Google offers A.I. research is improving search results
Google has enhanced its search-ranking system with software called BERT, or Bidirectional Encoder Representations from Transformers to its friends. It was developed in the company’s artificial intelligence labs and announced last fall, breaking records on reading comprehension questions that researchers use to test AI software.
Pandu Nayak, Google’s vice president of search, said at a briefing, that the muppet-monickered software has made Google’s search algorithm much better at handling long queries, or ones where the relationships between words are crucial. You’re now less likely to get frustrating responses to queries dependent on prepositions like for” and “to,” or negations such as “not” or “no.”
“This is the single biggest positive change we’ve had in the last five years,” Nayak said-at least according to Google’s measures of how ranking changes help people find what they want. Google declines to share the details. Google says it has been testing the upgrade but is now rolling it out widely.
One illustration of BERT’s power offered up by Google is how it helped its search engine interpret the query “Parking on hill with no curb.” The current version of its search algorithm responded to that as if it referred to a hill that did have a curb. The BERT-powered version highlights a page advising drivers to point their wheels toward the side of the road.
Another was the query “2019 brazil traveler to usa need a visa.” To a human, that’s a clear attempt to discover the requirements for Brazilians heading to the US, but pre-BERT Google misunderstood the crucial “to” and returned an article about US citizens traveling to Brazil as the top result. With BERT, the search engine correctly serves up a page about requirements for Brazilian citizens heading north.
Google says it receives billions of searches per day and that the BERT upgrade will affect rankings on one out of every 10. But Nayak says most users probably won’t notice. That doesn’t mean the change doesn’t matter to users, or Google. Anyone who has tried to switch search engines knows that the way Google’s ranking burrows into your expectations of the internet can be extremely powerful.
People outside the US turning to Google for help will see some of the most significant changes. Nayak said that the BERT upgrade helped its system get much better at identifying so-called featured snippets, particularly in languages other than English.
Google’s upgrade is a notable example of recent progress in software that attempts to understand language. It has made machine learning algorithms much better at decoding the subtleties of language by attending to the context around a particular word.
Machine learning has proved to be a powerful way to teach software to sort or interpret data such as images or text. But each program typically has to be “trained” using example data. That’s often been tricky to come by for text documents. Projects would depend on paying people to label specific examples, such as good and bad restaurant reviews.- The Wired.
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