Peter Bock

Getting it Right: R&D Methods for Science and Engineering, Second Edition, is an authoritative guide to the methodologies that produce coherent and complete R&D projects. Based on the author’s experience in large industrial firms, this book addresses the avoidance of common pitfalls that engineers and scientists routinely face in industry and academia. Special emphasis is placed on the comprehensive analysis of project problems, requirements, objectives, the use of standard and consistent terminology and procedures, the design of rigorous and reproducible experiments, the appropriate reduction and interpretation of project results, and the effective communication of project design, methods, results, and conclusions, embedded in a clear and modern framework of the Scientific Method. This fully updated new edition also includes an extended case study from industry, additional material about the evolution of knowledge and science and technology and a special focus on the discovery and nurture of technical innovation, both of which reinforce the importance of adherence to the described methodology in both academic and industrial venues. Professional engineers and researchers will find a highly consistent and practical reference for the rigorous conduct and clear communication of complex R&D projects. Students will also find a palatable introduction to the critical concepts of knowing, doing, and Getting it Right. Presents a standard methodology for conducting rigorous and complete R&D projects Includes a detailed case study from an experienced R&D research scientist and engineer Provides a consistent framework for knowledge organization and the Scientific Method

R&D Methods for Science and Engineering

Getting It Right

In this extraordinary new book, a pioneer in the research on Collective Learning Systems (an adaptive learning paradigm for artificial intelligence) describes the processes and mechanisms of human and artificial cognition, defines a fundamental building block for assembling large-scale adaptive systems (the learning cell) and proposes a design for the ultimate machine: a hierarchical network of 100 million learning cells that could exhibit the full range of cognitive capabilities of the human cerebral cortex. The author demonstrates that using the classical “expert system” approach to create such a vast knowledge base would require thousands of years to program all the necessary rules. He then explains how an adaptive Collective Learning System could achieve this goal in a matter of 20 years, much as humans do. Based on natural anatomical and behavioral precedents, Collective Learning enables a machine to learn the appropriate rules through trial-and-error interaction with the real world. In the course of explaining the principles of Collective Learning and his design for the ultimate machine, the author introduces a new theory of games for modelling the processes of the universe and discusses the philosophical issues raised by the prospect of creating machines that exhibit human-like intelligence. In addition to a number of small-scale software illustrations of Collective Learning, the final chapter presents the remarkable results of a large-scale research project directed by the author: a hardware and software simulation of the sub-symbolic image-processing functions of the primary visual cortex of the brain. To make the content palatable to a wide variety of readers, the book is written in a conversational style and laced with humor. Lengthy mathematical derivations and proofs have been omitted or abbreviated. Bibliographical references to scholarly journal papers and books are included to guide theoreticians to the attendant formalisms.

An Introduction to Collective Learning

The Emergence of Artificial Cognition

An internationally recognized scientist presents his theories and associated technology for the coming generations of adaptive intelligent machines. In this extraordinary book, the pioneer of research in collective learning systems (an adaptive learning paradigm for artificial intelligence) describes the processes of cognition, postulates a fundamental adaptive building block for assembling very large scale collective learning systems (the learning cell), and proposes a design for the ultimate machine: a hierarchical network of 100 million learning cells that could exhibit the full range of cognitive capabilities of the human mind. The author predicts that using the classical "expert system" approach to create such a vast knowledge base would require thousands of years to program all the rules. As a feasible alternative, he explains how a massive collective learning system could achieve this goal in about 20 years, much as humans do. Based on natural biological precedents, a collective learning system acquires its knowledge through trial-and-error interaction with the real world. To put it all in proper perspective, the author introduces a theory of games for modeling the various processes of the universe, presents a futuristic glimpse of the creation of the first artificially cognitive being, and discusses the philosophical issues raised by the prospect of creating machines that exhibit human-like cognition. Two chapters are devoted to the design and evaluation of collective learning systems. The final chapter presents the remarkable results of an on-going international research project directed by the author, a parallel-processing collective learning system that simulates the sub-symbolic adaptive vision functions of the brain.

Getting it Right: R&D Methods for Science and Engineering, Second Edition is an authoritative guide on the methodologies that produce coherent, rigorous and comprehensible R&D projects. Based on the author's experience of, and research into, the problems consistently encountered by R&D departments in large industrial firms, this book addresses common pitfalls engineers face. Emphasis is put on the comprehensive analysis of project problems, requirements, objectives, the use of standard and consistent terminology and procedures, the design of rigorous and reproducible experiments, the appropriate reduction and interpretation of project results, and the effective communication of project design, methods, results and conclusions. This fully updated new edition also includes an extended case study from industry, further reinforcing the importance of the methods described in a practical setting. Professional engineers and researchers will find a consistent and practical framework for the rigorous conduct and communication of complex research and development projects. Presents a standard methodology for conducting coherent, rigorous, comprehensible and consistent R&D projects Includes a new detailed case study from an experienced R&D research engineer Provides thorough introductions to the theories of knowledge and the scientific method

In fiktiven - realitätsnahen - Szenen wird das oft Skurrile des Alltags vor Augen geführt.

Bekenntnisse eines Bischofs

National Portrait Gallery (Great Britain)

National Portrait Gallery (Great Britain).

Richard Ormond

Early Victorian Portraits: Text

Over the past decade, the author has met with directors of R&D departments in large industrial firms, who are frustrated by the lack of coherent and consistent methodologies in R&D projects. As a direct result the author was asked to design and present a seminar to provide R&D engineers and scientists a standard methodology for conducting coherent, rigorous, comprehensible, and consistent R&D projects. The author also realized that this training should be included in engineering and science curricula in universities and colleges. To this end, he designed and presented a pilot course for his department that was received enthusiastically by students who participated. This course has now become a required course for all doctoral students in the author's department. This book has been designed to provide professional engineers, scientists, and students with a consistent and practical framework for the rigorous conduct and communication of complex research and development projects. Although courses and training in research methods are common and generally required of social science professionals, a vast majority of physical scientists and engineers have had no formal classroom training or on-the-job mentoring on proper procedures for research methods. Getting It Right emphasizes the comprehensive analysis of project problems, requirements, and objectives; the use of standard and consistent terminology and procedures; the design of rigorous and reproducible experiments; the appropriate reduction and interpretation of project results; and the effective communication of project design, methods, results, and conclusions. Presents a standard methodology for conducting coherent, rigorous, comprehensible, and consistent R&D projects Thoroughly researched to appeal to the needs of R&D engineers and scientists in industry Will also appeal to students of engineering and science

Peter Bock

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