8. AI's Promise
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Annual Report 2018–2019 Artmuseum.Princeton.Edu
Image Credits Kristina Giasi 3, 13–15, 20, 23–26, 28, 31–38, 40, 45, 48–50, 77–81, 83–86, 88, 90–95, 97, 99 Emile Askey Cover, 1, 2, 5–8, 39, 41, 42, 44, 60, 62, 63, 65–67, 72 Lauren Larsen 11, 16, 22 Alan Huo 17 Ans Narwaz 18, 19, 89 Intersection 21 Greg Heins 29 Jeffrey Evans4, 10, 43, 47, 51 (detail), 53–57, 59, 61, 69, 73, 75 Ralph Koch 52 Christopher Gardner 58 James Prinz Photography 76 Cara Bramson 82, 87 Laura Pedrick 96, 98 Bruce M. White 74 Martin Senn 71 2 Keith Haring, American, 1958–1990. Dog, 1983. Enamel paint on incised wood. The Schorr Family Collection / © The Keith Haring Foundation 4 Frank Stella, American, born 1936. Had Gadya: Front Cover, 1984. Hand-coloring and hand-cut collage with lithograph, linocut, and screenprint. Collection of Preston H. Haskell, Class of 1960 / © 2017 Frank Stella / Artists Rights Society (ARS), New York 12 Paul Wyse, Canadian, born United States, born 1970, after a photograph by Timothy Greenfield-Sanders, American, born 1952. Toni Morrison (aka Chloe Anthony Wofford), 2017. Oil on canvas. Princeton University / © Paul Wyse 43 Sally Mann, American, born 1951. Under Blueberry Hill, 1991. Gelatin silver print. Museum purchase, Philip F. Maritz, Class of 1983, Photography Acquisitions Fund 2016-46 / © Sally Mann, Courtesy of Gagosian Gallery © Helen Frankenthaler Foundation 9, 46, 68, 70 © Taiye Idahor 47 © Titus Kaphar 58 © The Estate of Diane Arbus LLC 59 © Jeff Whetstone 61 © Vesna Pavlovic´ 62 © David Hockney 64 © The Henry Moore Foundation / Artists Rights Society (ARS), New York 65 © Mary Lee Bendolph / Artist Rights Society (ARS), New York 67 © Susan Point 69 © 1973 Charles White Archive 71 © Zilia Sánchez 73 The paper is Opus 100 lb. -
Artificial Intelligence in Health Care: the Hope, the Hype, the Promise, the Peril
Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril Michael Matheny, Sonoo Thadaney Israni, Mahnoor Ahmed, and Danielle Whicher, Editors WASHINGTON, DC NAM.EDU PREPUBLICATION COPY - Uncorrected Proofs NATIONAL ACADEMY OF MEDICINE • 500 Fifth Street, NW • WASHINGTON, DC 20001 NOTICE: This publication has undergone peer review according to procedures established by the National Academy of Medicine (NAM). Publication by the NAM worthy of public attention, but does not constitute endorsement of conclusions and recommendationssignifies that it is the by productthe NAM. of The a carefully views presented considered in processthis publication and is a contributionare those of individual contributors and do not represent formal consensus positions of the authors’ organizations; the NAM; or the National Academies of Sciences, Engineering, and Medicine. Library of Congress Cataloging-in-Publication Data to Come Copyright 2019 by the National Academy of Sciences. All rights reserved. Printed in the United States of America. Suggested citation: Matheny, M., S. Thadaney Israni, M. Ahmed, and D. Whicher, Editors. 2019. Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. NAM Special Publication. Washington, DC: National Academy of Medicine. PREPUBLICATION COPY - Uncorrected Proofs “Knowing is not enough; we must apply. Willing is not enough; we must do.” --GOETHE PREPUBLICATION COPY - Uncorrected Proofs ABOUT THE NATIONAL ACADEMY OF MEDICINE The National Academy of Medicine is one of three Academies constituting the Nation- al Academies of Sciences, Engineering, and Medicine (the National Academies). The Na- tional Academies provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. -
AI Computer Wraps up 4-1 Victory Against Human Champion Nature Reports from Alphago's Victory in Seoul
