History and Philosophy of Neural Networks
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APA Newsletter on Philosophy and Computers, Vol. 18, No. 2 (Spring
NEWSLETTER | The American Philosophical Association Philosophy and Computers SPRING 2019 VOLUME 18 | NUMBER 2 FEATURED ARTICLE Jack Copeland and Diane Proudfoot Turing’s Mystery Machine ARTICLES Igor Aleksander Systems with “Subjective Feelings”: The Logic of Conscious Machines Magnus Johnsson Conscious Machine Perception Stefan Lorenz Sorgner Transhumanism: The Best Minds of Our Generation Are Needed for Shaping Our Future PHILOSOPHICAL CARTOON Riccardo Manzotti What and Where Are Colors? COMMITTEE NOTES Marcello Guarini Note from the Chair Peter Boltuc Note from the Editor Adam Briggle, Sky Croeser, Shannon Vallor, D. E. Wittkower A New Direction in Supporting Scholarship on Philosophy and Computers: The Journal of Sociotechnical Critique CALL FOR PAPERS VOLUME 18 | NUMBER 2 SPRING 2019 © 2019 BY THE AMERICAN PHILOSOPHICAL ASSOCIATION ISSN 2155-9708 APA NEWSLETTER ON Philosophy and Computers PETER BOLTUC, EDITOR VOLUME 18 | NUMBER 2 | SPRING 2019 Polanyi’s? A machine that—although “quite a simple” one— FEATURED ARTICLE thwarted attempts to analyze it? Turing’s Mystery Machine A “SIMPLE MACHINE” Turing again mentioned a simple machine with an Jack Copeland and Diane Proudfoot undiscoverable program in his 1950 article “Computing UNIVERSITY OF CANTERBURY, CHRISTCHURCH, NZ Machinery and Intelligence” (published in Mind). He was arguing against the proposition that “given a discrete- state machine it should certainly be possible to discover ABSTRACT by observation sufficient about it to predict its future This is a detective story. The starting-point is a philosophical behaviour, and this within a reasonable time, say a thousand discussion in 1949, where Alan Turing mentioned a machine years.”3 This “does not seem to be the case,” he said, and whose program, he said, would in practice be “impossible he went on to describe a counterexample: to find.” Turing used his unbreakable machine example to defeat an argument against the possibility of artificial I have set up on the Manchester computer a small intelligence. -
The Creation of Neuroscience
The Creation of Neuroscience The Society for Neuroscience and the Quest for Disciplinary Unity 1969-1995 Introduction rom the molecular biology of a single neuron to the breathtakingly complex circuitry of the entire human nervous system, our understanding of the brain and how it works has undergone radical F changes over the past century. These advances have brought us tantalizingly closer to genu- inely mechanistic and scientifically rigorous explanations of how the brain’s roughly 100 billion neurons, interacting through trillions of synaptic connections, function both as single units and as larger ensem- bles. The professional field of neuroscience, in keeping pace with these important scientific develop- ments, has dramatically reshaped the organization of biological sciences across the globe over the last 50 years. Much like physics during its dominant era in the 1950s and 1960s, neuroscience has become the leading scientific discipline with regard to funding, numbers of scientists, and numbers of trainees. Furthermore, neuroscience as fact, explanation, and myth has just as dramatically redrawn our cultural landscape and redefined how Western popular culture understands who we are as individuals. In the 1950s, especially in the United States, Freud and his successors stood at the center of all cultural expla- nations for psychological suffering. In the new millennium, we perceive such suffering as erupting no longer from a repressed unconscious but, instead, from a pathophysiology rooted in and caused by brain abnormalities and dysfunctions. Indeed, the normal as well as the pathological have become thoroughly neurobiological in the last several decades. In the process, entirely new vistas have opened up in fields ranging from neuroeconomics and neurophilosophy to consumer products, as exemplified by an entire line of soft drinks advertised as offering “neuro” benefits. -
Michael M. Merzenich
