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November 28, 2017

how niche websites can benefit by google's rankbrain

the rise of AI and deep learning in Google searches
the above image shows how " Rankbrain is using vectors to understand country and their capitals using AI, deep learning

Bloomberg News recently broke the story on a new artificial intelligence program from Google that it calls “Rank Brain”.“For the past few months, a “very large fraction” of the millions of queries a second that people type into the company’s search engine has been interpreted by an artificial intelligence system, nicknamed RankBrain.

Putting is simply Rank Brain is an artificial intelligence (AI) program used to help process Google search queries. RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities, called vectors, that the computer can understand.If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.Presently RankBrain is mainly used as a way to interpret the searches that people submit to find pages that might not have the exact words that were searched for and for searches that has different meaning across geographies. 

To cite an example, for a query "how much spoons of sugar will fill a cup, Google’s Rank Brain will show different search results based on things like what country the search was made from.This is because each country has different standards of measuring them. a normal cup in Australia will be of a different size that Austria .

RankBrain is mainly used as a way to interpret the searches that people submit to find pages that might not have the exact words that were searched for. It must be understood here that RankBrain is not a new Algorithm, Rankbrain is only a part of Google’s overall search “algorithm,” along with ( hummingbird, Penguin, Panda) which is used to sort through the billions of pages it knows about and find the ones deemed most relevant for particular queries. 

In particular, we know RankBrain is part of the overall Hummingbird algorithm because the Bloomberg article makes clear that RankBrain doesn’t handle all searches, as only the overall algorithm would. Hummingbird also contains other parts with names familiar to those in the SEO space, such as Panda, Penguin, and Payday designed to fight spam, Pigeon designed to improve local results.

The basic idea of using Artificial Intelligence and assigning mathematical vectors to search queries is due to the fact the present computers and algorithms does not understand natural human language so well enough, which forces people to do a lot of the heavy lifting— when they are searching for something 'unique or keywords which Google has never searched or a phrase which it cannot understand, for example, speaking "searchese" to find information online, or slogging through lengthy forms to book a trip. Computers ideally should understand the natural language better, so people can interact with them more easily and get any kind of semantic information without having to sweat it out.

While state-of-the-art technology is still miles away from this goal, Google's Rankbrain has started making significant progress using the latest machine learning and natural language processing techniques. Deep learning has markedly improved speech recognition and image classification. For example, studies have shown that computers can learn to recognize cats (and many other objects) just by observing a large number of images, without being trained explicitly on what a cat looks like. Now we apply neural networks to understanding words by having them “read” vast quantities of text on the web. Google says that its scaling this approach to datasets thousands of times larger than what has been possible before, and they have seen a dramatic improvement in performance.

To promote research on how machine learning can apply to natural language problems, Google has published an open source toolkit called word2vec that aims to learn the meaning behind words. Word2vec uses distributed representations of text to capture similarities among concepts. 

For example, it understands that Paris and France are related the same way Berlin and Germany are (capital and country), and not the same way Madrid and Italy are. This chart shows how well it can learn the concept of capital cities, just by reading lots of news articles -- with no human intervention.

So how does Rankbrain would affect your SEO ? For starters, Its important to step back and understand why RankBrain was deployed.The problem is with the sheer scale of search volumes today. 
Google processes three billion searches per day. In 2007, Google said that 20 - 25% of those queries had never been seen before. In 2013, it brought that number down to 15 percent and by 2015 it still hovers around the same number. But 15% of three billion is still a huge number of queries never entered by any human searcher — 450 million per day.That number by any imagination is huge, among those search keywords , some of them can be complex, multi-word queries, also called “long-tail” queries. RankBrain is designed to help better interpret those queries and effectively translate them, behind the scenes in a way, to find the best and relevant pages for the searcher.-So if you run a  very niche website targetting  rare long tail keywords ,you might see increase in traffic as Rankbrain tries to serve users using them as vectors by integrating state of art Artificial intelligence and Deep learning