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How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.
Making a Machine That Sees Like Us explains why and how our visual perceptions can provide us with an accurate representation of the external world. Along the way, it tells the story of a machine (a computational model) built by the authors that solves the computationally difficult problem of seeing the way humans do. This accomplishment required a radical paradigm shift - one that challenged preconceptions about visual perception and tested the limits of human behavior-modeling for practical application. The text balances scientific sophistication and compelling storytelling, making it accessible to both technical and general readers. Online demonstrations and references to the authors' previously published papers detail how the machine was developed and what drove the ideas needed to make it work. The authors contextualize their new theory of shape perception by highlighting criticisms and opposing theories, offering readers a fascinating account not only of their revolutionary results, but of the scientific process that guided the way.
An authority on creativity introduces us to AI-powered computers that are creating art, literature, and music that may well surpass the creations of humans. Today's computers are composing music that sounds “more Bach than Bach,” turning photographs into paintings in the style of Van Gogh's Starry Night, and even writing screenplays. But are computers truly creative—or are they merely tools to be used by musicians, artists, and writers? In this book, Arthur I. Miller takes us on a tour of creativity in the age of machines. Miller, an authority on creativity, identifies the key factors essential to the creative process, from “the need for introspection” to “the ability to discover the key problem.” He talks to people on the cutting edge of artificial intelligence, encountering computers that mimic the brain and machines that have defeated champions in chess, Jeopardy!, and Go. In the central part of the book, Miller explores the riches of computer-created art, introducing us to artists and computer scientists who have, among much else, unleashed an artificial neural network to create a nightmarish, multi-eyed dog-cat; taught AI to imagine; developed a robot that paints; created algorithms for poetry; and produced the world's first computer-composed musical, Beyond the Fence, staged by Android Lloyd Webber and friends. But, Miller writes, in order to be truly creative, machines will need to step into the world. He probes the nature of consciousness and speaks to researchers trying to develop emotions and consciousness in computers. Miller argues that computers can already be as creative as humans—and someday will surpass us. But this is not a dystopian account; Miller celebrates the creative possibilities of artificial intelligence in art, music, and literature.
From the Booker Prize winner and bestselling author of Atonement—”a sharply intelligent novel of ideas” (The New York Times) that asks whether a machine can understand the human heart, or whether we are the ones who lack understanding. Set in an uncanny alternative 1982 London—where Britain has lost the Falklands War, Margaret Thatcher battles Tony Benn for power, and Alan Turing achieves a breakthrough in artificial intelligence—Machines Like Me powerfully portrays two lovers who will be tested beyond their understanding. Charlie, drifting through life and dodging full-time employment, is in love with Miranda, a bright student who lives with a terrible secret. When Charlie comes into money, he buys Adam, one of the first generation of synthetic humans. With Miranda's assistance, he codesigns Adam's personality. The near-perfect human that emerges is beautiful, strong, and smart—and a love triangle soon forms. Ian McEwan's subversive, gripping novel poses fundamental questions: What makes us human—our outward deeds or our inner lives? Could a machine understand the human heart? This provocative and thrilling tale warns against the power to invent things beyond our control. Don’t miss Ian McEwan’s new novel, Lessons, coming in September!
NEW YORK TIMES BESTSELLER • Once in a great while, a book comes along that changes our view of the world. This magnificent novel from the Nobel laureate and author of Never Let Me Go is “an intriguing take on how artificial intelligence might play a role in our futures ... a poignant meditation on love and loneliness” (The Associated Press). • A GOOD MORNING AMERICA Book Club Pick! Here is the story of Klara, an Artificial Friend with outstanding observational qualities, who, from her place in the store, watches carefully the behavior of those who come in to browse, and of those who pass on the street outside. She remains hopeful that a customer will soon choose her. Klara and the Sun is a thrilling book that offers a look at our changing world through the eyes of an unforgettable narrator, and one that explores the fundamental question: what does it mean to love?
