 37513.3 Watson Services 37613.4 Additional Services and Tools 37913.5 Watson Developer Cloud Python SDK 38113.6 Case Study: Traveler’s Companion Translation App 38113.7 Watson Resources 39413.8 Wrap-Up 395Chapter 14: Machine Learning: Classification, Regression and Clustering 39714.1 Introduction to Machine Learning 39814.2 Case Study: Classification with k-Nearest Neighbors and the Digits Dataset, Part 1 40314.3 Case Study: Classification with k-Nearest Neighbors and the Digits Dataset, Part 2 41314.4 Case Study: Time Series and Simple Linear Regression 42014.5 Case Study: Multiple Linear Regression with the California Housing Dataset 42514.6 Case Study: Unsupervised Machine Learning, Part 1—Dimensionality Reduction 43814.7 Case Study: Unsupervised Machine Learning, Part 2—k-Means Clustering 44214.8 Wrap-Up 455Chapter 15: Deep Learning 45715.1 Introduction 45815.2 Keras Built-In Datasets 46115.3 Custom Anaconda Environments 46215.4 Neural Networks 46315.5 Tensors 46515.6 Convolutional Neural Networks for Vision; Multi-Classification with the MNIST Dataset 46715.7 Visualizing Neural Network Training with TensorBoard 48615.8 ConvnetJS: Browser-Based Deep-Learning Training and Visualization 48915.9 Recurrent Neural Networks for Sequences; Sentiment Analysis with the IMDb Dataset 48915.10 Tuning Deep Learning Models 49715.11 Convnet Models Pretrained on ImageNet 49815.12 Wrap-Up 499Chapter 16: Big Data: Hadoop, Spark, NoSQL and IoT 50116.1 Introduction 50216.2 Relational Databases and Structured Query Language (SQL) 50616.3 NoSQL and NewSQL Big-Data Databases: A Brief Tour 51716.4 Case Study: A MongoDB JSON Document Database 52016.5 Hadoop 53016.6 Spark 54116.7 Spark Streaming: Counting Twitter Hashtags Using the pyspark-notebook Docker Stack 55116.8 Internet of Things and Dashboards 56016.9 Wrap-Up 571Index 573

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Book SynopsisThe incredible and inspiring book behind the primetime Channel 4 documentary, Peter: The Human Cyborg''Peter''s story is one of the most extraordinary you will ever hear. Remarkable. I urge people to read it'' Stephen Fry''With candour and bravery, Peter tells how he explored new frontiers of science to give himself a chance of survival in a digital afterlife'' Daily Mail__________Peter didn''t choose to live forever. He simply chose not to die.Diagnosed with a rare but terminal Motor Neuron Disease, brilliant scientist Peter Scott-Morgan refused to accept that within a few short years he''d be dead.Instead, he embarked on a dangerous journey - to cross the border between mortality and immortality. He would meld his humanity with the latest computer and robotic technology to become Peter 2.0.This is the astonishing story of a man uniquely placed to pursue a new way of lifeTrade ReviewCompelling . . . Scott-Morgan is a true one-off. It is in the telling of the love story, rather than the technical details of becoming a cyborg, that this book succeeds * The Times *With candour and bravery, Peter tells how he explored new frontiers of science to give himself a chance of survival in a digital afterlife * Daily Mail *Peter's story is one of the most extraordinary you will ever hear . . . Remarkable. I urge people to read it -- Stephen FryA remarkable account of what it means to be human and what technology can really achieve * Sunday Telegraph *A remarkable story . . . you're left desperate to take nothing for granted * Radio Times *Astonishing * Daily Mail *What's striking is Peter's constant optimism, bravery and his ability to find radical answers to problems that have confounded Britain's brightest minds * Daily Telegraph *Life-affirming . . . The most extraordinary thing about scientist Dr Peter Scott-Morgan, aside from his optimism, is his relentless capacity for joy * Daily Mail *A soaring love story * Financial Times *Fascinating and extremely moving * Sun *Breathtaking . . . We were mesmerised by the boundless creative intelligence, positivity and love that pours from these pages. Profoundly inspiring * Attitude *The astonishing true story behind the primetime Channel 4 documentary about Peter Scott-Morgan, the first person to combine his very humanity with artificial intelligence and robotics to become a full cyborg. His discovery means that his terminal diagnosis is negotiable, something that will rewrite the future - and change the world * GQ *

