Authors: George Rajna
As part of a team of scientists from IBM and New York University, my colleagues and I are looking at new ways AI could be used to help ophthalmologists and optometrists further utilize eye images, and potentially help to speed the process for detecting glaucoma in images.  A team of EPFL scientists has now written a machine-learning program that can predict, in record time, how atoms will respond to an applied magnetic field.  Researchers from the University of Luxembourg, Technische Universität Berlin, and the Fritz Haber Institute of the Max Planck Society have combined machine learning and quantum mechanics to predict the dynamics and atomic interactions in molecules.  For the first time, physicists have demonstrated that machine learning can reconstruct a quantum system based on relatively few experimental measurements.  AlphaZero plays very unusually; not like a human, but also not like a typical computer. Instead, it plays with "real artificial" intelligence.  Predictions for an AI-dominated future are increasingly common, but Antoine Blondeau has experience in reading, and arguably manipulating, the runes—he helped develop technology that evolved into predictive texting and Apple's Siri.  Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology.  Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test.  A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning.  Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations.  Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. 
Comments: 52 Pages.
[v1] 2018-10-31 08:51:54
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