How do you begin to write an art history and what are the vital questions to ask? Which marks are most prominent in the visual culture of a particular place, and which are nearly invisible? In Future Possible (a riff on an Andy Jones monologue about how Newfoundlanders talk about their future, an attitude which he describes as "Future possible, possibly horrible"), Mireille Eagan and writers and artists such as Heather Igloliorte, Lisa Moore, Andy Jones, and Craig Francis Power navigate the tangled histories and cultures of Newfoundland and Labrador to investigate the visual output and to write the narrative that it has created. The result is an ambitious volume, arising from a two-part exhibition of the same name at The Rooms, that provides a multi-vocal, multi-faceted history spanning pre- and post-Confederation Newfoundland. Lavishly illustrated with 180 images of art and objects from the province's visual history, Future Possible features essays by curators and artists on topics such as pre-Confederation art; contemporary art, craft, and Indigenous culture; and outsider and folk art. This intriguing volume places artifacts from the province's history and work by iconic Newfoundland and Labrador artists such as David Blackwood and Helen Parsons Shepherd in conversation with works by contemporary artists like Jordan Bennett and Kym Greeley. Together they explore how history is told and retold through objects and images and how these objects and images, and the power structures that preserve them, define an understanding of place.

An inquiry into the limits of the possible. Our problems on Jupiter, Mercury, Venus - conquering Time - transport in the future - overcoming gravity - communications across space - benevolent electronic brains. The range of this enthralling book is immense: from the re-making of the human mind to the vast reaches of the universe. Newly revised, even the remarkable events of the last decade have affected few of the exciting speculations by Arthur C. Clarke - a scientist whose expert and wide knowledge is matched only by his brilliant imagination.

Every queer person lives with the trauma of AIDS, and this plays out intergenerationally. Usually we hear about two generations—the first, coming of age in the era of gay liberation, and then watching entire circles of friends die of a mysterious illness as the government did nothing to intervene. And now we hear about younger people growing up with effective treatment and prevention available, unable to comprehend the magnitude of the loss. But there is another generation between these two, one that came of age in the midst of the epidemic with the belief that desire intrinsically led to death, and internalized this trauma as part of becoming queer. Between Certain Death and a Possible Future: Queer Writing on Growing up with the AIDS Crisis offers crucial stories from this missing generation in AIDS literature and cultural politics. This wide-ranging collection includes 36 personal essays on the ongoing and persistent impact of the HIV/AIDS crisis in queer lives. Here you will find an expansive range of perspectives on a specific generational story—essays that explore and explode conventional wisdom, while also providing a necessary bridge between experiences. These essays respond, with eloquence and incisiveness, to the question: How do we reckon with the trauma that continues to this day, and imagine a way out?

NEW YORK TIMES BESTSELLER • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE ECONOMIST “The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow.”—Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week’s meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters." In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.

The first hopeful book about climate change, The Future Earth shows readers how to reverse the short- and long-term effects of climate change over the next three decades. The basics of climate science are easy. We know it is entirely human-caused. Which means its solutions will be similarly human-led. In The Future Earth, leading climate change advocate and weather-related journalist Eric Holthaus (“the Rebel Nerd of Meteorology”—Rolling Stone) offers a radical vision of our future, specifically how to reverse the short- and long-term effects of climate change over the next three decades. Anchored by world-class reporting, interviews with futurists, climatologists, biologists, economists, and climate change activists, it shows what the world could look like if we implemented radical solutions on the scale of the crises we face. What could happen if we reduced carbon emissions by 50 percent in the next decade? What could living in a city look like in 2030? How could the world operate in 2040, if the proposed Green New Deal created a 100 percent net carbon-free economy in the United States? This is the book for anyone who feels overwhelmed by the current state of our environment. Hopeful and prophetic, The Future Earth invites us to imagine how we can reverse the effects of climate change in our own lifetime and encourages us to enter a deeper relationship with the earth as conscientious stewards and to re-affirm our commitment to one another in our shared humanity.

Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future epidemics? In this context, active learning, often referred to as human or expert-in-the-loop learning, becomes imperative, enabling machines to commence learning from day one with minimal labeled data. In unsupervised learning, the focus shifts toward constructing advanced machine learning models like deep structured networks that autonomously learn over time, with human or expert intervention only when errors occur and for limited data—a process we term mentoring. In the context of Covid-19, this book explores the use of deep features to classify data into two clusters (0/1: Covid-19/non-Covid-19) across three distinct datasets: cough sound, Computed Tomography (CT) scan, and chest x-ray (CXR). Not to be confused, our primary objective is to provide a strong assertion on how active learning could potentially be used to predict disease from any upcoming epidemics. Upon request (education/training purpose), GitHub source codes are provided.