
"Genius Makers" unveils the maverick scientists who revolutionized AI at Google and Facebook. Walter Isaacson called it a "colorful page-turner" that humanizes tech's most transformative quest. What ethical price are we paying as Geoffrey Hinton's deep learning dreams reshape our world?
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In December 2012, a peculiar scene unfolded in Lake Tahoe. Geoff Hinton, a tall, distinguished AI researcher who hadn't sat down for seven years due to a back injury, found himself at the center of a high-stakes bidding war. Tech giants Google and Baidu were offering millions for his tiny company, DNNresearch. What made this three-person startup so valuable? Hinton and his students had achieved a breakthrough in neural networks that demonstrated unprecedented accuracy in image recognition-igniting what would become the deep learning revolution. This moment marked a dramatic turning point in artificial intelligence, but it was hardly the beginning of the story. The seeds had been planted decades earlier, in 1958, when Frank Rosenblatt unveiled the Perceptron-a machine heralded as an electronic brain capable of mimicking human cognition. "We are now on the threshold of an era that will be strongly influenced, and quite possibly dominated, by intelligent machines," Rosenblatt declared with remarkable prescience. But the Perceptron's abilities were vastly overstated, creating the first in a series of boom-and-bust cycles that would characterize AI's tumultuous history. The field soon split into competing camps: those who believed in brain-inspired neural networks versus those who favored rule-based symbolic AI. When Marvin Minsky published a devastating critique of the Perceptron's limitations, neural network research was effectively sidelined for nearly two decades-a technological road not taken that makes you wonder: how different might our world be if this approach hadn't been abandoned?
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Создано выпускниками Колумбийского университета в Сан-Франциско
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Создано выпускниками Колумбийского университета в Сан-Франциско

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