The Go Files: AI computer wraps up 4-1 victory against human champion Nature reports from AlphaGo's victory in Seoul. Tanguy Chouard 15 March 2016 SEOUL, SOUTH KOREA Google DeepMind Lee Sedol, who has lost 4-1 to AlphaGo. Tanguy Chouard, an editor with Nature, saw Google-DeepMind’s AI system AlphaGo defeat a human professional for the first time last year at the ancient board game Go. This week, he is watching top professional Lee Sedol take on AlphaGo, in Seoul, for a $1 million prize. It’s all over at the Four Seasons Hotel in Seoul, where this morning AlphaGo wrapped up a 4-1 victory over Lee Sedol — incidentally, earning itself and its creators an honorary '9-dan professional' degree from the Korean Baduk Association. After winning the first three games, Google-DeepMind's computer looked impregnable. But the last two games may have revealed some weaknesses in its makeup. Game four totally changed the Go world’s view on AlphaGo’s dominance because it made it clear that the computer can 'bug' — or at least play very poor moves when on the losing side. It was obvious that Lee felt under much less pressure than in game three. And he adopted a different style, one based on taking large amounts of territory early on rather than immediately going for ‘street fighting’ such as making threats to capture stones. This style – called ‘amashi’ – seems to have paid off, because on move 78, Lee produced a play that somehow slipped under AlphaGo’s radar. David Silver, a scientist at DeepMind who's been leading the development of AlphaGo, said the program estimated its probability as 1 in 10,000. -
Mind-Crafting: Anticipatory Critique of Transhumanist Mind-Uploading in German High Modernist Novels Nathan Jensen Bates a Disse
Mind-Crafting: Anticipatory Critique of Transhumanist Mind-Uploading in German High Modernist Novels Nathan Jensen Bates A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2018 Reading Committee: Richard Block, Chair Sabine Wilke Ellwood Wiggins Program Authorized to Offer Degree: Germanics ©Copyright 2018 Nathan Jensen Bates University of Washington Abstract Mind-Crafting: Anticipatory Critique of Transhumanist Mind-Uploading in German High Modernist Novels Nathan Jensen Bates Chair of the Supervisory Committee: Professor Richard Block Germanics This dissertation explores the question of how German modernist novels anticipate and critique the transhumanist theory of mind-uploading in an attempt to avert binary thinking. German modernist novels simulate the mind and expose the indistinct limits of that simulation. Simulation is understood in this study as defined by Jean Baudrillard in Simulacra and Simulation. The novels discussed in this work include Thomas Mann’s Der Zauberberg; Hermann Broch’s Die Schlafwandler; Alfred Döblin’s Berlin Alexanderplatz: Die Geschichte von Franz Biberkopf; and, in the conclusion, Irmgard Keun’s Das Kunstseidene Mädchen is offered as a field of future inquiry. These primary sources disclose at least three aspects of the mind that are resistant to discrete articulation; that is, the uploading or extraction of the mind into a foreign context. A fourth is proposed, but only provisionally, in the conclusion of this work. The aspects resistant to uploading are defined and discussed as situatedness, plurality, and adaptability to ambiguity. Each of these aspects relates to one of the three steps of mind- uploading summarized in Nick Bostrom’s treatment of the subject. -
Sustainable Development, Technological Singularity and Ethics
European Research Studies Journal Volume XXI, Issue 4, 2018 pp. 714- 725 Sustainable Development, Technological Singularity and Ethics Vyacheslav Mantatov1, Vitaly Tutubalin2 Abstract: The development of modern convergent technologies opens the prospect of a new technological order. Its image as a “technological singularity”, i.e. such “transhuman” stage of scientific and technical progress, on which the superintelligence will be practically implemented, seems to be quite realistic. The determination of the basic philosophical coordinates of this future reality in the movement along the path of sustainable development of mankind is the most important task of modern science. The article is devoted to the study of the basic ontological, epistemological and moral aspects in the reception of the coming technological singularity. The method of this study is integrating dialectical and system approach. The authors come to the conclusion: the technological singularity in the form of a “computronium” (superintelligence) opens up broad prospects for the sustainable development of mankind in the cosmic dimension. This superintelligence will become an ally of man in the process of cosmic evolution. Keywords: Technological Singularity, Superintelligence, Convergent Technologies, Cosmocentrism, Human and Universe JEL code: Q01, Q56. 1East Siberia State University of Technology and Management, Ulan-Ude, Russia [email protected] 2East Siberia State University of Technology and Management, Ulan-Ude, Russia, [email protected] V. Mantatov, V. Tutubalin 715 1. Introduction Intelligence organizes the world by organizing itself. J. Piaget Technological singularity is defined as a certain moment or stage in the development of mankind, when scientific and technological progress will become so fast and complex that it will be unpredictable. -
