Authors: George Rajna
We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment.  It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI.  Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services.  Microsoft on Wednesday unveiled new tools intended to democratize artificial intelligence by enabling machine smarts to be built into software from smartphone games to factory floors.  The closer we can get a machine translation to be on par with expert human translation, the happier lots of people struggling with translations will be.  Researchers have created a large, open source database to support the development of robot activities based on natural language input.  A pair of physicists with ETH Zurich has developed a way to use an artificial neural network to characterize the wave function of a quantum many-body system.  A team of researchers at Google's DeepMind Technologies has been working on a means to increase the capabilities of computers by combining aspects of data processing and artificial intelligence and have come up with what they are calling a differentiable neural computer (DNC.) In their paper published in the journal Nature, they describe the work they are doing and where they believe it is headed. To make the work more accessible to the public team members, Alexander Graves and Greg Wayne have posted an explanatory page on the DeepMind website.  Nobody understands why deep neural networks are so good at solving complex problems. Now physicists say the secret is buried in the laws of physics. 
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[v1] 2017-05-25 03:53:34
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