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    1. Modeling Gun Violence as a Contagion

      Modeling Gun Violence as a Contagion

      Modeling Gun Violence as a Contagion By Gregory Goth Researchers used machine learning to model the spread of gun violence in Chicago as a social contagion. Credit: Gary Waters/Getty Images Harvard University researcher Ben Green offers a succinct reason why his recent work addresses gun violence as a public health epidemic rather than as a matter strictly for law enforcement personnel "Certainly there is a role for police, though what we've seen is that you can't just arrest your way out of the problem of gun violence," Green, a doctoral student at Harvard, said. "And, notably, what ...

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    2. U.S. Intelligence Seeks a Universal Translator for Text Search in Any Language

      U.S. Intelligence Seeks a Universal Translator for Text Search in Any Language

      U.S. Intelligence Seeks a Universal Translator for Text Search in Any Language By Ars Technica The Machine Translation for English Retrieval of Information in Any Language program aims to give researchers and analysts a tool to help them search for documents in any of the more than 7,000 languages spoken worldwide.

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      Mentions: Iarpa
    3. Open Source Challenger Takes on Google Translate

      Open Source Challenger Takes on Google Translate

      Open Source Challenger Takes on Google Translate By InfoWorld A new machine translation framework developed by researchers at Harvard University and the company Systran could serve as an alternative to services such as Google Translate. Credit: CSO Staff A new open source machine translation framework could serve as an alternative to closed-source projects such as Google Translate.

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    4. Making Sense of Exabytes of Data at SC16

      Making Sense of Exabytes of Data at SC16

      Making Sense of Exabytes of Data at SC16 By Andrew Rosenbloom Katharine Frase. Credit: Inside HPC “Think about how you got here,” said Katharine Frase, formerly IBM CTO and more recently head of strategy and business development for IBM’s Watson Education unit, in her keynote at the SC16 (supercomputing) conference in Salt Lake City last week.

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    5. Google Translate: 'This Landmark Update Is Our Biggest Single Leap in 10 Years'

      Google Translate: 'This Landmark Update Is Our Biggest Single Leap in 10 Years'

      Share Google says it is has vastly improved the accuracy of Google Translate through its new Neural Machine Translation (NMT) system. NMT utilizes neural networks to train machines how to produce more natural, grammatically correct translations. The new system improves Google Translate's capacity for contextual translation by processing whole sentences or paragraphs at a time, rather than analyzing individual words.

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    6. Mobile App Behavior Often Appears at Odds With Privacy Policies

      Mobile App Behavior Often Appears at Odds With Privacy Policies

      Mobile App Behavior Often Appears at Odds With Privacy Policies By Carnegie Mellon University Share Mobile applications' privacy policies often are inconsistent with how an app actually collects and shares users' personal information, according to an automated analysis system developed by Carnegie Mellon University (CMU). Several federal and state laws require mobile apps to have privacy policies, but these policies can be incomplete or missing entirely.

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    7. Machines May Never Master the Distinctly Human Elements of Language

      Machines May Never Master the Distinctly Human Elements of Language

      Machines May Never Master the Distinctly Human Elements of Language By Quartz Artificial intelligence is difficult to develop because of the diffulty in learning and interpreting human language. Credit: Toru Hanai/Reuters Although Google's Neural Machine Translation system is able to produce translations that can sometimes match the accuracy of human translators, artificial intelligence (AI) might never be able to learn and completely understand human language.

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    8. Making Computers Explain Themselves

      Making Computers Explain Themselves

      Share In recent years, the best-performing systems in artificial-intelligence research have come courtesy of neural networks, which look for patterns in training data that yield useful predictions or classifications. A neural net might, for instance, be trained to recognize certain objects in digital images or to infer the topics of texts. But neural nets are black boxes. After training, a network may be very good at classifying data, but even its creators will have no idea why.

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    9. Cancer's Big Data Problem

      Cancer's Big Data Problem

      Share Data is pouring into the hands of cancer researchers, thanks to improvements in imaging, models, and understanding of genetics. Today the data from a single patient's tumor in a clinical trial can add up to one terabyte — the equivalent of 130,000 books. But we don't yet have the tools to efficiently process the mountain of genetic data to make more precise predictions for therapy. And it's needed: treating cancer remains a complex moving target.

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    10. Why Deep Learning Is Suddenly Changing Your Life

      Why Deep Learning Is Suddenly Changing Your Life

      Why Deep Learning Is Suddenly Changing Your Life By Fortune Recent breakthroughs have been made possible by a family of artificial intelligence techniques popularly known as deep learning, though most scientists still prefer to call them by their original academic designation: deep neural networks. Credit: Justin Metz Over the past four years, readers have doubtlessly noticed quantum leaps in the quality of a wide range of everyday technologies.

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    11. Google Translate Gets a Deep-Learning Upgrade

      Google Translate Gets a Deep-Learning Upgrade

      Google Translate Gets a Deep-Learning Upgrade By IEEE Spectrum Googles engineers recently delivered a Google Translate upgrade that harnesses the popular artificial intelligence technique known as deep learning. Credit: Yuki Mizuma Google has launched a Google Translate upgrade utilizing enhanced deep-learning techniques to produce more accurate translations. The neural machine translation system considers the entire sentence as one unit to be translated.

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    12. Researchers Want to Achieve Machine Translation of the 24 Languages of the EU

      Researchers Want to Achieve Machine Translation of the 24 Languages of the EU

      Researchers Want to Achieve Machine Translation of the 24 Languages of the EU By Saarland University Researchers are developing an automated system that will be able to translate between the languages of the European Union. Credit: blogs.apache.org Saarland University researchers are developing an automated system for translating between the languages of the European Union (EU) so comprehensible texts are achieved for as many language combinations as possible.

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    13. Reimagining search

      Reimagining search

      Share Ever since gerard salton of Cornell University developed the first computerized search engine (Salton's Magical Automatic Retriever of Text, or SMART) in the 1960s, search developers have spent decades essentially refining Salton's idea: take a query string, match it against a collection of documents, then calculate a set of relevant results and display them in a list.

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