Generative Models, Structural Similarity, and Mental Representation
The Mind as a Predictive Modelling Engine: Generative Models, Structural Similarity, and Mental Representation Daniel George Williams Trinity Hall College University of Cambridge This dissertation is submitted for the degree of Doctor of Philosophy August 2018 The Mind as a Predictive Modelling Engine: Generative Models, Structural Similarity, and Mental Representation Daniel Williams Abstract I outline and defend a theory of mental representation based on three ideas that I extract from the work of the mid-twentieth century philosopher, psychologist, and cybernetician Kenneth Craik: first, an account of mental representation in terms of idealised models that capitalize on structural similarity to their targets; second, an appreciation of prediction as the core function of such models; and third, a regulatory understanding of brain function. I clarify and elaborate on each of these ideas, relate them to contemporary advances in neuroscience and machine learning, and favourably contrast a predictive model-based theory of mental representation with other prominent accounts of the nature, importance, and functions of mental representations in cognitive science and philosophy. For Marcella Montagnese Preface Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared in the Preface and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. I further state that no substantial part of my dissertation has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. -
Transhumanism Between Human Enhancement and Technological Innovation*
Transhumanism Between Human Enhancement and Technological Innovation* Ion Iuga Abstract: Transhumanism introduces from its very beginning a paradigm shift about concepts like human nature, progress and human future. An overview of its ideology reveals a strong belief in the idea of human enhancement through technologically means. The theory of technological singularity, which is more or less a radicalisation of the transhumanist discourse, foresees a radical evolutionary change through artificial intelligence. The boundaries between intelligent machines and human beings will be blurred. The consequence is the upcoming of a post-biological and posthuman future when intelligent technology becomes autonomous and constantly self-improving. Considering these predictions, I will investigate here the way in which the idea of human enhancement modifies our understanding of technological innovation. I will argue that such change goes in at least two directions. On the one hand, innovation is seen as something that will inevitably lead towards intelligent machines and human enhancement. On the other hand, there is a direction such as “Singularity University,” where innovation is called to pragmatically solving human challenges. Yet there is a unifying spirit which holds together the two directions and I think it is the same transhumanist idea. Keywords: transhumanism, technological innovation, human enhancement, singularity Each of your smartphones is more powerful than the fastest supercomputer in the world of 20 years ago. (Kathryn Myronuk) If you understand the potential of these exponential technologies to transform everything from energy to education, you have different perspective on how we can solve the grand challenges of humanity. (Ray Kurzweil) We seek to connect a humanitarian community of forward-thinking people in a global movement toward an abundant future (Singularity University, Impact report 2014). -
ARCHITECTS of INTELLIGENCE for Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS of INTELLIGENCE
