The fundamental questions are answered, leaving only the details to be filled in. In this book, Dr Rupert Sheldrake, one of the world's most innovative scientists, shows that science is being constricted by assumptions that have hardened into dogmas. The 'scientific worldview' has become a belief system. All reality is material or physical. The world is a machine, made up of dead matter. Nature is purposeless. Consciousness is nothing but the physical activity of the brain. Free will is an illusion. God exists only as an idea in human minds, imprisoned within our skulls. Sheldrake examines these dogmas scientifically, and shows persuasively that science would be better off without them: freer, more interesting, and more fun.In The God Delusion Richard Dawkins used science to bash God, but here Rupert Sheldrake shows that Dawkins' understanding of what science can do is old-fashioned and itself a delusion.

    Yet consciousness is subjective, personal, and famously difficult to examine: philosophers have for centuries declared this mental entity so mysterious as to be impenetrable to science.In The Ravenous Brain, neuroscientist Daniel Bor departs sharply from this historical view, and builds on the latest research to propose a new model for how consciousness works. Bor argues that this brain-based faculty evolved as an accelerated knowledge gathering tool. Consciousness is effectively an idea factory -- that choice mental space dedicated to innovation, a key component of which is the discovery of deep structures within the contents of our awareness.This model explains our brains"; ravenous appetite for information -- and in particular, its constant search for patterns. Why, for instance, after all our physical needs have been met, do we recreationally solve crossword or Sudoku puzzles? Such behavior may appear biologically wasteful, but, according to Bor, this search for structure can yield immense evolutionary benefits -- it led our ancestors to discover fire and farming, pushed modern society to forge ahead in science and technology, and guides each one of us to understand and control the world around us. But the sheer innovative power of human consciousness carries with it the heavy cost of mental fragility.Bor discusses the medical implications of his theory of consciousness, and what it means for the origins and treatment of psychiatric ailments, including attention-deficit disorder, schizophrenia, manic depression, and autism. All mental illnesses, he argues, can be reformulated as disorders of consciousness -- a perspective that opens up new avenues of treatment for alleviating mental suffering.A controversial view of consciousness, The Ravenous Brain links cognition to creativity in an ingenious solution to one of science's biggest mysteries.

    In 'how brains think' a leading neurophysiologist - drawing on anthropology, evolutionary biology, linguistics and the neurosciences - argues that consciousness is a result of evolution.

    These cells, later dubbed mirror neurons, responded equally well during the monkey’s own motor actions, such as grabbing an object, and while the monkey watched someone else perform similar motor actions. Researchers speculated that the neurons allowed the monkey to understand others by simulating their actions in its own brain.Mirror neurons soon jumped species and took human neuroscience and psychology by storm. In the late 1990s theorists showed how the cells provided an elegantly simple new way to explain the evolution of language, the development of human empathy, and the neural foundation of autism. In the years that followed, a stream of scientific studies implicated mirror neurons in everything from schizophrenia and drug abuse to sexual orientation and contagious yawning.In The Myth of Mirror Neurons, neuroscientist Gregory Hickok reexamines the mirror neuron story and finds that it is built on a tenuous foundation—a pair of codependent assumptions about mirror neuron activity and human understanding. Drawing on a broad range of observations from work on animal behavior, modern neuroimaging, neurological disorders, and more, Hickok argues that the foundational assumptions fall flat in light of the facts. He then explores alternative explanations of mirror neuron function while illuminating crucial questions about human cognition and brain function: Why do humans imitate so prodigiously? How different are the left and right hemispheres of the brain? Why do we have two visual systems? Do we need to be able to talk to understand speech? What’s going wrong in autism? Can humans read minds?The Myth of Mirror Neurons not only delivers an instructive tale about the course of scientific progress—from discovery to theory to revision—but also provides deep insights into the organization and function of the human brain and the nature of communication and cognition.

    With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Pulitzer prize-winning New York Times science writer John Markoff argues that we must decide to design ourselves into our future, or risk being excluded from it altogether.In the past decade, Google introduced us to driverless cars; Apple debuted Siri, a personal assistant that we keep in our pockets; and an Internet of Things connected the smaller tasks of everyday life to the farthest reaches of the Web. Robots have become an integral part of society on the battlefield and the road; in business, education, and health care. Cheap sensors and powerful computers will ensure that in the coming years, these robots will act on their own. This new era offers the promise of immensely powerful machines, but it also reframes a question first raised more than half a century ago, when the intelligent machine was born. Will we control these systems, or will they control us?In Machines of Loving Grace, John Markoff offers a sweeping history of the complicated and evolving relationship between humans and computers. In recent years, the pace of technological change has accelerated dramatically, posing an ethical quandary. If humans delegate decisions to machines, who will be responsible for the consequences? As Markoff chronicles the history of automation, from the birth of the artificial intelligence and intelligence augmentation communities in the 1950s and 1960s, to the modern-day brain trusts at Google and Apple in Silicon Valley, and on to the expanding robotics economy around Boston, he traces the different ways developers have addressed this fundamental problem and urges them to carefully consider the consequences of their work. We are on the brink of the next stage of the computer revolution, Markoff argues, and robots will profoundly transform modern life. Yet it remains for us to determine whether this new world will be a utopia. Moreover, it is now incumbent upon the designers of these robots to draw a bright line between what is human and what is machine.After nearly forty years covering the tech industry, Markoff offers an unmatched perspective on the most drastic technology-driven societal shifts since the introduction of the Internet. Machines of Loving Grace draws on an extensive array of research and interviews to present an eye-opening history of one of the most pressing questions of our time, and urges us to remember that we still have the opportunity to design ourselves into the future—before it's too late.

    But the very existence of consciousness raises profound questions: Why would any collection of matter in the universe be conscious? How are we able to think about this? And why should we?In this wonderfully accessible book, Annaka Harris guides us through the evolving definitions, philosophies, and scientific findings that probe our limited understanding of consciousness. Where does it reside, and what gives rise to it? Could it be an illusion, or a universal property of all matter? As we try to understand consciousness, we must grapple with how to define it and, in the age of artificial intelligence, who or what might possess it. Conscious offers lively and challenging arguments that alter our ideas about consciousness—allowing us to think freely about it for ourselves, if indeed we can.

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.