At its simplest, Bayes’s theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes’s theorem is a description of almost everything. But who was the man who lent his name to this theorem?

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.

Confused about AI and worried about what it means for your future and the future of the world? You’re not alone. AI is everywhere—and few things are surrounded by so much hype, misinformation, and misunderstanding. In AI Snake Oil, computer scientists Arvind Narayanan and Sayash Kapoor cut through the confusion to give you an essential understanding of how AI works, why it often doesn’t, where it might be useful or harmful, and when you should suspect that companies are using AI hype to sell AI snake oil—products that don’t work, and probably never will.

Nvidia is the darling of the age of artificial intelligence: the company’s chips are powering the generative-AI revolution, and demand is insatiable. For all the current interest and attention, however, Nvidia is not of our time. Founded more than three decades ago in a Denny’s in East San Jose, for years it was known primarily in the then-niche world of computer gaming. In fact, the company’s leather-jacketed leader, Jensen Huang, is the longest-serving CEO in an industry marked by near constant turmoil and failure.

Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence - and even more so if we hope to participate in the future, rather than being simple bystanders.

From Oxford's leading AI researcher comes a fun and accessible tour through the history and future of one of the most cutting edge and misunderstood field in science: artificial intelligence.

Equal parts Sapiens, Behave, and Superintelligence, but wholly original in scope, A Brief History of Intelligence offers a paradigm shift for how we understand neuroscience and AI. Artificial intelligence entrepreneur Max Bennett chronicles the five “breakthroughs” in the evolution of human intelligence and reveals what brains of the past can tell us about the AI of tomorrow.

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.

What is life? This is among the most difficult open problems in science, right up there with the nature of consciousness and the existence of matter. All the definitions we have fall short. None help us understand how life originates or the full range of possibilities for what life on other planets might look like. In Life as No One Knows It, physicist and astrobiologist Sara Imari Walker argues that solving the origin of life requires radical new thinking and an experimentally testable theory for what life is.

Dip below the ocean’s surface and you are soon confronted by forms of life that could not seem more foreign to our own: sea sponges, soft corals, and serpulid worms, whose rooted bodies, intricate geometry, and flower-like appendages are more reminiscent of plant life or even architecture than anything recognizably animal. Yet these creatures are our cousins. As fellow members of the animal kingdom — the Metazoa— they can teach us much about the evolutionary origins of not only our bodies, but also our minds.

With the appearance of Grunch of Giants, R. Buckminster Fuller consummates his literary canon, his panoramic lifetime survey of all aspects of the responsibility of human beings for their own destiny. This book is a modern allegory - his long-gestated myth-of the villainy of capitalism and the fecklessness of classic economics. For Fuller, the academic discipline of economics is irrelevant since it derives from an invalid assumption of scarcity.

This is a practical, non-technical guide for business leaders, entrepreneurs, and curious minds. This comprehensive guide on agentic AI cuts through the hype and offers a clear, jargon-free strategic roadmap to understanding and applying this technology. The authors bring a rare perspective, having implemented agentic AI across diverse organizations—from global enterprises to agile startups—witnessing both remarkable successes and sobering failures.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

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.

A gripping journey of discovery, The Catalyst moves from the early experiments that first hinted at RNA's spectacular powers, to Cech's own paradigm-shifting finding that it can catalyze cellular reactions, to the cutting-edge biotechnologies poised to reshape our health.

The intellectual adventure story of the "double-slit" experiment, showing how a sunbeam split into two paths first challenged our understanding of light and then the nature of reality itself - and continues to almost 200 years later. Through Two Doors at Once celebrates the elegant simplicity of an iconic experiment and its profound reach. With his extraordinarily gifted eloquence, Anil Ananthaswamy travels around the world, through history and down to the smallest scales of physical reality we have yet fathomed. It is the most fantastic voyage you can take.

At its simplest, Bayes’s theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes’s theorem is a description of almost everything. But who was the man who lent his name to this theorem?

In the tradition of Oliver Sacks, a tour of the latest neuroscience of schizophrenia, autism, Alzheimer’s disease, ecstatic epilepsy, Cotard’s syndrome, out-of-body experiences, and other disorders - revealing the awesome power of the human sense of self from a master of science journalism. Anil Ananthaswamy’s extensive in-depth interviews venture into the lives of individuals who offer perspectives that will change how you think about who you are.

In this deeply original book, science writer Anil Ananthaswamy sets out in search of the telescopes and detectors that promise to answer the biggest questions in modern cosmology. Why is the universe expanding at an ever faster rate? What is the nature of the "dark matter" that makes up almost a quarter of the universe? Why does the universe appear fine-tuned for life? Are there others besides our own?

How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in AI strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network? As Peter Robin Hiesinger argues, "the information problem" underlies both fields.

All his life, David has been afflicted by a strange and uncomfortable feeling: that his leg belongs to somebody else. It's left him angst-ridden, depressed and confused - and after years of torment, the only way he can think to is to get rid of it completely. In this disturbing, award-winning investigation from the science and technology publisher MATTER, acclaimed writer Anil Ananthaswamy delves accompanies one man as he travels the world to get the illicit surgery he craves.

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 Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

Unlock the Secrets of AI Deep Learning and Neural Networks: Empower Your Future in Minutes a Day! Ready to dive into the world of artificial intelligence, but don’t know where to start? Whether you're a student, developer, or curious learner, this book takes you on a journey to master deep learning concepts, demystify neural networks, and transform your skills into real-world impact—all at your own pace.

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.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.

Confused about AI and worried about what it means for your future and the future of the world? You’re not alone. AI is everywhere—and few things are surrounded by so much hype, misinformation, and misunderstanding. In AI Snake Oil, computer scientists Arvind Narayanan and Sayash Kapoor cut through the confusion to give you an essential understanding of how AI works, why it often doesn’t, where it might be useful or harmful, and when you should suspect that companies are using AI hype to sell AI snake oil—products that don’t work, and probably never will.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.