Have your ever felt riled at the irrelevant and unwanted results a search engine throws in response to your query? Also Read - Google starts showing COVID-19 vaccine information in Search app
Don’t worry. A new computer program developed by scientists – including an Indian-origin researcher – at University of Washington and Allen Institute for Artificial Intelligence in Seattle is adept at teaching itself everything available on internet about a comprehensive visual concept. Called “Learning Everything about Anything” (LEVAN), the program searches millions of books and images on the web to learn all possible variations of a concept, then displays the results to users as a comprehensive, browsable list of images – helping them explore and understand topics quickly in great detail. Also Read - Google redesigning its Search results on mobile for better user experience
Major information resources such as dictionaries and encyclopedias have limited coverage as they are often manually curated. “The new program needs no human supervision and, thus, can automatically learn the visual knowledge for any concept,” said Santosh Divvala from Allen Institute for Artificial Intelligence. The program learns which terms are relevant by looking at the content of the images found on the web and identifying characteristic patterns across them using object recognition algorithms. Also Read - Google threatens to stop its Search engine in Australia, govt responds
“It is all about discovering associations between textual and visual data,” said Ali Farhadi, an assistant professor of computer science and engineering at University of Washington. “The program learns to tightly couple rich sets of phrases with pixels in images. This means that it can recognize instances of specific concepts when it sees them,” Farhadi explained. The research team will present a related paper this month at the annual conference titled “Computer Vision and Pattern Recognition” in Columbus, Ohio.