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Book SynopsisThis well-balanced, comprehensive and engaging review surveys the development of Artificial Intelligence over the last sixty years and highlights the likely transformative effects of AI on society over the next few decades.Trade Review'Incredibly interesting and comprehensive … five stars' - How It WorksTable of ContentsIntroduction • 1. The Development of AI • 2. The Capabilities of AI Today • 3. Limitations and Problems of AI Today • 4. The Future of AI • Conclusion

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Book SynopsisA Financial Times and Economist Book of the Year''Wonderfully stimulating... will teach you to see around corners'' - TIM HARFORD''A paean to cognitive agility and the elasticity of the imagination'' - ECONOMIST''Captivating... will transform the way you think'' MARISSA KING, PROFESSOR AT YALE SCHOOL OF MANAGEMENTThe power of mental models to make better decisionsWe''re often told that humans make bad decisions and that more data is better. But this is backwards: people are good at decisions precisely because we use mental models and can envision new realities outside of data. Great outcomes don''t depend so much on the final moment of choosing but on generating better alternatives to choose between. That''s framing. It''s a cognitive muscle we can strengthen to improve our lives, work and future -- to meet this historical moment. Framers shows how.Trade ReviewA tightly written prescription for smart thinking... A bold call to reinject pluralism and progressive human values into a decision-making process dominated by algorithms or gut instinct * Financial Times -- 2021 Summer Books List *A simply wonderful reimagining of human ingenuity. It will teach you to see around corners * Tim Harford, bestselling author of How To Make The World Add Up *Reveals how you can recognize the lenses that you're applying ... an important read -- a steady hand for our turbulent times * Adam Grant, #1 New York Times bestselling author of THINK AGAIN *A fascinating look at what makes humans special and how people can improve the way they think to stay ahead of the machines * Mustafa Suleyman, Co-founder of DeepMind, Vice-President of Google *A paean to cognitive agility and the elasticity of the imagination * The Economist *Packed with big ideas, great stories, values and verve that make it a delight to read. It will certainly change how you think-and might just change the world too * Annie Duke, best-selling author of THINKING IN BETS and former poker champion *A great book filled with fresh perspectives to help us out during the rise of AI so we can usher in the Age of Humanity * will.i.am, musician and entrepreneur *A captivating read... Framers will transform the way you think * Marissa King, Professor at Yale School of Management *Brilliantly shows that mental models are at the heart of creativity, critical thinking and innovation, and how we can get better at it to solve our toughest business and social challenges * Aaron Levie, CEO of Box *Provides insight into how we can all nurture more of a beginner's mind and manifest breakthrough ideas for building a better future * Marc Benioff, chairman and CEO, Salesforce *An appealing pop-science guide to creativity [and] an astute analysis of problem-solving * Kirkus Reviews *Humans today live a much easier, more comfortable, and more pleasant existence than ever before, but we also face our greatest existential challenges as a species, and in order to survive we will need not only cooperation, but a new and diverse set of cognitive frames ... [this book] teaches us how to better frame things for ourselves as individuals * Porchlight BOOK TO WATCH *

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Book SynopsisWith artificial intelligence on the rise, the way we run our organisations will changeand drastically. But what exactly will that future look like? And who will take the leading role: machines or people?In this compelling new book, leading management guru David De Cremer identifies the key areas where algorithms will collide with human skills, and assesses the likely outcomes.Will your next boss be a robot? Can an AI boss display the human qualities that define a good leader: compassion, empathy, imagination, ethics, and strategic awareness?Drawing on his own research findings, and those from thought leaders around the world, the author presents fascinating insights into the challenges that an automated work environment poses for organisations of the future.Leadership by Algorithm offers some startling conclusions that make clear the true nature of the power struggle between man and machine. It also identifies the leadership qualities needed to deal with this struggle most effectively.

