The Book of Why
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The Book of Why

Original price was: $15.00.Current price is: $4.50.

SKU: 10300936487217 Category:

Description

Self-help writer Eric Newborn’s motivational books have spawned a legion of devoted followers who swear that his ideas have pulled their lives from the brink. But after Eric can’t save his own wife from dying, he finds himself at a loss — the power of positive thinking is simply not enough to overcome his grief. Retreating to the home he and his wife shared on Martha’s Vineyard, Eric, with his dog as his closest companion, attempts to distance himself from the teachings he has come to hate.

But when a woman named Sam shows up at his door one night five years later, Eric must finally confront his heartache and reconcile his worldview with the pain he has suffered.

At once a powerful love story, a stirring portrait of a soul laid bare by grief, and a celebration of coincidence, connection, and the belief that true love never dies, The Book of Why explores the deep powers of the heart and mind to shape the world around us, blurring the lines between loss and love, fate and free will, despair and joy.

“This is a haunting and extraordinary book.” — Julie Orringer, author of The Invisible Bridge

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Sale!

The Book of Why

Original price was: $22.99.Current price is: $6.89.

SKU: 10578266161457 Category:

Description

The “extraordinary” (
Science Friday

), “illuminating” (
New York Times

) argument for how understanding causality has revolutionized science and will revolutionize artificial intelligence 

“Correlation is not causation.” This mantra, chanted by scientists for more than a century, once led to a virtual prohibition on causal talk. Today, with causal analysis taking center stage in AI and other applications, the old taboos are a thing of the past.

The causal revolution, instigated by Judea Pearl and others, established causality on a firm scientific basis.  Pearl showed how intuitive models can interface with data to help answer causal questions, such as whether a drug will cure an illness or, counterfactually, whether an illness would have persisted absent the drug. These models provide a blueprint for causal AI to learn and take responsibility for its mistakes.

Updated with a new preface and summary of recent advances, The Book of Why outlines the basics of cause and effect for lay readers and scientists alike, providing tools to explore the observable world and worlds that might have been.

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