Earlier this week, search giant Google announced that one of its biggest updates in years has finally been rolled out worldwide.
The update is better known as BERT, and stands for Bidirectional Encoder Representations from Transformers. Described by some as the biggest Google update in the last five years, this algorithm has been introduced to help the search company to better understand the pragmatics behind search queries – i.e. going beyond the exact keywords.
While BERT was introduced to Google at the end of October, the company has now announced that it has completed its global rollout. The announcement was made through a series of tweets to the Google SearchLiaison account, sent out on Monday.
In this series of tweets, the company revealed that the update was rolling out for over 70 languages – 72 to be precise – and listed each of them. It includes some of the most used languages such as Spanish, French, German, Chinese, Arabic and Russian, as well as some lesser spoken languages including Tagalog, Galician, Azeri, Tamil, Amharic, Khmer and Telugu.
BERT, our new way for Google Search to better understand language, is now rolling out to over 70 languages worldwide. It initially launched in Oct. for US English. You can read more about BERT below & a full list of languages is in this thread…. https://t.co/NuKVdg6HYM
— Google SearchLiaison (@searchliaison) December 9, 2019
Embedded within the opening tweet is a link to a blog post Google wrote in October, when it initially revealed BERT, in which it explains what the algorithm is and how it will be applied to search queries.
BERT’s purpose is to improve how Google understands the millions of search queries it receives on a daily basis. It hopes that if the search engine can understand a query better then, it will be able to direct searchers to the most appropriate results for their query. Therefore, with a better understanding of language and the way people use it to search, Google should improve the quality of search traffic.
The update also affects Featured Snippets, so for languages that have access to this feature, it is hoped that what users see within these snippets is more relevant and improved compared to the results that appeared beforehand.