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Pedro Domingos

The Master Algorithm

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Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. And in the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.Machine learning is the automation of discovery—the scientific method on steroids—that enables intelligent robots and computers to program themselves. No field of science today is more important yet more shrouded in mystery. Pedro Domingos, one of the field's leading lights, lifts the veil for the first time to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He charts a course through machine…
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478 printed pages

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Quotes

  • Maureen -has quoted5 years ago
    every 1 percent improvement in click prediction potentially means another half billion dollars in the bank, every year,
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    • Григорий Бhas quoted6 years ago
      Minsky’s theory of intelligence, as expressed in his book The Society of Mind, could be unkindly characterized as “the mind is just one damn thing after another.” The Society of Mind is a laundry list of hundreds of separate ideas, each with its own vignette. The problem with this approach to AI is that it doesn’t work; it’s stamp collecting by computer. Without machine learning, the number of ideas needed to build an intelligent agent is infinite. If a robot had all the same capabilities as a human except learning, the human would soon leave it in the dust.
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      • Григорий Бhas quoted6 years ago
        In the early days of AI, machine learning seemed like the obvious path to computers with humanlike intelligence; Turing and others thought it was the only plausible path. But then the knowledge engineers struck back, and by 1970 machine learning was firmly on the back burner.
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