It’s difficult to describe in a concise list with less than 1,000 words what the definitive direction of artificial intelligence is going to be in a 12-month span. 2016 surprised a number of people in terms of the speed of certain technologies’ development and the revised ETA of new AI-driven products hitting the public market.
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Here are the four trends that will dominate artificial intelligence in 2017.
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subhead1. Language processing will continue/subhead
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We could call this natural language processing or NLP, but let’s think more broadly about language for a moment. The key to cognition, for you mavens of Psychology 101, is sophisticated communication, even internal abstract thinking. That will continue to prove critical in driving machine learning ‘deeper.’
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One place to keep track of progress in the space is in machine translation, which will give you an idea of how sophisticated and accurate our software currently is in translating some of the nuance and implications of our spoken and written language.
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That will be the next step in getting personal assistant technology like Alexa, Siri, Google Assistant, or Cortana to interpret our commands and questions just a little bit better.
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subhead2. Efforts to square machine learning and big data with different health sectors will accelerate/subhead
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I envision a system that still has those predictive data pools. It looks at the different data you obtain that different labs are giving all the time, eBay Director of Data Science Kira Radinsky told an audience at Geektime TechFest 2016 last month, pioneering automated processes that can lead to those types of discoveries.
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Biotech researchers and companies are trying to get programs to automate drug discoveries, among other things. Finding correlations in data and extrapolating causation is not the same in all industries, nor in any one sector of medicine. Researchers in heart disease, neurological disorders, and various types of cancer…