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|Our Final Invention: Artificial Intelligence and the End of the Human Era
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Author: James Barrat
Brand: Barrat James
Elon Musk named Our Final Invention one of 5 books everyone should read about the future
A Huffington Post Definitive Tech Book of 2013
In as little as a decade, artificial intelligence could match and then surpass human intelligence. Corporations and government agencies around the world are pouring billions into achieving AI's Holy Grail―human-level intelligence. 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.
Through profiles of tech visionaries, industry watchdogs, and groundbreaking AI systems, James Barrat's Our Final Invention explores the 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?
- Our Final Invention Artificial Intelligence and the End of the Human Era
|Gödel, Escher, Bach: An Eternal Golden Braid
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Author: Douglas R. Hofstadter
Brand: Douglas R Hofstadter
Winner of the Pulitzer Prize
A metaphorical fugue on minds and machines in the spirit of Lewis Carroll
Douglas Hofstadter's book is concerned directly with the nature of "maps" or links between formal systems. However, according to Hofstadter, the formal system that underlies all mental activity transcends the system that supports it. If life can grow out of the formal chemical substrate of the cell, if consciousness can emerge out of a formal system of firing neurons, then so too will computers attain human intelligence. Gödel, Escher, Bach is a wonderful exploration of fascinating ideas at the heart of cognitive science: meaning, reduction, recursion, and much more.
Twenty years after it topped the bestseller charts, Douglas R. Hofstadter's Gödel, Escher, Bach: An Eternal Golden Braid is still something of a marvel. Besides being a profound and entertaining meditation on human thought and creativity, this book looks at the surprising points of contact between the music of Bach, the artwork of Escher, and the mathematics of Gödel. It also looks at the prospects for computers and artificial intelligence (AI) for mimicking human thought. For the general reader and the computer techie alike, this book still sets a standard for thinking about the future of computers and their relation to the way we think.
Hofstadter's great achievement in Gödel, Escher, Bach was making abstruse mathematical topics (like undecidability, recursion, and 'strange loops') accessible and remarkably entertaining. Borrowing a page from Lewis Carroll (who might well have been a fan of this book), each chapter presents dialogue between the Tortoise and Achilles, as well as other characters who dramatize concepts discussed later in more detail. Allusions to Bach's music (centering on his Musical Offering) and Escher's continually paradoxical artwork are plentiful here. This more approachable material lets the author delve into serious number theory (concentrating on the ramifications of Gödel's Theorem of Incompleteness) while stopping along the way to ponder the work of a host of other mathematicians, artists, and thinkers.
The world has moved on since 1979, of course. The book predicted that computers probably won't ever beat humans in chess, though Deep Blue beat Garry Kasparov in 1997. And the vinyl record, which serves for some of Hofstadter's best analogies, is now left to collectors. Sections on recursion and the graphs of certain functions from physics look tantalizing, like the fractals of recent chaos theory. And AI has moved on, of course, with mixed results. Yet Gödel, Escher, Bach remains a remarkable achievement. Its intellectual range and ability to let us visualize difficult mathematical concepts help make it one of this century's best for anyone who's interested in computers and their potential for real intelligence. --Richard Dragan
Topics Covered: J.S. Bach, M.C. Escher, Kurt Gödel: biographical information and work, artificial intelligence (AI) history and theories, strange loops and tangled hierarchies, formal and informal systems, number theory, form in mathematics, figure and ground, consistency, completeness, Euclidean and non-Euclidean geometry, recursive structures, theories of meaning, propositional calculus, typographical number theory, Zen and mathematics, levels of description and computers; theory of mind: neurons, minds and thoughts; undecidability; self-reference and self-representation; Turing test for machine intelligence.
- Godel Escher Bach An Eternal Golden Braid
|The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
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Author: Pedro Domingos
Brand: Domingos Pedro
"Wonderfully erudite, humorous, and easy to read." --KDNuggets
In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner-the Master Algorithm-and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
- The Master Algorithm How the Quest for the Ultimate Learning Machine Will Remake Our World
|Interaction Design: Beyond Human-Computer Interaction
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Author: Jenny Preece
A new edition of the #1 text in the Human Computer Interaction field!
Hugely popular with students and professionals alike, Interaction Design is an ideal resource for learning the interdisciplinary skills needed for interaction design, human–computer interaction, information design, web design and ubiquitous computing.
This text offers a cross-disciplinary, practical and process-oriented introduction to the field, showing not just what principles ought to apply to interaction design, but crucially how they can be applied.
An accompanying website contains extensive additional teaching and learning material including slides for each chapter, comments on chapter activities and a number of in-depth case studies written by researchers and designers.
|Pattern Recognition and Machine Learning (Information Science and Statistics)
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Author: Christopher M. Bishop
Brand: Christopher M Bishop
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
- Pattern Recognition and Machine Learning
|Grokking Algorithms: An illustrated guide for programmers and other curious people
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Author: Aditya Bhargava
Brand: Bhargava Aditya
Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.
Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on Manning Publications' YouTube channel.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs.
