As an example, taken from Pandu’s article, “Here’s a search for, “2019 brazil traveler to the USA needs a visa.” Pandu says. ” The word to and its relationship to the other words in the query are particularly important to understanding the meaning.” He further states, “It’s about a Brazilian traveling to the US and not the other way around. Previously, our algorithms wouldn’t understand the importance of this connection.” BERT, can supposedly grasp sentence structure nuance and know the word “to” is essential, thus Google can improve the quality of the query result.
Unknown Effects of the BERT Update
Machine learning is excellent until it is not. If the algorithm understands incorrectly and the results are not helpful, it can be challenging to know why. Furthermore, while Google believes that it has ensured the new Google algorithm update will not increase bias, those training the model are themselves prone to bias. Because BERT is trained on thousands of sentences, each having a possibility of bias, it is something for which we should be aware.
Google has claimed that it does not believe there will be a significant difference in where they direct traffic. However, when Google makes a change to its search algorithm of this magnitude, everyone involved takes notice. Many companies live and die by Google’s SERP ranking changes.
As web professionals, we should all be aware of the potential impacts of this or any change. We believe this update is one of the most significant changes Google has rolled out in at least the last five years. You can guess that Google’s guidance will be the same as it always is. “If you are following our content guidelines you should see no negative impact.” That is hard to take for face value when they are claiming to improve the results by 10% as that likely means someone may lose out on the related search. However, in the end, we hope that this means truly means that search results returned on a given query are more meaningful.