Authors: George Rajna
Neural networks learn to perform computational tasks by analyzing large sets of training data. But once they've been trained, even their designers rarely have any idea what data elements they're processing.  Researchers from Disney Research, Pixar Animation Studios, and the University of California, Santa Barbara have developed a new technology based on artificial intelligence (AI) and deep learning that eliminates this noise and thereby enables production-quality rendering at much faster speeds.  Now, one group reports in ACS Nano that they have developed an artificial synapse capable of simulating a fundamental function of our nervous system— the release of inhibitory and stimulatory signals from the same "pre-synaptic" terminal.  Researchers from France and the University of Arkansas have created an artificial synapse capable of autonomous learning, a component of artificial intelligence.  Intelligent machines of the future will help restore memory, mind your children, fetch your coffee and even care for aging parents.  Unlike experimental neuroscientists who deal with real-life neurons, computational neuroscientists use model simulations to investigate how the brain functions.  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.  A team of researchers working at the University of California (and one from Stony Brook University) has for the first time created a neural-network chip
Comments: 33 Pages.
[v1] 2017-07-01 04:24:01
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