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    1. Translation technology is useful, but should not replace learning languages

      Translation technology is useful, but should not replace learning languages

      Republish our articles for free, online or in print, under Creative Commons licence. The benefits of language-learning go far beyond being able to translate. 9to5google.com Messenger For many years now, there have been calls for Australians to learn languages, particularly Asian languages, as the world economy pivots to the Asia-Pacific. But the number of students learning languages in Australia has remained stubbornly low .

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    2. Are self-driving cars the future of mobility for disabled people?

      Are self-driving cars the future of mobility for disabled people?

      Are self-driving cars the future of mobility for disabled people? Srikanth Saripalli Texas A&M University 22 hrs ago Srikanth Saripalli , Texas A&M University (THE CONVERSATION) Self-driving cars could revolutionize how disabled people get around their communities and even travel far from home. People who can’t see well or with physical or mental difficulties that prevent them from driving safely often rely on others – or local government or nonprofit agencies – to help them get around.

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    3. Natural language processing and affective computing

      Natural language processing and affective computing

      Republish our articles for free, online or in print, under Creative Commons licence. Translations Read this article in English and French How can a machine understand who said what? Messenger What are the natural extensions of machine learning (ML) and deep learning as well as natural language processing (NLP) and affective computing (AC)? To many people, what distinguish machines from humans is emotion.

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    4. Deep learning and neural networks

      Deep learning and neural networks

      Republish our articles for free, online or in print, under Creative Commons licence. Translations Read this article in English and French Neural network. If then else / Wikimedia , CC BY-SA Messenger Have you ever toyed with the idea of what machine learning actually does? If machine learning is a pack horse for information processing, a neural network is the carrot that draws the horse forward.

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    5. Figuring out what Aussies think about Trump on Twitter is pretty difficult

      Figuring out what Aussies think about Trump on Twitter is pretty difficult

      Figuring out what Aussies think about Trump on Twitter is pretty difficult 783 Trump's election has been met with division, to say the least - but less so in Australia Image: Slate Scott Bingley, Paul Hawking for The Conversation 2017-01-22 07:00:01 UTC Follow @conversationuk Australians reacted more "positive" than "negative" to the election of Donald Trump as the next president of the United States, according to a sentiment analysis study of tweets that were posted at the time.

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    6. Your smartphone knows a lot about you, but what about your mental health?

      Your smartphone knows a lot about you, but what about your mental health?

      Smartphones come with an assortment of sensors that can track behaviours such as our internet search and browse history, where we go, what music we listen to, who we speak to, just to name a few. The habitual nature of people means this data could be used to give insight into our mental wellbeing. Acute changes in behavioural patterns may indicate a need for support, and the use of any health diaries on a smartphone may enable us to monitor chronic conditions more effectively.

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      Mentions: Apple Australia IBM
    7. Artificial intelligence in medicine is promising, but doubts remain

      Artificial intelligence in medicine is promising, but doubts remain

      print Shutterstock.com Scientists in Japan reportedly saved a woman’s life by applying artificial intelligence to help them diagnose a rare form of cancer. Faced with a 60-year-old woman whose cancer diagnosis was unresponsive to treatment, they supplied an AI system with huge amounts of clinical cancer case data, and it diagnosed the rare leukemia that had stumped the clinicians in just ten minutes.

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      Mentions: Japan
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