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Book SynopsisThe development of effective and usable software for spatial computing platforms like virtual reality (VR) requires an understanding of how these devices create new possibilities (and new perils) when it comes to interactions between humans and computers. Virtual Reality Usability Design provides readers with an understanding of the techniques and technologies required to design engaging and effective VR applications.The book covers both the mechanics of how human senses and the mind experience immersive virtual environments, as well as how to leverage these mechanics to create human-focused virtual experiences. Deeply rooted in principles of human perception and computational interaction, the current and future limitations of these replacements are also considered. Full of real-world examples, this book is an indispensable guide for any practising VR developer interested in making efficient and effective interfaces. Meanwhile, explorations of concrete theory in their practical application will be useful for VR students and researchers alike.Table of Contents1. What Makes Virtual Reality Remarkable? 2. Making the Virtual Seem Real 3. Sensation and Perception 4. Supporting Primary Senses 5. Supporting Peripheral Senses 6. Perceiving Space and Scale 7. Further Psychological Effects of Inhabiting a Virtual Environment 8. Experience Usability 9. Fictions of Physics 10. Locomotion and Navigation 11. Activities and Interactions 12. Information Display 13. Translating Traditional Interfaces for VR

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Book SynopsisWe live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyTable of Contents1 Edge computing-enabled secure information-centric networking: Privacy challenges, benefits, and future trends KAVISH TOMAR, SARISHMA DANGI, AND SACHIN SHARMA2 Weighted attack graphs and behavioral cyber game theory for cyber risk quantification FLORIAN K. KAISER, MARCUS WIENS, AND FRANK SCHULTMANN3 NetFlow-based botnet detection in IoT edge environment using ensemble gradient boosting machine learning framework D. SANTHADEVI AND B. JANET4 Exploring the possibility of blockchain and smart contract-based digital certificate P. RAVI KUMAR, P. HERBERT RAJ, AND SHARUL TAJUDDIN5 Senso Scale: A framework to preserve privacy over cloud using sensitivity range NIHARIKA SINGH, ISHU GUPTA, AND ASHUTOSH KUMAR SINGH6 Addressing the cybersecurity issues in cloud computing SHIVANSHU OLIYHAN AND CHANDRASHEKHAR AZAD7 Role of medical image encryption algorithms in cloud platform for teleradiology applications SIJU JOHN AND S. N. KUMAR8 Machine-learning approach for detecting cyberattacks in Medical Internet of Things THULASI M. SANTHI AND M. C. HELEN MARY9 Secure IoV-enabled systems at Fog Computing: Layout, security, and optimization algorithms and open issuesANSHU DEVI, RAMESH KAIT, AND VIRENDER RANGA10 A capability maturity model and value judgment systems for a distributed network of ethical and context aware digital twin agents MEZZOUR GHITA, BENHADOU SIHAM, MEDROMI HICHAM, AND GRIGUER HAFID11 A detailed cram on artificial intelligence industrial systems 4.0 P. DHARANYADEVI, R. SRI SAIPRIYA, T. C. ADITYAA, B. SENTHILNAYAKI, M. JULIE THERESE, A. DEVI, AND K. VENKATALAKSHMI12 Ensuring liveliness property in safety-critical systems ANKUR MAURYA, SHARAD NIGAM, AND DIVYA KUMAR13 Machine learning for intelligent analytics JYOTI POKHARIYA, PANKAJ KUMAR MISHRA, AND JYOTI KANDPAL14 Secure 3D route optimization of combat vehicles in war field using IoV ALOK NATH PANDEY, PIYUSH AGARWAL, AND SACHIN SHARMA15 Healthcare therapy for treating teenagers with internet addiction using behavioral patterns and neuro-feedback analysis B. DHANALAKSHMI, K. SELVAKUMAR, AND L. SAI RAMESH16 Containerization in cloud computing for OS-level virtualization MANOJ KUMAR PATRA, BIBHUDATTA SAHOO, AND ASHOK KUMAR TURUK17 An adaptive deep learning approach for stock price forecasting RESHMA MO, JITENDRA KUMAR, AND ABHISHEK VERMA