MARTIN FORD ARCHITECTS OF INTELLIGENCE For Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS OF INTELLIGENCE THE TRUTH ABOUT AI FROM THE PEOPLE BUILDING IT MARTIN FORD ARCHITECTS OF INTELLIGENCE Copyright © 2018 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. Acquisition Editors: Ben Renow-Clarke Project Editor: Radhika Atitkar Content Development Editor: Alex Sorrentino Proofreader: Safis Editing Presentation Designer: Sandip Tadge Cover Designer: Clare Bowyer Production Editor: Amit Ramadas Marketing Manager: Rajveer Samra Editorial Director: Dominic Shakeshaft First published: November 2018 Production reference: 2201118 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK ISBN 978-1-78913-151-2 www.packt.com Contents Introduction ........................................................................ 1 A Brief Introduction to the Vocabulary of Artificial Intelligence .......10 How AI Systems Learn ........................................................11 Yoshua Bengio .....................................................................17 Stuart J. -
In-Datacenter Performance Analysis of a Tensor Processing Unit
In-Datacenter Performance Analysis of a Tensor Processing Unit Presented by Josh Fried Background: Machine Learning Neural Networks: ● Multi Layer Perceptrons ● Recurrent Neural Networks (mostly LSTMs) ● Convolutional Neural Networks Synapse - each edge, has a weight Neuron - each node, sums weights and uses non-linear activation function over sum Propagating inputs through a layer of the NN is a matrix multiplication followed by an activation Background: Machine Learning Two phases: ● Training (offline) ○ relaxed deadlines ○ large batches to amortize costs of loading weights from DRAM ○ well suited to GPUs ○ Usually uses floating points ● Inference (online) ○ strict deadlines: 7-10ms at Google for some workloads ■ limited possibility for batching because of deadlines ○ Facebook uses CPUs for inference (last class) ○ Can use lower precision integers (faster/smaller/more efficient) ML Workloads @ Google 90% of ML workload time at Google spent on MLPs and LSTMs, despite broader focus on CNNs RankBrain (search) Inception (image classification), Google Translate AlphaGo (and others) Background: Hardware Trends End of Moore’s Law & Dennard Scaling ● Moore - transistor density is doubling every two years ● Dennard - power stays proportional to chip area as transistors shrink Machine Learning causing a huge growth in demand for compute ● 2006: Excess CPU capacity in datacenters is enough ● 2013: Projected 3 minutes per-day per-user of speech recognition ○ will require doubling datacenter compute capacity! Google’s Answer: Custom ASIC Goal: Build a chip that improves cost-performance for NN inference What are the main costs? Capital Costs Operational Costs (power bill!) TPU (V1) Design Goals Short design-deployment cycle: ~15 months! Plugs in to PCIe slot on existing servers Accelerates matrix multiplication operations Uses 8-bit integer operations instead of floating point How does the TPU work? CISC instructions, issued by host. -
Ryokoakamaexploringemptines
University of Huddersfield Repository Akama, Ryoko Exploring Empitness: An Investigation of MA and MU in My Sonic Composition Practice Original Citation Akama, Ryoko (2015) Exploring Empitness: An Investigation of MA and MU in My Sonic Composition Practice. Doctoral thesis, University of Huddersfield. This version is available at http://eprints.hud.ac.uk/26619/ The University Repository is a digital collection of the research output of the University, available on Open Access. Copyright and Moral Rights for the items on this site are retained by the individual author and/or other copyright owners. Users may access full items free of charge; copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational or not-for-profit purposes without prior permission or charge, provided: • The authors, title and full bibliographic details is credited in any copy; • A hyperlink and/or URL is included for the original metadata page; and • The content is not changed in any way. For more information, including our policy and submission procedure, please contact the Repository Team at: [email protected]. http://eprints.hud.ac.uk/ EXPLORING EMPTINESS AN INVESTIGATION OF MA AND MU IN MY SONIC COMPOSITION PRACTICE Ryoko Akama A commentary accompanying the publication portfolio submitted to the University of Huddersfield in partial fulfillment of the requirements for the degree of Doctor of Philosophy ! The University of Huddersfield School of Music, Humanities and Media April, 2015 Title: Exploring Emptiness Subtitle: An investigation of ma and mu in my sonic composition practice Name of student: Ryoko Akama Supervisor: Prof. -