Michael M. Merzenich BORN: Lebanon, Oregon May 15, 1942 EDUCATION: Public Schools, Lebanon, Oregon (1924–1935) University of Portland (Oregon), B.S. (1965) Johns Hopkins University, Ph.D. (1968) University of Wisconsin Postdoctoral Fellow (1968–1971) APPOINTMENTS: Assistant and Associate Professor, University of California at San Francisco (1971–1980) Francis A. Sooy Professor, University of California at San Francisco (1981–2008) President and CEO, Scientifi c Learning Corporation (1995–1996) Chief Scientifi c Offi cer, Scientifi c Learning Corporation (1996–2003) Chief Scientifi c Offi cer, Posit Science Corporation (2004–present) President and CEO, Brain Plasticity Institute (2008–present) HONORS AND AWARDS (SELECTED): Cortical Discoverer Prize, Cajal Club (1994) IPSEN Prize (Paris, 1997) Zotterman Prize (Stockholm, 1998) Craik Prize (Cambridge, 1998) National Academy of Sciences, U.S.A. (1999) Lashley Award, American Philosophical Society (1999) Thomas Edison Prize (Menlo Park, NJ, 2000) American Psychological Society Distinguished Scientifi c Contribution Award (2001) Zülch Prize, Max-Planck Society (2002) Genius Award, Cure Autism Now (2002) Purkinje Medal, Czech Academy (2003) Neurotechnologist of the Year (2006) Institute of Medicine (2008) Michael M. Merzenich has conducted studies defi ning the functional organization of the auditory and somatosensory nervous systems. Initial models of a commercially successful cochlear implant (now distributed by Boston Scientifi c) were developed in his laboratory. Seminal research on cortical plasticity conducted in his laboratory contributed to our current understanding of the phenomenology of brain plasticity across the human lifetime. Merzenich extended this research into the commercial world by co-founding three brain plasticity-based therapeutic software companies (Scientifi c Learning, Posit Science, and Brain Plasticity Institute). -
Abstract Papers
Workshop on Philosophy & Engineering WPE2008 The Royal Academy of Engineering London November 10th-12th 2008 Supported by the Royal Academy of Engineering, Illinois Foundry for Innovation in Engineering Education (iFoundry), the British Academy, ASEE Ethics Division, the International Network for Engineering Studies, and the Society for Philosophy & Technology Co-Chairs: David E. Goldberg and Natasha McCarthy Deme Chairs: Igor Aleksander, W Richard Bowen, Joseph C. Pitt, Caroline Whitbeck Contents 1. Workshop Schedule p.2 2. Abstracts – plenary sessions p.5 3. Abstracts – contributed papers p.7 4. Abstracts – poster session p.110 1 Workshop Schedule Monday 10 November 2008 All Plenary sessions take place in F4, the main lecture room 9.00 – 9.30 Registration 9.30 – 9.45 Welcome and introduction of day’s theme(s) Taft Broome and Natasha McCarthy 09.45 – 10.45 Billy V. Koen: Toward a Philosophy of Engineering: An Engineer’s Perspective 10. 45 – 11.15 Coffee break 11. 15 – 12.45 Parallel session – submitted papers A. F1 Mikko Martela Esa Saarinen, Raimo P. Hämäläinen, Mikko Martela and Jukka Luoma: Systems Intelligence Thinking as Engineering Philosophy David Blockley: Integrating Hard and Soft Systems Maarten Frannsen and Bjørn Jespersen: From Nutcracking to Assisted Driving: Stratified Instrumental Systems and the Modelling of Complexity B. F4 Ton Monasso: Value-sensitive design methodology for information systems Ibo van de Poel: Conflicting values in engineering design and satisficing Rose Sturm and Albrecht Fritzsche: The dynamics of practical wisdom in IT- professions C. G1 Ed Harris: Engineering Ethics: From Preventative Ethics to Aspirational Ethics Bocong Li: The Structure and Bonds of Engineering Communities Priyan Dias: The Engineer’s Identity Crisis:Homo Faber vs. -
Generative Linguistics and Neural Networks at 60: Foundation, Friction, and Fusion*
Generative linguistics and neural networks at 60: foundation, friction, and fusion* Joe Pater, University of Massachusetts Amherst October 3, 2018. Abstract. The birthdate of both generative linguistics and neural networks can be taken as 1957, the year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt. This paper traces the development of these two approaches to cognitive science, from their largely autonomous early development in their first thirty years, through their collision in the 1980s around the past tense debate (Rumelhart and McClelland 1986, Pinker and Prince 1988), and their integration in much subsequent work up to the present. Although this integration has produced a considerable body of results, the continued general gulf between these two lines of research is likely impeding progress in both: on learning in generative linguistics, and on the representation of language in neural modeling. The paper concludes with a brief argument that generative linguistics is unlikely to fulfill its promise of accounting for language learning if it continues to maintain its distance from neural and statistical approaches to learning. 