There is a robotics revolution underway. A record 3.1 million robots are working in factories right now, doing everything from assembling computers to packing goods and monitoring air quality and performance. A far greater number of smart machines impact our lives in countless other ways—improving the precision of surgeons, cleaning our homes, extending our reach to distant worlds—and we’re on the cusp of even more exciting opportunities.

When you put learning at the center of everything you do, you grow your career, your leadership, your relationships, and your joy and fulfillment in life. But even for people who are naturally curious and interested in solving problems, being an effective learner who can turn their learning into action takes insight and practice. With infectious enthusiasm and optimism, David Novak shows you how to master active learning.

As it absorbs data, gains agency, and intermediates between humans and reality, AI will help us to address enormous crises, from climate change to geopolitical conflicts to income inequality. It might well solve some of the greatest mysteries of our universe, revolutionize fields as diverse as medicine and architecture, and elevate the human spirit to unimaginable heights. But it will also pose challenges on a scale and of an intensity that we have never seen.

In T-Minus AI: Humanity's Countdown to Artificial Intelligence and the New Pursuit of Global Power, author Michael Kanaan explains the realities of AI from a human-oriented perspective that's easy to comprehend. A recognized national expert and the U.S. Air Force's first Chairperson for Artificial Intelligence, Kanaan weaves a compelling new view on our history of innovation and technology to masterfully explain what each of us should know about modern computing, AI, and machine learning.

Artificial intelligence does the seemingly impossible - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

In this groundbreaking treatise, Palantir co-founder and CEO Alexander C. Karp and Nicholas W. Zamiska offer a searing critique of our collective abandonment of ambition, arguing that in order for the U.S. and its allies to retain their global edge—and preserve the freedoms we take for granted—the software industry must renew its commitment to addressing our most urgent challenges, including the new arms race of artificial intelligence. The government, in turn, must embrace the most effective features of the engineering mindset that has propelled Silicon Valley’s success.

From two of America’s most respected journalists, an unflinching and explosive reckoning with one of the most fateful decisions in American political history: Joe Biden’s run for reelection despite evidence of his serious decline—amid desperate efforts to hide the extent of that deterioration.

Something new entered our world in November 2022—the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on our own, humans had developed a kind of co-intelligence that could augment, or even replace, human thinking. Through his writing, speaking, and teaching, Mollick has become one of the most prominent and provocative explainers of AI.

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.