1. Articles in category: Machine Translation

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    1. Reading a neural network’s mind | Mit News

      Reading a neural network’s mind | Mit News

      Login or Subscribe Newsletter Neural nets are so named because they roughly approximate the structure of the human brain. Typically, they’re arranged into layers, and each layer consists of many simple processing units — nodes — each of which is connected to several nodes in the layers above and below. Data is fed into the lowest layer, whose nodes process it and pass it to the next layer.

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    2. Artificial Intelligence still isn't a game changer

      Artificial Intelligence still isn't a game changer

      OPINION: Artificial Intelligence still isn't a game changer Opinion 00pm / Leonid Bershidsky Robots are advancing exponentially while human learning occurs at a much slower pace. Picture: Shutterstock INTERNATIONAL - Not much time passes these days between so-called major advancements in artificial intelligence. Yet researchers are not much closer than they were decades ago to the big goal: actually replicating human intelligence.

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      Mentions: China Google Russian
    3. Learn how to classify images with TensorFlow

      Learn how to classify images with TensorFlow

      Learn how to classify images with TensorFlow Learn how to classify images with TensorFlow Create a simple, yet powerful neural network to classify images using the open source TensorFlow software library. 08 Dec 2017 Adam Monsen Feed 7 Recent advancements in deep learning algorithms and hardware performance have enabled researchers and companies to make giant strides in areas such as image recognition, speech recognition, recommendation engines, and machine translation.

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      Mentions: Google Brain
    4. Machine Translation (MT) Market Research Report 2017

      Algoro Research Consultants Pvt. Ltd. - Friday, December 8, 2017. Machine Translation (MT) Market Research Report 2017

      Machine Translation (MT) in Global market, especially in North America, Europe, China, Japan, Latin America and India, focuses on top manufacturers in global market, with capacity, production, price, revenue and market share for each manufacturer, covering :AppTek

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      Mentions: Japan India China
    5. Deep Learning Scaling is Predictable, Empirically

      Deep Learning Scaling is Predictable, Empirically

      Deep Learning Scaling is Predictable, Empirically Deep Learning Scaling is Predictable, Empirically Our digital world and data are growing faster today than any time in the past—even faster than our computing power. Deep learning helps us quickly make sense of immense data, and offers users the best AI-powered products and experiences. To continually improve user experience, our challenge, then, is to quickly improve our deep learning models for existing and emerging application domains.

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    6. Electrical Steering Column Lock Market Size to See USD 31 Billion Worth by 2024: Growth Factors & Trends

      Electrical Steering Column Lock Market Size to See USD 31 Billion Worth by 2024: Growth Factors & Trends

      Electrical Steering Column Lock Market Size to See USD 31 Billion Worth by 2024: Growth Factors & Trends Press release from: marketstudyreport.com PR Agency: Market Study Report MarketStudyReport.com adds a new Electrical Steering Column Lock Market research report that provides a detailed market overview as well as industry analysis for / of companies, manufacturers and distributors covering data on gross margin, cost structure, consumption value, sale price and more.

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      Mentions: Japan Israel India
    7. Healthcare Natural Language Processing Market: Efforts to Reduce Incidental Errors Ensure Swift Uptake

      Healthcare Natural Language Processing Market: Efforts to Reduce Incidental Errors Ensure Swift Uptake

      Press release from: Transparency Market Research PR Agency: Transparency Market Research The top three players leading the pack in the global healthcare natural language processing market held a share of 41% in 2015. IBM Corporation, Apple, Inc., and Microsoft Corporation emerged as the leading players due to ongoing investments in research and development of NLP technologies for the healthcare sector.

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    8. Healthcare Natural Language Processing Market: Key Players, Growth, Analysis, 2016–2024

      Healthcare Natural Language Processing Market: Key Players, Growth, Analysis, 2016–2024 United States, 7 December 2017 -- Healthcare Natural Language Processing Market - Global Industry Analysis, Size, Share, Growth, Trends and Forecast 2016 – 2024The top three players leading the pack in the global healthcare natural language processing market held a share of 41% in 2015.

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    9. Lingotek Extends Access to Neural MT to 80K+ Connector Users

      Lingotek Extends Access to Neural MT to 80K+ Connector Users

      Lingotek Extends Access to Neural MT to 80K+ Connector Users Google, Microsoft and Lingotek Multilingual API users get superior translation with AI pattern recognition ET | Source: Lingotek LEHI, Utah, Lingotek | The Translation Network announced today that the company has expanded access to neural machine translation (NMT) to its vast network of Lingotek - Inside users. Users of Lingotek’s translation management system (TMS) already had access to both Microsoft’s and Google’s NMT engines.

