What is Google RankBrain? What exactly happens when you whip out your phone and perform a fast Google search to get an answer to a question? Most of us are aware that Google has a massive algorithm that understands organic search and posts results based on a specified ranking. Thus far, so good.
However, Google put a substantial amount of AI technology in its search engine, which leads us to RankBrain. RankBrain is a machine learning algorithm that plays a significant role in how Google search results are returned, affecting many aspects of our online lives. Here’s a rundown of how everything works.
What is Google RankBrain?
The official term for a Google AI model that incorporates machine learning is RankBrain. Machine learning is the process by which an AI model runs data tests and teaches itself to be more accurate. For example, an AI taught to recognise human faces can receive feedback when it is incorrect and utilise that feedback to improve its estimations. Machine learning AIs become incredibly precise with enough resources and time, and few organisations have more resources or time than Google.
RankBrain is now designed to improve Google’s search engine algorithm, which returns results when you enter something into the search field. Google introduced AI in 2015 and 2016 to effectively comprehend people’s searches and search intent. It was especially interested in moving beyond words so that the search engine could interpret the “thing” users were looking for.
RankBrain initially had just a tiny impact on the search engine algorithm. It got more significant as it expanded and acquired more training. Google now considers it the third most important ranking indicator in the search engine, thus it has a significant impact on the results you see.
How does RankBrain work?
We don’t know how it works because it’s a private and well-guarded AI technology. But we do know a lot about it because of what Google has previously openly disclosed to developers and other projects the corporation has worked on.
RankBrain is part of a bigger, decade-long Google effort to move away from searching for words and towards searching for concepts, dubbed Strings to Things. Google employs an interpretative technology known as Hummingbird to accomplish this. Hummingbird transforms data into Machine IDs or labels that characterise a Thing.
This could be a person, an object, a colour, a famous monument, or anything else that can be searched. Hummingbird uses smart labels to connect concepts based on how they’re searched and what the text says about them.
However, things change all the time, and there is always an opportunity for error. The Machine ID system is used by RankBrain’s AI to test and improve the results’ correctness. It observes how people interact with internet content and uses that knowledge to infer their intent, which it then repeats. In theory, it eventually generates an effective filter that prioritises the helpful, accurate search results that users want.
For example, if someone searches for “secrets of the Aztecs,” RankBrain assists the search engine in determining whether the query is referring to a famous book, a theory about an Aztec legend, a video game, and so on. If there is a sudden influx of articles about an old Aztec healing diet, RankBrain changes the concepts to make that connection. The process becomes more intricate, but you get the concept.
RankBrain examines everything to accomplish this. This includes what devices conduct a search, what time of day a search occurs, what it knows about a searcher’s demographics, and so on. RankBrain doesn’t need to recognise search terms because it has so much data. The context of the data and previous results are sufficient to make an AI-educated prediction for even the most bizarre searches.
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