Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

Electronic communication is radically altering literacy practices. Silicon Literacies unravels the key features of the new communication order to explore the social, cultural and educational impact of silicon literacy practices. Written by leading international scholars from a range of disciplines, the essays in this collection examine the implications of text produced on a keyboard, visible on a screen and transmitted through a global network of computers. The book covers topics as diverse as role-playing in computer games, the use of graphic symbols in on-screen texts and Internet degree programmes to reveal that being literate is to do with understanding how different modalities combine to create meaning. Recognizing that reading and writing are only part of what people have to learn to be literate, the contributors enhance our understanding of the ways in which the use of new technologies influence, shape and sometimes transform literacy practices.

Silicon photonics is beginning to play an important role in driving innovations in communication and computation for an increasing number of applications, from health care and biomedical sensors to autonomous driving, datacenter networking, and security. In recent years, there has been a significant amount of effort in industry and academia to innovate, design, develop, analyze, optimize, and fabricate systems employing silicon photonics, shaping the future of not only Datacom and telecom technology but also high-performance computing and emerging computing paradigms, such as optical computing and artificial intelligence. Different from existing books in this area, Silicon Photonics for High-Performance Computing and Beyond presents a comprehensive overview of the current state-of-the-art technology and research achievements in applying silicon photonics for communication and computation. It focuses on various design, development, and integration challenges, reviews the latest advances spanning materials, devices, circuits, systems, and applications. Technical topics discussed in the book include: • Requirements and the latest advances in high-performance computing systems • Device- and system-level challenges and latest improvements to deploy silicon photonics in computing systems • Novel design solutions and design automation techniques for silicon photonic integrated circuits • Novel materials, devices, and photonic integrated circuits on silicon • Emerging computing technologies and applications based on silicon photonics Silicon Photonics for High-Performance Computing and Beyond presents a compilation of 19 outstanding contributions from academic and industry pioneers in the field. The selected contributions present insightful discussions and innovative approaches to understand current and future bottlenecks in high-performance computing systems and traditional computing platforms, and the promise of silicon photonics to address those challenges. It is ideal for researchers and engineers working in the photonics, electrical, and computer engineering industries as well as academic researchers and graduate students (M.S. and Ph.D.) in computer science and engineering, electronic and electrical engineering, applied physics, photonics, and optics.

"As soon as she heard me enter, Elvia awoke from a light sleep that had overcome her as she anxiously waited: 'How did it go?' Excited, I exclaimed: 'It works!' We embraced, almost overwhelmed with feelings of euphoria and happiness, aware that something epochal had happened. On that cold January night of 1971, the world's first microprocessor was born!" The creation of the microprocessor launched the digital age. The key technology allowing unprecedented integration, and the design of the world's first microprocessor, the Intel 4004, were the achievement of Federico Faggin. Shrinking an entire computer onto a tiny and inexpensive piece of silicon would come to define our daily lives, imbuing myriad devices and everyday objects with computational intelligence. In Silicon, internationally recognized inventor and entrepreneur Federico Faggin chronicles his "four lives" his formative years in war-torn Northern Italy; his pioneering work in American microelectronics; his successful career as a high-tech entrepreneur; and his more recent explorations into the mysteries of consciousness. In this heartfelt memoir, Faggin paints vivid anecdotes, steps readers through society-changing technological breakthroughs, and shares personal insights, as each of his lives propels the next.

A data-rich study of the difficult partnerships between the colleges, universities, and businesses of Silicon Valley. Universities and colleges often operate between two worlds: higher education and economic systems. With a mission rooted in research, teaching, and public service, institutions of higher learning are also economic drivers in their regions, under increasing pressure to provide skilled workers to local companies. It is impossible to understand how current developments are affecting colleges without attending to the changes in both the higher education system and in the economic communities in which they exist. W. Richard Scott, Michael W. Kirst, and colleagues focus on the changing relations between colleges and companies in one vibrant economic region: the San Francisco Bay Area. Colleges and tech companies, they argue, have a common interest in knowledge generation and human capital, but they operate in social worlds that substantially differ, making them uneasy partners. Colleges are a part of a long tradition that stresses the importance of precedent, academic values, and liberal education. High-tech companies, by contrast, value innovation and know-how, and they operate under conditions that reward rapid response to changing opportunities. The economy is changing faster than the postsecondary education system. Drawing on quantitative and historical data from 1970 to 2012 as well as 14 case studies of colleges, this book describes a rich and often tense relationship between higher education and the tech industry. It focuses on the ways in which various types of colleges have endeavored—and often failed—to meet the demands of a vibrant economy and concludes with a discussion of current policy recommendations, suggestions for improvements and reforms at the state level, and a proposal to develop a regional body to better align educational and economic development.

Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include: large scale analog systems in silicon neuromorphic silicon auditory (ear) and vision (eye) systems in silicon learning and adaptation in silicon merging biology and technology micropower analog circuit design analog memory analog interchipcommunication on digital buses £/LIST£ Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.