As Google continues to leverage more artificial intelligence and machine learning in Google Search, one may wonder in what ways does AI and machine learning help Google Search perform its daily tasks. Since 2015, when Google introduced its first AI into search named RankBrain, Google has continued to deploy AI systems to better understand language and thus improve the search results Google presents to its searches.
Several months ago we sent Google a number of questions around how Google uses its AI in search, including RankBrain, neural matching, BERT and Google’s latest AI breakthrough – MUM. We’ve come up with more of an understanding of when Google uses AI, which AI does what in Google Search, how these various AI algorithms may work together, how they have changed over the years and what, if anything, search marketers need to know when it comes to how Google uses AI in search.
We spoke with Danny Sullivan, the Public Liaison for Google Search, to help with the answers to many of these questions. In short, RankBrain, neural matching and BERT are used in Google’s ranking system across many, if not most, queries and look at understanding the language of both the query and content it is ranking. However, MUM is not currently used for ranking purposes, it is currently only used for COVID vaccine naming and powers the related topics in videos results.
It starts by writing content for humans
You hear it all the time from Google representatives and from many SEOs: write...
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