Friday September 05, 2014

Teaching computers to see

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Researchers are building computer systems that can see and understand the world around us. And they're getting better every year. Olga Russakovsky (Stanford) and Geoffrey E. Hinton (University of Toronto, Google) weigh in on this year's Large Scale Visual Recognition Challenge results, and the future of computer vision and artificial intelligence.

<p>Nora mentioned this related Mashable story about <a href="http://mashable.com/2014/08/13/passive-hashtags/">advertising and selfies</a></p> <p>Nora also mentioned the the popular video that's been making the rounds in the last few weeks called <a href="https://www.youtube.com/watch?v=7Pq-S557XQU">Humans Need Not Apply</a>. It's generating lots of conversation for its argument that artificial intelligence is rapidly replacing human jobs in all kinds of sectors. It's a topic we've explored in depth on Spark:</p> <ul> <li>Stuart Russell on <a href="http://www.cbc.ca/spark/blog/2014/06/01/are-we-taking-ai-seriously-enough/">taking AI seriously</a></li> <li>Our <a href="http://www.cbc.ca/spark/episodes/2013/06/14/blog-and-aut-title-217-the-future-of-work-workplace-science-rethinking-recruiting-and-the-resume-the/">Future of Work special</a></li> <li>Andrew McAfee on <a href="http://www.cbc.ca/spark/full-interviews/2012/01/20/full-interview-andrew-mcafee-on-race-against-the-machine/">automation and long term unemployment</a></li> <li>Farhad Manjoo on <a href="http://www.cbc.ca/spark/blog/2011/10/07/spark-158-october-9-12-2011/">white collar robots</a></li> </ul>