For Readers of Ray Kurzweil and Michio Kaku, a New Look at the Cutting Edge of Artificial Intelligence Imagine a robotic stuffed animal that can read and respond to a child’s emotional state, a commercial that can recognize and change based on a customer’s facial expression, or a company that can actually create feelings as though a person were experiencing them naturally. Heart of the Machine explores the next giant step in the relationship between humans and technology: the ability of computers to recognize, respond to, and even replicate emotions. Computers have long been integral to our lives, and their advances continue at an exponential rate. Many believe that artificial intelligence equal or superior to human intelligence will happen in the not-too-distance future; some even think machine consciousness will follow. Futurist Richard Yonck argues that emotion, the first, most basic, and most natural form of communication, is at the heart of how we will soon work with and use computers. Instilling emotions into computers is the next leap in our centuries-old obsession with creating machines that replicate humans. But for every benefit this progress may bring to our lives, there is a possible pitfall. Emotion recognition could lead to advanced surveillance, and the same technology that can manipulate our feelings could become a method of mass control. And, as shown in movies like Her and Ex Machina, our society already holds a deep-seated anxiety about what might happen if machines could actually feel and break free from our control. Heart of the Machine is an exploration of the new and inevitable ways in which mankind and technology will interact. The paperback edition has a new foreword by Rana el Kaliouby, PhD, a pioneer in artificial emotional intelligence, as well as the cofounder and CEO of Affectiva, the acclaimed AI startup spun off from the MIT Media Lab.
The fascinating story behind the machines that trade trillions of dollars every day “A Bildungsroman, one jacket blurb calls this book—and sure, it’s a traditional coming-of-age tale. But the story itself is anything but conventional. The pleasures of the book lie in the story of their bumpy path to success.” Canadian Business In 1968, Michael Goodkin is about to graduate from Columbia University. While his classmates interview for jobs, he daydreams of seeing the world as a man of independent means. Noticing that there are no computers on Wall Street and drawing on his experiences as a failed teenage investor and successful gambler, he has an epiphany: since no one knows the right price for anything, the only way to beat the market is to make a computer that comes up with the wrong answer faster than the professionals. And thus begins a journey that takes this provincial Midwesterner from nearly broke to opulent Park Avenue. The Wrong Answer Faster is the story of unintended consequences: how a technique originally created to minimize market risk spiraled into a multi-trillion dollar game with unparalleled risks. Having founded and sold a firm that changed the world, Goodkin left New York to travel and play backgammon—only to return to found another groundbreaking firm, Numerix, a software company that substituted computational physics for econometrics to better manage derivative risk. The story of the computerization of Wall Street by the man at the helm Packed with keen insights, based almost entirely on poker, backgammon and game theory Goodkin's unique insight to the markets is that everyone has the wrong answers The solution is not to try to beat the market but to come up with the wrong answers faster The epic tale of the untold story how one man with a great idea decided not to play the market but to revolutionize the financial world for generations to come by creating the most ground breaking tool for market players since the ticker tape.
A haunting story of guilt and blame in the wake of a drowning, the first novel by the author of Spectacle Susan Steinberg’s first novel, Machine, is a dazzling and innovative leap forward for a writer whose most recent book, Spectacle, gained her a rapturous following. Machine revolves around a group of teenagers—both locals and wealthy out-of-towners—during a single summer at the shore. Steinberg captures the pressures and demands of this world in a voice that effortlessly slides from collective to singular, as one girl recounts a night on which another girl drowned. Hoping to assuage her guilt and evade a similar fate, she pieces together the details of this tragedy, as well as the breakdown of her own family, and learns that no one, not even she, is blameless. A daring stylist, Steinberg contrasts semicolon-studded sentences with short lines that race down the page. This restless approach gains focus and power through a sharply drawn narrative that ferociously interrogates gender, class, privilege, and the disintegration of identity in the shadow of trauma. Machine is the kind of novel—relentless and bold—that only Susan Steinberg could have written.
Inspired by a brother's high school science project--a perpetual motion machine that could save the world-- The Perpetual Motion Machine is a memoir in essays that attempts to save a sibling by depicting the visceral pain that accompanies longing for some past impossibility. The collection has been a science project in its study of memory, in the calculation and plotting of the moments that make up a childhood. The preparation has been "in the field" in that it is built upon the gathering of lived experience; the evidence is photo albums, family interviews, and anecdotes from friends. The project has been one giant experiment--to see if they can all make it out alive.