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    10. Lingotek Extends Access to Neural MT to 80K+ Connector Users

      Lingotek Extends Access to Neural MT to 80K+ Connector Users [December 06, 2017] Lingotek Extends Access to Neural MT to 80K+ Connector Users LEHI, Utah, Dec. 06, 2017 (GLOBE NEWSWIRE) -- Lingotek | The Translation Network announced today that the company has expanded access to neural machine translation (NMT) to its vast network of Lingotek - Inside users. Users of Lingotek’s translation management system (TMS) already had access to both Microsoft’s and Google’s NMT engines.

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    11. Topic:U3859eguf9492njs

      The Wikipedia I write for (Simple English) prevents page creation from machine translation, and as such references are not copied to the target language. Until support is added for dynamically copying references, I suggest the following workaround: - Using the options gear next to "publish," set the destination to a personal draft. - Translate your article with placeholders for your reference (such as "[1]") - Publish the draft and edit the article again.

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      Mentions: FAQ
    12. SDL Selects Appian for Digital Transformation 12-06

      SDL Selects Appian for Digital Transformation 12-06

      12-06 13:33:01 Appian Automates and Digitizes SDL's Core Business; Streamlining Operations, Enhancing Integration, Restructuring Best Practices and Enabling Faster Decision Making RESTON, Va., Dec. 06, 2017 (GLOBE NEWSWIRE) -- Appian (NASDAQ:APPN), a leading Low-Code and Business Process Management platform provider, today announced SDL selected Appian to automate and digitize its core language services business in support of the company's digital transformation strategy.

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      Mentions: Reston SDL
    13. SDL Selects Appian for Digital Transformation

      SDL Selects Appian for Digital Transformation Appian Automates and Digitizes SDL's Core Business; Streamlining Operations, Enhancing Integration, Restructuring Best Practices and Enabling Faster Decision Making RESTON, Va., Dec. 06, 2017 (GLOBE NEWSWIRE) -- Appian (NASDAQ:APPN), a leading Low-Code and Business Process Management platform provider, today announced SDL selected Appian to automate and digitize its core language services business in support of the company's digital transformation strategy. Using Appian's low-code development platform in the cloud enables SDL to rapidly unify data from across systems and processes, and present them through a single intuitive interface, resulting in significant improvements ...

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      Mentions: Reston SDL
    14. SDL Selects Appian for Digital Transformation

      SDL Selects Appian for Digital Transformation

      Register Sign In SDL Selects Appian for Digital Transformation Appian Automates and Digitizes SDL’s Core Business; Streamlining Operations, Enhancing Integration, Restructuring Best Practices and Enabling Faster Decision Making December 06, 2017 07:30 ET | Source: Appian Corporation RESTON, Va., Appian (NASDAQ: APPN ), a leading Low-Code and Business Process Management platform provider, today announced SDL selected Appian to automate and digitize its core language services business in support of the company’s digital transformation strategy. Using Appian’s low-code development platform in the cloud enables SDL to rapidly unify data from across systems and processes, and present them through a ...

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      Mentions: Reston SDL
    15. Lingotek Extends Access to Neural MT to 80K+ Connector Users

      LEHI, Utah, Dec. 06, 2017 (GLOBE NEWSWIRE) -- Lingotek | The Translation Network announced today that the company has expanded access to neural machine translation (NMT) to its vast network of Lingotek - Inside users. Users of Lingotek’s translation management system (TMS) already had access to both Microsoft’s and Google’s NMT engines.

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    16. Appian Corporation: SDL Selects Appian for Digital Transformation

      Appian Corporation: SDL Selects Appian for Digital Transformation

      Appian Corporation: SDL Selects Appian for Digital Transformation Appian Automates and Digitizes SDL's Core Business; Streamlining Operations, Enhancing Integration, Restructuring Best Practices and Enabling Faster Decision Making RESTON, Va., 2017-12-06 13:30 CET (GLOBE NEWSWIRE) -- Appian (NASDAQ:APPN), a leadingLow-Code and Business Process Managementplatform provider, today announced SDL selected Appian to automate and digitize its core language services business in support of the company's digital transformation strategy. Using Appian's low-code development platform in the cloud enables SDL to rapidly unify data from across systems and processes, and present them through a single intuitive interface, resulting in significant ...