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisAI and specifically LLMs revolutionize our lives with new technologies appearing at an unprecedented rate. These technologies can potentially change how we understand human conversations, from the dialogues of married couples to diplomatic conversations.The current book explains how to use LLMs to analyze human conversations and how better LLMs can be developed by incorporating a deep theoretical understanding.Drawing on case studies from Pulp Fiction to diplomatic meetings, the book provides detailed, approachable, and theoretically grounded explanations of how LLMs can help us understand conversations.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisMLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.

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Book SynopsisTwo neuroscientists trace a sweeping new vision of consciousness across eighteen increasingly intelligent minds, from microbes to humankind and beyond

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisFrom the cars people drive to the phones in their pockets, computers are found everywhere in our world, and they're becoming smarter. But what makes a computer program intelligent? How can some programs beat humans at chess or trivia games? Can computers and robots really think and learn on their own? Or are they just following complex programming? In this non-fiction graphic novel, readers can follow Max Axiom and the Society of Super Scientists as they learn how artificial intelligence works and how AI is used in the world today.

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Book SynopsisAndy Pardoe is a leading AI thought leader, consultant, speaker and author. He is the Founder & CEO of the Wisdom Works Group consultancy and is also the Managing Partner of Wisdom Works Ventures, a specialist accelerator for AI startups. He is the Chair of the Deep Tech Innovation Centre at the University of Warwick. He is based in London, UK.

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Book SynopsisNicole Alexander is a marketing leader and educator with over 25 years of experience driving growth, innovation and transformation. She is an Adjunct Professor at NYU, a Lecturer at Section School and a Board Member at Per Scholas. She has held prominent leadership roles, including Global Head of Marketing at Meta, SVP of Innovation at Ipsos and VP of Innovation for Greater China at Nielsen. She lives in New York, NY.

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Book SynopsisA leader in the data economy explains how we arrived at AI—and how we can navigate its future. In The Datapreneurs, Bob Muglia helps us understand how innovation in data and information technology have led us to AI—and how this technology must shape our future. The long-time Microsoft executive, former CEO of Snowflake, and current tech investor maps the evolution of the modern data stack and how it has helped build today’s economy and society. And he explains how humanity must create a new social contract for the artificial general intelligence (AGI)—autonomous machines intelligent as people—that he expects to arrive in less than a decade. Muglia details his personal experience in the foundational years of computing and data analytics, including with Bill Gates and Sam Altman, the CEO of OpenAI, the creator of ChatGPT, and others that are not household names—yet. He builds upon Isaac Asimov’s Laws of Robotics to explore the moral, ethical, and legal implications of today’s smart machines, and how a combination of human and machine intelligence could create an era of progress and prosperity where all the people on Earth can have what they need and want without destroying our natural environment.The Datapreneurs is a call to action. AGI is surely coming. Muglia believes that tech business leaders, ethicists, policy leaders, and even the general public must collaborate answer the short- and long-term questions raised by its emergence. And he argues that we had better get going, because advances are coming so fast that society risks getting caught flatfooted—with potentially disastrous consequences. Trade Review"Muglia rightly refocuses us on the people, not just the algorithms and machines, behind the next wave of artificial intelligence." —Satya Nadella, Chairman and CEO, Microsoft “As a values-based leader, Bob brings a unique point of view that inspires others to solve today’s greatest technical challenges.” —Mark C Thompson, chief executive leadership coach and New York Times bestselling author Bob remained at the forefront of data technology throughout his career, and his informed perspective makes this book extremely compelling.”—Paul Maritz, technology investor, former CEO of VMware, and former group vice president at Microsoft "As the Information Age evolves into the Age of AI, data has never been more critical to the enterprise or, dare I say, humanity. There is nobody better than Bob to frame the important conversations about the data road ahead."—Brad Gerstner, Serial Entrepreneur and Founder / CEO of Altimeter Capital

