Google Is Already Late to China’s AI Revolution

#Google Is Already Late to China’s #AI Revolution  via @WIRED #machinelearning

  • Deep learning and related technologies are fundamentally changing the way Google works, and they will change so many other companies—even entire industries—over the next several years.
  • But many others have embraced deep learning in big ways, including the largest internet companies in China.
  • These included Jeff Dean, the head of the Google Brain AI lab, and Jia Li, who helps oversees artificial intelligence across the company’s increasingly important cloud computing services.
  • Like the company’s other online services, the Google cloud isn’t available in China.
  • And despite what Schmidt implied, Chinese companies like Baidu and Tencent are already starting to offer machine learning tools atop its own cloud computing services.

Google wants to spread its AI revolution to China. But the revolution has already arrived.
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Why Google’s CEO Is Excited About Automating Artificial Intelligence

Google’s CEO is excited about seeing #AI take over some work of his AI experts

  • Sundar Pichai at the company’s annual developer conference in Mountain View, experts are in short supply as companies in many industries rush to take advantage of recent strides in the power of artificial intelligence.
  • At Google’s annual developer conference today, Pichai introduced a project called AutoML coming out of the company’s Google Brain artificial intelligence research group.
  • The company is trying to lure new customers in the corporate cloud computing market, where it lags leader Amazon and second-place Microsoft (see “Google Reveals Powerful New AI Chip and is targeted at making it easier to use a technique called deep learning, which Google and others use to power speech and image recognition, translation, and robotics (see “10 Breakthrough Technologies 2013: Deep Learning”).
  • “We do it by intuition,” says Quoc Le, a machine-learning researcher at Google working on the AutoML project.Last month, Le and fellow researcher Barret Zoph presented results from experiments in which they tasked a machine-learning system with figuring out the best architecture to use to have software learn to solve language and image-recognition tasks.On the image task, their system rivaled the best architectures designed by human experts.
  • But like many ideas in the field of artificial intelligence, the power of deep learning is allowing new progress.

AI software that can help make AI software could accelerate progress on making computers smarter.
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