en
Erik Brynjolfsson,Harvard Business Review,Thomas H. Davenport,Andrew McAfee,H. James Wilson

Artificial Intelligence

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Companies that don't use AI will soon be obsolete.
From making faster, better decisions to automating rote work to enabling robots to respond to emotions, AI and machine learning are already reshaping business and society. What should you and your company be doing today to ensure that you're poised for success and keeping up with your competitors in the age of AI?
Artificial Intelligence: The Insights You Need from Harvard Business Review brings you today's most essential thinking on AI and explains how to launch the right initiatives at your company to capitalize on the opportunity of the machine intelligence revolution.
Business is changing. Will you adapt or be left behind?
Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues--blockchain, cybersecurity, AI, and more--each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.
Эта книга сейчас недоступна
131 бумажная страница
Дата публикации оригинала
2019
Год выхода издания
2019
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Впечатления

  • Chiefделится впечатлением3 года назад
    👍Worth reading
    🔮Hidden Depths
    💡Learnt A Lot
    🎯Worthwhile
    🚀Unputdownable

Цитаты

  • Chiefцитирует3 года назад
    Though all of these advances are relatively recent, they hark back to the very beginnings of AI in the 1950s, when a number of researchers began to pursue top-down models for mimicking human intelligence. But when progress proved elusive and the rich potential for bottom-up machine learning methods became apparent, the top-down approach was largely abandoned. Today, however, through powerful new research and computational techniques, top-down AI has been reborn. As its great promise begins to be fulfilled, smart companies will put their money where the mind is.

    TAKEAWAYS

    As AI develops, it will rely less on bottom-up big data and more on top-down reasoning that resembles the way humans approach problems and tasks. This will enable us to apply AI more broadly
  • Chiefцитирует3 года назад
    Humans routinely, and often effortlessly, sort through probabilities and act on the likeliest, even with relatively little prior experience. Machines are now being taught to mimic such reasoning through the application of Gaussian processes—probabilistic models that can deal with extensive uncertainty, act on sparse data, and learn from experience. Alphabet, Google’s parent company,
  • Chiefцитирует3 года назад
    broadly applied than ever, creating opportunities for early adopters even in businesses and activities to which it previously seemed unsuited.

    In the recent past, AI advanced through deep learning and machine learning, building up systems from the bottom by training them on mountains of data. For instance, driverless vehicles are trained on as many traffic situations as possible. But these data-hungry neural networks, as they are called, have serious limitations. They especially have trouble handling “edge” cases—situations where little data exists. A driverless car that can handle crosswalks, pedestrians, and traffic has trouble processing anomalies like children dressed in unusual Halloween costumes, weaving across the street after dusk.

    Many systems are also easily stumped. The iPhone X’s facial recognition system doesn’t recognize “morning faces”—a user’s

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