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Book Synopsis'I wish it was science fiction, but I know it's not.' Jaan Tallinn, co-founder of Skype'If you read just one book that makes you confront scary high-tech realities that we'll soon have no choice but to address, make it this one.' Washington Post Corporations and government agencies around the world have for years been pouring billions into achieving AI's Holy Grail - human-level intelligence. But once AI has attained it, scientists argue, it will have survival drives much like our own. We may be forced to compete with a rival more cunning, more powerful, and more alien than we can imagine.First published ten years ago, Our Final Invention predicted much of the artificial 'intelligence explosion' that is now ripping through our culture, and was named by Elon Musk as one of five books everyone should read about the future. Now with an urgent new preface, James Barrat's landmark work explores the ethics, history and future perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to?Trade ReviewOur Final Invention is a thrilling detective story, and also the best book yet written on the most important problem of the twenty-first century -- Luke Muehlhauser, Executive Director, Machine Intelligence Research InstituteThe compelling story of humanity's most critical challenge. A Silent Spring for the twenty-first century. -- Michael Vassar, former President, Singularity InstituteAn important and disturbing book -- Huw Price, co-founder, Cambridge University Centre for the Study of Existential RiskEnthusiasts dominate observers of progress in artificial intelligence; the minority who disagree are alarmed, articulate and perhaps growing in numbers, and Barrat delivers a thoughtful account of their worries -- Kirkus ReviewsThis book makes an important case that without extraordinary care in our planning, powerful "thinking" machines present at least as many risks as benefits . . . Our Final Invention makes an excellent read for technophiles as well as readers wishing to get a glimpse of the near future as coloured by rapidly improving technological competence -- New York Journal of BooksA dark new book by James Barrat, Our Final Invention lays out a strong case for why we should be at least a little worried -- NewYorker.comYou can skip coffee this week - Our Final Invention will keep you wide-awake -- Singularity HubScience fiction has long explored the implications of humanlike machines (think of Asimov's I, Robot), but Barrat's thoughtful treatment adds a dose of reality -- Science NewsBarrat has talked to all the significant American players in the effort to create recursively self-improving artificial general intelligence in machines. He makes a strong case that AGI with human-level intelligence will be developed in the next couple of decades . . . His thoughtful case about the dangers of ASI gives even the most cheerful technological optimist much to think about. -- ReasonBarrat's book is excellently written and deeply researched. It does a great job of communicating to general readers the danger of mistakes in AI design and implementation. -- Bill Hibbard, author of 'Super-Intelligent Machines'

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Book SynopsisThis volume gathers together cutting-edge research from the Third Workshop on Algorithmic Foundations of Robotics and gives a solid overview of the state of the art in robot algorithms. The papers cover core problems in robotics, such as motion planning, sensor-based planning, manipulation, and assembly planning. They also examine the application of robotic algorithms in domains like molecular modeling, geometric modeling, and computer-assisted surgery.

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Book SynopsisThis is a comprehensive volume on robot teams that will be the standard reference on multi-robot systems. The volume provides not only the essentials of multi-agent robotics theory but also descriptions of exemplary implemented systems demonstrating the key concepts of multi-robot research. Information is presented in a descriptive manner and augmented with detailed mathematical formulations, photos, diagrams, and source code examples.

