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The obvious is so difficult

Look at that dog. It is wagging its tail, looks like it has seen his owner approaching it. Looking, recognising the wagging dog and deducing why it looks happy is not rocket science. And yet it is a most difficult task for a computer. What is obvious to us is usually very hard (it used to be impossible) for a computer.
Now a program developed by researchers at the University of Washington and the Allen Institute for artificial intelligence is making significant steps towards providing a computer the capability to "understand" an image. 
This feat is performed through a mixture of hard number crunching and artificial intelligence approach. 
The researchers have explored images on millions of books made available by Google and on billions of web pages associating the text to the images and then using artificial intelligence approaches to extract meaning from pictures and reinforce that meaning with the text going along with them (in proximity, not necessarily in a caption).
You can see an example of the kind of concept association made with the term "walking" and a given picture.
It might seem easy but it is actually extremely complex and it really amazes me that we have been able to reach this point. It really shows that the line between humans and computers is getting fuzzier and the question is not if computer will ever get smarter than humans but when it will happen…

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. He's currently the Chair of the Symbiotic Autonomous Systems Initiative of IEEE-FDC. Until April 2017 he led the EIT Digital Italian Node and up to September 2018 he was the Head of the EIT Digital Industrial Doctoral School. Previously, up to December 2011, he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the Industry Advisory Board within the Future Directions Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books. He writes a daily blog,  http://sites.ieee.org/futuredirections/category/blog/, with commentary on innovation in various technology and market areas.