About the Book
Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them.
- Covers search, sort, and graph algorithms
- Over 400 pictures with detailed walkthroughs
- Performance trade-offs between algorithms
- Python-based code samples
About the Reader
This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms.
About the Author
Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io.
Table of Contents
- Introduction to algorithms
- Selection sort
- Hash tables
- Breadth-first search
- Dijkstra's algorithm
- Greedy algorithms
- Dynamic programming
- K-nearest neighbors
- Grokking Algorithms An Illustrated Guide for Programmers and Other Curious People
|Code: The Hidden Language of Computer Hardware and Software
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Author: Charles Petzold
What do flashlights, the British invasion, black cats, and seesaws have to do with computers? In CODE, they show us the ingenious ways we manipulate language and invent new means of communicating with each other. And through CODE, we see how this ingenuity and our very human compulsion to communicate have driven the technological innovations of the past two centuries.
Using everyday objects and familiar language systems such as Braille and Morse code, author Charles Petzold weaves an illuminating narrative for anyone who’s ever wondered about the secret inner life of computers and other smart machines.
It’s a cleverly illustrated and eminently comprehensible story—and along the way, you’ll discover you’ve gained a real context for understanding today’s world of PCs, digital media, and the Internet. No matter what your level of technical savvy, CODE will charm you—and perhaps even awaken the technophile within.
Charles Petzold's latest book, Code: The Hidden Language of Computer Hardware and Software, crosses over into general-interest nonfiction from his usual programming genre. It's a carefully written, carefully researched gem that will appeal to anyone who wants to understand computer technology at its essence. Readers learn about number systems (decimal, octal, binary, and all that) through Petzold's patient (and frequently entertaining) prose and then discover the logical systems that are used to process them. There's loads of historical information too. From Louis Braille's development of his eponymous raised-dot code to Intel Corporation's release of its early microprocessors, Petzold presents stories of people trying to communicate with (and by means of) mechanical and electrical devices. It's a fascinating progression of technologies, and Petzold presents a clear statement of how they fit together.
The real value of Code is in its explanation of technologies that have been obscured for years behind fancy user interfaces and programming environments, which, in the name of rapid application development, insulate the programmer from the machine. In a section on machine language, Petzold dissects the instruction sets of the genre-defining Intel 8080 and Motorola 6800 processors. He walks the reader through the process of performing various operations with each chip, explaining which opcodes poke which values into which registers along the way. Petzold knows that the hidden language of computers exhibits real beauty. In Code, he helps readers appreciate it. --David Wall
Topics covered: Mechanical and electrical representations of words and numbers, number systems, logic gates, performing mathematical operations with logic gates, microprocessors, machine code, memory and programming languages.
|Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
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Author: Kevin P. Murphy
Brand: Murphy Kevin P
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.
The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
- The Machine Learning A Probabilistic Perspective
|Blockchain Basics: A Non-Technical Introduction in 25 Steps
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Author: Daniel Drescher
In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.
This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical concepts that make up the blockchain and their role in business-relevant applications.
What You'll Learn
- What the blockchain is
- Why it is needed and what problem it solves
- Why there is so much excitement about the blockchain and its potential
- Major components and their purpose
- How various components of the blockchain work and interact
- Limitations, why they exist, and what has been done to overcome them
- Major application scenarios
Who This Book Is For
Everyone who wants to get a general idea of what blockchain technology is, how it works, and how it will potentially change the financial system as we know it
- Blockchain Technology Explained: The Ultimate Beginner’s Guide About Blockchain Wallet, Mining, Bitcoin, Ethereum, Litecoin, Zcash, Monero, Ripple, Dash, IOTA And Smart Contracts
- Blockchain: The Beginners Guide To Understanding The Technology Behind Bitcoin & Cryptocurrency (The Future of Money)
- Blockchain For Dummies (For Dummies (Computer/Tech))
- Blockchain: Ultimate guide to understanding blockchain, bitcoin, cryptocurrencies, smart contracts and the future of money.
- Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World
- Mastering Bitcoin: Programming the Open Blockchain
- Ethereum: Blockchains, Digital Assets, Smart Contracts, Decentralized Autonomous Organizations
- The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology
- That Book on Blockchain: A One-Hour Intro
- Ethereum: The Ultimate Guide to the World of Ethereum, Ethereum Mining, Ethereum Investing, Smart Contracts, Dapps and DAOs, Ether, Blockchain Technology
|Introduction to Machine Learning with Python: A Guide for Data Scientists
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Author: Andreas C. Müller
Brand: Mueller Andreas C
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.
You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.
With this book, you’ll learn:
- Fundamental concepts and applications of machine learning
- Advantages and shortcomings of widely used machine learning algorithms
- How to represent data processed by machine learning, including which data aspects to focus on
- Advanced methods for model evaluation and parameter tuning
- The concept of pipelines for chaining models and encapsulating your workflow
- Methods for working with text data, including text-specific processing techniques
- Suggestions for improving your machine learning and data science skills
- Introduction to Machine Learning with Python A Guide for Data Scientists
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