How Singular? How singular is the Singularity? Will it happen in an instant? Lets consider again the derivation of the word. In mathematics a singularity is a value that is beyond any limit - in essence, infinity. The Singularity as we have discussed it in this book, does not achieve infinite levels of computation, memory, as any other other measurable attribute. But it certainly achieves vast levels of all these qualities, including intelligence. With the reverse engineering of the human brain we will be able to apply the parallel, self-organizing, chaotic, algorithms of human intelligence to enormously powerful computational substrates. This intelligence will then be in a position to improve its own design, both hardware and software, in a rapidly accelerating iterative process.

"Following his blockbuster biography of Steve Jobs, The Innovators is Walter Isaacson's revealing story of the people who created the computer and the Internet. It is destined to be the standard history of the digital revolution and an indispensable guide to how innovation really happens. What were the talents that allowed certain inventors and entrepreneurs to turn their visionary ideas into disruptive realities? What led to their creative leaps? Why did some succeed and others fail? In his masterly saga, Isaacson begins with Ada Lovelace, Lord Byron's daughter, who pioneered computer programming in the 1840s. He explores the fascinating personalities that cr eated our current digital revolution, such as Vannevar Bush, Alan Turing, John von Neumann, J.C.R. Licklider, Doug Engelbart, Robert Noyce, Bill Gates, Steve Wozniak, Steve Jobs, Tim Berners-Lee, and Larry Page. This is the story of how their minds worked and what made them so inventive. It's also a narrative of how their ability to collaborate and master the art of teamwork made them even more creative. For an era that seeks to foster innovation, creativity, and teamwork, The Innovators shows how they happen"--

This introductory text covers the key areas of computer science, including recursive function theory, formal languages, and automata. It assumes a minimal background in formal mathematics. The book is divided into five parts: Computability, Grammars and Automata, Logic, Complexity, and Unsolvability. * Computability theory is introduced in a manner that makes maximum use of previous programming experience, including a "universal" program that takes up less than a page. * The number of exercises included has more than tripled. * Automata theory, computational logic, and complexity theory are presented in a flexible manner, and can be covered in a variety of different arrangements.

"Combinators have inspired ideas about computation ever since they were first invented in 1920, and in this innovative book, Stephen Wolfram provides a modern view of combinators and their significance. Informed by his work on the computational universe of possible programs and on computational language design, Wolfram explains new and existing ideas about combinators with unique clarity and stunning visualizations, as well as provides insights on their historical connections and the curious story of Moses Schönfinkel, inventor of combinators. Though invented well before Turing machines, combinators have often been viewed as an inaccessibly abstract approach to computation. This book brings them to life as never before in a thought-provoking and broadly accessible exposition of interest across mathematics and computer science, as well as to those concerned with the foundations of formal and computational thinking, and with the history of ideas"--

Procedural languages are generally well understood and their formal foundations cast in the forms of various lambda-calculi. For object- oriented languages however the situation is not as clear-cut. In this book the authors propose and develop a different approach by developing object calculi in which objects are treated as primitives. Using object calculi,the authors are able to explain both the semantics of objects and their typing rules and demonstrate how to develop all of the most important concepts of object-oriented programming languages: self, dynamic dispatch, classes, inheritance, protected and private methods, prototyping, subtyping, covariance and contravariance, and method specialization. Many researchers and graduate students will find this an important development of the underpinnings of object-oriented programming.

Computer A Mixed Language Approach describes computer programming from a mixed language perspective. More specifically, it examines how to make effective use of the hardware and software aspects of the total system using the mixed languages that are a composite of the absolute machine languages and the more facile problem-oriented languages. In addition to the absolute machine language required by the computer "hardware" and the problem-oriented language provided by the "software" of symbolic assembly programs and compilers, a third kind of programming language is considered, namely, the symbolic machine language. Comprised of nine chapters, this book illustrates mixed language programming using Fortran and the Fortran Symbolic Assembly Program. The discussion begins by describing a modern digital computer and introducing the general theory of number systems. Subsequent chapters focus on the way in which computing machines are organized to perform their functions; how a computer executes the sequence of instructions and performs a given calculation, a process known as coding; and non-arithmetic instructions used on computers. Subroutines, input-output, and assembly of complete programs are also explored. The final chapter is devoted to Fortran and programs written completely in Fortran, as well as executive programs and programs in mixed languages. This monograph is intended for both professional programmers-to-be and non-professionals in computer programming.

1 Introduction.- 2 Definitions and First Properties of Computation.- 3 Computation over a Ring.- 4 Decision Problems and Complexity over a Ring.- 5 The Class NP and NP-Complete Problems.- 6 Integer Machines.- 7 Algebraic Settings for the Problem "P ? NP?".- 8 Newton's Method.- 9 Fundamental Theorem of Algebra: Complexity Aspects.- 10 Bézout's Theorem.- 11 Condition Numbers and the Loss of Precision of Linear Equations.- 12 The Condition Number for Nonlinear Problems.- 13 The Condition Number in ?(H(d).- 14 Complexity and the Condition Number.- 15 Linear Programming.- 16 Deterministic Lower Bounds.- 17 Probabilistic Machines.- 18 Parallel Computations.- 19 Some Separations of Complexity Classes.- 20 Weak Machines.- 21 Additive Machines.- 22 Nonuniform Complexity Classes.- 23 Descriptive Complexity.- References.

"Building on his highly successful textbook on C++, David Yevick provides a concise yet comprehensive one-stop course in three key programming languages, C++, Java and Octave (a freeware alternative to MATLAB). Employing only public-domain software to ensure straightforward implementation for all readers, this book presents a unique overview of numerical and programming techniques relevant to scientific programming, including object-oriented programming, elementary and advanced topics in numerical analysis, physical system modeling, scientific graphics, software engineering and performance issues. Relevant features of each programming language are illustrated with short, incisive examples, and the installation and application of the software is described in detail. Compact, transparent code in all three programming languages is applied to the fundamental equations of quantum mechanics, electromagnetics, mechanics and statistical mechanics. Uncommented versions of the code that can be immediately modified and adapted are provided online for the more involved programs. This compact, practical text is an invaluable introduction for students in all undergraduate- and graduate-level courses in the physical sciences or engineering that require numerical modeling, and also a key reference for instructors and scientific programmers"--