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      Mentions: Reston SDL
    17. SDL Selects Appian for Digital Transformation

      Appian Automates and Digitizes SDL's Core Business; Streamlining Operations, Enhancing Integration, Restructuring Best Practices and Enabling Faster Decision Making RESTON, Va., Dec. 06, 2017 (GLOBE NEWSWIRE) -- Appian (NASDAQ:APPN), a leading Low-Code and Business Process Management platform provider, today announced SDL selected Appian to automate and digitize its core language services business in support of the company's digital transformation strategy.

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      Mentions: Reston SDL
    18. SDL Selects Appian for Digital Transformation

      SDL Selects Appian for Digital Transformation

      | 06.12.2017, 13:30 | 72 | 0 | 0 Appian Automates and Digitizes SDL's Core Business; Streamlining Operations, Enhancing Integration, Restructuring Best Practices and Enabling Faster Decision Making RESTON, Va., Dec. 06, 2017 (GLOBE NEWSWIRE) -- Appian (NASDAQ:APPN), a leading Low-Code and Business Process Management platform provider, today announced SDL selected Appian to automate and digitize its core language services business in support of the company's digital transformation strategy.

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      Mentions: Reston SDL
    19. Chinese search engine Sogou takes on Google in complex language processing for AI

      Chinese search engine Sogou takes on Google in complex language processing for AI

      Artificial intelligence Chinese search engine Sogou takes on Google in complex language processing for AI China’s second largest search engine raised US$585 million in New York IPO in November, but is in no hurry to make money, says CEO PUBLISHED : Wednesday, 06 December, 2017, 6:43am UPDATED : Wednesday, 06 December, 2017, 6:57am China’s Airbnb to introduce check-ins using facial recognition 4 Dec 2017 Chinese search engine Sogou is focused on perfecting the language processing skills seen as a key step towards broader artificial intelligence applications – even if that means going head to head with US leader ...

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    20. IBM’s new A.I. predicts chemical reactions, could revolutionize drug development

      IBM’s new A.I. predicts chemical reactions, could revolutionize drug development

      IBM’s new A.I. predicts chemical reactions, could revolutionize drug development Luke Dormehl Subscribe on YouTube From building the Deep Blue computer that beat Garry Kasparov at chess to the Watson artificial intelligence (A.I.) that won Jeopardy , IBM has been responsible for some high-profile public demonstrations of A.I. in action. Its latest showcase is less high concept, but potentially far more transformative — applying machine learning technology to the subject of organic chemistry.

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    21. IBM’s new A.I. predicts chemical reactions, could revolutionize drug development

      IBM’s new A.I. predicts chemical reactions, could revolutionize drug development

      Subscribe on YouTube From building the Deep Blue computer that beat Garry Kasparov at chess to the Watson artificial intelligence (A.I.) that won Jeopardy , IBM has been responsible for some high-profile public demonstrations of A.I. in action. Its latest showcase is less high concept, but potentially far more transformative — applying machine learning technology to the subject of organic chemistry. As described in a new research paper , the A.I.

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    22. IBM’s new A.I. predicts chemical reactions, could revolutionize drug development

      IBM’s new A.I. predicts chemical reactions, could revolutionize drug development

      Home > Emerging Tech > IBM’s new A.I. predicts chemical reactions… IBM’s new A.I. predicts chemical reactions, could revolutionize drug development Is Taco Bell really your friend? New Snapchat update weeds brands from… Get today's popular Digital Trends articles in your inbox: From building the Deep Blue computer that beat Garry Kasparov at chess to the Watson artificial intelligence (A.I.) that won Jeopardy , IBM has been responsible for some high-profile public demonstrations of A.I.

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    23. Using neural networks to predict outcomes of organic chemistry

      Using neural networks to predict outcomes of organic chemistry

      Using neural networks to predict outcomes of organic chemistry December 5, 2017 The web-based tool is simple, and the model is trained end-to-end, fully data-driven and without to aid of querying a database or any additional external information. Credit: IBM For more than 200 years, the synthesis of organic molecules remains one of the most important tasks in organic chemistry.

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      Mentions: IBM
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  5. People in the News

    1. (7 articles) John Searle
    2. (5 articles) Kai-Fu Lee
    3. (3 articles) Garry Kasparov
    4. (3 articles) Lingotek Lingotek
    5. (3 articles) Rob Vandenberg
    6. (2 articles) Stephen Hawking
    7. (1 articles) Taco Bell
    8. (1 articles) Alan Turing
    9. (1 articles) John McCarthy
    10. (1 articles) Robert Bosch
    11. (1 articles) Marvin Minsky
    12. (1 articles) Terry Winograd