1. Introduction At the beginning of 1957, two men nearing their 29th birthdays published work that laid the foundation for two radically different approaches to cognitive science. One of these men, Noam Chomsky, continues to contribute sixty years later to the field that he founded, generative linguistics. The book he published in 1957, Syntactic Structures, has been ranked as the most influential work in cognitive science from the 20th century.1 The other one, Frank Rosenblatt, had by the late 1960s largely moved on from his research on perceptrons – now called neural networks – and died tragically young in 1971. -
Reflections on the Past Two Decades of Neuroscience
VIEWPOINT medium of conceptual space is: how do we combine these twin paths to understand Reflections on the past two decades the transmission of representations in the network of the brain? Although answering of neuroscience that question will surely build on the prior paradigms, neither seems equipped to Danielle S. Bassett , Kathleen E. Cullen , Simon B. Eickhoff , provide a complete solution; the former offers the dots within, whereas the latter Martha J. Farah , Yukiko Goda , Patrick Haggard , Hailan Hu , offers the lines between. Yet obtaining such Yasmin L. Hurd , Sheena A. Josselyn , Baljit S. Khakh , Jürgen A. Knoblich , a solution is important for deciphering the Panayiota Poirazi , Russell A. Poldrack , Marco Prinz , Pieter R. Roelfsema , mechanism of the brain’s fundamental goal: Tara L. Spires-Jones , Mriganka Sur and Hiroki R. Ueda information processing. The efforts towards such a solution that I find particularly Abstract | The first issue of Nature Reviews Neuroscience was published 20 years promising are those that move beyond ago, in 2000. To mark this anniversary, in this Viewpoint article we asked a selection descriptive characterization or correlative of researchers from across the field who have authored pieces published in the approaches, and towards theory; that is, journal in recent years for their thoughts on notable and interesting developments theory instantiated in an interpretable and generalizable mathematical model in neuroscience, and particularly in their areas of the field, over the past two that encodes a conceptual principle, and decades. They also provide some thoughts on current lines of research and theory as supported by (but not composed questions that excite them. -
THE IDEA of the BRAIN Also by Matthew Cobb
THE IDEA OF THE BRAIN also by matthew cobb Life’s Greatest Secret: The Race to Crack the Genetic Code The Egg and Sperm Race: The 17th-Century Scientists Who Unravelled the Secrets of Sex, Life and Growth Smell: A Very Short Introduction The Resistance: The French Fight Against the Nazis Eleven Days in August: The Liberation of Paris in 1944 THE IDEA OF THE BRAIN THE PAST AND FUTURE OF NEUROSCIENCE MATTHEW COBB New York Copyright © 2020 by Matthew Cobb Cover design by XXX Cover image [Credit here] Cover copyright © 2020 Hachette Book Group, Inc. Hachette Book Group supports the right to free expression and the value of copyright. The purpose of copyright is to encourage writers and artists to produce the creative works that enrich our culture. The scanning, uploading, and distribution of this book without permission is a theft of the author’s intellectual property. If you would like permission to use material from the book (other than for review purposes), please contact [email protected]. Thank you for your support of the author’s rights. Basic Books Hachette Book Group 1290 Avenue of the Americas, New York, NY 10104 www.basicbooks.com Printed in the United States of America First published in Great Britain in 2020 by Profile Books Ltd First US Edition: April 2020 Published by Basic Books, an imprint of Perseus Books, LLC, a subsidiary of Hachette Book Group, Inc. The Basic Books name and logo is a trademark of the Hachette Book Group. The Hachette Speakers Bureau provides a wide range of authors for speaking events. -
APA Newsletters NEWSLETTER on PHILOSOPHY and COMPUTERS
