Dynamically Typed

BERT in Google Search

Improved natural language understanding in Google Search. (Google)

Improved natural language understanding in Google Search. (Google)

Google Search now uses the BERT language model to better understand natural language search queries:

This breakthrough was the result of Google research on transformers: models that process words in relation to all the other words in a sentence, rather than one-by-one in order. BERT models can therefore consider the full context of a word by looking at the words that come before and after it—particularly useful for understanding the intent behind search queries.

The query in the screenshots above is a good example of what BERT brings to the table: its understanding of the word “to” between “brazil traveler” and “usa” means that it no longer confuses whether the person is from Brazil and going to the USA or the other way around. Google is even using concepts that BERT learns from English-language web content for other languages, which led to “significant improvements in languages like Korean, Hindi and Portuguese.” Read more in Pandu Nayak’s post for Google’s The Keyword blog: Understanding searches better than ever before.