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Book SynopsisThe next generation of AI is here—use it to lead your business forward.If you read nothing else on artificial intelligence and machine learning, read these 10 articles. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you understand the future direction of AI, bring your AI initiatives to scale, and use AI to transform your organization.This book will inspire you to: Create a new AI strategy Learn to work with intelligent robots Get more from your marketing AI Be ready for ethical and regulatory challenges Understand how generative AI is game changing Stop tinkering with AI and go all in This collection of articles includes "Competing in the Age of AI," by Marco Iansiti and Karim R. Lakhani; "How to Win with Machine Learning," by Ajay Agrawal, Joshua Gans, and Avi Goldfarb; "Developing a Digital Mindset," by Tsedal Neeley and Paul Leonardi; "Learning to Work with Intelligent Machines," by Matt Beane; "Getting AI to Scale," by Tim Fountaine, Brian McCarthy, and Tamim Saleh; "Why You Aren't Getting More from Your Marketing AI," by Eva Ascarza, Michael Ross, and Bruce G. S. Hardie; "The Pitfalls of Pricing Algorithms," by Marco Bertini and Oded Koenigsberg; "A Smarter Strategy for Using Robots," by Ben Armstrong and Julie Shah; "Why You Need an AI Ethics Committee," by Reid Blackman; "Robots Need Us More Than We Need Them," by H. James Wilson and Paul R. Daugherty; "Stop Tinkering with AI," by Thomas H. Davenport and Nitin Mittal; and "ChatGPT Is a Tipping Point for AI," by Ethan Mollick.HBR's 10 Must Reads paperback series is the definitive collection of books for new and experienced leaders alike. Leaders looking for the inspiration that big ideas provide, both to accelerate their own growth and that of their companies, should look no further. HBR's 10 Must Reads series focuses on the core topics that every ambitious manager needs to know: leadership, strategy, change, managing people, and managing yourself. Harvard Business Review has sorted through hundreds of articles and selected only the most essential reading on each topic. Each title includes timeless advice that will be relevant regardless of an ever‐changing business environment.

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Book SynopsisIn alignment with BCS AI Foundation and Essentials certificates, this introductory guide provides the understanding you need to start building artificial intelligence (AI) capability into your organisation. You will learn how AI is being utilised today to support products, services, science and engineering, and how it is likely to be used in the future to balance the talents of humans and machines. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed. You will delve into the theory behind AI and machine learning projects, examining techniques for learning from data, the use of neural networks and why algorithms are so important in the development of a new AI agent or system.Trade Review'This book is a welcome read for those who want to know more about AI but don’t have a degree level background in the underlying subjects. It successfully brings the beginner up to speed and is written with such enthusiasm that the more complex topics become manageable. For a foundation level book it covers an impressive content range, whilst also providing a solid grounding in Machine Learning. The topics are clearly and succinctly exemplified by 3 case studies which bring AI into the real world.' -- Rosie Sheldon * Senior Trainer, TSG-training *'Many commentators see AI as the key enabler of the fifth industrial revolution. In this clear and concise guide to the BCS Artificial Intelligence Foundation qualification, Andrew Lowe and Steve Lawless set out to clearly explain the core concepts around artificial intelligence, machine learning, applications in robotics and more. A ‘must have’ guide in preparation for the BCS AI Foundation exam, this book will not only assist with exam success, but will capture your imagination to the possibilities in front of us when reimagining the human vs machine relationship.' -- Richard Webber * Digital Transformation Programme Manager, Ravensbourne University London *'This is a great book for executives to understand how AI may fit into their company and the types of benefits that they may gain and some of the pitfalls they may fall into. The book gives a clear picture of where AI fits with other types of decision-making processes. It covers many different aspects of how AI can be developed and how it affects society, with a particular focus on ethics and the human machine interface.' -- Dr Paul Edward Mort, B.Eng. (Hons), PhD, MBA, MIMechE CEng FNucI * Innovation Lead for Special Nuclear Materials, Sellafield Ltd *'Produces a great storm of ideas and thoughts with a funny touch from the authors...This is a piece of art and a “must read", for good immersion in the theme.' -- David Mondragón Tapia * IT & Business Consultant, DieresiS - Business and Professional Services *'This book is a highly recommended read for those starting out on Artificial Intelligence learning or as a refresher, written by two very knowledgeable authors, who put across the subject in an easy to understand manner.' -- Mat Gardam * Cyber Security Professional *'Manages to provide a fundamental grounding in the theory and application of AI without relying on mathematical or data science skills...the theory is colourfully illustrated with examples of both AI successes and challenges, which will prove an invaluable foundation to the reader's learning from experience in the world of Artificial Intelligence.' -- Mark Ainsworth * Director and Business Analyst, Promising ICT Limited *Table of Contents Introduction - Ethical and Sustainable Human and Artificial AI Artificial Intelligence and Robotics Applying The Benefits of AI and Identifying Challenges and Risks Starting AI - How to Build A Machine Learning Toolbox Algorithms The Management, Roles and Responsibilities of Humans and Machines AI in Use in Industry - Reimagining Everything in the Fourth Industrial Revolution AI Case Studies