Transitions Spring 2014 # from the Archives … Fall of 2016 Marked the 50Th Anniversary of Prescott College Opening Its Doors
TransitionS Celebrating 50 Years of Innovation Transitions Spring 2014 # From the Archives … Fall of 2016 marked the 50th anniversary of Prescott College opening its doors. We’ve been taking time to look back, and reflect on the winding journey that has led us to where we stand today. Transitions has played an important role in keeping our friends and alumni connected to campus. Enjoy the selection of historic covers! From Last Issue: We didn’t hear from anyone about this image! If you know the who, what or when about these animated performers, let us know at [email protected]. Photos courtesy of the College Archives Prescott Connect with us There are more ways than ever to tell us what’s on your mind: Call us. We’d love to hear your feedback Email us at (928) 350-4506 [email protected] Transitions Magazine Twitter users can follow Join our Facebook Prescott College Prescott College at community. Log on to 220 Grove Ave. twitter.com/PrescottCollege facebook.com/PrescottCollege Prescott, AZ 86301 Cover photo: 50th Anniversary mural by the Spring 2017 Public Art: Mural Painting class Contents TransitionS 8 Alumni Bike Cuba with Former Faculty Publisher and Editor 12 Charles Franklin Parker’s Rose Window Ashley Hust 14 Prescott College Ratings and Rankings Designer Miriam Glade 15 Rock Climbing Board of Trustees Contributing Writers 16 Student Wins EPA Fellowship Michael Belef • Scott Bennett • Sue Bray • Paul Burkhardt June Burnside Tackett • Susan DeFreitas • Liz Faller 17 Prescott College Innovations in Higher Ed Elizabeth Fawley • John Flicker • Ashley Hust • Maria Johnson • Leslie Laird • Nelson Lee • David Mazurkiewicz 18 50th Anniversary Celebration Robert Miller • Jorge Miros • Amanda Pekar • Mark Riegner • Micah Riegner • Elisabeth Ruffner • Kayla Sargent • Peter Sherman, • Marie Smith • Wyatt Smith 22 Kino Fellows: Where Are They Now? Astrea Strawn • David White • Gratia Winship • Lisa Zander 24 Leslie Laird Reflects On Path to PC Staff Photographers Shayna Beasley • Miriam Glade • Ashley Hust 26 Ronald C. -
The Computational Attitude in Music Theory
The Computational Attitude in Music Theory Eamonn Bell Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Eamonn Bell All rights reserved ABSTRACT The Computational Attitude in Music Theory Eamonn Bell Music studies’s turn to computation during the twentieth century has engendered particular habits of thought about music, habits that remain in operation long after the music scholar has stepped away from the computer. The computational attitude is a way of thinking about music that is learned at the computer but can be applied away from it. It may be manifest in actual computer use, or in invocations of computationalism, a theory of mind whose influence on twentieth-century music theory is palpable. It may also be manifest in more informal discussions about music, which make liberal use of computational metaphors. In Chapter 1, I describe this attitude, the stakes for considering the computer as one of its instruments, and the kinds of historical sources and methodologies we might draw on to chart its ascendance. The remainder of this dissertation considers distinct and varied cases from the mid-twentieth century in which computers or computationalist musical ideas were used to pursue new musical objects, to quantify and classify musical scores as data, and to instantiate a generally music-structuralist mode of analysis. I present an account of the decades-long effort to prepare an exhaustive and accurate catalog of the all-interval twelve-tone series (Chapter 2). This problem was first posed in the 1920s but was not solved until 1959, when the composer Hanns Jelinek collaborated with the computer engineer Heinz Zemanek to jointly develop and run a computer program.