Google BERT: Google has announced one of the biggest updates to its search algorithm in years. By using new neural network techniques to better understand query intent, Google says it can now show more relevant results for about one in 10 searches in the U.S. in English (with support for other languages and locations as well). 
For featured snippets, the update is already working globally.
Every search algorithm update is often very subtle. An update that affects 10% of searches is a big deal (and certainly keeps SEO experts around the world on their toes).
Google says this update will work better for longer, more complex queries, and in many other ways, so you'll love searching on Google because it's easier to type a complete sentence than a string of keywords.
The technology behind this new neural network is called “Bidirectional Encoder Representations from Transformers” and we will refer to it simply as BERT.
Google first talked about BERT last year and open-sourced the code for its application to pre-trained models.
Transformers are one of the most recent developments in machine learning. They work particularly well for data where the sequence of elements is important, which obviously makes them a very useful tool for working with natural language and, therefore, in search queries.
This BERT update also marks the first time Google is using the latest Tensor Processing Unit (TPU) chips to display search results.
Ideally, this means that Google Search will now be able to understand exactly what you're looking for and provide more relevant search results and snippets.
The Google BERT update started rolling out this week, so you'll have a chance to see some of its results in search results.