APA Newsletters NEWSLETTER ON PHILOSOPHY AND COMPUTERS Volume 08, Number 1 Fall 2008 FROM THE EDITOR, PETER BOLTUC FROM THE CHAIR, MICHAEL BYRON PAPERS ON ROBOT CONSCIOUSNESS Featured Article STAN FRANKLIN, BERNARD J. BAARS, AND UMA RAMAMURTHY “A Phenomenally Conscious Robot?” GILBERT HARMAN “More on Explaining a Gap” BERNARD J. BAARS, STAN FRANKLIN, AND UMA RAMAMURTHY “Quod Erat Demonstrandum” ANTONIO CHELLA “Perception Loop and Machine Consciousness” MICHAEL WHEELER “The Fourth Way: A Comment on Halpin’s ‘Philosophical Engineering’” DISCUSSION ARTICLES ON FLORIDI TERRELL WARD BYNUM “Toward a Metaphysical Foundation for Information Ethics” JOHN BARKER “Too Much Information: Questioning Information Ethics” © 2008 by The American Philosophical Association EDWARD HOWLETT SPENCE “Understanding Luciano Floridi’s Metaphysical Theory of Information Ethics: A Critical Appraisal and an Alternative Neo-Gewirthian Information Ethics” DISCUSSION ARTICLES ON BAKER AMIE L. THOMASSON “Artifacts and Mind-Independence: Comments on Lynne Rudder Baker’s ‘The Shrinking Difference between Artifacts and Natural Objects’” BETH PRESTON “The Shrinkage Factor: Comment on Lynne Rudder Baker’s ‘The Shrinking Difference between Artifacts and Natural Objects’” PETER KROES AND PIETER E. VERMAAS “Interesting Differences between Artifacts and Natural Objects” BOOK REVIEW Amie Thomasson: Ordinary Objects REVIEWED BY HUAPING LU-ADLER PAPERS ON ONLINE EDUCATION H.E. BABER “Access to Information: The Virtuous and Vicious Circles of Publishing” VINCENT C. MÜLLER “What A Course on Philosophy of Computing Is Not” GORDANA DODIG-CRNKOVIC “Computing and Philosophy Global Course” NOTES CONSTANTINOS ATHANASOPOULOS “Report on the International e-Learning Conference for Philosophy, Theology and Religious Studies, York, UK, May 14th-15th, 2008” “Call for Papers on the Ontological Status of Web-Based Objects” APA NEWSLETTER ON Philosophy and Computers Piotr Bołtuć, Editor Fall 2008 Volume 08, Number 1 phenomenal consciousness remains open. -
History of Neuroscience Neurobiology & Behavior 255 Winter 2017
History of Neuroscience Neurobiology & Behavior 255 Winter 2017 Course Syllabus “The past is never dead. It isn’t even past.” William Faulkner Course Description: An overview of the conceptual and technical foundations of neuroscience from ancient times to the present. The subjects include synapses, neurons, brain organization, sensory, motor, regulatory and cognitive systems, learning and memory and human brain function and dysfunction. Course Coordinator: Larry Cahill, [email protected] Room 116 Bonney Bldg (inner office) Lecturers: Faculty from several UCI Schools and Departments (see roster) Time: Fridays 9:00 - 11:50 A.M. There will be two lectures per day, starting at 9:00 A.M. and 10:30 A.M., respectively. Place: Room 1201 McGaugh Hall Course text: Minds behind the brain: A history of the pioneers and their discoveries, Stanley Finger, Oxford University Press, 2000. Evaluation: The course grade will be determined primarily by a paper, which is due on the last day of class. No excuses for late papers will be accepted. Late papers will have a reduced grade. Any topic from a historical perspective is OK but it must be approved by Dr. Cahill. The paper should be 20-30 pages in length (double-spaced) plus bibliography, figures, tables and footnotes. Selecting a Topic and Obtaining Materials: Because of the historical nature of the paper, it will be necessary to begin obtaining materials, many of which may have to be gotten through interlibrary loan, about the 4th-5th week. Therefore, the general topic should be selected by the 3rd week. You should do some preliminary bibliographic work and reading at the earliest possible time, refining your topic and preferably formulating a specific question that you will attempt to answer. -
Neuroscience Innovation Report
Neuroscience Innovation Report 2018 Powered by Neuroscience Innovation Report 2018 Introduction In 1559, surgeons Ambroise Paré and Andreas Vesalius received permission from Queen Catherine to autopsy the brain of King Henri II of France, who had succumbed to an intracranial haemorrhage. While today this would be seen a normal investigative procedure, at the time it was a daring request. Dissections were usually performed only on criminals, who would be sentenced to the procedure as a posthumous punishment. It is unclear why Catherine gave in to Paré and Vesalius, since it was obvious that the cause of death was the lance injury he sustained in a jousting tournament. But when their predictions of the type of damage they’d find inside Henri’s brain, and where