The book you are holding, Stories Past: Found History in the Carnegie Mellon University Archives (Spring 2018), was written, edited, and published by four undergraduate students in Carnegie Mellon University's IntegrativeDesign, Arts andTechnology Network (IDeATe) program. These four students spent a semester poring through four archive collections looking for narrative threads that would allow them to tell stories using the history of the university.The only mandate: find a connection between the past and the present. The students engaged in design thinking exercises to help them find narrative connections between the archives. They worked with external groups and organizations to help contextualize the information they found. What they have produced are stories culled from the past that are as relevant today as they were when they happened last centu
What does it mean to be Marked by Love? The more I peel away the rules and expectations and exhausting obligations, the more I find the love of Jesus. These things don’t peel away easily—more like a price tag that you pick off in a million tiny pieces. But with every scrap removed there is exposed a treasure of love that was there the whole time—disguised and hidden by religion. -- Tim Stevens ### Jesus said the one thing that would set his disciples apart from others…they would be known by their love for each other. No tattoo. No uniform. No team colors or logos or code words. The one thing that would mark the followers of Jesus—love. Consider. . . How would I treat someone who I disagree with in a political discussion if I ran everything I said through a filter of love? How would I treat the family member who drives me crazy if I were marked by love? What would be different about my social media posts or comments if I really loved the people I was responding to or writing about? How would I talk about or act toward the LGBTQ community if I was actually following in Jesus’ steps? This is real life stuff. Join seasoned author Tim Stevens as he walks you through 31 story-driven chapters that will challenge and encourage you to filter every thought, behavior, word, and action through a lens of love. If you’ve ever been discouraged by Christianity—whether you’re a lifelong churchgoer or you gave up on religion a long time ago—Marked by Love will be a game-changer in your faith journey.
This book is a history of artificial intelligence, that audacious effort to duplicate in an artifact what we consider to be our most important property—our intelligence. It is an invitation for anybody with an interest in the future of the human race to participate in the inquiry.
In Art to Come Terry Smith—who is widely recognized as one of the world's leading historians and theorists of contemporary art—traces the emergence of contemporary art and further develops his concept of contemporaneity. Smith shows that embracing contemporaneity as both a historical concept and a condition of the globalized world allows us to grasp how contemporary art exists in a fluid space of increasing interdependencies, multiple contemporaneous modernities, and persistent inequalities. Throughout these essays, Smith offers systematic proposals for writing contemporary art's histories while assessing how curators, critics, philosophers, artists, and art historians are currently doing so. Among other topics, Smith examines the intersection of architecture with other visual arts, Chinese art since the Cultural Revolution, how philosophers are theorizing concepts associated with the contemporary, Australian Indigenous art, and the current state of art history. Art to Come will be essential reading for artists, art students, curators, gallery workers, historians, critics, and theorists.
While political history has plenty to say about the impact of Ronald Reagan’s election to the presidency in 1980, four Senate races that same year have garnered far less attention—despite their similarly profound political effect. Tuesday Night Massacre looks at those races. In examining the defeat in 1980 of Idaho’s Frank Church, South Dakota’s George McGovern, John Culver of Iowa, and Birch Bayh of Indiana, Marc C. Johnson tells the story of the beginnings of the divisive partisanship that has become a constant feature of American politics. The turnover of these seats not only allowed Republicans to gain control of the Senate for the first time since 1954 but also fundamentally altered the conduct of American politics. The incumbents were politicians of national reputation who often worked with members of the other party to accomplish significant legislative objectives—but they were, Johnson suggests, unprepared and ill-equipped to counter nakedly negative emotional appeals to the “politically passive voter.” Such was the campaign of the National Conservative Political Action Committee (NCPAC), the organization founded by several young conservative political activists who targeted these four senators for defeat. Johnson describes how such groups, amassing a great amount of money, could make outrageous and devastating claims about incumbents—“baby killers” who were “soft on communism,” for example—on behalf of a candidate who remained above the fray. Among the key players in this sordid drama are NCPAC chairman Terry Dolan; Washington lobbyist Charles Black, a top GOP advisor to several presidential campaigns and one-time business partner of Paul Manafort; and Roger Stone, self-described “dirty trickster” for Richard Nixon and confidant of Donald Trump. Connecting the dots between the Goldwater era of the 1960s and the ascent of Trump, Tuesday Night Massacre charts the radicalization of the Republican Party and the rise of the independent expenditure campaign, with its divisive, negative techniques, a change that has deeply—and perhaps permanently—warped the culture of bipartisanship that once prevailed in American politics.
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning
"An eloquent and essential correction to contemporary discussions of the American working class."—The Nation From the ongoing issues of poverty, health, housing, and employment to the recent upsurge of lethal police-community relations, the black working class stands at the center of perceptions of social and racial conflict today. Journalists and public policy analysts often discuss the black poor as “consumers” rather than “producers,” as “takers” rather than “givers,” and as “liabilities” instead of “assets.” In his engrossing history, Workers on Arrival, Joe William Trotter, Jr., refutes these perceptions by charting the black working class’s vast contributions to the making of America. Covering the last four hundred years since Africans were first brought to Virginia in 1619, Trotter traces the complicated journey of black workers from the transatlantic slave trade to the demise of the industrial order in the twenty-first century. At the center of this compelling, fast-paced narrative are the actual experiences of these African American men and women. A dynamic and vital history of remarkable contributions despite repeated setbacks, Workers on Arrival expands our understanding of America’s economic and industrial growth, its cities, ideas, and institutions, and the real challenges confronting black urban communities today.
A thorough rethinking of a field deserves to take a shape that is in itself new. Interacting with Print delivers on this premise, reworking the history of print through a unique effort in authorial collaboration. The book itself is not a typical monograph—rather, it is a “multigraph,” the collective work of twenty-two scholars who together have assembled an alphabetically arranged tour of key concepts for the study of print culture, from Anthologies and Binding to Publicity and Taste. Each entry builds on its term in order to resituate print and book history within a broader media ecology throughout the eighteenth and nineteenth centuries. The central theme is interactivity, in three senses: people interacting with print; print interacting with the non-print media that it has long been thought, erroneously, to have displaced; and people interacting with each other through print. The resulting book will introduce new energy to the field of print studies and lead to considerable new avenues of investigation.
Artificial intelligence (AI) may be the most beneficial technological development of the twenty-first century.Media hype and raised expectations for results, however, have clouded understanding of the true nature of AI—including its limitations and potential. AI at War provides a balanced and practical understanding of applying AI to national security and warfighting professionals as well as a wide array of other readers. Although the themes and findings of the chapters are relevant across the U.S. Department of Defense, to include all Services, the Joint Staff and defense agencies as well as allied and partner ministries of defense, this book is a case study of warfighting functions in the Naval Services—the U.S. Navy and U.S. Marine Corps. Sam J. Tangredi and George Galdorisi bring together over thirty experts, ranging from former DOD officials and retired flag officers to scientists and active duty junior officers. These contributors present views on a vast spectrum of subjects pertaining to the implementation of AI in modern warfare, including strategy, policy, doctrine, weapons, and ethical concerns.