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Book SynopsisIn alignment with BCS AI Foundation and Essentials certificates, this introductory guide provides the understanding you need to start building artificial intelligence (AI) capability into your organisation. You will learn how AI is being utilised today and how it is likely to be used in the future to balance the talents of humans and machines. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed.

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Book SynopsisIs Apple conscious? Could a cyber–human system sense a potential terrorist attack? Or make diagnosing a rare and little-known disease routine? Computers are not replacing us: they are enhancing us. Different intelligences are joining together to do things we thought were impossible. Whether it’s devising innovations to tackle climate change, helping job seekers and employers find one another, or identifying the outbreak of a serious disease, groups of humans and machines are already working together to solve all sorts of problems. And they will do a lot more. The future will be like another world – a place where we’ll think differently. In many ways, we are already there.Trade Review‘Malone does a terrific job of explaining how collective intelligence has evolved.’ * City A.M. *‘Superminds is the first book I have seen that deeply explores the power of information technology to enable truly new forms of human organization. I really love the premise and thoughtfulness of the book, and I highly recommend it if you want to understand and make sense of what we are likely to see in the next few years!’ -- Jimmy Wales, Wikipedia founder‘Superminds offers a fascinating deep dive into the science of collective human intelligence, and how communities of minds may ultimately be integrated with AI to produce a new, composite super-intelligence that might soon be leveraged to help solve some of humanity’s most pressing problems.’ -- Martin Ford, author of the bestselling The Rise of the Robots‘From the father of collective intelligence…a refreshingly realistic view of how computers will supercharge collective intelligence and how these superminds can help us tackle the most complex problems that face the world today.’ -- Joi Ito, Director, MIT Media Lab, and author of Whiplash‘Thomas Malone was a decade ahead of most of the rest of us in thinking about the future of work. Now – in this fascinating book – he has done it again, looking ahead to a hyper-connected world and introducing us to new vistas of human capability and creativity achievable through collective intelligence. By thinking imaginatively about our future, Malone helps us think differently about the present.’ -- Anne Marie-Slaughter, CEO of New America and author of Unfinished Business‘Malone takes us on an intentional journey into thinking about thought, intelligence, reasoning, and consciousness. He sees these notions in extremely broad terms that have changed my views of what it means to “think” – a property that emerges from aggregations and organized structures. I may never see a four-legged table the same way again!’ -- Vint Cerf, Vice President and Chief Internet Evangelist, Google‘Forget artificial intelligence. Instead, think collective intelligence, putting “AI in combination with humans who provide whatever skills and general intelligence the machines don’t yet have themselves.” The possibilities are endless. A book rich in speculation about how collective thinking might solve big problems such as climate change; of interests to fans of Daniel Dennett, Steven Pinker, and other big-picture thinkers.’ * Kirkus *‘The story of human civilization has fundamentally been the story of coordination: in families, tribes, markets, nations. The challenge we now face is learning how to collaborate at an unprecedented scale, with both human and nonhuman partners alike – be they institutions, decentralized networks or intelligent machines. Superminds opens a window into what may be the defining question of the coming century.’ -- Brian Christian, author of Algorithms to Live By‘An energizing book, filling the reader with a sense of wonder and hope for the future.’ * Booklist *‘After helping introduce the phrase “Future of Work” in his 2004 book with that name, Tom Malone is back to remind us that the real impact of technology will come not only from AI but also from harnessing human minds at hyperscale. In this well-researched and highly readable book, he explores provocatively and practically the opportunities and challenges that superminds will help us address in businesses and society. Leaders who care about the power of human minds in a world enabled by digital technologies must read this book.’ -- James Manyika, Chairman, McKinsey Global Institute

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