they’d find it, proved to be true, it led to a turning point in the history of neuroscience – proof that a deeper understanding of the brain lay in science rather than superstition. Today, neuroscience is continuing to innovate in our understanding of the structure of the brain. The data generated is so huge that many of these innovations are focused on creating ways to more efficiently catalogue and retrieve information from hundreds of thousands of brain scans made by researchers around the world. Platforms, such as the Human Connectome Project, and Open fMRI, have been established to share brain imaging data and analyse it collaboratively. Researchers like Julie Korenberg, at the University of Utah in Salt Lake City, are working on developing 3D coordinate systems to align various types of neuroimaging data to allow anyone to pick a point on one image and look at the same point at another resolution, a Google Earth of neuroimaging. -
CAP 5636 - Advanced Artificial Intelligence
CAP 5636 - Advanced Artificial Intelligence Introduction This slide-deck is adapted from the one used by Chelsea Finn at CS221 at Stanford. CAP 5636 Instructor: Lotzi Bölöni http://www.cs.ucf.edu/~lboloni/ Slides, homeworks, links etc: http://www.cs.ucf.edu/~lboloni/Teaching/CAP5636_Fall2021/index.html Class hours: Tue, Th 12:00PM - 1:15PM COVID considerations: UCF expects you to get vaccinated and wear a mask Classes will be in-person, but will be recorded on Zoom. Office hours will be over Zoom. Motivating artificial intelligence It is generally not hard to motivate AI these days. There have been some substantial success stories. A lot of the triumphs have been in games, such as Jeopardy! (IBM Watson, 2011), Go (DeepMind’s AlphaGo, 2016), Dota 2 (OpenAI, 2019), Poker (CMU and Facebook, 2019). On non-game tasks, we also have systems that achieve strong performance on reading comprehension, speech recognition, face recognition, and medical imaging benchmarks. Unlike games, however, where the game is the full problem, good performance on a benchmark does not necessarily translate to good performance on the actual task in the wild. Just because you ace an exam doesn’t necessarily mean you have perfect understanding or know how to apply that knowledge to real problems. So, while promising, not all of these results translate to real-world applications Dangers of AI From the non-scientific community, we also see speculation about the future: that it will bring about sweeping societal change due to automation, resulting in massive job loss, not unlike the industrial revolution, or that AI could even surpass human-level intelligence and seek to take control. -
Neural Network
© 2014 IJIRT | Volume 1 Issue 5 | ISSN : 2349-6002 NEURAL NETWORK Neha, Aastha Gupta, Nidhi Abstract- This research paper gives a short description 1.1.BIOLOGICAL MOTIVATION of what an artificial neural network is and its biological motivation .A clear description of the various ANN The human brain is a great information processor, models and its network topologies has been given. It even though it functions quite slower than an also focuses on the different learning paradigms. This ordinary computer. Many researchers in the field of paper also focuses on the applications of ANN. artificial intelligence look to the organization of the I. INTRODUCTION brain as a model for building intelligent machines.If we think of a sort of the analogy between the In machine learning and related fields, artificial complex webs of interconnected neurons in a brain neural networks (ANNs) are basically and the densely interconnected units making up computational models ,inspired by the biological an artificial neural network, where each unit,which is nervous system (in particular the brain), and are used just like a biological neuron,is capable of taking in a to estimate or the approximate functions that can number of inputs and also producing an output. depend on a large number of inputs applied . The complexity of real neurons is highly abstracted Artificial neural networks are generally presented as when modelling artificial systems of interconnected nerve cells or neurons(“as neurons. These basically consist of inputs (like they are called”) which can compute values from synapses), which are multiplied by weights inputs, and are capable of learning,which is possible (i.e the strength of the respective signals), and then is only due to their adaptive nature.